def testDegreeDistribution(self):
#We want to see how the degree distribution changes with kronecker powers
numVertices = 3
numFeatures = 0
vList = VertexList(numVertices, numFeatures)
initialGraph = SparseGraph(vList)
initialGraph.addEdge(0, 1)
initialGraph.addEdge(1, 2)
for i in range(numVertices):
initialGraph.addEdge(i, i)
logging.debug((initialGraph.outDegreeSequence()))
logging.debug((initialGraph.degreeDistribution()))
k = 2
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
logging.debug((graph.outDegreeSequence()))
logging.debug((graph.degreeDistribution()))
k = 3
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
logging.debug((graph.degreeDistribution()))
def KroneckerEdgeList(n):
init = SparseGraph(4)
init[0, 1] = 1
init[0, 2] = 1
init[0, 3] = 1
for i in range(4):
init[i, i] = 1
k = int(log(n, 4)) + 1
generator = KroneckerGenerator(init, k)
graph = generator.generate()
l, _ = graph.adjacencyList()
return convertAdjListToEdgeList(l)
def testGenerate(self):
k = 2
numVertices = 1000
numFeatures = 0
vList = VertexList(numVertices, numFeatures)
initialGraph = SparseGraph(vList)
initialGraph.addEdge(0, 1)
initialGraph.addEdge(1, 2)
for i in range(numVertices):
initialGraph.addEdge(i, i)
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
print (graph.size)
def testGenerate(self):
k = 2
numVertices = 3
numFeatures = 0
vList = VertexList(numVertices, numFeatures)
initialGraph = SparseGraph(vList)
initialGraph.addEdge(0, 1)
initialGraph.addEdge(1, 2)
for i in range(numVertices):
initialGraph.addEdge(i, i)
d = initialGraph.diameter()
degreeSequence = initialGraph.outDegreeSequence()
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
d2 = graph.diameter()
degreeSequence2 = graph.outDegreeSequence()
self.assertTrue((numpy.kron(degreeSequence,
degreeSequence) == degreeSequence2).all())
self.assertTrue(graph.getNumVertices() == numVertices**k)
self.assertTrue(
graph.getNumDirEdges() == initialGraph.getNumDirEdges()**k)
self.assertEquals(d, d2)
#Try different k
k = 3
generator.setK(k)
graph = generator.generate()
d3 = graph.diameter()
degreeSequence3 = graph.outDegreeSequence()
self.assertTrue((numpy.kron(degreeSequence,
degreeSequence2) == degreeSequence3).all())
self.assertTrue(graph.getNumVertices() == numVertices**k)
self.assertTrue(
graph.getNumDirEdges() == initialGraph.getNumDirEdges()**k)
self.assertEquals(d, d3)
#Test the multinomial degree distribution
logging.debug(degreeSequence)
logging.debug(degreeSequence2)
logging.debug(degreeSequence3)
initialGraph = SparseGraph(VertexList(5, 1))
initialGraph.addEdge(1, 2)
initialGraph.addEdge(2, 3)
initialGraph.addEdge(1, 4)
initialGraph.addEdge(2, 4)
initialGraph.addEdge(1, 3)
initialGraph.addEdge(0, 1)
for i in range(5):
initialGraph.addEdge(i, i)
## Now we are using the seed graph to recrusively generate a kronecker graph that has
## 5^5 = 3125 vertexes
k = 6
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
## Number of runs
runs = 10000
# In[3]:
x = graph.adjacencyMatrix()
# In[4]:
# plt.figure(figsize=(12,12))
# plt.matshow(x,cmap=plt.cm.gray)
# plt.show()
