causal_networkx.io.to_numpy#

causal_networkx.io.to_numpy(causal_graph)[source]#

Convert causal graph to a numpy adjacency array.

Parameters:

causal_graph : instance of DAG

The causal graph.

Returns:

numpy_graph : np.ndarray of shape (n_nodes, n_nodes)

The numpy array that represents the graph. The values representing edges are mapped according to a pre-defined set of values. See Notes.

Notes

The adjacency matrix is defined where the ijth entry of numpy_graph has a non-zero entry if there is an edge from i to j. The ijth entry is symmetric with the jith entry if the edge is ‘undirected’, or ‘bidirected’. Then specific edges are mapped to the following values:

  • directed edge (->): 1

  • undirected edge (–): 2

  • bidirected edge (<->): 3

  • circle endpoint (-o): 4

Circle endpoints can be symmetric, but they can also contain a tail, or a directed edge at the other end.