gmplot-1.1.1/0000755000076500000240000000000012762101470013447 5ustar mwoodsstaff00000000000000gmplot-1.1.1/gmplot/0000755000076500000240000000000012762101470014751 5ustar mwoodsstaff00000000000000gmplot-1.1.1/gmplot/__init__.py0000644000076500000240000000004512762101412017055 0ustar mwoodsstaff00000000000000from .gmplot import GoogleMapPlotter gmplot-1.1.1/gmplot/color_dicts.py0000644000076500000240000001012712762101412017624 0ustar mwoodsstaff00000000000000mpl_color_map = { 'b': 'blue', 'g': 'green', 'r': 'red', 'c': 'cyan', 'm': 'magenta', 'y': 'yellow', 'k': 'black', 'w': 'white' } # TODO: Copy matplotlib.colors.cnames # That list has 147 colors. The below is only 120. =( html_color_codes = { 'aliceblue': '#F0F8FF', 'antiquewhite': '#FAEBD7', 'aqua': '#00FFFF', 'aquamarine': '#7FFFD4', 'azure': '#F0FFFF', 'beige': '#F5F5DC', 'bisque': '#FFE4C4', 'black': '#000000', 'blanchedalmond': '#FFEBCD', 'blue': '#0000FF', 'blueviolet': '#8A2BE2', 'brown': '#A52A2A', 'burlywood': '#DEB887', 'cadetblue': '#5F9EA0', 'chartreuse': '#7FFF00', 'chocolate': '#D2691E', 'coral': '#FF7F50', 'cornflowerblue': '#6495ED', 'cornsilk': '#FFF8DC', 'crimson': '#DC143C', 'cyan': '#00FFFF', 'darkblue': '#00008B', 'darkcyan': '#008B8B', 'darkgoldenrod': '#B8860B', 'darkgray': '#A9A9A9', 'darkgreen': '#006400', 'darkkhaki': '#BDB76B', 'darkmagenta': '#8B008B', 'darkolivegreen': '#556B2F', 'darkorange': '#FF8C00', 'darkorchid': '#9932CC', 'darkred': '#8B0000', 'darksalmon': '#E9967A', 'darkseagreen': '#8FBC8F', 'darkslateblue': '#483D8B', 'darkslategray': '#2F4F4F', 'darkturquoise': '#00CED1', 'darkviolet': '#9400D3', 'deeppink': '#FF1493', 'deepskyblue': '#00BFFF', 'dimgray': '#696969', 'dodgerblue': '#1E90FF', 'firebrick': '#B22222', 'floralwhite': '#FFFAF0', 'forestgreen': '#228B22', 'fuchsia': '#FF00FF', 'gainsboro': '#DCDCDC', 'ghostwhite': '#F8F8FF', 'gold': '#FFD700', 'goldenrod': '#DAA520', 'gray': '#808080', 'green': '#008000', 'greenyellow': '#ADFF2F', 'honeydew': '#F0FFF0', 'hotpink': '#FF69B4', 'indianred': '#CD5C5C', 'indigo': '#4B0082', 'ivory': '#FFFFF0', 'khaki': '#F0E68C', 'lavender': '#E6E6FA', 'lavenderblush': '#FFF0F5', 'lawngreen': '#7CFC00', 'lemonchiffon': '#FFFACD', 'lightblue': '#ADD8E6', 'lightcoral': '#F08080', 'lightcyan': '#E0FFFF', 'lightgoldenrodyellow': '#FAFAD2', 'lightgray': '#D3D3D3', 'lightgreen': '#90EE90', 'lightpink': '#FFB6C1', 'lightsalmon': '#FFA07A', 'lightseagreen': '#20B2AA', 'lightskyblue': '#87CEFA', 'lightslategray': '#778899', 'lightsteelblue': '#B0C4DE', 'lightyellow': '#FFFFE0', 'lime': '#00FF00', 'limegreen': '#32CD32', 'linen': '#FAF0E6', 'magenta': '#FF00FF', 'maroon': '#800000', 'mediumaquamarine': '#66CDAA', 'mediumblue': '#0000CD', 'mediumorchid': '#BA55D3', 'mediumpurple': '#9370DB', 'mediumseagreen': '#3CB371', 'mediumslateblue': '#7B68EE', 'mediumspringgreen': '#00FA9A', 'mediumturquoise': '#48D1CC', 'mediumvioletred': '#C71585', 'midnightblue': '#191970', 'mintcream': '#F5FFFA', 'mistyrose': '#FFE4E1', 'moccasin': '#FFE4B5', 'navajowhite': '#FFDEAD', 'navy': '#000080', 'oldlace': '#FDF5E6', 'olive': '#808000', 'olivedrab': '#6B8E23', 'orange': '#FFA500', 'orangered': '#FF4500', 'orchid': '#DA70D6', 'palegoldenrod': '#EEE8AA', 'palegreen': '#98FB98', 'paleturquoise': '#AFEEEE', 'palevioletred': '#DB7093', 'papayawhip': '#FFEFD5', 'peachpuff': '#FFDAB9', 'peru': '#CD853F', 'pink': '#FFC0CB', 'plum': '#DDA0DD', 'powderblue': '#B0E0E6', 'purple': '#800080', 'red': '#FF0000', 'rosybrown': '#BC8F8F', 'royalblue': '#4169E1', 'saddlebrown': '#8B4513', 'salmon': '#FA8072', 'sandybrown': '#F4A460', 'seagreen': '#2E8B57', 'seashell': '#FFF5EE', 'sienna': '#A0522D', 'silver': '#C0C0C0', 'skyblue': '#87CEEB', 'slateblue': '#6A5ACD', 'slategray': '#708090', 'snow': '#FFFAFA', 'springgreen': '#00FF7F', 'steelblue': '#4682B4', 'tan': '#D2B48C', 'teal': '#008080', 'thistle': '#D8BFD8', 'tomato': '#FF6347', 'turquoise': '#40E0D0', 'violet': '#EE82EE', 'wheat': '#F5DEB3', 'white': '#FFFFFF', 'whitesmoke': '#F5F5F5', 'yellow': '#FFFF00', 'yellowgreen': '#9ACD32' } gmplot-1.1.1/gmplot/gmplot.py0000644000076500000240000004015012762101412016621 0ustar mwoodsstaff00000000000000import math import requests import json import os from .color_dicts import mpl_color_map, html_color_codes def safe_iter(var): try: return iter(var) except TypeError: return [var] class GoogleMapPlotter(object): def __init__(self, center_lat, center_lng, zoom): self.center = (float(center_lat), float(center_lng)) self.zoom = int(zoom) self.grids = None self.paths = [] self.shapes = [] self.points = [] self.heatmap_points = [] self.radpoints = [] self.gridsetting = None self.coloricon = os.path.join(os.path.dirname(__file__), 'markers/%s.png') self.color_dict = mpl_color_map self.html_color_codes = html_color_codes @classmethod def from_geocode(cls, location_string, zoom=13): lat, lng = cls.geocode(location_string) return cls(lat, lng, zoom) @classmethod def geocode(self, location_string): geocode = requests.get( 'http://maps.googleapis.com/maps/api/geocode/json?address="%s"' % location_string) geocode = json.loads(geocode.text) latlng_dict = geocode['results'][0]['geometry']['location'] return latlng_dict['lat'], latlng_dict['lng'] def grid(self, slat, elat, latin, slng, elng, lngin): self.gridsetting = [slat, elat, latin, slng, elng, lngin] def marker(self, lat, lng, color='#FF0000', c=None, title="no implementation"): if c: color = c color = self.color_dict.get(color, color) color = self.html_color_codes.get(color, color) self.points.append((lat, lng, color[1:], title)) def scatter(self, lats, lngs, color=None, size=None, marker=True, c=None, s=None, **kwargs): color = color or c size = size or s or 40 kwargs["color"] = color kwargs["size"] = size settings = self._process_kwargs(kwargs) for lat, lng in zip(lats, lngs): if marker: self.marker(lat, lng, settings['color']) else: self.circle(lat, lng, size, **settings) def circle(self, lat, lng, radius, color=None, c=None, **kwargs): color = color or c kwargs.setdefault('face_alpha', 0.5) kwargs.setdefault('face_color', "#000000") kwargs.setdefault("color", color) settings = self._process_kwargs(kwargs) path = self.get_cycle(lat, lng, radius) self.shapes.append((path, settings)) def _process_kwargs(self, kwargs): settings = dict() settings["edge_color"] = kwargs.get("color", None) or \ kwargs.get("edge_color", None) or \ kwargs.get("ec", None) or \ "#000000" settings["edge_alpha"] = kwargs.get("alpha", None) or \ kwargs.get("edge_alpha", None) or \ kwargs.get("ea", None) or \ 1.0 settings["edge_width"] = kwargs.get("edge_width", None) or \ kwargs.get("ew", None) or \ 1.0 settings["face_alpha"] = kwargs.get("alpha", None) or \ kwargs.get("face_alpha", None) or \ kwargs.get("fa", None) or \ 0.3 settings["face_color"] = kwargs.get("color", None) or \ kwargs.get("face_color", None) or \ kwargs.get("fc", None) or \ "#000000" settings["color"] = kwargs.get("color", None) or \ kwargs.get("c", None) or \ settings["edge_color"] or \ settings["face_color"] # Need to replace "plum" with "#DDA0DD" and "c" with "#00FFFF" (cyan). for key, color in settings.items(): if 'color' in key: color = self.color_dict.get(color, color) color = self.html_color_codes.get(color, color) settings[key] = color settings["closed"] = kwargs.get("closed", None) return settings def plot(self, lats, lngs, color=None, c=None, **kwargs): color = color or c kwargs.setdefault("color", color) settings = self._process_kwargs(kwargs) path = zip(lats, lngs) self.paths.append((path, settings)) def heatmap(self, lats, lngs, threshold=10, radius=10, gradient=None, opacity=0.6, dissipating=True): """ :param lats: list of latitudes :param lngs: list of longitudes :param threshold: :param radius: The hardest param. Example (string): :return: """ settings = {} settings['threshold'] = threshold settings['radius'] = radius settings['gradient'] = gradient settings['opacity'] = opacity settings['dissipating'] = dissipating settings = self._process_heatmap_kwargs(settings) heatmap_points = [] for lat, lng in zip(lats, lngs): heatmap_points.append((lat, lng)) self.heatmap_points.append((heatmap_points, settings)) def _process_heatmap_kwargs(self, settings_dict): settings_string = '' settings_string += "heatmap.set('threshold', %d);\n" % settings_dict['threshold'] settings_string += "heatmap.set('radius', %d);\n" % settings_dict['radius'] settings_string += "heatmap.set('opacity', %f);\n" % settings_dict['opacity'] dissipation_string = 'true' if settings_dict['dissipating'] else 'false' settings_string += "heatmap.set('dissipating', %s);\n" % (dissipation_string) gradient = settings_dict['gradient'] if gradient: gradient_string = "var gradient = [\n" for r, g, b, a in gradient: gradient_string += "\t" + "'rgba(%d, %d, %d, %d)',\n" % (r, g, b, a) gradient_string += '];' + '\n' gradient_string += "heatmap.set('gradient', gradient);\n" settings_string += gradient_string return settings_string def polygon(self, lats, lngs, color=None, c=None, **kwargs): color = color or c kwargs.setdefault("color", color) settings = self._process_kwargs(kwargs) shape = zip(lats, lngs) self.shapes.append((shape, settings)) # create the html file which include one google map and all points and # paths def draw(self, htmlfile): f = open(htmlfile, 'w') f.write('\n') f.write('\n') f.write( '\n') f.write( '\n') f.write('Google Maps - pygmaps \n') f.write('\n') f.write('\n') f.write('\n') f.write( '\n') f.write( '\t
\n') f.write('\n') f.write('\n') f.close() ############################################# # # # # # # Low level Map Drawing # # # # # # ############################################# def write_grids(self, f): if self.gridsetting is None: return slat = self.gridsetting[0] elat = self.gridsetting[1] latin = self.gridsetting[2] slng = self.gridsetting[3] elng = self.gridsetting[4] lngin = self.gridsetting[5] self.grids = [] r = [ slat + float(x) * latin for x in range(0, int((elat - slat) / latin))] for lat in r: self.grids.append( [(lat + latin / 2.0, slng + lngin / 2.0), (lat + latin / 2.0, elng + lngin / 2.0)]) r = [ slng + float(x) * lngin for x in range(0, int((elng - slng) / lngin))] for lng in r: self.grids.append( [(slat + latin / 2.0, lng + lngin / 2.0), (elat + latin / 2.0, lng + lngin / 2.0)]) for line in self.grids: settings = self._process_kwargs({"color": "#000000"}) self.write_polyline(f, line, settings) def write_points(self, f): for point in self.points: self.write_point(f, point[0], point[1], point[2], point[3]) def get_cycle(self, lat, lng, rad): # unit of radius: meter cycle = [] d = (rad / 1000.0) / 6378.8 lat1 = (math.pi / 180.0) * lat lng1 = (math.pi / 180.0) * lng r = [x * 10 for x in range(36)] for a in r: tc = (math.pi / 180.0) * a y = math.asin( math.sin(lat1) * math.cos(d) + math.cos(lat1) * math.sin(d) * math.cos(tc)) dlng = math.atan2(math.sin( tc) * math.sin(d) * math.cos(lat1), math.cos(d) - math.sin(lat1) * math.sin(y)) x = ((lng1 - dlng + math.pi) % (2.0 * math.pi)) - math.pi cycle.append( (float(y * (180.0 / math.pi)), float(x * (180.0 / math.pi)))) return cycle def write_paths(self, f): for path, settings in self.paths: self.write_polyline(f, path, settings) def write_shapes(self, f): for shape, settings in self.shapes: self.write_polygon(f, shape, settings) # TODO: Add support for mapTypeId: google.maps.MapTypeId.SATELLITE def write_map(self, f): f.write('\t\tvar centerlatlng = new google.maps.LatLng(%f, %f);\n' % (self.center[0], self.center[1])) f.write('\t\tvar myOptions = {\n') f.write('\t\t\tzoom: %d,\n' % (self.zoom)) f.write('\t\t\tcenter: centerlatlng,\n') f.write('\t\t\tmapTypeId: google.maps.MapTypeId.ROADMAP\n') f.write('\t\t};\n') f.write( '\t\tvar map = new google.maps.Map(document.getElementById("map_canvas"), myOptions);\n') f.write('\n') def write_point(self, f, lat, lon, color, title): f.write('\t\tvar latlng = new google.maps.LatLng(%f, %f);\n' % (lat, lon)) f.write('\t\tvar img = new google.maps.MarkerImage(\'%s\');\n' % (self.coloricon % color)) f.write('\t\tvar marker = new google.maps.Marker({\n') f.write('\t\ttitle: "%s",\n' % title) f.write('\t\ticon: img,\n') f.write('\t\tposition: latlng\n') f.write('\t\t});\n') f.write('\t\tmarker.setMap(map);\n') f.write('\n') def write_polyline(self, f, path, settings): clickable = False geodesic = True strokeColor = settings.get('color') or settings.get('edge_color') strokeOpacity = settings.get('edge_alpha') strokeWeight = settings.get('edge_width') f.write('var PolylineCoordinates = [\n') for coordinate in path: f.write('new google.maps.LatLng(%f, %f),\n' % (coordinate[0], coordinate[1])) f.write('];\n') f.write('\n') f.write('var Path = new google.maps.Polyline({\n') f.write('clickable: %s,\n' % (str(clickable).lower())) f.write('geodesic: %s,\n' % (str(geodesic).lower())) f.write('path: PolylineCoordinates,\n') f.write('strokeColor: "%s",\n' % (strokeColor)) f.write('strokeOpacity: %f,\n' % (strokeOpacity)) f.write('strokeWeight: %d\n' % (strokeWeight)) f.write('});\n') f.write('\n') f.write('Path.setMap(map);\n') f.write('\n\n') def write_polygon(self, f, path, settings): clickable = False geodesic = True strokeColor = settings.get('edge_color') or settings.get('color') strokeOpacity = settings.get('edge_alpha') strokeWeight = settings.get('edge_width') fillColor = settings.get('face_color') or settings.get('color') fillOpacity= settings.get('face_alpha') f.write('var coords = [\n') for coordinate in path: f.write('new google.maps.LatLng(%f, %f),\n' % (coordinate[0], coordinate[1])) f.write('];\n') f.write('\n') f.write('var polygon = new google.maps.Polygon({\n') f.write('clickable: %s,\n' % (str(clickable).lower())) f.write('geodesic: %s,\n' % (str(geodesic).lower())) f.write('fillColor: "%s",\n' % (fillColor)) f.write('fillOpacity: %f,\n' % (fillOpacity)) f.write('paths: coords,\n') f.write('strokeColor: "%s",\n' % (strokeColor)) f.write('strokeOpacity: %f,\n' % (strokeOpacity)) f.write('strokeWeight: %d\n' % (strokeWeight)) f.write('});\n') f.write('\n') f.write('polygon.setMap(map);\n') f.write('\n\n') def write_heatmap(self, f): for heatmap_points, settings_string in self.heatmap_points: f.write('var heatmap_points = [\n') for heatmap_lat, heatmap_lng in heatmap_points: f.write('new google.maps.LatLng(%f, %f),\n' % (heatmap_lat, heatmap_lng)) f.write('];\n') f.write('\n') f.write('var pointArray = new google.maps.MVCArray(heatmap_points);' + '\n') f.write('var heatmap;' + '\n') f.write('heatmap = new google.maps.visualization.HeatmapLayer({' + '\n') f.write('\n') f.write('data: pointArray' + '\n') f.write('});' + '\n') f.write('heatmap.setMap(map);' + '\n') f.write(settings_string) if __name__ == "__main__": mymap = GoogleMapPlotter(37.428, -122.145, 16) # mymap = GoogleMapPlotter.from_geocode("Stanford University") mymap.grid(37.42, 37.43, 0.001, -122.15, -122.14, 0.001) mymap.marker(37.427, -122.145, "yellow") mymap.marker(37.428, -122.146, "cornflowerblue") mymap.marker(37.429, -122.144, "k") lat, lng = mymap.geocode("Stanford University") mymap.marker(lat, lng, "red") mymap.circle(37.429, -122.145, 100, "#FF0000", ew=2) path = [(37.429, 37.428, 37.427, 37.427, 37.427), (-122.145, -122.145, -122.145, -122.146, -122.146)] path2 = [[i+.01 for i in path[0]], [i+.02 for i in path[1]]] path3 = [(37.433302 , 37.431257 , 37.427644 , 37.430303), (-122.14488, -122.133121, -122.137799, -122.148743)] path4 = [(37.423074, 37.422700, 37.422410, 37.422188, 37.422274, 37.422495, 37.422962, 37.423552, 37.424387, 37.425920, 37.425937), (-122.150288, -122.149794, -122.148936, -122.148142, -122.146747, -122.14561, -122.144773, -122.143936, -122.142992, -122.147863, -122.145953)] mymap.plot(path[0], path[1], "plum", edge_width=10) mymap.plot(path2[0], path2[1], "red") mymap.polygon(path3[0], path3[1], edge_color="cyan", edge_width=5, face_color="blue", face_alpha=0.1) mymap.heatmap(path4[0], path4[1], threshold=10, radius=40) mymap.heatmap(path3[0], path3[1], threshold=10, radius=40, dissipating=False, gradient=[(30,30,30,0), (30,30,30,1), (50, 50, 50, 1)]) mymap.scatter(path4[0], path4[1], c='r', marker=True) mymap.scatter(path4[0], path4[1], s=90, marker=False, alpha=0.1) # Get more points with: # http://www.findlatitudeandlongitude.com/click-lat-lng-list/ scatter_path = ([37.424435, 37.424417, 37.424417, 37.424554, 37.424775, 37.425099, 37.425235, 37.425082, 37.424656, 37.423957, 37.422952, 37.421759, 37.420447, 37.419135, 37.417822, 37.417209], [-122.142048, -122.141275, -122.140503, -122.139688, -122.138872, -122.138078, -122.137241, -122.136405, -122.135568, -122.134731, -122.133894, -122.133057, -122.13222, -122.131383, -122.130557, -122.129999]) mymap.scatter(scatter_path[0], scatter_path[1], c='r', marker=True) mymap.draw('./mymap.html') gmplot-1.1.1/gmplot/markers/0000755000076500000240000000000012762101470016415 5ustar mwoodsstaff00000000000000gmplot-1.1.1/gmplot/markers/000000.png0000644000076500000240000000065112762101412017640 0ustar mwoodsstaff00000000000000PNG  IHDR"hbKGD^IDATH?K@oN*?/A N ߁Pplq t7ũ[)nuP%B礉<ˇ.%œm`5pkO!m̳&N#+ 8bT횠vT@\/ȳK]#7w ˞@F q:Fyi /R=c ˿  uJ)剶=ނ9OgqU>WP^, 4S8@ gX/]w_tPOu E;x|B_Pk\7賌!''.N=&IENDB`gmplot-1.1.1/gmplot/markers/000080.png0000644000076500000240000000122012762101412017641 0ustar mwoodsstaff00000000000000PNG  IHDR"hbKGDEIDATH;hQ!E,|_!ZQ;Av`#(I &Dv$0f,d_pϜwsoJuu`#I ԨO[0lĊ=8?GI#F,HHM<`")6cnP_)^lC_t? 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A matplotlib-like interface to generate the HTML and javascript to render all the data you'd like on top of Google Maps. Several plotting methods make creating exploratory map views effortless. Here's a crash course: :: import gmplot gmap = gmplot.GoogleMapPlotter(37.428, -122.145, 16) gmap.plot(latitudes, longitudes, 'cornflowerblue', edge_width=10) gmap.scatter(more_lats, more_lngs, '#3B0B39', size=40, marker=False) gmap.scatter(marker_lats, marker_lngs, 'k', marker=True) gmap.heatmap(heat_lats, heat_lngs) gmap.draw("mymap.html") Geocoding --------- ``gmplot`` contains a simple wrapper around Google's geocoding service enabling map initilization to the location of your choice. Rather than providing latitude, longitude, and zoom level during initialization, grab your gmplot instance with a location: :: gmap = gmplot.from_geocode("San Francisco") Plot types ---------- * Polygons with fills. * Drop pins. * Scatter points. * Grid lines. * Heatmaps. .. image:: http://i.imgur.com/dTNkbZ7.png Misc. ----- Code hosted on `GitHub `_ Install easily with ``pip install gmplot`` from PyPI. Inspired by Yifei Jiang's (jiangyifei@gmail.com) pygmaps_ module. .. _pygmaps: http://code.google.com/p/pygmaps/ Keywords: python wrapper google maps Platform: UNKNOWN gmplot-1.1.1/gmplot.egg-info/requires.txt0000644000076500000240000000001012762101470021032 0ustar mwoodsstaff00000000000000requestsgmplot-1.1.1/gmplot.egg-info/SOURCES.txt0000644000076500000240000000736212762101470020337 0ustar mwoodsstaff00000000000000MANIFEST.in README.rst setup.py gmplot/__init__.py gmplot/color_dicts.py gmplot/gmplot.py gmplot.egg-info/PKG-INFO gmplot.egg-info/SOURCES.txt gmplot.egg-info/dependency_links.txt gmplot.egg-info/requires.txt gmplot.egg-info/top_level.txt gmplot/markers/000000.png gmplot/markers/000080.png gmplot/markers/00008B.png gmplot/markers/0000CD.png gmplot/markers/0000FF.png gmplot/markers/006400.png gmplot/markers/008000.png gmplot/markers/008080.png gmplot/markers/008B8B.png gmplot/markers/00BFFF.png gmplot/markers/00CED1.png gmplot/markers/00FA9A.png gmplot/markers/00FF00.png gmplot/markers/00FF7F.png gmplot/markers/00FFFF.png gmplot/markers/191970.png gmplot/markers/1E90FF.png gmplot/markers/20B2AA.png gmplot/markers/228B22.png gmplot/markers/2E8B57.png gmplot/markers/2F4F4F.png gmplot/markers/32CD32.png gmplot/markers/3CB371.png gmplot/markers/40E0D0.png gmplot/markers/4169E1.png gmplot/markers/4682B4.png gmplot/markers/483D8B.png gmplot/markers/48D1CC.png gmplot/markers/4B0082.png gmplot/markers/556B2F.png gmplot/markers/5F9EA0.png gmplot/markers/6495ED.png gmplot/markers/66CDAA.png gmplot/markers/696969.png gmplot/markers/6A5ACD.png gmplot/markers/6B8E23.png gmplot/markers/708090.png gmplot/markers/778899.png gmplot/markers/7B68EE.png gmplot/markers/7CFC00.png gmplot/markers/7FFF00.png gmplot/markers/7FFFD4.png gmplot/markers/800000.png gmplot/markers/800080.png gmplot/markers/808000.png gmplot/markers/808080.png gmplot/markers/87CEEB.png gmplot/markers/87CEFA.png gmplot/markers/8A2BE2.png gmplot/markers/8B0000.png gmplot/markers/8B008B.png gmplot/markers/8B4513.png gmplot/markers/8FBC8F.png gmplot/markers/90EE90.png gmplot/markers/9370DB.png gmplot/markers/9400D3.png gmplot/markers/98FB98.png gmplot/markers/9932CC.png gmplot/markers/9ACD32.png gmplot/markers/A0522D.png gmplot/markers/A52A2A.png gmplot/markers/A9A9A9.png gmplot/markers/ADD8E6.png gmplot/markers/ADFF2F.png gmplot/markers/AFEEEE.png gmplot/markers/B0C4DE.png gmplot/markers/B0E0E6.png gmplot/markers/B22222.png gmplot/markers/B8860B.png gmplot/markers/BA55D3.png gmplot/markers/BC8F8F.png gmplot/markers/BDB76B.png gmplot/markers/C0C0C0.png gmplot/markers/C71585.png gmplot/markers/CD5C5C.png gmplot/markers/CD853F.png gmplot/markers/D2691E.png gmplot/markers/D2B48C.png gmplot/markers/D3D3D3.png gmplot/markers/D8BFD8.png gmplot/markers/DA70D6.png gmplot/markers/DAA520.png gmplot/markers/DB7093.png gmplot/markers/DC143C.png gmplot/markers/DCDCDC.png gmplot/markers/DDA0DD.png gmplot/markers/DEB887.png gmplot/markers/E0FFFF.png gmplot/markers/E6E6FA.png gmplot/markers/E9967A.png gmplot/markers/EE82EE.png gmplot/markers/EEE8AA.png gmplot/markers/F08080.png gmplot/markers/F0E68C.png gmplot/markers/F0F8FF.png gmplot/markers/F0FFF0.png gmplot/markers/F0FFFF.png gmplot/markers/F4A460.png gmplot/markers/F5DEB3.png gmplot/markers/F5F5DC.png gmplot/markers/F5F5F5.png gmplot/markers/F5FFFA.png gmplot/markers/F8F8FF.png gmplot/markers/FA8072.png gmplot/markers/FAEBD7.png gmplot/markers/FAF0E6.png gmplot/markers/FAFAD2.png gmplot/markers/FDF5E6.png gmplot/markers/FF0000.png gmplot/markers/FF00FF.png gmplot/markers/FF1493.png gmplot/markers/FF4500.png gmplot/markers/FF6347.png gmplot/markers/FF69B4.png gmplot/markers/FF7F50.png gmplot/markers/FF8C00.png gmplot/markers/FFA07A.png gmplot/markers/FFA500.png gmplot/markers/FFB6C1.png gmplot/markers/FFC0CB.png gmplot/markers/FFD700.png gmplot/markers/FFDAB9.png gmplot/markers/FFDEAD.png gmplot/markers/FFE4B5.png gmplot/markers/FFE4C4.png gmplot/markers/FFE4E1.png gmplot/markers/FFEBCD.png gmplot/markers/FFEFD5.png gmplot/markers/FFF0F5.png gmplot/markers/FFF5EE.png gmplot/markers/FFF8DC.png gmplot/markers/FFFACD.png gmplot/markers/FFFAF0.png gmplot/markers/FFFAFA.png gmplot/markers/FFFF00.png gmplot/markers/FFFFE0.png gmplot/markers/FFFFF0.png gmplot/markers/FFFFFF.pnggmplot-1.1.1/gmplot.egg-info/top_level.txt0000644000076500000240000000000712762101470021172 0ustar mwoodsstaff00000000000000gmplot gmplot-1.1.1/MANIFEST.in0000644000076500000240000000007512762101412015203 0ustar mwoodsstaff00000000000000recursive-include gmplot *.png recursive-include gmplot *.py gmplot-1.1.1/PKG-INFO0000644000076500000240000000410212762101470014541 0ustar mwoodsstaff00000000000000Metadata-Version: 1.0 Name: gmplot Version: 1.1.1 Summary: Provide a matplotlib like interface to plotting data with Google Maps Home-page: https://github.com/vgm64/gmplot Author: Michael Woods Author-email: physicsmichael@gmail.com License: MIT Description: gmplot ====== Plotting data on Google Maps, the easy way. A matplotlib-like interface to generate the HTML and javascript to render all the data you'd like on top of Google Maps. Several plotting methods make creating exploratory map views effortless. Here's a crash course: :: import gmplot gmap = gmplot.GoogleMapPlotter(37.428, -122.145, 16) gmap.plot(latitudes, longitudes, 'cornflowerblue', edge_width=10) gmap.scatter(more_lats, more_lngs, '#3B0B39', size=40, marker=False) gmap.scatter(marker_lats, marker_lngs, 'k', marker=True) gmap.heatmap(heat_lats, heat_lngs) gmap.draw("mymap.html") Geocoding --------- ``gmplot`` contains a simple wrapper around Google's geocoding service enabling map initilization to the location of your choice. Rather than providing latitude, longitude, and zoom level during initialization, grab your gmplot instance with a location: :: gmap = gmplot.from_geocode("San Francisco") Plot types ---------- * Polygons with fills. * Drop pins. * Scatter points. * Grid lines. * Heatmaps. .. image:: http://i.imgur.com/dTNkbZ7.png Misc. ----- Code hosted on `GitHub `_ Install easily with ``pip install gmplot`` from PyPI. Inspired by Yifei Jiang's (jiangyifei@gmail.com) pygmaps_ module. .. _pygmaps: http://code.google.com/p/pygmaps/ Keywords: python wrapper google maps Platform: UNKNOWN gmplot-1.1.1/README.rst0000644000076500000240000000250712762101412015136 0ustar mwoodsstaff00000000000000gmplot ====== Plotting data on Google Maps, the easy way. A matplotlib-like interface to generate the HTML and javascript to render all the data you'd like on top of Google Maps. Several plotting methods make creating exploratory map views effortless. Here's a crash course: :: import gmplot gmap = gmplot.GoogleMapPlotter(37.428, -122.145, 16) gmap.plot(latitudes, longitudes, 'cornflowerblue', edge_width=10) gmap.scatter(more_lats, more_lngs, '#3B0B39', size=40, marker=False) gmap.scatter(marker_lats, marker_lngs, 'k', marker=True) gmap.heatmap(heat_lats, heat_lngs) gmap.draw("mymap.html") Geocoding --------- ``gmplot`` contains a simple wrapper around Google's geocoding service enabling map initilization to the location of your choice. Rather than providing latitude, longitude, and zoom level during initialization, grab your gmplot instance with a location: :: gmap = gmplot.from_geocode("San Francisco") Plot types ---------- * Polygons with fills. * Drop pins. * Scatter points. * Grid lines. * Heatmaps. .. image:: http://i.imgur.com/dTNkbZ7.png Misc. ----- Code hosted on `GitHub `_ Install easily with ``pip install gmplot`` from PyPI. Inspired by Yifei Jiang's (jiangyifei@gmail.com) pygmaps_ module. .. _pygmaps: http://code.google.com/p/pygmaps/ gmplot-1.1.1/setup.cfg0000644000076500000240000000007312762101470015270 0ustar mwoodsstaff00000000000000[egg_info] tag_build = tag_date = 0 tag_svn_revision = 0 gmplot-1.1.1/setup.py0000644000076500000240000000127712762101430015164 0ustar mwoodsstaff00000000000000import os from setuptools import setup, find_packages __version__ = '1.1.1' def read(fname): return open(os.path.join(os.path.dirname(__file__), fname)).read() setup( name = 'gmplot', version = __version__, author = 'Michael Woods', author_email = 'physicsmichael@gmail.com', url = 'https://github.com/vgm64/gmplot', description = 'Provide a matplotlib like interface to plotting data with Google Maps', long_description=read('README.rst'), license='MIT', keywords='python wrapper google maps', packages = find_packages(), include_package_data=True, package_data = { 'gmplot': ['markers/*.png'], }, install_requires=['requests'], )