def testGraphDisplay(self):
try:
import networkx
import matplotlib
except ImportError as error:
logging.debug(error)
return
#Show
numFeatures = 1
numVertices = 20
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
ell = 2
m = 2
generator = BarabasiAlbertGenerator(ell, m)
graph = generator.generate(graph)
logging.debug((graph.degreeDistribution()))
nxGraph = graph.toNetworkXGraph()
nodePositions = networkx.spring_layout(nxGraph)
nodesAndEdges = networkx.draw_networkx(nxGraph, pos=nodePositions)
def testGraphDisplay(self):
try:
import networkx
import matplotlib
except ImportError as error:
logging.debug(error)
return
#Show
numFeatures = 1
numVertices = 20
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
ell = 2
m = 2
generator = BarabasiAlbertGenerator(ell, m)
graph = generator.generate(graph)
logging.debug((graph.degreeDistribution()))
nxGraph = graph.toNetworkXGraph()
nodePositions = networkx.spring_layout(nxGraph)
nodesAndEdges = networkx.draw_networkx(nxGraph, pos=nodePositions)
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 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 = StochasticKroneckerGenerator(initialGraph, k)
graph = generator.generateGraph()
logging.debug((graph.outDegreeSequence()))
logging.debug((graph.degreeDistribution()))
k = 3
generator = StochasticKroneckerGenerator(initialGraph, k)
graph = generator.generateGraph()
logging.debug((graph.degreeDistribution()))
def testDegreeDistribution(self):
numFeatures = 0
numVertices = 100
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
alpha = 10.0
p = 0.01
dim = 2
generator = GeometricRandomGenerator(graph)
graph = generator.generateGraph(alpha, p, dim)
logging.debug((graph.degreeDistribution()))
def testDegreeDistribution(self):
numFeatures = 0
numVertices = 100
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
alpha = 10.0
p = 0.01
dim = 2
generator = GeometricRandomGenerator(graph)
graph = generator.generateGraph(alpha, p, dim)
logging.debug((graph.degreeDistribution()))
