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