def test_progress(self):
metaknowledge.VERBOSE_MODE = True
tmpIO = io.StringIO()
P = _ProgressBar(0, "testing", output=tmpIO, dummy=True)
metaknowledge.writeEdgeList(
self.G,
fileEName,
_progBar=P,
)
tmpIO.seek(0)
s = ''.join(tmpIO.readlines())
self.assertEqual(len(s), 0)
P = _ProgressBar(0, "testing", output=tmpIO)
metaknowledge.writeEdgeList(self.G, fileEName, _progBar=P)
tmpIO.seek(0)
os.remove(fileEName)
s = ''.join(tmpIO.readlines())
self.assertEqual(s[-14], '[')
self.assertEqual(s[-1], '%')
P.finish("done test")
tmpIO.seek(0)
s = ''.join(tmpIO.readlines())
self.assertEqual(
s[-81:-3],
'done test 0.'
)
metaknowledge.VERBOSE_MODE = False
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 test_progress(self):
metaknowledge.VERBOSE_MODE = True
tmpIO = io.StringIO()
P = _ProgressBar(0, "testing", output = tmpIO, dummy = True)
metaknowledge.writeEdgeList(self.G, fileEName, _progBar = P, )
tmpIO.seek(0)
s = ''.join(tmpIO.readlines())
self.assertEqual(len(s), 0)
P = _ProgressBar(0, "testing", output = tmpIO)
metaknowledge.writeEdgeList(self.G, fileEName, _progBar = P)
tmpIO.seek(0)
s = ''.join(tmpIO.readlines())
self.assertFalse("]100.0%" in s)
self.assertTrue("Done edge list" in s)
os.remove(fileEName)
metaknowledge.VERBOSE_MODE = False
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)
