def testInit(self):
numVertices = 0
numFeatures = 1
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
numVertices = 10
numFeatures = 1
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
self.assertEquals(graph.weightMatrixType(), scipy.sparse.csr_matrix)
self.assertRaises(ValueError, SparseGraph, [])
self.assertRaises(ValueError, SparseGraph, vList, 1)
self.assertRaises(ValueError, SparseGraph, vList, True, 1)
#Now test invalid values of W
W = numpy.zeros((numVertices, numVertices))
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices + 1, numVertices))
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices, numVertices))
W[0, 1] = 1
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices, numVertices))
graph = SparseGraph(vList, W=W)
self.assertEquals(graph.weightMatrixType(), scipy.sparse.lil_matrix)
#Test intialising with non-empty graph
numVertices = 10
W = scipy.sparse.csr_matrix((numVertices, numVertices))
W[1, 0] = 1.1
W[0, 1] = 1.1
graph = SparseGraph(numVertices, W=W)
self.assertEquals(graph[1, 0], 1.1)
#Test just specifying number of vertices
graph = SparseGraph(numVertices)
self.assertEquals(graph.size, numVertices)
#Try creating a sparse matrix of dtype int
graph = SparseGraph(numVertices, dtype=numpy.int)
self.assertEquals(graph.W.dtype, numpy.int)
graph[0, 0] = 1.2
self.assertEquals(graph[0, 0], 1)
#Test the different sparse matrix formats
graph = SparseGraph(numVertices, frmt="lil")
self.assertEquals(type(graph.W), scipy.sparse.lil_matrix)
graph = SparseGraph(numVertices, frmt="csr")
self.assertEquals(type(graph.W), scipy.sparse.csr_matrix)
graph = SparseGraph(numVertices, frmt="csc")
self.assertEquals(type(graph.W), scipy.sparse.csc_matrix)
def testInit(self):
numVertices = 0
numFeatures = 1
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
numVertices = 10
numFeatures = 1
vList = VertexList(numVertices, numFeatures)
graph = SparseGraph(vList)
self.assertEquals(graph.weightMatrixType(), scipy.sparse.csr_matrix)
self.assertRaises(ValueError, SparseGraph, [])
self.assertRaises(ValueError, SparseGraph, vList, 1)
self.assertRaises(ValueError, SparseGraph, vList, True, 1)
#Now test invalid values of W
W = numpy.zeros((numVertices, numVertices))
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices+1, numVertices))
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices, numVertices))
W[0, 1] = 1
self.assertRaises(ValueError, SparseGraph, vList, True, W)
W = scipy.sparse.lil_matrix((numVertices, numVertices))
graph = SparseGraph(vList, W=W)
self.assertEquals(graph.weightMatrixType(), scipy.sparse.lil_matrix)
#Test intialising with non-empty graph
numVertices = 10
W = scipy.sparse.csr_matrix((numVertices, numVertices))
W[1, 0] = 1.1
W[0, 1] = 1.1
graph = SparseGraph(numVertices, W=W)
self.assertEquals(graph[1, 0], 1.1)
#Test just specifying number of vertices
graph = SparseGraph(numVertices)
self.assertEquals(graph.size, numVertices)
#Try creating a sparse matrix of dtype int
graph = SparseGraph(numVertices, dtype=numpy.int)
self.assertEquals(graph.W.dtype, numpy.int)
graph[0, 0] = 1.2
self.assertEquals(graph[0, 0], 1)
#Test the different sparse matrix formats
graph = SparseGraph(numVertices, frmt="lil")
self.assertEquals(type(graph.W), scipy.sparse.lil_matrix)
graph = SparseGraph(numVertices, frmt="csr")
self.assertEquals(type(graph.W), scipy.sparse.csr_matrix)
graph = SparseGraph(numVertices, frmt="csc")
self.assertEquals(type(graph.W), scipy.sparse.csc_matrix)
