def test_graphwrite(self): metaknowledge.writeGraph(self.G, fileShortName, suffix = filesuffix) tmpG = metaknowledge.readGraph(fileEName, fileNName) self.assertEqual(len(tmpG.edges()), len(self.G.edges())) self.assertEqual(len(tmpG.nodes()), len(self.G.nodes())) os.remove(fileEName) os.remove(fileNName)
def test_graphwrite(self): metaknowledge.writeGraph(self.G, fileShortName, suffix=filesuffix) tmpG = metaknowledge.readGraph(fileEName, fileNName) self.assertEqual(len(tmpG.edges()), len(self.G.edges())) self.assertEqual(len(tmpG.nodes()), len(self.G.nodes())) os.remove(fileEName) os.remove(fileNName)
def outputNetwork(clargs, grph): outDict = collections.OrderedDict([ ('1', "edge list and node attribute list"), ('2', "edge list"), ('3', "node attribute list"), ('4', "graphml (SLOW)"), ]) try: import metaknowledge.contour except ImportError: import metaknowledge else: outDict['0'] = "view graph" outDict.move_to_end('0', last=False) print("The network contains {} nodes and {} edges.".format( len(grph.nodes()), len(grph.edges()))) outID = int(inputMenu(outDict, header="What type of output to you want? ")) if outID == 0: metaknowledge.contour.quickVisual(grph) outputNetwork(clargs, grph) elif outID == 1: while True: try: outName = getOutputName(clargs, '', checking=False) metaknowledge.writeGraph(grph, outName, overwrite=False) except OSError: if clargs.name: metaknowledge.writeGraph(grph, outName, overwrite=True) break else: overWrite = yesorNo("{}, overwrite (y/n)? ") if overWrite: metaknowledge.writeGraph(grph, outName, overwrite=True) break else: pass else: break elif outID == 2: outName = getOutputName(clargs, '.csv') metaknowledge.writeEdgeList(grph, outName) elif outID == 3: outName = getOutputName(clargs, '.csv') metaknowledge.writeNodeAttributeFile(grph, outName) else: outName = getOutputName(clargs, '.graphml') nx.write_graphml(grph, outName)
def outputNetwork(clargs, grph): outDict = collections.OrderedDict([ ('1', "edge list and node attribute list"), ('2', "edge list"), ('3', "node attribute list"), ('4', "graphml (SLOW)"), ]) try: import metaknowledge.contour except ImportError: import metaknowledge else: outDict['0'] = "view graph" outDict.move_to_end('0', last = False) print("The network contains {} nodes and {} edges.".format(len(grph.nodes()), len(grph.edges()))) outID = int(inputMenu(outDict, header = "What type of output to you want? ")) if outID == 0: metaknowledge.contour.quickVisual(grph) outputNetwork(clargs, grph) elif outID == 1: while True: try: outName = getOutputName(clargs, '', checking = False) metaknowledge.writeGraph(grph, outName, overwrite = False) except OSError: if clargs.name: metaknowledge.writeGraph(grph, outName, overwrite = True) break else: overWrite = yesorNo("{}, overwrite (y/n)? ") if overWrite: metaknowledge.writeGraph(grph, outName, overwrite = True) break else: pass else: break elif outID == 2: outName = getOutputName(clargs, '.csv') metaknowledge.writeEdgeList(grph, outName) elif outID == 3: outName = getOutputName(clargs, '.csv') metaknowledge.writeNodeAttributeFile(grph, outName) else: outName = getOutputName(clargs, '.graphml') nx.write_graphml(grph, outName)