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 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)
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 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()
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 29 12:45:00 2015
@author: Pankaj
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.sparse
import scipy as sp
from scipy import linalg
from scipy import sparse as sps
from scipy.sparse import linalg as spla
from apgl.graph import *
from apgl.generator.KroneckerGenerator import KroneckerGenerator
initialGraph = SparseGraph(VertexList(5, 1))
initialGraph.addEdge(1, 2)
initialGraph.addEdge(2, 3)
for i in range(5):
initialGraph.addEdge(i,i)
k=2
generator = KroneckerGenerator(initialGraph, k)
graph = generator.generate()
