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- from_numpy_matrix(A, create_using=None)¶
Return a graph from numpy matrix.
The numpy matrix is interpreted as an adjacency matrix for the graph.
A : numpy matrix
An adjacency matrix representation of a graph
create_using : NetworkX graph
Use specified graph for result. The default is Graph()
If the numpy matrix has a single data type for each matrix entry it will be converted to an appropriate Python data type.
If the numpy matrix has a user-specified compound data type the names of the data fields will be used as attribute keys in the resulting NetworkX graph.
Simple integer weights on edges:
>>> import numpy >>> A=numpy.matrix([[1,1],[2,1]]) >>> G=nx.from_numpy_matrix(A)
User defined compound data type on edges:
>>> import numpy >>> dt=[('weight',float),('cost',int)] >>> A=numpy.matrix([[(1.0,2)]],dtype=dt) >>> G=nx.from_numpy_matrix(A) >>> G.edges() [(0, 0)] >>> G['cost'] 2 >>> G['weight'] 1.0