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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:
    graph array_like

      Input graph. Shape should be (n_nodes, n_nodes).

    null_value float or None, optional

      Value that denotes non-edges in the graph. Default is zero.

    nan_null bool, optional

      If True (default), then NaN entries are treated as non-edges

    infinity_null bool, optional

      If True (default), then infinite entries (both positive and negative) are treated as null edges.

    copy bool, optional

      If True (default), then the array data is copied. See `numpy.array` for more details.

  Returns:
    csgraph MaskedArray

      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)