def testNonzero(self):
try:
from pysparse import spmatrix
from apgl.util.PySparseUtils import PySparseUtils
except ImportError as error:
return
n = 10
X = spmatrix.ll_mat(n, n)
self.assertTrue(
(PySparseUtils.nonzero(X)[0] == numpy.array([], numpy.int)).all())
self.assertTrue(
(PySparseUtils.nonzero(X)[0] == numpy.array([], numpy.int)).all())
X[1, 1] = 5
X[2, 4] = 6.1
X[3, 1] = 2.5
self.assertTrue(
(PySparseUtils.nonzero(X)[0] == numpy.array([1, 2, 3],
numpy.int)).all())
self.assertTrue(
(PySparseUtils.nonzero(X)[1] == numpy.array([1, 4, 1],
numpy.int)).all())
def multiply(self, graph):
"""
Multiply the edge weights of the input graph to the current one. Results in an
intersection of the edges.
:param graph: the input graph.
:type graph: :class:`apgl.graph.PySparseGraph`
:returns: A new graph with edge weights which are multiples of the current and graph
"""
Parameter.checkClass(graph, PySparseGraph)
if graph.getNumVertices() != self.getNumVertices():
raise ValueError(
"Can only add edges from graph with same number of vertices")
if self.undirected != graph.undirected:
raise ValueError(
"Both graphs must be either undirected or directed")
if self.W.nnz < graph.W.nnz:
(rows, cols) = PySparseUtils.nonzero(self.W)
else:
(rows, cols) = PySparseUtils.nonzero(graph.W)
arr1 = numpy.zeros(len(rows))
arr2 = numpy.zeros(len(rows))
self.W.take(arr1, rows, cols)
graph.W.take(arr2, rows, cols)
arr1 = arr1 * arr2
newGraph = PySparseGraph(self.vList, self.undirected)
newGraph.W.put(arr1, rows, cols)
return newGraph
def multiply(self, graph):
"""
Multiply the edge weights of the input graph to the current one. Results in an
intersection of the edges.
:param graph: the input graph.
:type graph: :class:`apgl.graph.PySparseGraph`
:returns: A new graph with edge weights which are multiples of the current and graph
"""
Parameter.checkClass(graph, PySparseGraph)
if graph.getNumVertices() != self.getNumVertices():
raise ValueError("Can only add edges from graph with same number of vertices")
if self.undirected != graph.undirected:
raise ValueError("Both graphs must be either undirected or directed")
if self.W.nnz < graph.W.nnz:
(rows, cols) = PySparseUtils.nonzero(self.W)
else:
(rows, cols) = PySparseUtils.nonzero(graph.W)
arr1 = numpy.zeros(len(rows))
arr2 = numpy.zeros(len(rows))
self.W.take(arr1, rows, cols)
graph.W.take(arr2, rows, cols)
arr1 = arr1 * arr2
newGraph = PySparseGraph(self.vList, self.undirected)
newGraph.W.put(arr1, rows, cols)
return newGraph
def setDiff(self, graph):
"""
Find the edges in the current graph which are not present in the input
graph.
:param graph: the input graph.
:type graph: :class:`apgl.graph.PySparseGraph`
:returns: A new graph with edges from the current graph and not in the input graph.
"""
Parameter.checkClass(graph, PySparseGraph)
if graph.getNumVertices() != self.getNumVertices():
raise ValueError("Can only add edges from graph with same number of vertices")
if self.undirected != graph.undirected:
raise ValueError("Both graphs must be either undirected or directed")
A1 = self.nativeAdjacencyMatrix()
A2 = graph.nativeAdjacencyMatrix()
(rows, cols) = PySparseUtils.nonzero(A1)
arr1 = numpy.zeros(len(rows))
arr2 = numpy.zeros(len(rows))
A1.take(arr1, rows, cols)
A2.take(arr2, rows, cols)
arr1 = arr1 - arr2
A1.put(arr1, rows, cols)
newGraph = PySparseGraph(self.vList, self.undirected)
newGraph.W = A1
return newGraph
def setDiff(self, graph):
"""
Find the edges in the current graph which are not present in the input
graph.
:param graph: the input graph.
:type graph: :class:`apgl.graph.PySparseGraph`
:returns: A new graph with edges from the current graph and not in the input graph.
"""
Parameter.checkClass(graph, PySparseGraph)
if graph.getNumVertices() != self.getNumVertices():
raise ValueError(
"Can only add edges from graph with same number of vertices")
if self.undirected != graph.undirected:
raise ValueError(
"Both graphs must be either undirected or directed")
A1 = self.nativeAdjacencyMatrix()
A2 = graph.nativeAdjacencyMatrix()
(rows, cols) = PySparseUtils.nonzero(A1)
arr1 = numpy.zeros(len(rows))
arr2 = numpy.zeros(len(rows))
A1.take(arr1, rows, cols)
A2.take(arr2, rows, cols)
arr1 = arr1 - arr2
A1.put(arr1, rows, cols)
newGraph = PySparseGraph(self.vList, self.undirected)
newGraph.W = A1
return newGraph
def testSum(self):
try:
from pysparse import spmatrix
from apgl.util.PySparseUtils import PySparseUtils
except ImportError as error:
return
n = 10
X = spmatrix.ll_mat(n, n)
self.assertEquals(PySparseUtils.sum(X), 0.0)
X[1, 1] = 5
X[2, 4] = 6.1
X[3, 1] = 2.5
self.assertEquals(PySparseUtils.sum(X), 13.6)
def testSum(self):
try:
from pysparse import spmatrix
from apgl.util.PySparseUtils import PySparseUtils
except ImportError as error:
return
n = 10
X = spmatrix.ll_mat(n, n)
self.assertEquals(PySparseUtils.sum(X), 0.0)
X[1, 1] = 5
X[2, 4] = 6.1
X[3, 1] = 2.5
self.assertEquals(PySparseUtils.sum(X), 13.6)
def testNonzero(self):
try:
from pysparse import spmatrix
from apgl.util.PySparseUtils import PySparseUtils
except ImportError as error:
return
n = 10
X = spmatrix.ll_mat(n, n)
self.assertTrue((PySparseUtils.nonzero(X)[0]==numpy.array([], numpy.int)).all())
self.assertTrue((PySparseUtils.nonzero(X)[0]==numpy.array([], numpy.int)).all())
X[1, 1] = 5
X[2, 4] = 6.1
X[3, 1] = 2.5
self.assertTrue((PySparseUtils.nonzero(X)[0]==numpy.array([1,2,3], numpy.int)).all())
self.assertTrue((PySparseUtils.nonzero(X)[1]==numpy.array([1,4,1], numpy.int)).all())
def nativeAdjacencyMatrix(self):
"""
Return the adjacency matrix in sparse format.
"""
A = spmatrix.ll_mat(self.vList.getNumVertices(), self.vList.getNumVertices())
nonzeros = PySparseUtils.nonzero(self.W)
A.put(1, nonzeros[0], nonzeros[1])
return A
def nativeAdjacencyMatrix(self):
"""
Return the adjacency matrix in sparse format.
"""
A = spmatrix.ll_mat(self.vList.getNumVertices(),
self.vList.getNumVertices())
nonzeros = PySparseUtils.nonzero(self.W)
A.put(1, nonzeros[0], nonzeros[1])
return A
def getAllDirEdges(self):
"""
Returns the set of directed edges of the current graph as a matrix in which each
row corresponds to an edge. For an undirected graph, there is an edge from
v1 to v2 and from v2 to v1 if v2!=v1.
:returns: A matrix with 2 columns, and each row corresponding to an edge.
"""
(rows, cols) = PySparseUtils.nonzero(self.W)
edges = numpy.c_[rows, cols]
return edges
def getAllDirEdges(self):
"""
Returns the set of directed edges of the current graph as a matrix in which each
row corresponds to an edge. For an undirected graph, there is an edge from
v1 to v2 and from v2 to v1 if v2!=v1.
:returns: A matrix with 2 columns, and each row corresponding to an edge.
"""
(rows, cols) = PySparseUtils.nonzero(self.W)
edges = numpy.c_[rows, cols]
return edges
def neighbourOf(self, vertexIndex):
"""
Return an array of the indices of vertices than have an edge going to the input
vertex.
:param vertexIndex: the index of a vertex.
:type vertexIndex: :class:`int`
:returns: An array of the indices of all vertices with an edge towards the input vertex.
"""
Parameter.checkIndex(vertexIndex, 0, self.vList.getNumVertices())
neighbours = PySparseUtils.nonzero(self.W[:, vertexIndex])[0]
return numpy.array(neighbours)
def neighbourOf(self, vertexIndex):
"""
Return an array of the indices of vertices than have an edge going to the input
vertex.
:param vertexIndex: the index of a vertex.
:type vertexIndex: :class:`int`
:returns: An array of the indices of all vertices with an edge towards the input vertex.
"""
Parameter.checkIndex(vertexIndex, 0, self.vList.getNumVertices())
neighbours = PySparseUtils.nonzero(self.W[:, vertexIndex])[0]
return numpy.array(neighbours)
def neighbours(self, vertexIndex):
"""
Return an array of the indices of neighbours. In the case of a directed
graph it is an array of those vertices connected by an edge from the current
one.
:param vertexIndex: the index of a vertex.
:type vertexIndex: :class:`int`
:returns: An array of the indices of all neigbours of the input vertex.
"""
Parameter.checkIndex(vertexIndex, 0, self.vList.getNumVertices())
neighbours = PySparseUtils.nonzero(self.W[int(vertexIndex), :])[1]
return numpy.array(neighbours)
def neighbours(self, vertexIndex):
"""
Return an array of the indices of neighbours. In the case of a directed
graph it is an array of those vertices connected by an edge from the current
one.
:param vertexIndex: the index of a vertex.
:type vertexIndex: :class:`int`
:returns: An array of the indices of all neigbours of the input vertex.
"""
Parameter.checkIndex(vertexIndex, 0, self.vList.getNumVertices())
neighbours = PySparseUtils.nonzero(self.W[int(vertexIndex), :])[1]
return numpy.array(neighbours)
def runSum():
for i in range(1000):
i = PySparseUtils.sum(A)
print(i)
def runNonZeros():
for i in range(1000):
(rows, cols) = PySparseUtils.nonzero(A)
nzVals = numpy.zeros(len(rows))
A.take(nzVals, rows, cols)
def runNonZeros():
for i in range(1000):
(rows, cols) = PySparseUtils.nonzero(A)
nzVals = numpy.zeros(len(rows))
A.take(nzVals, rows, cols)
def runSum():
for i in range(1000):
i = PySparseUtils.sum(A)
print(i)