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# from_numpy_matrix¶

from_numpy_matrix(A, create_using=None)[source]

Return a graph from numpy matrix.

The numpy matrix is interpreted as an adjacency matrix for the graph.

Parameters : A : numpy matrix An adjacency matrix representation of a graph create_using : NetworkX graph Use specified graph for result. The default is Graph()

Notes

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.

Examples

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(data=True)
[(0, 0, {'cost': 2, 'weight': 1.0})]
```