scipy.sparse.csgraph.

csgraph_masked_from_dense#

scipy.sparse.csgraph.csgraph_masked_from_dense(graph, null_value=0, nan_null=True, infinity_null=True, copy=True)#

Construct a masked array graph representation from a dense matrix.

Added in version 0.11.0.

Parameters:

grapharray_like: Input graph. Shape should be (n_nodes, n_nodes).
null_valuefloat or None, optional: Value that denotes non-edges in the graph. Default is zero.
nan_nullbool, optional: If True (default), then NaN entries are treated as non-edges
infinity_nullbool, optional: If True (default), then infinite entries (both positive and negative) are treated as null edges.
copybool, optional: If True (default), then the array data is copied. See numpy.array for more details.

Returns:

csgraphMaskedArray: masked array representation of graph

Examples

>>> from scipy.sparse.csgraph import csgraph_masked_from_dense

>>> graph = [
... [0, 1, 2, 0],
... [0, 0, 0, 1],
... [0, 0, 0, 3],
... [0, 0, 0, 0]
... ]

>>> csgraph_masked_from_dense(graph)
masked_array(
  data=[[--,  1,  2, --],
        [--, --, --,  1],
        [--, --, --,  3],
        [--, --, --, --]],
  mask=[[ True, False, False,  True],
        [ True,  True,  True, False],
        [ True,  True,  True, False],
        [ True,  True,  True,  True]],
  fill_value=0)