csa-0.1.0/ 0000755 0005140 0005140 00000000000 11735363223 011623 5 ustar mdj mdj 0000000 0000000 csa-0.1.0/README 0000644 0005140 0005140 00000013240 11735362304 012502 0 ustar mdj mdj 0000000 0000000 This is a demonstration implementation in Python of the Connection-Set
Algebra (Djurfeldt, Mikael (2012), Neuroinformatics)
* Purpose
The CSA library provides elementary connection-sets and operators for
combining them. It also provides an iteration interface to such
connection-sets enabling efficient iteration over existing connections
with a small memory footprint also for very large networks. The CSA
can be used as a component of neuronal network simulators or other
tools.
* License
CSA is released under the GNU General Public License
* Requirements
CSA is dependent on Numpy and Matplotlib
* Introduction
A connection set is a set of existing connections between a set of
source nodes and a set of target nodes. Typically, source and target
nodes are neurons in a neuronal network, but targets could also be
particular structures of a neuron, such synaptic sites. Sources and
targets are enumerated by integers and a connection is represented by
a pair of integers, one denoting the source node and one the target
node. Source and target can be (and is often) the same set.
CSA connection sets are usually infinite. This is a simplification
compared to the common situation of finite source and target sets in
that the sizes of these sets do not need to be considered. Connection
sets can have arbitrary values associated with connections. Pure
connection sets without any values associated are called masks.
* Getting started
** Basics
To get access to the CSA in Python, type:
from csa import *
The mask representing all possible connections between an infinite
source and target set is:
full
To display a finite portion of the corresponding connectivity matrix,
type:
show (full)
One-to-one connectivity (where source node 0 is connected to target
node 0, source 1 to target 1 etc) is represented by the mask oneToOne:
show (oneToOne)
The default portion displayed by "show" is (0, 29) x (0, 29).
(0, 99) x (0, 99) can be displayed using:
show (oneToOne, 100, 100)
If source and target set is the same, oneToOne describes
self-connections. We can use CSA to compute the set of connections
consisting of all possible connections except for self-connections
using the set difference operator "-":
show (full - oneToOne)
Finite connection sets can be represented using either lists of
connections, with connections represented as tuples:
show ([(22, 7), (8, 23)])
or using the Cartesian product of intervals:
show (cross (xrange (10), xrange (20)))
We can form a finite version of the infinite oneToOne by taking the
intersection "*" with a finite connection set:
c = cross (xrange (10), xrange (10)) * oneToOne
show (c)
Finite connection sets can be tabulated:
tabulate (c)
In Python, finite connection sets provide an iterator interface:
for x in cross (xrange (10), xrange (10)) * oneToOne:
print x
** Random connectivity and the block operator
Connectivity where the existence of each possible connection is
determined by a Bernoulli trial with probability p is expressed with
the random mask random (p), e.g.:
show (random (0.5))
The block operator expands each connection in the operand into a
rectangular block in the resulting connection matrix, e.g.:
show (block (5,3) * random (0.5))
Note that "*" here means operator application. There is also a
quadratic version of the operator:
show (block (10) * random (0.7))
Using intersection and set difference, we can now formulate a more
complex mask:
show (block (10) * random (0.7) * random (0.5) - oneToOne)
** Geometry
In CSA, the basic tool to handle distance dependent connectivity is
metrics. Metrics are value sets d (i, j). Metrics can be defined
through geometry functions. A geometry function maps an index to a
position. We can, for example, assign a random position in the unit
square to each index:
g = random2d (900)
The positions of the grid described by g have indices from 0 to 899
and can be displayed like this:
gplot2d (g, 900)
Alternatively, we can arrange indices in a 30 x 30 grid within the
unit square:
g = grid2d (30)
We can now define the euclidean metric on this grid:
d = euclidMetric2d (g)
An example of a distance dependent connection set is the disc mask
Disc (r) * d which connects each index i to all indices j within a
distance d (i, j) < r:
c = disc (r) * d
To examine the result we can employ the function gplotsel2d (g, c, i)
which displays the targets g (j) of i in the connection set c:
gplotsel2d (g, c, 434)
In the case where the connection set represents a projection between
two different coordinate systems, we define one geometry function for
each. In the following example g1 is direction in visual space in arc
minutes while g2 is position in the cortical representation of the
Macaque fovea in mm:
g1 = grid2d (30)
g2 = grid2d (30, x0 = -7.0, xScale = 8.0, yScale = 8.0)
We now define a projection operator which takes visual coordinates
into cortical (Dow et al. 1985):
import cmath
@ProjectionOperator
def GvspaceToCx (p):
w = 7.7 * cmath.log (complex (p[0] + 0.33, p[1]))
return (w.real, w.imag)
To see how the grid g1 is transformed into cortical space, we type:
gplot2d (GvspaceToCx * g1, 900)
The inverse projection is defined:
@ProjectionOperator
def GcxToVspace (p):
c = cmath.exp (complex (p[0], p[1]) / 7.7) - 0.33
return (c.real, c.imag)
Real receptive field sizes vary with eccentricity. Assume, for now,
that we want to connect each target index to sources within a disc of
constant radius. We then need to project back into visual space and
use the disc operator:
c = disc (0.1) * euclidMetric2d (g1, GcxToVspace * g2)
Again, we use gplotsel2d to check the result:
gplotsel2d (g2, c, 282)
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to collect a royalty for further conveying from those to whom you convey
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License would be to refrain entirely from conveying the Program.
13. Use with the GNU Affero General Public License.
Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed
under version 3 of the GNU Affero General Public License into a single
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License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License,
section 13, concerning interaction through a network will apply to the
combination as such.
14. Revised Versions of this License.
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be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
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If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's
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15. Disclaimer of Warranty.
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APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
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IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
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THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
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PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
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17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
Copyright (C)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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You should have received a copy of the GNU General Public License
along with this program. If not, see .
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
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Copyright (C)
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
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under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
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The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
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.
csa-0.1.0/MANIFEST.in 0000644 0005140 0005140 00000000055 11735362304 013360 0 ustar mdj mdj 0000000 0000000 include setup.py MANIFEST.in
include COPYING
csa-0.1.0/PKG-INFO 0000644 0005140 0005140 00000002150 11735363223 012716 0 ustar mdj mdj 0000000 0000000 Metadata-Version: 1.1
Name: csa
Version: 0.1.0
Summary: The Connection-Set Algebra implemented in Python
Home-page: http://software.incf.org/software/csa/
Author: Mikael Djurfeldt
Author-email: mikael@djurfeldt.com
License: GPLv3
Description: The CSA library provides elementary connection-sets and operators for
combining them. It also provides an iteration interface to such
connection-sets enabling efficient iteration over existing connections
with a small memory footprint also for very large networks. The CSA
can be used as a component of neuronal network simulators or other
tools.
Keywords: computational neuroscience modeling connectivity
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Topic :: Scientific/Engineering
Requires: numpy
Requires: matplotlib
csa-0.1.0/setup.py 0000644 0005140 0005140 00000002627 11735362304 013343 0 ustar mdj mdj 0000000 0000000 #!/usr/bin/env python
from distutils.core import setup
from csa.version import __version__
long_description = """The CSA library provides elementary connection-sets and operators for
combining them. It also provides an iteration interface to such
connection-sets enabling efficient iteration over existing connections
with a small memory footprint also for very large networks. The CSA
can be used as a component of neuronal network simulators or other
tools."""
setup (
name = "csa",
version = __version__,
packages = ['csa',],
author = "Mikael Djurfeldt", # add your name here if you contribute to the code
author_email = "mikael@djurfeldt.com",
description = "The Connection-Set Algebra implemented in Python",
long_description = long_description,
license = "GPLv3",
keywords = "computational neuroscience modeling connectivity",
url = "http://software.incf.org/software/csa/",
classifiers = ['Development Status :: 2 - Pre-Alpha',
'Environment :: Console',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU General Public License (GPL)',
'Natural Language :: English',
'Operating System :: OS Independent',
'Programming Language :: Python :: 2',
'Topic :: Scientific/Engineering'],
requires = ['numpy', 'matplotlib'],
)
csa-0.1.0/csa/ 0000755 0005140 0005140 00000000000 11735363223 012371 5 ustar mdj mdj 0000000 0000000 csa-0.1.0/csa/misc.py 0000644 0005140 0005140 00000002307 11735362304 013677 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import _misc
def disc (r):
return _misc.Disc (r)
def rectangle (width, height):
return _misc.Rectangle (width, height)
def gaussian (sigma, cutoff):
return _misc.Gaussian (sigma, cutoff)
def block (M, N = None):
return _misc.Block (M, M if N == None else N)
transpose = _misc.Transpose ()
def shift (M, N):
return _misc.Shift (M, N)
fix = _misc.Fix ()
def block1 (N):
return _misc.Block (N)
#del _misc # not for export
csa-0.1.0/csa/_misc.py 0000644 0005140 0005140 00000017754 11735362304 014052 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import math
import random
import copy
import connset as cs
import valueset as vs
import _elementary
from csaobject import *
class Random (cs.Operator):
def __mul__ (self, valueSet):
return ValueSetRandomMask (valueSet)
def __call__ (self, p = None, N = None, fanIn = None, fanOut = None):
if p != None:
assert N == None and fanIn == None and fanOut == None, \
'inconsistent parameters'
return _elementary.ConstantRandomMask (p)
elif N != None:
assert fanIn == None and fanOut == None, \
'inconsistent parameters'
return _elementary.SampleNRandomOperator (N)
elif fanIn != None:
assert fanOut == None, \
'inconsistent parameters'
return _elementary.FanInRandomOperator (fanIn)
elif fanOut != None:
return _elementary.FanOutRandomOperator (fanOut)
assert False, 'inconsistent parameters'
class ValueSetRandomMask (cs.Mask):
def __init__ (self, valueSet):
cs.Mask.__init__ (self)
self.valueSet = valueSet
self.state = random.getstate ()
def startIteration (self, state):
random.setstate (self.state)
return self
def iterator (self, low0, high0, low1, high1, state):
for j in xrange (low1, high1):
for i in xrange (low0, high0):
if random.random () < self.valueSet (i, j):
yield (i, j)
def _to_xml (self):
return CSAObject.apply ('times', 'random', self.valueSet._to_xml ())
class Disc (cs.Operator):
def __init__ (self, r):
self.r = r
def __mul__ (self, metric):
return DiscMask (self.r, metric)
class DiscMask (cs.Mask):
def __init__ (self, r, metric):
cs.Mask.__init__ (self)
self.r = r
self.metric = metric
def iterator (self, low0, high0, low1, high1, state):
for j in xrange (low1, high1):
for i in xrange (low0, high0):
if self.metric (i, j) < self.r:
yield (i, j)
class Rectangle (cs.Operator):
def __init__ (self, width, height):
self.width = width
self.height = height
def __mul__ (self, gFunction):
if isinstance (gFunction, tuple):
return RectangleMask (self.width, self.height,
gFunction[0], gFunction[1])
else:
return RectangleMask (self.width, self.height, gFunction, gFunction)
class RectangleMask (cs.Mask):
def __init__ (self, width, height, g0, g1):
cs.Mask.__init__ (self)
self.hwidth = width / 2.0
self.hheight = height / 2.0
self.g0 = g0
self.g1 = g1
def iterator (self, low0, high0, low1, high1, state):
for j in xrange (low1, high1):
for i in xrange (low0, high0):
p0 = self.g0 (i)
p1 = self.g1 (j)
dx = p0[0] - p1[0]
dy = p0[1] - p1[1]
if abs (dx) < self.hwidth and abs (dy) < self.hheight:
yield (i, j)
class Gaussian (cs.Operator):
def __init__ (self, sigma, cutoff):
self.sigma = sigma
self.cutoff = cutoff
def __mul__ (self, metric):
return GaussianValueSet (self, metric)
class GaussianValueSet (OpExprValue, vs.ValueSet):
def __init__ (self, operator, metric):
OpExprValue.__init__ (self, operator, metric)
self.sigma22 = 2 * operator.sigma * operator.sigma
self.cutoff = operator.cutoff
self.metric = metric
def __call__ (self, i, j):
d = self.metric (i, j)
return math.exp (- d * d / self.sigma22) if d < self.cutoff else 0.0
class Block (cs.Operator):
def __init__ (self, M, N):
self.M = M
self.N = N
def __mul__ (self, other):
c = cs.coerceCSet (other)
if isinstance (c, cs.Mask):
return BlockMask (self.M, self.N, c)
else:
return cs.ConnectionSet (BlockCSet (self.M, self.N, c))
class BlockMask (cs.Mask):
def __init__ (self, M, N, mask):
cs.Mask.__init__ (self)
self.M = M
self.N = N
self.m = mask
def iterator (self, low0, high0, low1, high1, state):
maskIter = self.m.iterator (low0 / self.M,
(high0 + self.M - 1) / self.M,
low1 / self.N,
(high1 + self.N - 1) / self.N,
state)
try:
pre = []
(i, j) = maskIter.next ()
while True:
# collect connections in one connection matrix column
post = j
while j == post:
pre.append (i)
(i, j) = maskIter.next ()
# generate blocks for the column
for jj in xrange (max (self.N * post, low1),
min (self.N * (post + 1), high1)):
for k in pre:
for ii in xrange (max (self.M * k, low0),
min (self.M * (k + 1), high0)):
yield (ii, jj)
pre = []
except StopIteration:
if pre:
# generate blocks for the last column
for jj in xrange (max (self.N * post, low1),
min (self.N * (post + 1), high1)):
for k in pre:
for ii in xrange (max (self.M * k, low0),
min (self.M * (k + 1), high0)):
yield (ii, jj)
class Transpose (cs.Operator):
def __mul__ (self, other):
c = cs.coerceCSet (other)
if isinstance (c, cs.Mask):
return other.transpose ()
else:
return cs.ConnectionSet (other.transpose ())
class Shift (cs.Operator):
def __init__ (self, M, N):
self.M = M
self.N = N
def __mul__ (self, other):
c = cs.coerceCSet (other)
if isinstance (c, cs.Mask):
return other.shift (self.M, self.N)
else:
return cs.ConnectionSet (other.shift (self.M, self.N))
class Fix (cs.Operator):
def __mul__ (self, other):
c = cs.coerceCSet (other)
if isinstance (c, cs.Mask):
return FixedMask (other)
else:
return cs.ConnectionSet (FixedCSet (other))
class FixedMask (cs.FiniteMask):
def __init__ (self, mask):
cs.FiniteMask.__init__ (self)
ls = []
for c in mask:
ls.append (c)
self.connections = ls
targets = map (cs.target, ls)
self.low0 = min (ls)[0]
self.high0 = max (ls)[0] + 1
self.low1 = min (targets)
self.high1 = max (targets) + 1
def iterator (self, low0, high0, low1, high1, state):
if not self.isBoundedBy (low0, high0, low1, high1):
return iter (self.connections)
else:
return self.boundedIterator (low0, high0, low1, high1)
def boundedIterator (self, low0, high0, low1, high1):
for c in self.connections:
if low0 <= c[0] and c[0] < high0 \
and low1 <= c[1] and c[1] < high1:
yield c
csa-0.1.0/csa/valueset.py 0000644 0005140 0005140 00000015001 11735362304 014567 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
from csaobject import *
class ValueSet (CSAObject):
def __init__ (self):
CSAObject.__init__ (self, "valueset")
def __neg__ (self):
return GenericValueSet (lambda i, j: - self (i, j))
def __add__ (self, other):
if not callable (other):
return maybeAffine (other, 1.0, self)
elif isinstance (other, (QuotedValueSet, AffineValueSet)):
return other.__add__ (self)
elif isinstance (other, GenericValueSet):
return GenericValueSet (lambda i, j: self (i, j) + other.function (i, j))
else:
return GenericValueSet (lambda i, j: self (i, j) + other (i, j))
def __radd__ (self, other):
return self.__add__ (other)
def __sub__ (self, other):
return self.__add__ (- other)
def __rsub__ (self, other):
return self.__neg__ ().__add__ (other)
def __mul__ (self, other):
if not callable (other):
return maybeAffine (0.0, other, self)
elif isinstance (other, (QuotedValueSet, AffineValueSet)):
return other.__mul__ (self)
elif isinstance (other, GenericValueSet):
return GenericValueSet (lambda i, j: self (i, j) * other.function (i, j))
else:
return GenericValueSet (lambda i, j: self (i, j) * other (i, j))
def __rmul__ (self, other):
return self.__mul__ (other)
class QuotedValueSet (ValueSet):
def __init__ (self, expression):
ValueSet.__init__ (self)
self.expression = expression
def __call__ (self, i, j):
return self.expression
def __neg__ (self):
return QuotedValueSet (- self.expression)
def __add__ (self, other):
if not callable (other):
return QuotedValueSet (self.expression + other)
elif isinstance (other, QuotedValueSet):
return QuotedValueSet (self.expression + other.expression)
elif isinstance (other, AffineValueSet):
return other.__add__ (self)
else:
return maybeAffine (self.expression, 1.0, other)
def __mul__ (self, other):
if not callable (other):
return QuotedValueSet (self.expression * other)
elif isinstance (other, QuotedValueSet):
return QuotedValueSet (self.expression * other.expression)
elif isinstance (other, AffineValueSet):
return other.__mul__ (self)
else:
return maybeAffine (0.0, self.expression, other)
class GenericValueSet (ValueSet):
def __init__ (self, function):
ValueSet.__init__ (self)
self.function = function
def __call__ (self, i, j):
return self.function (i, j)
def __neg__ (self):
return GenericValueSet (lambda i, j: - self.function (i, j))
def __add__ (self, other):
if not callable (other):
return maybeAffine (other, 1.0, self.function)
elif isinstance (other, (QuotedValueSet, AffineValueSet)):
return other.__add__ (self)
elif isinstance (other, GenericValueSet):
return GenericValueSet (lambda i, j: self.function (i, j) + other.function (i, j))
else:
return GenericValueSet (lambda i, j: self.function (i, j) + other (i, j))
def __mul__ (self, other):
if not callable (other):
return maybeAffine (0.0, other, self.function)
elif isinstance (other, (QuotedValueSet, AffineValueSet)):
return other.__mul__ (self)
elif isinstance (other, GenericValueSet):
return GenericValueSet (lambda i, j: self.function (i, j) * other.function (i, j))
else:
return GenericValueSet (lambda i, j: self.function (i, j) * other (i, j))
class AffineValueSet (ValueSet):
def __init__ (self, constant, coefficient, function):
ValueSet.__init__ (self)
self.const = constant
self.coeff = coefficient
self.func = function
def __call__ (self, i, j):
return self.const + self.coeff * self.func (i, j)
def __neg__ (self):
return maybeAffine (- self.const, - self.coeff, self.func)
def __add__ (self, other):
if not callable (other):
return maybeAffine (self.const + other, self.coeff, self.func)
elif isinstance (other, QuotedValueSet):
return maybeAffine (self.const + other.expression,
self.coeff, self.func)
elif isinstance (other, AffineValueSet):
f = lambda i, j: \
self.const * self.func (i, j) \
+ other.const * other.func (i, j)
return maybeAffine (self.const + other.const,
1.0,
f)
def __mul__ (self, other):
if not callable (other):
return maybeAffine (self.const * other,
self.coeff * other,
self.func)
elif isinstance (other, QuotedValueSet):
return maybeAffine (self.const * other.expression,
self.coeff * other.expression,
self.func)
elif isinstance (other, AffineValueSet):
f = lambda i, j: \
other.const * self.coeff * self.func (i, j) \
+ self.const * other.coeff * other.func (i, j) \
+ self.coeff * other.coeff \
* self.func (i, j) * other.func (i, j)
return maybeAffine (self.const * other.const,
1.0,
f)
def maybeAffine (const, coeff, func):
if coeff == 0.0:
return QuotedValueSet (const)
elif const == 0.0 and coeff == 1.0:
return GenericValueSet (func)
else:
return AffineValueSet (const, coeff, func)
csa-0.1.0/csa/intervalset.py 0000644 0005140 0005140 00000031375 11735362304 015313 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import sys
from csaobject import *
infinity = sys.maxint - 1
# Interval sets are represented as ordered lists of closed intervals
#
class IntervalSet (CSAObject):
tag = 'intervalset'
@staticmethod
# return true if tuple i represents a well-formed interval
def goodInterval (i):
return len (i) == 2 \
and isinstance (i[0], int) \
and isinstance (i[1], int) \
and i[0] <= i[1]
@staticmethod
def xrangeToIntervals (x):
if not x:
return []
elif len (x) == 1:
return [(x[0], x[0])]
elif x[1] - x[0] == 1:
return [(x[0], x[-1])]
else:
return ((e, e) for e in x)
@staticmethod
def coerce (s):
if not isinstance (s, list):
s = [ s ]
res = []
for x in s:
if isinstance (x, tuple):
assert IntervalSet.goodInterval (x), 'malformed interval'
res.append (x)
elif isinstance (x, int):
res.append ((x, x))
elif isinstance (x, xrange):
res += IntervalSet.xrangeToIntervals (x)
else:
raise TypeError, "can't interpret element as interval"
s = res
s.sort ()
# merge intervals
# by construction we know that i[0] <= i[1] for i in s
res = []
N = 0
if s:
lastLower = s[0][0]
lastUpper = s[0][1]
assert lastLower >= 0, 'only positive values allowed'
for i in s[1:]:
assert lastLower < i[0] and lastUpper < i[0], 'intervals overlap'
if i[0] - lastUpper == 1:
lastUpper = i[1]
else:
res.append ((lastLower, lastUpper))
N += 1 + lastUpper - lastLower
lastLower = i[0]
lastUpper = i[1]
res.append ((lastLower, lastUpper))
N += 1 + lastUpper - lastLower
return (res, N)
def __init__ (self, s = [], intervals = None, nIntegers = None):
if intervals:
self.intervals = intervals
self.nIntegers = nIntegers
else:
(self.intervals, self.nIntegers) = self.coerce (s)
def repr (self):
return 'IntervalSet(%r)' % self.intervals
def __len__ (self):
return self.nIntegers
def __contains__ (self, n):
for i in self.intervals:
if n > i[1]:
continue
elif n >= i[0]:
return True
else:
return False
return False
def __iter__ (self):
for i in self.intervals:
for e in xrange (i[0], i[1] + 1):
yield e
def __invert__ (self):
return ComplementaryIntervalSet (intervals = self.intervals, \
nIntegers = self.nIntegers)
def __add__ (self, other):
if not isinstance (other, IntervalSet):
other = IntervalSet (other)
return self.union (other)
def __radd__ (self, other):
return IntervalSet (other).union (self)
def __sub__ (self, other):
if not isinstance (other, IntervalSet):
other = IntervalSet (other)
return self.intersection (~other)
def __rsub__ (self, other):
return IntervalSet (other).intersection (~self)
def __mul__ (self, other):
if not isinstance (other, IntervalSet):
other = IntervalSet (other)
return self.intersection (other)
def __rmul__ (self, other):
return IntervalSet (other).intersection (self)
def finite (self):
return True
def shift (self, N):
if not self or N == 0:
return self
intervals = []
nIntegers = self.nIntegers
for (i, j) in self.intervals:
i += N
j += N
if i >= 0:
intervals.append ((i, j))
elif j >= 0:
intervals.append ((0, j))
nIntegers += i
return IntervalSet (intervals = intervals, nIntegers = nIntegers)
def intervalIterator (self):
return iter (self.intervals)
def boundedIterator (self, low, high):
iterator = iter (self.intervals)
i = iterator.next ()
while i[1] < low:
i = iterator.next ()
while i[0] < high:
for e in xrange (max (low, i[0]), min (i[1] + 1, high)):
yield e
i = iterator.next ()
def count (self, low, high):
iterator = iter (self.intervals)
c = 0
try:
i = iterator.next ()
while i[1] < low:
i = iterator.next ()
while i[0] < high:
c += min (i[1] + 1, high) - max (low, i[0])
i = iterator.next ()
except StopIteration:
pass
return c
def min (self):
return self.intervals[0][0]
def max (self):
return self.intervals[-1][1]
def intersection (self, other):
res = []
N = 0
iter0 = self.intervalIterator ()
iter1 = other.intervalIterator ()
try:
i0 = iter0.next ()
i1 = iter1.next ()
while True:
if i0[1] <= i1[1]:
if i0[1] >= i1[0]:
lower = max (i0[0], i1[0])
res.append ((lower, i0[1]))
N += 1 + i0[1] - lower
i0 = iter0.next ()
else:
if i1[1] >= i0[0]:
lower = max (i0[0], i1[0])
res.append ((lower, i1[1]))
N += 1 + i1[1] - lower
i1 = iter1.next ()
except StopIteration:
pass
iset = IntervalSet ()
iset.intervals = res
iset.nIntegers = N
return iset
def union (self, other):
if isinstance (other, ComplementaryIntervalSet):
return ~(~self).intersection (~other)
iset = IntervalSet ()
if not other.nIntegers:
iset.intervals = list (self.intervals)
iset.nIntegers = self.nIntegers
return iset
if not self.nIntegers:
iset.intervals = list (other.intervals)
iset.nIntegers = other.nIntegers
return iset
res = []
N = 0
iter0 = self.intervalIterator ()
iter1 = other.intervalIterator ()
i0 = iter0.next ()
i1 = iter1.next ()
if i0[0] <= i1[0]:
(lower, upper) = i0
else:
(lower, upper) = i1
try:
while True:
if i0[0] <= i1[0]:
if i0[0] <= upper + 1:
if i0[1] > upper:
upper = i0[1]
else:
res.append ((lower, upper))
N += 1 + upper - lower
(lower, upper) = i0
try:
i0 = iter0.next ()
except StopIteration:
if i1[0] <= upper + 1:
if i1[1] > upper:
upper = i1[1]
i1 = (lower, upper)
else:
res.append ((lower, upper))
N += 1 + upper - lower
while True:
res.append (i1)
N += 1 + i1[1] - i1[0]
i1 = iter1.next ()
else:
if i1[0] <= upper + 1:
if i1[1] > upper:
upper = i1[1]
else:
res.append ((lower, upper))
N += 1 + upper - lower
(lower, upper) = i1
try:
i1 = iter1.next ()
except StopIteration:
if i0[0] <= upper + 1:
if i0[1] > upper:
upper = i0[1]
i0 = (lower, upper)
else:
res.append ((lower, upper))
N += 1 + upper - lower
while True:
res.append (i0)
N += 1 + i0[1] - i0[0]
i0 = iter0.next ()
except StopIteration:
pass
iset.intervals = res
iset.nIntegers = N
return iset
def _to_xml (self):
intervals = [ E ('interval', E ('cn', str (i)), E ('cn', str (j)))
for (i, j) in self.intervals ]
return E (IntervalSet.tag, *intervals)
@classmethod
def from_xml (cls, element, env = {}):
intervals = []
for ivalElement in element.getchildren ():
ival = ivalElement.getchildren ()
intervals.append ((int (ival[0].text), int (ival[1].text)))
return IntervalSet (intervals)
CSAObject.tag_map[CSA + IntervalSet.tag] = (IntervalSet, CUSTOM)
class ComplementaryIntervalSet (IntervalSet):
def __init__ (self, s = [], intervals = None, nIntegers = None):
IntervalSet.__init__ (self, s, intervals, nIntegers)
def repr (self):
if not self.intervals:
return 'N'
else:
return '~IntervalSet(%r)' % self.intervals
def __nonzero__ (self):
return True
def __len__ (self):
raise RuntimeError, 'ComplementaryIntervalSet has infinite length'
def __contains__ (self, n):
for i in self.intervals:
if n < i[0]:
continue
elif n <= i[1]:
return False
else:
return True
return True
def __iter__ (self):
raise RuntimeError, "can't interate over ComplementaryIntervalSet"
def __invert__ (self):
return IntervalSet (intervals = self.intervals, \
nIntegers = self.nIntegers)
def finite (self):
return False
def shift (self, N):
iset = IntervalSet (intervals = self.intervals, \
nIntegers = self.nIntegers).shift (N)
return ComplementaryIntervalSet (intervals = iset.intervals, \
nIntegers = iset.nIntegers)
def intervalIterator (self):
start = 0
for i in self.intervals:
if i[0] > 0:
yield (start, i[0] - 1)
start = i[1] + 1
yield (start, infinity)
def boundedIterator (self, low, high):
raise RuntimeError, "can't interate over ComplementaryIntervalSet"
def count (self, low, high):
iterator = iter (self.intervals)
c = 0
prev = low
try:
i = iterator.next ()
while i[1] < low:
i = iterator.next ()
while i[0] < high:
c += i[0] - prev
prev = i[1] + 1
i = iterator.next ()
except StopIteration:
pass
if prev < high:
c += high - prev
return c
def min (self):
if not self.intervals or self.intervals[0][0] > 0:
return 0
else:
return self.intervals[0][1] + 1
def max (self):
raise RuntimeError, 'the maximum of a ComplementaryIntervalSet is infinity'
def intersection (self, other):
if isinstance (other, ComplementaryIntervalSet):
return ~(~self).union (~other)
else:
return IntervalSet.intersection (self, other)
def union (self, other):
return ~(~self).intersection (~other)
def _to_xml (self):
if not self.intervals:
return E ('N')
else:
return E ('apply', E ('complement'), IntervalSet._to_xml (self))
N = ComplementaryIntervalSet ([])
CSAObject.tag_map[CSA + 'N'] = (N, SINGLETON)
csa-0.1.0/csa/closure.py 0000644 0005140 0005140 00000003160 11735362304 014416 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
from csaobject import *
import inspect
try:
from lxml import etree
from lxml.builder import E
except ImportError:
pass
class Closure (CSAObject):
tag = 'closure'
name = tag
def __init__ (self, formals, e):
self.formals = formals
self.etree = e
@staticmethod
def formalToXML (formal):
return E ('bvar', E ('ci', formal))
def _to_xml (self):
formals = map (Closure.formalToXML, self.formals)
return E ('bind', E ('closure'), *formals + [ self.etree ])
def __call__ (self, *args):
assert len (args) == len (self.formals), "arguments %s don't match formals %s" % (args, self.formals)
bindings = {}
for (formal, arg) in map (None, self.formals, args):
bindings[formal] = arg
return CSAObject.from_xml (self.etree, bindings)
registerTag (Closure.tag, Closure, BINDOPERATOR)
csa-0.1.0/csa/plot.py 0000644 0005140 0005140 00000006076 11735362304 013731 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import numpy as _numpy
import matplotlib
import matplotlib.pyplot as _plt
import elementary
# This function was autogenerated by boilerplate.py. Do not edit as
# changes will be lost
def inverseGray():
'''
set the default colormap to gray and apply to current image if any.
See help(colormaps) for more information
'''
_plt.rc('image', cmap='gray_r')
im = _plt.gci()
if im is not None:
im.set_cmap(_plt.cm.gray_r)
_plt.draw_if_interactive()
def show (cset, N0 = 30, N1 = None):
N1 = N0 if N1 == None else N1
_plt.clf ()
_plt.axis ('equal')
a = _numpy.zeros ((N0, N1))
for (i, j) in elementary.cross (xrange (N0), xrange (N1)) * cset:
a[i,j] += 1.0
_plt.imshow (a, interpolation='nearest')
_plt.show ()
def gplotsel2d (g, cset, source = elementary.N, target = elementary.N, N0 = 900, N1 = None, value = None, range=[], lines = True):
N1 = N0 if N1 == None else N1
_plt.clf ()
_plt.axis ('equal')
gplot2d (g, N1, color = 'grey', show = False)
cset = elementary.cross (source, target) * cset
N = len (cset)
if lines:
marker = 'ro-'
else:
marker = 'ro'
if elementary.arity (cset):
if value != None:
if range:
normalize = matplotlib.colors.Normalize (*range)
else:
normalize = matplotlib.colors.Normalize ()
normalize.autoscale ([v[value] for (i, j, v) in cset.c])
cmap = matplotlib.cm.get_cmap ()
for (i, j, v) in cset.c:
color = cmap (normalize (v[value]))
_plt.plot ([g (i)[0], g (j)[0]], [g (i)[1], g (j)[1]], \
marker, color = color, mfc = color)
else:
for (i, j, v) in cset.c:
_plt.plot ([g (i)[0], g (j)[0]], [g (i)[1], g (j)[1]], marker)
else:
for (i, j) in cset:
_plt.plot ([g (i)[0], g (j)[0]], [g (i)[1], g (j)[1]], marker)
_plt.show ()
def gplot2d (g, N, color = None, show = True):
if show:
_plt.clf ()
_plt.axis ('equal')
x = []
y = []
for i in xrange (0, N):
pos = g (i)
x.append (pos[0])
y.append (pos[1])
if color != None:
_plt.plot (x, y, 'o', color = color)
else:
_plt.plot (x, y, 'bo')
if show:
_plt.show ()
#del numpy, plt
csa-0.1.0/csa/_elementary.py 0000644 0005140 0005140 00000026042 11735362304 015252 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import random
import numpy
import copy
import connset as cs
import intervalset as iset
from csaobject import *
class FullMask (cs.IntervalSetMask):
tag = 'full'
def __init__ (self):
cs.IntervalSetMask.__init__ (self, iset.N, iset.N)
self.name = FullMask.tag
CSAObject.tag_map[CSA + FullMask.tag] = (self, SINGLETON)
def __call__ (self, N0, N1 = None):
if N1 == None:
N1 = N0
return cs.FiniteISetMask (iset.IntervalSet ((0, N0 - 1)), \
iset.IntervalSet ((0, N1 - 1)))
class OneToOne (cs.Mask):
tag = 'oneToOne'
def __init__ (self):
cs.Mask.__init__ (self)
self.name = OneToOne.tag
CSAObject.tag_map[CSA + OneToOne.tag] = (self, SINGLETON)
def iterator (self, low0, high0, low1, high1, state):
for i in xrange (max (low0, low1), min (high0, high1)):
yield (i, i)
class ConstantRandomMask (cs.Mask):
tag = 'randomMask'
def __init__ (self, p):
cs.Mask.__init__ (self)
self.p = p
self.state = random.getstate ()
self.name = ConstantRandomMask.tag
def startIteration (self, state):
random.setstate (self.state)
return self
def iterator (self, low0, high0, low1, high1, state):
for j in xrange (low1, high1):
for i in xrange (low0, high0):
if random.random () < self.p:
yield (i, j)
def repr (self):
return 'random(%s)' % self.p
def _to_xml (self):
return CSAObject.apply (ConstantRandomMask.tag, self.p)
registerTag (ConstantRandomMask.tag, ConstantRandomMask, 1)
class SampleNRandomOperator (cs.Operator):
tag = 'random_N'
def __init__ (self, N):
self.N = N
def __mul__ (self, other):
assert isinstance (other, cs.Finite) \
and isinstance (other, cs.Mask), \
'expected finite mask'
return SampleNRandomMask (self.N, other)
def repr (self):
return 'random(N = %s)' % self.N
def _to_xml (self):
return CSAObject.apply (SampleNRandomOperator.tag, self.N)
registerTag (SampleNRandomOperator.tag, SampleNRandomOperator, 1)
class SampleNRandomMask (cs.Finite,cs.Mask):
# The algorithm based on first sampling the number of connections
# per partition has been arrived at through discussions with Hans
# Ekkehard Plesser.
#
def __init__ (self, N, mask):
cs.Mask.__init__ (self)
self.N = N
assert isinstance (mask, cs.FiniteISetMask), \
'SampleNRandomMask currently only operates on FiniteISetMask:s'
self.mask = mask
self.randomState = random.getstate ()
self.npRandomState = numpy.random.get_state ()
def bounds (self):
return self.mask.bounds ()
def startIteration (self, state):
obj = copy.copy (self) # local state: N, N0, perTarget, sources
random.setstate (self.randomState)
obj.isPartitioned = False
if 'partitions' in state:
obj.isPartitioned = True
partitions = map (self.mask.intersection, state['partitions'])
sizes = map (len, partitions)
total = sum (sizes)
# The following yields the same result on all processes.
# We should add a seed function to the CSA.
if 'seed' in state:
seed = state['seed']
else:
seed = 'SampleNRandomMask'
numpy.random.seed (hash (seed))
N = numpy.random.multinomial (self.N, numpy.array (sizes) \
/ float (total))
obj.N = N[state['selected']]
obj.mask = partitions[state['selected']]
assert isinstance (obj.mask, cs.FiniteISetMask), \
'SampleNRandomMask iterator only handles finite IntervalSetMask partitions'
obj.mask = obj.mask.startIteration (state)
obj.N0 = len (obj.mask.set0)
obj.lastBound0 = False
N1 = len (obj.mask.set1)
numpy.random.set_state (self.npRandomState)
obj.perTarget = numpy.random.multinomial (obj.N, [1.0 / N1] * N1)
return obj
def iterator (self, low0, high0, low1, high1, state):
m = self.mask.set1.count (0, low1)
if self.isPartitioned and m > 0:
# "replacement" for a proper random.jumpahead (n)
# This is required so that different partitions of this
# mask aren't produced using the same stream of random
# numbers.
random.seed (random.getrandbits (32) + m)
if self.lastBound0 != (low0, high0):
self.lastBound0 = (low0, high0)
self.sources = []
for i in self.mask.set0.boundedIterator (low0, high0):
self.sources.append (i)
nSources = len (self.sources)
for j in self.mask.set1.boundedIterator (low1, high1):
s = []
for k in xrange (0, self.perTarget[m]):
i = random.randint (0, self.N0 - 1)
if i < nSources:
s.append (self.sources[i])
s.sort ()
for i in s:
yield (i, j)
m += 1
def repr (self):
return self._repr_applyop ('random(N=%s)' % self.N, self.mask)
def _to_xml (self):
return E ('apply',
E ('times'),
CSAObject.apply (SampleNRandomOperator.tag, self.N),
self.mask._to_xml ())
class FanInRandomOperator (cs.Operator):
tag = 'random_fanIn'
def __init__ (self, fanIn):
self.fanIn = fanIn
def __mul__ (self, other):
assert isinstance (other, cs.Finite) \
and isinstance (other, cs.Mask), \
'expected finite mask'
return FanInRandomMask (self.fanIn, other)
def repr (self):
return 'random(fanIn=%s)' % self.fanIn
def _to_xml (self):
return CSAObject.apply (FanInRandomOperator.tag, self.fanIn)
registerTag (FanInRandomOperator.tag, FanInRandomOperator, 1)
# This code is copied and modified from SampleNRandomMask
# *fixme* refactor code and eliminate code duplication
class FanInRandomMask (cs.Finite, cs.Mask):
# The algorithm based on first sampling the number of connections
# per partition has been arrived at through discussions with Hans
# Ekkehard Plesser.
#
def __init__ (self, fanIn, mask):
cs.Mask.__init__ (self)
self.fanIn = fanIn
assert isinstance (mask, cs.FiniteISetMask), \
'FanInRandomMask currently only operates on FiniteISetMask:s'
self.mask = mask
self.randomState = random.getstate ()
def bounds (self):
return self.mask.bounds ()
def startIteration (self, state):
obj = copy.copy (self) # local state: N, N0, perTarget, sources
random.setstate (self.randomState)
obj.isPartitioned = False
if 'partitions' in state:
obj.isPartitioned = True
partitions = map (self.mask.intersection, state['partitions'])
# The following yields the same result on all processes.
# We should add a seed function to the CSA.
if 'seed' in state:
seed = state['seed']
else:
seed = 'FanInRandomMask'
# Numpy.random.seed requires unsigned integer
numpy.random.seed (abs (hash (seed)))
selected = state['selected']
obj.mask = partitions[selected]
assert isinstance (obj.mask, cs.FiniteISetMask), \
'FanInRandomMask iterator only handles finite IntervalSetMask partitions'
obj.mask = obj.mask.startIteration (state)
obj.N0 = len (obj.mask.set0)
obj.lastBound0 = False
if obj.isPartitioned:
obj.perTarget = []
for j in obj.mask.set1:
size = 0
sourceDist = numpy.zeros (len (partitions))
for k in xrange (len (partitions)):
if j in partitions[k].set1:
sourceDist[k] = len (partitions[k].set0)
sourceDist /= sum (sourceDist)
dist = numpy.random.multinomial (self.fanIn, sourceDist)
obj.perTarget.append (dist[selected])
else:
obj.perTarget = [self.fanIn] * len (obj.mask.set1)
return obj
def iterator (self, low0, high0, low1, high1, state):
m = self.mask.set1.count (0, low1)
if self.isPartitioned and m > 0:
# "replacement" for a proper random.jumpahead (n)
# This is required so that different partitions of this
# mask aren't produced using the same stream of random
# numbers.
random.seed (random.getrandbits (32) + m)
if self.lastBound0 != (low0, high0):
self.lastBound0 = (low0, high0)
self.sources = []
for i in self.mask.set0.boundedIterator (low0, high0):
self.sources.append (i)
nSources = len (self.sources)
for j in self.mask.set1.boundedIterator (low1, high1):
s = []
for k in xrange (0, self.perTarget[m]):
i = random.randint (0, self.N0 - 1)
if i < nSources:
s.append (self.sources[i])
s.sort ()
for i in s:
yield (i, j)
m += 1
def repr (self):
return self._repr_applyop ('random(fanIn=%s)' % self.fanIn, self.mask)
def _to_xml (self):
return E ('apply',
E ('times'),
CSAObject.apply (FanInRandomOperator.tag, self.fanIn),
self.mask._to_xml ())
class FanOutRandomOperator (cs.Operator):
tag = 'random_fanOut'
def __init__ (self, fanOut):
self.fanOut = fanOut
def __mul__ (self, other):
assert isinstance (other, cs.Finite) \
and isinstance (other, cs.Mask), \
'expected finite mask'
return FanInRandomMask (self.fanOut, other.transpose ()).transpose ()
def repr (self):
return 'random(fanOut=%s)' % self.fanOut
def _to_xml (self):
return CSAObject.apply (FanOutRandomOperator.tag, self.fanOut)
registerTag (FanOutRandomOperator.tag, FanOutRandomOperator, 1)
csa-0.1.0/csa/__init__.py 0000644 0005140 0005140 00000002032 11735362304 014476 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
from version import __version__
from connset import Mask
from connset import ConnectionSet
from elementary import *
#from operators import *
#from arithmetic import *
from misc import *
from geometry import *
from csaobject import parse, from_xml
from plot import *
from closure import *
from conngen import *
csa-0.1.0/csa/elementary.py 0000644 0005140 0005140 00000004600 11735362304 015107 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import sys as _sys
import intervalset as _iset
import connset as _cs
import valueset as _vs
import _elementary
import _misc
from csaobject import registerTag
# Connection-Set constructor
#
def cset (mask, *valueSets):
if valueSets:
c = _cs.ExplicitCSet (mask, *valueSets)
return _cs.ConnectionSet (c)
else:
return mask
registerTag (_cs.CSet.tag, cset, 1)
# Selectors
#
def mask (obj):
cset = _cs.coerceCSet (obj)
return cset.mask ()
def value (obj, k):
assert isinstance (obj, _cs.ConnectionSet), 'expected connection-set'
return obj.c.value (k)
def arity (obj):
if isinstance (obj, _cs.ConnectionSet):
return obj.c.arity
else:
return 0
# Value-set constructor
#
def vset (obj):
if not callable (obj):
return _vs.QuotedValueSet (obj)
else:
return _vs.GenericValueSet (obj)
# Intervals
#
def ival (beg, end):
return _iset.IntervalSet ((beg, end))
N = _iset.N
# Cartesian product
#
def cross (set0, set1):
return _cs.intervalSetMask (set0, set1)
# Elementary masks
#
empty = cross ([], [])
full = _elementary.FullMask ()
oneToOne = _elementary.OneToOne ()
random = _misc.Random ()
# Support for parallel simulator
#
def partition (c, masks, selected, seed = None):
if isinstance (c, _cs.Mask):
return _cs.MaskPartition (c, masks, selected, seed)
elif isinstance (c, _cs.ConnectionSet):
return _cs.ConnectionSet (_cs.CSetPartition (c, masks, selected, seed))
# Utilities
#
def tabulate (c):
for x in c:
print x[0],
for e in x[1:]:
print '\t', e,
print
#del _elementary, cs, sys # not for export
csa-0.1.0/csa/connset.py 0000644 0005140 0005140 00000102570 11735362304 014420 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import copy
import intervalset
import valueset
from csaobject import *
# This is the fundamental connection-set class
# which is also the base class for masks
#
class CSet (CSAObject):
tag = 'cset'
def __init__ (self, mask, *valueSets):
CSAObject.__init__ (self, "icset");
self._mask = mask
self.valueSets = list (valueSets)
self.arity = len (self.valueSets)
def repr (self, name = None):
if self.arity:
if not name:
name = self.name
vreprs = []
for k in xrange (self.arity):
v = self.value (k)
if isinstance (v, CSAObject):
vreprs += ", %s" % v.repr ()
else:
vreprs += ", %s" % v
return "%s (%s%s)" % (self.name, self.mask (), "".join (vreprs))
else:
if self.mask () == self:
return self.name
else:
return "%s (%s)" % (self.name, self.mask ())
def mask (self):
#*fixme* remove this condition?
if self._mask == None:
self._mask = self.makeMask ()
return self._mask
def value (self, k):
if self.valueSets[k] == None:
self.valueSets[k] = self.makeValueSet (k)
return self.valueSets[k]
def makeValueSet (self, k):
if isFinite (self.mask ()):
return self.makeFiniteValueSet (k, self.mask ().bounds ())
raise RuntimeError, "don't know how to return value set for this connection-set"
def makeFiniteValueSet (self, k, bounds):
raise RuntimeError, "don't know how to return value set for this connection-set"
def __len__ (self):
return len (self.mask ())
def __iter__ (self):
# this code is used for full connection sets
if isFinite (self.mask ()):
state = State ()
obj = self.startIteration (state)
(low0, high0, low1, high1) = self.bounds ()
return obj.iterator (low0, high0, low1, high1, state)
else:
raise RuntimeError, 'attempt to retrieve iterator over infinite connection-set'
def bounds (self):
return self.mask ().bounds ()
def startIteration (self, state):
obj = copy.copy (self)
obj._mask = self.mask ().startIteration (state)
return obj
def iterator (self, low0, high0, low1, high1, state):
for (i, j) in self._mask.iterator (low0, high0, low1, high1, state):
yield (i, j, [ v (i, j) for v in self.valueSets ])
def multisetSum (self, other):
return CSetMultisetSum (self, other)
def intersection (self, other):
assert isinstance (other, Mask), 'expected Mask operand'
return SubCSet (self,
self.mask ().intersection (other), *self.valueSets)
def difference (self, other):
assert isinstance (other, Mask), 'expected Mask operand'
return SubCSet (self, self.mask ().difference (other), *self.valueSets)
# This is the connection-set wrapper class which has as its only purpose
# to wrap non mask connection-sets so that the same code can implement
# connection-sets of different arity. Some type dispatch is also done here.
#
class ConnectionSet (CSAObject):
def __init__ (self, c):
CSAObject.__init__ (self, "cset")
self.c = c
def repr (self):
return self.c.repr ()
def __len__ (self):
return len (self.c)
def __iter__ (self):
return ConnectionSet.iterators[self.c.arity] (self)
def iter0 (self):
assert False, 'Should not have executed ConnectionSet.iter0'
def iter1 (self):
for (i, j, vs) in iter (self.c):
(v0,) = vs
yield (i, j, v0)
def iter2 (self):
for (i, j, vs) in iter (self.c):
(v0, v1) = vs
yield (i, j, v0, v1)
def iter3 (self):
for (i, j, vs) in iter (self.c):
(v0, v1, v2) = vs
yield (i, j, v0, v1, v2)
def __add__ (self, other):
if isNumber (other):
return ConnectionSet (self.c.addScalar (other))
else:
return ConnectionSet (self.c.multisetSum (coerceCSet (other)))
def __radd__ (self, other):
return self.__add__ (other)
def __sub__ (self, other):
if isNumber (other):
return ConnectionSet (self.c.addScalar (- other))
else:
return ConnectionSet (self.c.difference (coerceCSet (other)))
def __rsub__ (self, other):
return ConnectionSet (self.c.__neg__ ().addScalar (other))
def __mul__ (self, other):
if isNumber (other):
return ConnectionSet (self.c.mulScalar (other))
else:
return ConnectionSet (self.c.intersection (coerceCSet (other)))
def __rmul__ (self, other):
return self.__mul__ (other)
ConnectionSet.iterators = [ ConnectionSet.iter0, \
ConnectionSet.iter1, \
ConnectionSet.iter2, \
ConnectionSet.iter3 ]
# Some helper functions
def source (x):
return x[0]
def target (x):
return x[1]
def isNumber (x):
return isinstance (x, (int, long, float, complex))
def coerceCSet (obj):
if isinstance (obj, list):
return ExplicitMask (obj)
elif isinstance (obj, ConnectionSet):
return obj.c
assert isinstance (obj, Mask), 'expected connection-set'
return obj
def valueSet (obj):
return valueset.QuotedValueSet (obj)
def coerceValueSet (obj):
if callable (obj):
return obj
else:
return valueSet (obj)
def isFinite (x):
return isinstance (x, Finite)
def isEmpty (x):
iterator = iter (x.mask ())
try:
iterator.next ()
return False
except StopIteration:
return True
def transpose (obj):
return obj.transpose ()
# This is the fundamental mask class
#
class Mask (CSet):
def __init__ (self):
CSet.__init__ (self, self)
def __len__ (self):
N = 0
for c in self:
N += 1
return N
def __iter__ (self):
raise RuntimeError, 'attempt to retrieve iterator over infinite mask'
def __add__ (self, other):
return self.multisetSum (other)
def __sub__ (self, other):
return self.difference (other)
def __mul__ (self, other):
if isinstance (other, Mask):
return self.intersection (other)
elif isinstance (other, list):
return self.intersection (ExplicitMask (other))
elif isinstance (other, ConnectionSet):
return other.__mul__ (self)
else:
return NotImplemented
def __rmul__ (self, other):
if isinstance (other, list):
return self.intersection (ExplicitMask (other))
else:
return NotImplemented
def __invert__ (self):
return self.complement ()
def transpose (self):
assert isFinite (self), \
'transpose currently only supports finite masks'
return TransposedMask (self)
def shift (self, M, N):
return shiftedMask (self, M, N)
def startIteration (self, state):
# default action:
return self
def iterator (self, low0, high0, low1, high1, state):
return NotImplemented
def multisetSum (self, other):
if isFinite (self) and isFinite (other):
return FiniteMaskMultisetSum (self, other)
else:
return MaskMultisetSum (self, other)
def intersection (self, other):
# IntervalSetMask implements a specialized version of intersection
if isinstance (other, IntervalSetMask):
return other.intersection (self)
# Generate Finite instances if either operand is finite
elif isFinite (self):
return FiniteMaskIntersection (self, other)
elif isFinite (other):
return FiniteMaskIntersection (other, self)
else:
return MaskIntersection (self, other)
def complement (self):
return MaskComplement (self)
def difference (self, other):
return MaskDifference (self, other)
class Finite (object):
def bounds (self):
return NotImplemented
def maxBounds (self, b1, b2):
return (min (b1[0], b2[0]), max (b1[1], b2[1]),
min (b1[2], b2[2]), max (b1[3], b2[3]))
def __iter__ (self):
state = State ()
obj = self.startIteration (state)
(low0, high0, low1, high1) = self.bounds ()
return obj.iterator (low0, high0, low1, high1, state)
class FiniteMask (Finite, Mask):
def __init__ (self):
Mask.__init__ (self)
self.low0 = 0
self.high0 = 0
self.low1 = 0
self.high1 = 0
def bounds (self):
return (self.low0, self.high0, self.low1, self.high1)
def isBoundedBy (self, low0, high0, low1, high1):
return low0 > self.low0 or high0 < self.high0 \
or low1 > self.low1 or high1 < self.high1
# not used
class NoParIterator ():
def __init__ (self):
self.subIterator = False
def iterator (self, low0, high0, low1, high1, state):
print low0, high0, low1, high1
if not self.subIterator:
self.subIterator = self.noParIterator (state)
self.lastC = self.subIterator.next ()
c = self.lastC
while c[1] < low1:
c = self.subIterator.next ()
while c[1] < high1:
j = c[1]
while c[1] == j and c[0] < low0:
c = self.subIterator.next ()
while c[1] == j and c[0] < high0:
yield c
c = self.subIterator.next ()
while c[1] == j:
c = self.subIterator.next ()
self.lastC = c
class BinaryMask (BinaryCSAObject, Mask):
def __init__ (self, operator, op1, op2, precedence):
Mask.__init__ (self)
BinaryCSAObject.__init__ (self, operator, op1, op2, precedence)
def startIteration (self, state):
obj = copy.copy (self)
obj.op1 = self.op1.startIteration (state)
obj.op2 = self.op2.startIteration (state)
return obj
class MaskIntersection (BinaryMask):
def __init__ (self, op1, op2):
BinaryMask.__init__ (self, '*', op1, op2, 1)
def iterator (self, low0, high0, low1, high1, state):
iter1 = self.op1.iterator (low0, high0, low1, high1, state)
iter2 = self.op2.iterator (low0, high0, low1, high1, state)
(i1, j1) = iter1.next ()
(i2, j2) = iter2.next ()
while True:
if (j1, i1) < (j2, i2):
(i1, j1) = iter1.next ()
elif (j2, i2) < (j1, i1):
(i2, j2) = iter2.next ()
else:
yield (i1, j1)
(i1, j1) = iter1.next ()
(i2, j2) = iter2.next ()
class FiniteMaskIntersection (Finite, MaskIntersection):
def __init__ (self, op1, op2):
assert isFinite (op1)
MaskIntersection.__init__ (self, op1, op2)
def bounds (self):
return self.op1.bounds ()
class MaskMultisetSum (BinaryMask):
def __init__ (self, op1, op2):
BinaryMask.__init__ (self, "+", op1, op2, 0)
def iterator (self, low0, high0, low1, high1, state):
iter1 = self.op1.iterator (low0, high0, low1, high1, state)
iter2 = self.op2.iterator (low0, high0, low1, high1, state)
try:
(i1, j1) = iter1.next ()
except StopIteration:
(i2, j2) = iter2.next ()
while True:
yield (i2, j2)
(i2, j2) = iter2.next ()
try:
(i2, j2) = iter2.next ()
except StopIteration:
while True:
yield (i1, j1)
(i1, j1) = iter1.next ()
while True:
i1s = i1
j1s = j1
while (j1, i1) <= (j2, i2):
yield (i1, j1)
try:
(i1, j1) = iter1.next ()
except StopIteration:
while True:
yield (i2, j2)
(i2, j2) = iter2.next ()
while (j2, i2) <= (j1s, i1s):
yield (i2, j2)
try:
(i2, j2) = iter2.next ()
except StopIteration:
while True:
yield (i1, j1)
(i1, j1) = iter1.next ()
class FiniteMaskMultisetSum (Finite, MaskMultisetSum):
def __init__ (self, op1, op2):
assert isFinite (op1) and isFinite (op2)
MaskMultisetSum.__init__ (self, op1, op2)
def bounds (self):
return self.maxBounds (self.op1.bounds (), self.op2.bounds ())
class MaskDifference (BinaryMask):
def __init__ (self, op1, op2):
BinaryMask.__init__ (self, "-", op1, op2, 0)
def iterator (self, low0, high0, low1, high1, state):
iter1 = self.op1.iterator (low0, high0, low1, high1, state)
iter2 = self.op2.iterator (low0, high0, low1, high1, state)
(i1, j1) = iter1.next ()
(i2, j2) = iter2.next ()
while True:
if (j1, i1) < (j2, i2):
yield (i1, j1)
(i1, j1) = iter1.next ()
continue
elif (i1, j1) == (i2, j2):
(i1, j1) = iter1.next ()
try:
(i2, j2) = iter2.next ()
except StopIteration:
while True:
yield (i1, j1)
(i1, j1) = iter1.next ()
def cmpPostOrder (c0, op1):
return cmp ((c0[1], c0[0]), (op1[1], op1[0]))
class ExplicitMask (FiniteMask):
def __init__ (self, connections):
FiniteMask.__init__ (self)
self.connections = list (connections)
self.connections.sort (cmpPostOrder)
if connections:
self.low0 = min ((i for (i, j) in self.connections))
self.high0 = max ((i for (i, j) in self.connections)) + 1
self.low1 = self.connections[0][1]
self.high1 = self.connections[-1][1] + 1
def __len__ (self):
return len (self.connections)
def iterator (self, low0, high0, low1, high1, state):
if not self.isBoundedBy (low0, high0, low1, high1):
return iter (self.connections)
else:
return self.boundedIterator (low0, high0, low1, high1, state)
def boundedIterator (self, low0, high0, low1, high1, state):
iterator = iter (self.connections)
(i, j) = iterator.next ()
while j < low1:
(i, j) = iterator.next ()
while j < high1:
if low0 <= i and i < high0:
yield (i, j)
(i, j) = iterator.next ()
class IntervalSetMask (Mask):
tag = 'cross'
def __init__ (self, set0, set1):
Mask.__init__ (self)
self.set0 = set0
self.set1 = set1
@staticmethod
def _sets_to_repr (set0, set1):
return 'cross(%s, %s)' % (set0.repr (), set1.repr ())
def repr (self):
return self._sets_to_repr (self.set0, self.set1)
def __contains__ (self, c):
return c[0] in self.set0 and c[1] in self.set1
def transpose (self):
return IntervalSetMask (self.set1, self.set0)
def shift (self, M, N):
return IntervalSetMask (self.set0.shift (M), self.set1.shift (N))
def iterator (self, low0, high0, low1, high1, state):
iterator1 = self.set1.intervalIterator ()
i1 = iterator1.next ()
while i1[1] < low1:
i1 = iterator1.next ()
while i1[0] < high1:
for j in xrange (max (i1[0], low1), min (i1[1] + 1, high1)):
iterator0 = self.set0.intervalIterator ()
try:
i0 = iterator0.next ()
while i0[1] < low0:
i0 = iterator0.next ()
if i0[1] < high0:
for i in xrange (max (i0[0], low0), i0[1] + 1):
yield (i, j)
i0 = iterator0.next ()
while i0[1] < high0:
for i in xrange (i0[0], i0[1] + 1):
yield (i, j)
i0 = iterator0.next ()
for i in xrange (i0[0], min (i0[1] + 1, high0)):
yield (i, j)
else:
for i in xrange (max (i0[0], low0), min (i0[1] + 1, high0)):
yield (i, j)
except StopIteration:
pass
i1 = iterator1.next ()
def intersection (self, other):
if isinstance (other, IntervalSetMask):
set0 = self.set0.intersection (other.set0)
set1 = self.set1.intersection (other.set1)
return intervalSetMask (set0, set1)
else:
return ISetBoundedMask (self.set0, self.set1, other)
def multisetSum (self, other):
if isinstance (other, IntervalSetMask):
if not self.set0.intersection (other.set0) \
or not self.set1.intersection (other.set1):
set0 = self.set0.union (other.set0)
set1 = self.set1.union (other.set1)
return intervalSetMask (set0, set1)
else:
raise RuntimeError, \
'sums of overlapping IntervalSetMask:s not yet supported'
else:
return FiniteMask.multisetSum (self, other)
@staticmethod
def _sets_to_xml (set0, set1):
return CSAObject.apply (IntervalSetMask.tag, set0, set1)
def _to_xml (self):
return self._sets_to_xml (self.set0, self.set1)
class FiniteISetMask (FiniteMask, IntervalSetMask):
def __init__ (self, set0, set1):
FiniteMask.__init__ (self)
IntervalSetMask.__init__ (self, set0, set1)
if self.set0 and self.set1:
self.low0 = self.set0.min ()
self.high0 = self.set0.max () + 1
self.low1 = self.set1.min ()
self.high1 = self.set1.max () + 1
def __len__ (self):
return len (self.set0) * len (self.set1)
def transpose (self):
return FiniteISetMask (self.set1, self.set0)
def shift (self, M, N):
return FiniteISetMask (self.set0.shift (M), self.set1.shift (N))
def iterator (self, low0, high0, low1, high1, state):
if not self.isBoundedBy (low0, high0, low1, high1):
return self.simpleIterator ()
else:
return IntervalSetMask.iterator (self, low0, high0, low1, high1, state)
def simpleIterator (self):
for j in self.set1:
for i in self.set0:
yield (i, j)
class FiniteSourcesISetMask (IntervalSetMask):
def __init__ (self, set0, set1):
IntervalSetMask.__init__ (self, set0, set1)
def transpose (self):
return FiniteTargetsISetMask (self.set1, self.set0)
def shift (self, M, N):
return FiniteSourcesISetMask (self.set0.shift (M), \
self.set1.shift (N))
class FiniteTargetsISetMask (IntervalSetMask):
def __init__ (self, set0, set1):
IntervalSetMask.__init__ (self, set0, set1)
def transpose (self):
return FiniteSourcesISetMask (self.set1, self.set0)
def shift (self, M, N):
return FiniteTargetsISetMask (self.set0.shift (M), \
self.set1.shift (N))
def intervalSetMask (set0, set1):
set0 = set0 if isinstance (set0, intervalset.IntervalSet) \
else intervalset.IntervalSet (set0)
set1 = set1 if isinstance (set1, intervalset.IntervalSet) \
else intervalset.IntervalSet (set1)
if set0.finite ():
if set1.finite ():
return FiniteISetMask (set0, set1)
else:
return FiniteSourcesISetMask (set0, set1)
else:
if set1.finite ():
return FiniteTargetsISetMask (set0, set1)
else:
return IntervalSetMask (set0, set1)
CSAObject.tag_map[CSA + IntervalSetMask.tag] = (intervalSetMask, 2)
class ISetBoundedMask (FiniteMask):
def __init__ (self, set0, set1, mask):
FiniteMask.__init__ (self)
self.precedence = 1
self.set0 = set0
self.set1 = set1
self.subMask = mask
inf = intervalset.infinity
if isFinite (mask):
(low0, high0, low1, high1) = mask.bounds ()
else:
(low0, high0, low1, high1) = (0, inf, 0, inf)
if self.set0 and self.set1:
self.low0 = max (self.set0.min (), low0)
if self.set0.finite ():
self.high0 = min (self.set0.max () + 1, high0)
else:
self.high0 = high0
self.low1 = max (self.set1.min (), low1)
if self.set1.finite ():
self.high1 = min (self.set1.max () + 1, high1)
else:
self.high1 = high1
assert self.high0 != inf and self.high1 != inf, 'infinite ISetBoundedMask:s currently not supported'
def startIteration (self, state):
obj = copy.copy (self)
obj.subMask = self.subMask.startIteration (state)
return obj
def iterator (self, low0, high0, low1, high1, state):
if not self.isBoundedBy (low0, high0, low1, high1):
return self.simpleIterator (state)
else:
return self.boundedIterator (low0, high0, low1, high1, state)
def simpleIterator (self, state):
for i1 in self.set1.intervalIterator ():
for i0 in self.set0.intervalIterator ():
for e in self.subMask.iterator (i0[0], i0[1] + 1,
i1[0], i1[1] + 1,
state):
yield e
def boundedIterator (self, low0, high0, low1, high1, state):
iterator1 = self.set1.intervalIterator ()
i1 = iterator1.next ()
while i1[1] < low1:
i1 = iterator1.next ()
while i1[0] < high1:
i1 = (max (i1[0], low1), min (i1[1], high1 - 1))
iterator0 = self.set0.intervalIterator ()
try:
i0 = iterator0.next ()
while i0[1] < low0:
i0 = iterator0.next ()
if i0[1] < high0:
for e in self.subMask.iterator (max (i0[0], low0),
i0[1] + 1,
i1[0], i1[1] + 1,
state):
yield e
i0 = iterator0.next ()
while i0[1] < high0:
for e in self.subMask.iterator (i0[0], i0[1] + 1,
i1[0], i1[1] + 1,
state):
yield e
i0 = iterator0.next ()
for e in self.subMask.iterator (i0[0],
min (i0[1] + 1, high0),
i1[0], i1[1] + 1,
state):
yield e
else:
for e in self.subMask.iterator (max (i0[0], low0),
min (i0[1] + 1, high0),
i1[0], i1[1] + 1,
state):
yield e
except StopIteration:
pass
i1 = iterator1.next ()
def repr (self):
return '%s*%s' % (IntervalSetMask._sets_to_repr (self.set0, self.set1),
self.subMask._repr_as_op2 (self.precedence))
def _to_xml (self):
return E ('apply',
E ('times'),
IntervalSetMask._sets_to_xml (self.set0, self.set1),
self.subMask._to_xml ())
# The ExplicitCSet captures the original value sets before coercion.
# It is used in the implementation of the "cset" constructor.
#
class ExplicitCSet (CSet):
def __init__ (self, mask, *valueSets):
if isinstance (mask, list):
mask = ExplicitMask (mask)
self.originalValueSets = valueSets
CSet.__init__ (self, mask, *map (coerceValueSet, valueSets))
def value (self, k):
return self.originalValueSets[k]
# SubCSet is used in the cases where a new CSet can be created by
# an operation on the mask.
#
class SubCSet (CSet):
def __init__ (self, cset, mask, *valueSets):
CSet.__init__ (self, mask, *valueSets)
self.subCSet = cset
def value (self, k):
if self.valueSets[k] == None:
self.valueSets[k] = self.makeValueSet (k)
# defer to subCSet in case it is an ExplicitCSet
return self.subCSet.value (k)
def makeValueSet (self, k):
if isFinite (self.mask ()):
bounds = self.mask ().bounds ()
return self.subCSet.makeFiniteValueSet (k, bounds)
else:
return self.subCSet.makeValueSet (k)
class BinaryCSet (BinaryCSAObject, CSet):
def __init__ (self, operator, op1, op2):
CSet.__init__ (self, None, *[ None for v in op1.valueSets ])
self.name = operator
self.op1 = op1
self.op2 = op2
self.valueSetMap = None
def makeFiniteValueSet (self, k, bounds):
if self.valueSetMap == None:
self.valueSetMap = self.makeValueSetMap (bounds)
return lambda i, j: self.valueSetMap[(i, j)][k]
def makeValueSetMap (self, bounds):
m = {}
state = State ()
obj = self.startIteration (state)
(low0, high0, low1, high1) = bounds
for (i, j, v) in obj.iterator (low0, high0, low1, high1, state):
m[(i, j)] = v
return m
class BinaryCSets (BinaryCSet):
def __init__ (self, operator, op1, op2):
assert op1.arity == op2.arity, 'binary operation on connection-sets with different arity'
BinaryCSet.__init__ (self, operator, op1, op2)
class CSetIntersection (BinaryCSet):
def __init__ (self, op1, op2):
assert isinstance (op2, Mask), 'expected Mask operand'
BinaryCSet.__init__ (self, "*", op1, op2)
self._mask = op1.mask ().intersection (op2)
def iterator (self, low0, high0, low1, high1, state):
iter1 = self.op1.iterator (low0, high0, low1, high1, state)
iter2 = self.op2.iterator (low0, high0, low1, high1, state)
(i1, j1, v1) = iter1.next ()
(i2, j2) = iter2.next ()
while True:
if (j1, i1) < (j2, i2):
(i1, j1, v1) = iter1.next ()
elif (j2, i2) < (j1, i1):
(i2, j2) = iter2.next ()
else:
yield (i1, j1, v1)
(i1, j1, v1) = iter1.next ()
(i2, j2) = iter2.next ()
class CSetMultisetSum (BinaryCSets):
def __init__ (self, op1, op2):
BinaryCSet.__init__ (self, "+", op1, op2)
self._mask = op1.mask ().multisetSum (op2.mask ())
def iterator (self, low0, high0, low1, high1, state):
iter1 = self.op1.iterator (low0, high0, low1, high1, state)
iter2 = self.op2.iterator (low0, high0, low1, high1, state)
try:
(i1, j1, v1) = iter1.next ()
except StopIteration:
(i2, j2, v2) = iter2.next ()
while True:
yield (i2, j2, v2)
(i2, j2, v2) = iter2.next ()
try:
(i2, j2, v2) = iter2.next ()
except StopIteration:
while True:
yield (i1, j1, v1)
(i1, j1, v1) = iter1.next ()
while True:
i1s = i1
j1s = j1
while (j1, i1) <= (j2, i2):
yield (i1, j1, v1)
try:
(i1, j1, v1) = iter1.next ()
except StopIteration:
while True:
yield (i2, j2, v2)
(i2, j2, v2) = iter2.next ()
while (j2, i2) <= (j1s, i1s):
yield (i2, j2, v2)
try:
(i2, j2, v2) = iter2.next ()
except StopIteration:
while True:
yield (i1, j1, v1)
(i1, j1, v1) = iter1.next ()
def intersection (self, other):
assert isinstance (other, Mask), 'expected Mask operand'
if isFinite (self) or isFinite (other):
# since operands are finite we are allowed to use isEmpty
if isEmpty (self.op2.mask ().intersection (other)):
return self.op1.intersection (other)
if isEmpty (self.op1.mask ().intersection (other)):
return self.op2.intersection (other)
return CSetIntersection (self, other)
class TransposedMask (Finite, Mask):
def __init__ (self, mask):
self.subMask = mask
def transpose (self):
return self.subMask
def bounds (self):
(low0, high0, low1, high1) = self.subMask.bounds ()
return (low1, high1, low0, high0)
def startIteration (self, state):
obj = copy.copy (self)
obj.transposedState = state.transpose ()
obj.subMask = self.subMask.startIteration (obj.transposedState)
return obj
def iterator (self, low0, high0, low1, high1, state):
ls = []
for c in self.subMask.iterator (low1, high1, low0, high0, \
self.transposedState):
ls.append ((c[1], c[0]))
ls.sort (cmpPostOrder)
return iter (ls)
class ShiftedMask (Mask):
def __init__ (self, mask, M, N):
self.subMask = mask
self.M = M
self.N = N
def startIteration (self, state):
obj = copy.copy (self)
obj.subMask = self.subMask.startIteration (state)
return obj
def iterator (self, low0, high0, low1, high1, state):
low0 -= self.M
high0 -= self.M
low1 -= self.N
high1 -= self.N
for (i, j) in self.subMask.iterator (max (low0, 0), high0, \
max (low1, 0), high1, \
state):
(i1, j1) = (i + self.M, j + self.N)
if i1 >= 0 and j1 >= 0:
yield (i1, j1)
class FiniteShiftedMask (Finite, ShiftedMask):
def bounds (self):
(low0, high0, low1, high1) = self.subMask.bounds ()
low0 += self.M
high0 += self.M
low1 += self.N
high1 += self.N
return (max (low0, 0), high0, max (low1, 0), high1)
def shiftedMask (mask, M, N):
if isFinite (mask):
return FiniteShiftedMask (mask, M, N)
else:
return ShiftedMask (mask, M, N)
class State (dict):
def transpose (self):
if 'partitions' in self:
s = State (self)
s['partitions'] = map (transpose, s['partitions'])
return s
else:
return self
class MaskPartition (Finite, Mask):
def __init__ (self, mask, partitions, selected, seed):
Mask.__init__ (self)
#*fixme* How can we know when this is not necessary?
self.subMask = partitions[selected] * mask
#domain = IntervalSetMask ([], [])
#for m in partitions:
# assert isFinite (m), 'partitions must be finite'
# domain = domain.multisetSum (m)
self.state = { #'domain' : domain,
'partitions' : partitions,
'selected' : selected }
if seed != None:
self.state['seed'] = seed
def bounds (self):
return self.subMask.bounds ()
def startIteration (self, state):
for key in self.state:
state[key] = self.state[key]
return self.subMask.startIteration (state)
def iterator (self, low0, high0, low1, high1, state):
raise RuntimeError, 'iterator called on wrong object'
class CSetPartition (CSet):
def __init__ (self, c, partitions, selected, seed):
#*fixme* How can we know when this is not necessary?
self.subCSet = (partitions[selected] * c).c
CSet.__init__ (self, self.subCSet.mask (), *self.subCSet.valueSets)
self.state = { #'domain' : domain,
'partitions' : partitions,
'selected' : selected }
if seed != None:
self.state['seed'] = seed
def makeFiniteValueSet (self, k, bounds):
return self.subCSet.makeFiniteValueSet (k, bounds);
def bounds (self):
return self.subCSet.bounds ()
def startIteration (self, state):
for key in self.state:
state[key] = self.state[key]
return self.subCSet.startIteration (state)
def iterator (self, low0, high0, low1, high1, state):
raise RuntimeError, 'iterator called on wrong object'
csa-0.1.0/csa/csaobject.py 0000644 0005140 0005140 00000014520 11735362304 014701 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
try:
from lxml import etree
from lxml.builder import E
except ImportError:
pass
csa_tag = 'CSA'
csa_namespace = 'http://software.incf.org/software/csa/1.0'
CSA = '{%s}' % csa_namespace
CUSTOM = -4
OPERATOR = -3
BINDOPERATOR = -2
SINGLETON = -1
def to_xml (obj):
if isinstance (obj, str):
return E (obj)
elif isinstance (obj, (int, float)):
return E ('cn', str (obj))
elif isinstance (obj, CSAObject):
return obj._to_xml ()
else:
raise RuntimeError, "don't know how to turn %s into xml" % obj
# precedence levels:
#
# 0 + -
# 1 *
# 2 ~
class CSAObject (object):
tag_map = {}
def __init__ (self, name, precedence = 3):
self.name = name
self.precedence = precedence
def __repr__ (self):
return 'CSA(%s)' % self.repr ()
def repr (self):
if hasattr (self, 'name'):
return self.name
else:
return self.__class__.__name__
def _repr_as_op2 (self, parentPrecedence):
if self.precedence <= parentPrecedence:
return '(%s)' % self.repr ()
else:
return self.repr ()
def _repr_applyop (self, op_repr, obj):
return '%s*%s' % (op_repr, obj._repr_as_op2 (1))
def to_xml (self):
return E (csa_tag, self._to_xml (), xmlns=csa_namespace)
def _to_xml (self):
return E (self.name)
@classmethod
def apply (cls, operator, *operands):
return E ('apply', to_xml (operator), *map (to_xml, operands))
@classmethod
def formalFromXML (cls, element):
assert element.tag == CSA + 'bvar'
nodes = element.getchildren ()
assert nodes[0].tag == CSA + 'ci'
return nodes[0].text
@classmethod
def from_xml (cls, element, env = {}):
if element.tag == CSA + 'cn':
return eval (element.text)
elif element.tag == CSA + 'ci':
#*fixme* Implement env as lists of dictionaries
return env[element.text]
elif element.tag == CSA + 'apply':
nodes = element.getchildren ()
operator = nodes[0].tag
operands = [ cls.from_xml (e, env) for e in nodes[1:] ]
if operator == CSA + 'plus':
return operands[0].__add__ (operands[1])
elif operator == CSA + 'minus':
return operands[0].__sub__ (operands[1])
elif operator == CSA + 'times':
return operands[0].__mul__ (operands[1])
elif operator == CSA + 'complement':
return operands[0].__invert__ ()
else:
# Function or operator application
entry = CSAObject.tag_map[operator]
obj = entry[0]
if entry[1] == OPERATOR:
return obj * operands[1]
else:
return obj (*operands)
elif element.tag == CSA + 'bind':
nodes = element.getchildren ()
tag = nodes[0].tag
entry = CSAObject.tag_map[tag]
if entry[1] != BINDOPERATOR:
raise RuntimeError, "unknown binding operator tag %s" % tag
bindingOperator = entry[0]
bvars = [ CSAObject.formalFromXML (e) for e in nodes[1:-1] ]
return bindingOperator (bvars, nodes[-1])
elif element.tag in CSAObject.tag_map:
entry = CSAObject.tag_map[element.tag]
obj = entry[0]
if entry[1] == SINGLETON:
return obj
elif entry[1] == CUSTOM:
return obj.from_xml (element, env)
else:
return obj ()
else:
raise RuntimeError, "don't know how parse tag %s" % element.tag
def xml (e):
print etree.tostring (e)
def write(self, file):
doc = self.to_xml ()
etree.ElementTree(doc).write (file, encoding="UTF-8",
pretty_print=True, xml_declaration=True)
class BinaryCSAObject (CSAObject):
operator_table = {'+': 'plus', '-': 'minus', '*': 'times'}
def __init__ (self, name, op1, op2, precedence = 0):
CSAObject.__init__ (self, name, precedence)
self.op1 = op1
self.op2 = op2
def repr (self):
if isinstance (self.op1, CSAObject):
op1 = self.op1.repr ()
if self.op1.precedence < self.precedence:
op1 = "(%s)" % op1
else:
op1 = self.op1
if isinstance (self.op2, CSAObject):
op2 = self.op2._repr_as_op2 (self.precedence)
else:
op2 = self.op2
return "%s%s%s" % (op1, self.name, op2)
def _to_xml (self):
if isinstance (self.op1, CSAObject):
op1 = self.op1._to_xml ()
else:
op1 = self.op1
if isinstance (self.op2, CSAObject):
op2 = self.op2._to_xml ()
else:
op2 = self.op2
if self.name in BinaryCSAObject.operator_table:
op = BinaryCSAObject.operator_table[self.name]
else:
op = self.name
return E ('apply', E (op), op1, op2)
class OpExprValue (BinaryCSAObject):
def __init__ (self, operator, operand):
BinaryCSAObject.__init__ (self, '*', operator, operand, 1)
class Operator (CSAObject):
def __init__ (self, name='ioperator'):
CSAObject.__init__ (self, name)
def from_xml (root):
assert root.nsmap[None] == csa_namespace
return CSAObject.from_xml (root.getchildren ()[0])
def parse (filename):
doc = etree.parse (filename)
return from_xml (doc.getroot())
def registerTag (tag, obj, mode):
CSAObject.tag_map[CSA + tag] = (obj, mode)
csa-0.1.0/csa/version.py 0000644 0005140 0005140 00000001372 11735362304 014432 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
__version__ = "0.1.0"
csa-0.1.0/csa/geometry.py 0000644 0005140 0005140 00000004450 11735362304 014600 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
import math as _math
import random as _random
import numpy as _numpy
import intervalset as _iset
def grid2d (width, xScale = 1.0, yScale = 1.0, x0 = 0.0, y0 = 0.0):
xScale /= width
yScale /= width
g = lambda i: \
(x0 + xScale * (i % width), y0 + yScale * (i / width))
g.type = 'grid'
g.width = width
g.xScale = xScale
g.yScale = yScale
g.x0 = x0
g.y0 = y0
g.inverse = lambda x, y: \
int (round (x / xScale - x0)) \
+ width * int (round (y / yScale - y0))
return g
def random2d (N, xScale = 1.0, yScale = 1.0):
coords = [(xScale * _random.random (), yScale * _random.random ())
for i in xrange (0, N)]
g = lambda i: coords[i]
g.type = 'ramdom'
g.N = N
g.xScale = xScale
g.yScale = yScale
# We should use a KD-tree here
g.inverse = lambda x, y, domain=_iset.IntervalSet ((0, N - 1)): \
_numpy.array ([euclidDistance2d ((x, y), g(i)) \
for i in domain]).argmin () \
+ domain.min ()
return g
def euclidDistance2d (p1, p2):
dx = p1[0] - p2[0]
dy = p1[1] - p2[1]
return _math.sqrt (dx * dx + dy * dy)
class ProjectionOperator (object):
def __init__ (self, projection):
self.projection = projection
def __mul__ (self, g):
projection = self.projection
return lambda i: projection (g (i))
def euclidMetric2d (g1, g2 = None):
g2 = g1 if g2 == None else g2
return lambda i, j: euclidDistance2d (g1 (i), g2 (j))
#del random
csa-0.1.0/csa/conngen.py 0000644 0005140 0005140 00000004600 11735362304 014371 0 ustar mdj mdj 0000000 0000000 #
# This file is part of the Connection-Set Algebra (CSA).
# Copyright (C) 2010,2011,2012 Mikael Djurfeldt
#
# CSA is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# CSA is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
try:
from nineml.connection_generator import ConnectionGenerator
HAVE_CG=True
except ImportError:
HAVE_CG=False
if HAVE_CG:
from csaobject import from_xml
from elementary import arity, cross, partition
from closure import Closure
class CSAConnectionGenerator (ConnectionGenerator):
def __init__ (self, cset):
self.cset = cset
self.generator = False
@property
def arity (self):
return arity (self.cset)
def setMask (self, mask):
self.setMasks ([mask], 0)
def setMasks (self, masks, local):
csaMasks = map (CSAConnectionGenerator.makeMask, masks)
self.generator = partition (self.cset, csaMasks, local)
@staticmethod
def makeMask (mask):
return cross (CSAConnectionGenerator.makeIList (mask.sources),
CSAConnectionGenerator.makeIList (mask.targets))
@staticmethod
def makeIList (iset):
if iset.skip == 1:
return iset.intervals
else:
ls = []
for ivl in iset.intervals:
for i in xrange (ivl[0], ivl[1] + 1, iset.skip):
ls.append ((i, i))
return ls
def __len__ (self):
return self.generator.__len__ ()
def __iter__ (self):
return self.generator.__iter__ ()
def connectionGeneratorClosureFromXML (element):
cset = from_xml (element)
if isinstance (cset, Closure):
return lambda *args: CSAConnectionGenerator (cset (*args))
else:
return lambda: CSAConnectionGenerator (cset)