to_numpy_recarray¶

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

Returns the graph adjacency matrix as a NumPy recarray.

Deprecated since version 2.7: to_numpy_recarray is deprecated and will be removed in NetworkX 3.0. Use nx.to_numpy_array(G, dtype=dtype, weight=None).view(np.recarray) instead.

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. The default is dtype([("weight", float)]).
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]]