def build_probability_matrix(graph, coeff=1.0):
#Get square matrix of shape nxn, where n is number of nodes of the given graph.
dimension = len(graph)
matrix = empty_matrix((dimension, dimension))
probability = coeff / float(dimension)
matrix.fill(probability)
return matrix
def build_probability_matrix(graph):
dimension = len(graph.nodes())
matrix = empty_matrix((dimension, dimension))
probability = 1 / float(dimension)
matrix.fill(probability)
return matrix
def build_probability_matrix(graph):
dimension = len(graph.nodes())
matrix = empty_matrix((dimension,dimension))
probability = 1 / float(dimension)
matrix.fill(probability)
return matrix
def build_probability_matrix(graph):
# print "Called Build prob mat!!"
dimension = len(graph.nodes())
matrix = empty_matrix((dimension, dimension))
probability = 1 / float(dimension)
matrix.fill(probability)
return matrix
def build_probability_matrix(graph):
"""Get square matrix of shape (n, n), where n is number of nodes of the
given `graph`.
Parameters
----------
graph : :class:`~gensim.summarization.graph.Graph`
Given graph.
Returns
-------
numpy.ndarray, shape = [n, n]
Eigenvector of matrix `a`, n is number of nodes of `graph`.
"""
dimension = len(graph.nodes())
matrix = empty_matrix((dimension, dimension))
probability = 1.0 / float(dimension)
matrix.fill(probability)
return matrix
