def test_diffusionGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC)
Gcr_ut = metaknowledge.diffusionGraph(self.RC,
self.RC,
sourceType="CR",
targetType="UT")
self.assertEqual(
metaknowledge.graphStats(G, sentenceString=True),
'The graph has 42 nodes, 1569 edges, 0 isolates, 35 self loops, a density of 0.91115 and a transitivity of 0.894934'
)
self.assertEqual(
metaknowledge.graphStats(Gcr_ut, sentenceString=True),
'The graph has 528 nodes, 3591 edges, 246 isolates, 0 self loops, a density of 0.0129054 and a transitivity of 0'
)
def test_multiGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC, labelEdgesBy='PY')
metaknowledge.dropEdges(G, dropSelfLoops=True)
#multigraphs have issues their edge counts are somewhat unpredictable
self.assertEqual(
metaknowledge.graphStats(G,
stats=('nodes', 'isolates', 'loops'),
sentenceString=True),
'The graph has 42 nodes, 0 isolates and 0 self loops')
def test_multiGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC, labelEdgesBy = 'PY')
metaknowledge.dropEdges(G, dropSelfLoops = True)
#multigraphs have issues their edge counts are somewhat unpredictable
self.assertEqual(metaknowledge.graphStats(G, stats = ('nodes', 'isolates', 'loops'), sentenceString = True), 'The graph has 42 nodes, 0 isolates and 0 self loops')
def test_diffusionGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC)
Gcr_ut = metaknowledge.diffusionGraph(self.RC, self.RC, sourceType = "CR", targetType = "UT")
self.assertEqual(metaknowledge.graphStats(G, sentenceString = True), 'The graph has 42 nodes, 1569 edges, 0 isolates, 35 self loops, a density of 0.91115 and a transitivity of 0.894934')
self.assertEqual(metaknowledge.graphStats(Gcr_ut, sentenceString = True), 'The graph has 528 nodes, 3591 edges, 246 isolates, 0 self loops, a density of 0.0129054 and a transitivity of 0')
def test_multiGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC, labelEdgesBy = 'PY')
self.assertEqual(metaknowledge.graphStats(G, stats = ('nodes', 'edges', 'isolates', 'loops', 'density')), 'The graph has 33 nodes, 31 edges, 11 isolates, 0 self loops and a density of 0.0293561')
def test_diffusionGraph(self):
G = metaknowledge.diffusionGraph(self.RC, self.RC)
Gcr_ut = metaknowledge.diffusionGraph(self.RC, self.RC, sourceType = "CR", targetType = "UT")
self.assertEqual(metaknowledge.graphStats(G), 'The graph has 33 nodes, 31 edges, 11 isolates, 0 self loops, a density of 0.0293561 and a transitivity of 0.127907')
self.assertEqual(metaknowledge.graphStats(Gcr_ut), 'The graph has 525 nodes, 597 edges, 254 isolates, 0 self loops, a density of 0.00217012 and a transitivity of 0')
self.assertEqual(G.edges(data = True).pop()[2]['weight'], 1)
