`scipy.sparse.csgraph._tools:reconstruct_path`

Signature

def reconstruct_path ( csgraph , predecessors , directed = True )

Construct a tree from a graph and a predecessor list.

csgraph : array_like or sparse array or matrix: The N x N matrix representing the directed or undirected graph from which the predecessors are drawn.
predecessors : array_like, one dimension: The length-N array of indices of predecessors for the tree. The index of the parent of node i is given by predecessors[i].
directed : bool, optional: If True (default), then operate on a directed graph: only move from point i to point j along paths csgraph[i, j]. If False, then operate on an undirected graph: the algorithm can progress from point i to j along csgraph[i, j] or csgraph[j, i].

cstree : csr matrix: The N x N directed compressed-sparse representation of the tree drawn from csgraph which is encoded by the predecessor list.

import numpy as np
from scipy.sparse import csr_array
from scipy.sparse.csgraph import reconstruct_path

✓

graph = [
[0, 1, 2, 0],
[0, 0, 0, 1],
[0, 0, 0, 3],
[0, 0, 0, 0]
]
graph = csr_array(graph)

✓

print(graph)

✗

pred = np.array([-9999, 0, 0, 1], dtype=np.int32)

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cstree = reconstruct_path(csgraph=graph, predecessors=pred, directed=False)
cstree.todense()

✓