def testAddVertices(self):
numFeatures = 5
vList = VertexList(10, numFeatures)
vList.setVertex(1, numpy.ones(numFeatures) * 0.1)
self.assertEquals(vList.getNumVertices(), 10)
nptst.assert_array_equal(vList[1], numpy.ones(numFeatures) * 0.1)
vList.addVertices(5)
self.assertEquals(vList.getNumVertices(), 15)
vList.setVertex(11, numpy.ones(numFeatures) * 2)
nptst.assert_array_equal(vList[1], numpy.ones(numFeatures) * 0.1)
nptst.assert_array_equal(vList[11], numpy.ones(numFeatures) * 2)
def testAddVertices(self):
numFeatures = 5
vList = VertexList(10, numFeatures)
vList.setVertex(1, numpy.ones(numFeatures)*0.1)
self.assertEquals(vList.getNumVertices(), 10)
nptst.assert_array_equal(vList[1], numpy.ones(numFeatures)*0.1)
vList.addVertices(5)
self.assertEquals(vList.getNumVertices(), 15)
vList.setVertex(11, numpy.ones(numFeatures)*2)
nptst.assert_array_equal(vList[1], numpy.ones(numFeatures)*0.1)
nptst.assert_array_equal(vList[11], numpy.ones(numFeatures)*2)
def testFullTransGraph(self):
transGraph = self.egoSimulator.fullTransGraph()
#Create a simple graph and deterministic classifier
numExamples = 10
numFeatures = 3
#Here, the first element is gender (say) with female = 0, male = 1
vList = VertexList(numExamples, numFeatures)
vList.setVertex(0, numpy.array([0,0,1]))
vList.setVertex(1, numpy.array([1,0,0]))
vList.setVertex(2, numpy.array([1,0,0]))
vList.setVertex(3, numpy.array([1,0,0]))
vList.setVertex(4, numpy.array([0,0,1]))
vList.setVertex(5, numpy.array([0,0,1]))
vList.setVertex(6, numpy.array([0,0,0]))
vList.setVertex(7, numpy.array([1,0,0]))
vList.setVertex(8, numpy.array([0,0,1]))
vList.setVertex(9, numpy.array([1,0,0]))
sGraph = SparseGraph(vList)
sGraph.addEdge(0, 1, 1)
sGraph.addEdge(0, 2, 1)
sGraph.addEdge(0, 3, 1)
sGraph.addEdge(4, 5, 1)
sGraph.addEdge(4, 6, 1)
sGraph.addEdge(6, 7, 1)
sGraph.addEdge(6, 8, 1)
sGraph.addEdge(6, 9, 1)
simulator = EgoSimulator(sGraph, self.dc)
logging.debug("Writing out full transmission graph")
transGraph = simulator.fullTransGraph()
self.assertEquals(transGraph.isUndirected(), False)
self.assertEquals(transGraph.getNumEdges(), 11)
self.assertEquals(transGraph.getEdge(0,1), 1)
self.assertEquals(transGraph.getEdge(0,2), 1)
self.assertEquals(transGraph.getEdge(0,3), 1)
self.assertEquals(transGraph.getEdge(4,5), 1)
self.assertEquals(transGraph.getEdge(4,6), 1)
self.assertEquals(transGraph.getEdge(5,4), 1)
self.assertEquals(transGraph.getEdge(6,4), 1)
self.assertEquals(transGraph.getEdge(6,7), 1)
self.assertEquals(transGraph.getEdge(6,8), 1)
self.assertEquals(transGraph.getEdge(6,9), 1)
self.assertEquals(transGraph.getEdge(8,6), 1)
self.assertEquals(transGraph.getVertexList(), vList)
def testSaveLoad(self):
try:
vList = VertexList(self.numVertices, self.numFeatures)
vList.setVertex(0, numpy.array([1, 2, 3]))
vList.setVertex(1, numpy.array([4, 5, 6]))
vList.setVertex(2, numpy.array([7, 8, 9]))
tempDir = PathDefaults.getTempDir()
fileName = tempDir + "vList"
vList.save(fileName)
vList2 = VertexList.load(fileName)
self.assertTrue((vList.getVertices() == vList2.getVertices()).all())
except IOError as e:
logging.warn(e)
pass
def testSaveLoad(self):
try:
vList = VertexList(self.numVertices, self.numFeatures)
vList.setVertex(0, numpy.array([1, 2, 3]))
vList.setVertex(1, numpy.array([4, 5, 6]))
vList.setVertex(2, numpy.array([7, 8, 9]))
tempDir = PathDefaults.getTempDir()
fileName = tempDir + "vList"
vList.save(fileName)
vList2 = VertexList.load(fileName)
self.assertTrue(
(vList.getVertices() == vList2.getVertices()).all())
except IOError as e:
logging.warn(e)
pass
def readFromFile(self, fileName):
inFile = open(fileName, "r")
numFeatures = 1
graphList = []
line = inFile.readline()
while line != "":
#First 3 lines are useless
inFile.readline()
inFile.readline()
#4th line has edge information
line = inFile.readline()
valueList = line.split(None)
numVertices = int(valueList[0])
#Not strictly the number of edges, as molecules can have multiple edges
#between a pair of atoms
numEdges = int(valueList[1])
vList = VertexList(numVertices, numFeatures)
for i in range(numVertices):
line = inFile.readline()
valueList = line.split(None)
vList.setVertex(i, numpy.array([self.atomDict[valueList[3]]]))
graph = SparseGraph(vList)
for i in range(numEdges):
line = inFile.readline()
valueList = line.split(None)
graph.addEdge(int(valueList[0]) - 1, int(valueList[1]) - 1)
graphList.append(graph)
#Ignore next two lines
inFile.readline()
inFile.readline()
line = inFile.readline()
return graphList
def readFromFile(self, fileName):
inFile = open(fileName,"r")
numFeatures = 1
graphList = []
line = inFile.readline()
while line != "":
#First 3 lines are useless
inFile.readline()
inFile.readline()
#4th line has edge information
line = inFile.readline()
valueList = line.split(None)
numVertices = int(valueList[0])
#Not strictly the number of edges, as molecules can have multiple edges
#between a pair of atoms
numEdges = int(valueList[1])
vList = VertexList(numVertices, numFeatures)
for i in range(numVertices):
line = inFile.readline()
valueList = line.split(None)
vList.setVertex(i, numpy.array([self.atomDict[valueList[3]]]))
graph = SparseGraph(vList)
for i in range(numEdges):
line = inFile.readline()
valueList = line.split(None)
graph.addEdge(int(valueList[0])-1, int(valueList[1])-1)
graphList.append(graph)
#Ignore next two lines
inFile.readline()
inFile.readline()
line = inFile.readline()
return graphList
def generateIndicatorVertices(self, numVertices, mu, sigma, p):
"""
Generate a set of vertices from the means and variances of Y using
the multivariate normal distribution. Also add at
the end an indicator variables which is 1 with probability p.
"""
if not (sigma.T == sigma).all():
raise ValueError("Must use symmetric sigma matrix: " + str(sigma))
n = mu.shape[0]
X = numpy.zeros((numVertices, n+1), numpy.int32)
X[:, 0:n] = numpy.round(random.multivariate_normal(mu, sigma, numVertices)).astype(numpy.int32)
X[:, n] = (random.rand(numVertices) < p).astype(numpy.int32)
vList = VertexList(numVertices, n+1)
for i in range(0, numVertices):
vList.setVertex(i, X[i, :])
return vList
def readFromFile(self, fileName):
X = numpy.loadtxt(fileName, skiprows=1, converters=self.converters)
vertexIds = numpy.zeros(X.shape[0] * 2)
#First, we will map the vertex Ids to a set of numbers
for i in range(0, X.shape[0]):
vertexIds[2 * i] = X[i, self.vertex1IdIndex]
vertexIds[2 * i + 1] = X[i, self.vertex2IdIndex]
vertexIds = numpy.unique(vertexIds)
numVertices = vertexIds.shape[0]
numFeatures = len(self.vertex1Indices)
vList = VertexList(numVertices, numFeatures)
sGraph = SparseGraph(vList, self.undirected)
for i in range(0, X.shape[0]):
vertex1Id = X[i, self.vertex1IdIndex]
vertex2Id = X[i, self.vertex2IdIndex]
vertex1 = X[i, self.vertex1Indices]
vertex2 = X[i, self.vertex2Indices]
vertex1VListId = numpy.nonzero(vertexIds == vertex1Id)[0]
vertex2VListId = numpy.nonzero(vertexIds == vertex2Id)[0]
vertex1VListId = int(vertex1VListId)
vertex2VListId = int(vertex2VListId)
vList.setVertex(vertex1VListId, vertex1)
vList.setVertex(vertex2VListId, vertex2)
sGraph.addEdge(vertex1VListId, vertex2VListId, self.edgeWeight)
logging.info("Read " + fileName + " with " +
str(sGraph.getNumVertices()) + " vertices and " +
str(sGraph.getNumEdges()) + " edges")
return sGraph
def readFromFile(self, fileName):
X = numpy.loadtxt(fileName, skiprows=1, converters=self.converters)
vertexIds = numpy.zeros(X.shape[0]*2)
#First, we will map the vertex Ids to a set of numbers
for i in range(0, X.shape[0]):
vertexIds[2*i] = X[i, self.vertex1IdIndex]
vertexIds[2*i+1] = X[i, self.vertex2IdIndex]
vertexIds = numpy.unique(vertexIds)
numVertices = vertexIds.shape[0]
numFeatures = len(self.vertex1Indices)
vList = VertexList(numVertices, numFeatures)
sGraph = SparseGraph(vList, self.undirected)
for i in range(0, X.shape[0]):
vertex1Id = X[i, self.vertex1IdIndex]
vertex2Id = X[i, self.vertex2IdIndex]
vertex1 = X[i, self.vertex1Indices]
vertex2 = X[i, self.vertex2Indices]
vertex1VListId = numpy.nonzero(vertexIds==vertex1Id)[0]
vertex2VListId = numpy.nonzero(vertexIds==vertex2Id)[0]
vertex1VListId = int(vertex1VListId)
vertex2VListId = int(vertex2VListId)
vList.setVertex(vertex1VListId, vertex1)
vList.setVertex(vertex2VListId, vertex2)
sGraph.addEdge(vertex1VListId, vertex2VListId, self.edgeWeight)
logging.info("Read " + fileName + " with " + str(sGraph.getNumVertices()) + " vertices and " + str(sGraph.getNumEdges()) + " edges")
return sGraph
def testAdvanceGraph2(self):
#Create a simple graph and deterministic classifier
numExamples = 10
numFeatures = 3
#Here, the first element is gender (say) with female = 0, male = 1
vList = VertexList(numExamples, numFeatures)
vList.setVertex(0, numpy.array([0,0,1]))
vList.setVertex(1, numpy.array([1,0,0]))
vList.setVertex(2, numpy.array([1,0,0]))
vList.setVertex(3, numpy.array([1,0,0]))
vList.setVertex(4, numpy.array([0,0,1]))
vList.setVertex(5, numpy.array([0,0,1]))
vList.setVertex(6, numpy.array([0,0,0]))
vList.setVertex(7, numpy.array([1,0,0]))
vList.setVertex(8, numpy.array([0,0,1]))
vList.setVertex(9, numpy.array([1,0,0]))
sGraph = SparseGraph(vList)
sGraph.addEdge(0, 1, 1)
sGraph.addEdge(0, 2, 1)
sGraph.addEdge(0, 3, 1)
sGraph.addEdge(4, 5, 1)
sGraph.addEdge(4, 6, 1)
sGraph.addEdge(6, 7, 1)
sGraph.addEdge(6, 8, 1)
sGraph.addEdge(6, 9, 1)
simulator = EgoSimulator(sGraph, self.dc)
simulator.advanceGraph()
self.assertEquals(simulator.getNumIterations(), 1)
self.assertEquals(sGraph.getVertex(0)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(1)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(2)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(3)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(4)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(5)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(6)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(7)[numFeatures-1], 0)
self.assertEquals(sGraph.getVertex(8)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(9)[numFeatures-1], 0)
#Advance again and all egos have information
simulator.advanceGraph()
self.assertEquals(simulator.getNumIterations(), 2)
self.assertEquals(sGraph.getVertex(0)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(1)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(2)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(3)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(4)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(5)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(6)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(7)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(8)[numFeatures-1], 1)
self.assertEquals(sGraph.getVertex(9)[numFeatures-1], 1)
#Should be no change
simulator.advanceGraph()
self.assertEquals(simulator.getNumIterations(), 3)
#Check the correct alters are added at each step
self.assertTrue((simulator.getAlters(0) == numpy.array([1,2,3,6])).all())
self.assertTrue((simulator.getAlters(1) == numpy.array([7,9])).all())
self.assertTrue((simulator.getAlters(2) == numpy.array([])).all())
#Check that the transmission graph is okay
transGraph = simulator.getTransmissionGraph()
self.assertEquals(transGraph.getNumVertices(), 9)
self.assertEquals(transGraph.getNumEdges(), 7)
self.assertEquals(transGraph.getAllVertexIds(), [0, 1, 2, 3, 4, 6, 7, 8, 9])
for i in transGraph.getAllVertexIds():
self.assertTrue((transGraph.getVertex(i) == sGraph.getVertex(i)).all())
def setUp(self):
self.tol = 10**-4
self.numVertices = 5
self.numFeatures = 2
vertexList1 = VertexList(self.numVertices, self.numFeatures)
vertexList1.setVertex(0, numpy.array([1, 1]))
vertexList1.setVertex(1, numpy.array([1, 2]))
vertexList1.setVertex(2, numpy.array([3, 2]))
vertexList1.setVertex(3, numpy.array([4, 2]))
vertexList1.setVertex(4, numpy.array([2, 6]))
vertexList2 = VertexList(self.numVertices, self.numFeatures)
vertexList2.setVertex(0, numpy.array([1, 3]))
vertexList2.setVertex(1, numpy.array([7, 2]))
vertexList2.setVertex(2, numpy.array([3, 22]))
vertexList2.setVertex(3, numpy.array([54, 2]))
vertexList2.setVertex(4, numpy.array([2, 34]))
self.sGraph1 = SparseGraph(vertexList1)
self.sGraph1.addEdge(0, 1)
self.sGraph1.addEdge(0, 2)
self.sGraph1.addEdge(1, 2)
self.sGraph1.addEdge(2, 3)
self.sGraph2 = SparseGraph(vertexList2)
self.sGraph2.addEdge(0, 1)
self.sGraph2.addEdge(0, 2)
self.sGraph2.addEdge(1, 2)
self.sGraph2.addEdge(2, 3)
self.sGraph2.addEdge(3, 4)
self.sGraph3 = SparseGraph(vertexList2)
self.sGraph3.addEdge(4, 1)
self.sGraph3.addEdge(4, 2)
self.sGraph3.addEdge(1, 2)
self.sGraph3.addEdge(1, 0)
def setUp(self):
self.tol = 10**-4
self.numVertices = 5
self.numFeatures = 2
vertexList1 = VertexList(self.numVertices, self.numFeatures)
vertexList1.setVertex(0, numpy.array([1, 1]))
vertexList1.setVertex(1, numpy.array([1, 2]))
vertexList1.setVertex(2, numpy.array([3, 2]))
vertexList1.setVertex(3, numpy.array([4, 2]))
vertexList1.setVertex(4, numpy.array([2, 6]))
vertexList2 = VertexList(self.numVertices, self.numFeatures)
vertexList2.setVertex(0, numpy.array([1, 3]))
vertexList2.setVertex(1, numpy.array([7, 2]))
vertexList2.setVertex(2, numpy.array([3, 22]))
vertexList2.setVertex(3, numpy.array([54, 2]))
vertexList2.setVertex(4, numpy.array([2, 34]))
self.sGraph1 = SparseGraph(vertexList1)
self.sGraph1.addEdge(0, 1)
self.sGraph1.addEdge(0, 2)
self.sGraph1.addEdge(1, 2)
self.sGraph1.addEdge(2, 3)
self.sGraph2 = SparseGraph(vertexList2)
self.sGraph2.addEdge(0, 1)
self.sGraph2.addEdge(0, 2)
self.sGraph2.addEdge(1, 2)
self.sGraph2.addEdge(2, 3)
self.sGraph2.addEdge(3, 4)
self.sGraph3 = SparseGraph(vertexList2)
self.sGraph3.addEdge(4, 1)
self.sGraph3.addEdge(4, 2)
self.sGraph3.addEdge(1, 2)
self.sGraph3.addEdge(1, 0)
