to_numpy_recarray¶

to_numpy_recarray(G, nodelist=None, dtype=[('weight', <type 'float'>)], order=None)[source]¶

Return the graph adjacency matrix as a NumPy recarray.

Parameters:	G (graph) – The NetworkX graph used to construct the NumPy matrix. nodelist (list, optional) – The rows and columns are ordered according to the nodes in $nodelist$ . If $nodelist$ is None, then the ordering is produced by G.nodes(). dtype (NumPy data-type, optional) – A valid NumPy named dtype used to initialize the NumPy recarray. The data type names are assumed to be keys in the graph edge attribute dictionary. order ({‘C’, ‘F’}, optional) – Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory. If None, then the NumPy default is used.
Returns:	M – The graph with specified edge data as a Numpy recarray
Return type:	NumPy recarray

Notes

When $nodelist$ does not contain every node in $G$ , the matrix is built from the subgraph of $G$ that is induced by the nodes in $nodelist$ .

Examples

>>> G = nx.Graph()
>>> G.add_edge(1,2,weight=7.0,cost=5)
>>> A=nx.to_numpy_recarray(G,dtype=[('weight',float),('cost',int)])
>>> print(A.weight)
[[ 0.  7.]
 [ 7.  0.]]
>>> print(A.cost)
[[0 5]
 [5 0]]