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)
