networkx.convert_matrix.to_numpy_recarray

to_numpy_recarray(G, nodelist=None, dtype=None, order=None)[source]

Returns the graph adjacency matrix as a NumPy recarray.

Parameters
Ggraph

The NetworkX graph used to construct the NumPy recarray.

nodelistlist, 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().

dtypeNumPy 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
MNumPy recarray

The graph with specified edge data as a Numpy recarray

Notes

When nodelist does not contain every node in G, the adjacency 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]]