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
G (graph) – The NetworkX graph used to construct the NumPy recarray.
nodelist (list, optional) – The rows and columns are ordered according to the nodes in
nodelist
. Ifnodelist
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 inG
, the adjacency matrix is built from the subgraph ofG
that is induced by the nodes innodelist
.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]]