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Function to_numpy_array

networkx/convert_matrix.py:882–1117  ·  view source on GitHub ↗

Returns the graph adjacency matrix as a NumPy array. Parameters ---------- G : graph The NetworkX graph used to construct the NumPy array. nodelist : list, optional The rows and columns are ordered according to the nodes in `nodelist`. If `nodelist` is ``Non

(
    G,
    nodelist=None,
    dtype=None,
    order=None,
    multigraph_weight=sum,
    weight="weight",
    nonedge=0.0,
)

Source from the content-addressed store, hash-verified

880
881@nx._dispatchable(edge_attrs="weight") # edge attrs may also be obtained from `dtype`
882def to_numpy_array(
883 G,
884 nodelist=None,
885 dtype=None,
886 order=None,
887 multigraph_weight=sum,
888 weight="weight",
889 nonedge=0.0,
890):
891 """Returns the graph adjacency matrix as a NumPy array.
892
893 Parameters
894 ----------
895 G : graph
896 The NetworkX graph used to construct the NumPy array.
897
898 nodelist : list, optional
899 The rows and columns are ordered according to the nodes in `nodelist`.
900 If `nodelist` is ``None``, then the ordering is produced by ``G.nodes()``.
901
902 dtype : NumPy data type, optional
903 A NumPy data type used to initialize the array. If None, then the NumPy
904 default is used. The dtype can be structured if `weight=None`, in which
905 case the dtype field names are used to look up edge attributes. The
906 result is a structured array where each named field in the dtype
907 corresponds to the adjacency for that edge attribute. See examples for
908 details.
909
910 order : {'C', 'F'}, optional
911 Whether to store multidimensional data in C- or Fortran-contiguous
912 (row- or column-wise) order in memory. If None, then the NumPy default
913 is used.
914
915 multigraph_weight : callable, optional
916 An function that determines how weights in multigraphs are handled.
917 The function should accept a sequence of weights and return a single
918 value. The default is to sum the weights of the multiple edges.
919
920 weight : string or None optional (default = 'weight')
921 The edge attribute that holds the numerical value used for
922 the edge weight. If an edge does not have that attribute, then the
923 value 1 is used instead. `weight` must be ``None`` if a structured
924 dtype is used.
925
926 nonedge : array_like (default = 0.0)
927 The value used to represent non-edges in the adjacency matrix.
928 The array values corresponding to nonedges are typically set to zero.
929 However, this could be undesirable if there are array values
930 corresponding to actual edges that also have the value zero. If so,
931 one might prefer nonedges to have some other value, such as ``nan``.
932
933 Returns
934 -------
935 A : NumPy ndarray
936 Graph adjacency matrix
937
938 Raises
939 ------

Callers 1

to_pandas_adjacencyFunction · 0.85

Calls 10

appendMethod · 0.80
keysMethod · 0.80
valuesMethod · 0.80
number_of_edgesMethod · 0.45
copyMethod · 0.45
subgraphMethod · 0.45
is_multigraphMethod · 0.45
edgesMethod · 0.45
getMethod · 0.45
is_directedMethod · 0.45

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