breadth_first_order — SciPy v1.15.3 Manual (original) (raw)

scipy.sparse.csgraph.

scipy.sparse.csgraph.breadth_first_order(csgraph, i_start, directed=True, return_predecessors=True)#

Return a breadth-first ordering starting with specified node.

Note that a breadth-first order is not unique, but the tree which it generates is unique.

Added in version 0.11.0.

Parameters:

csgrapharray_like or sparse array or matrix

The N x N compressed sparse graph. The input csgraph will be converted to csr format for the calculation.

i_startint

The index of starting node.

directedbool, 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 find the shortest path on an undirected graph: the algorithm can progress from point i to j along csgraph[i, j] or csgraph[j, i].

return_predecessorsbool, optional

If True (default), then return the predecessor array (see below).

Returns:

node_arrayndarray, one dimension

The breadth-first list of nodes, starting with specified node. The length of node_array is the number of nodes reachable from the specified node.

predecessorsndarray, one dimension

Returned only if return_predecessors is True. The length-N list of predecessors of each node in a breadth-first tree. If node i is in the tree, then its parent is given by predecessors[i]. If node i is not in the tree (and for the parent node) then predecessors[i] = -9999.

Notes

If multiple valid solutions are possible, output may vary with SciPy and Python version.

Examples

from scipy.sparse import csr_array from scipy.sparse.csgraph import breadth_first_order

graph = [ ... [0, 1, 2, 0], ... [0, 0, 0, 1], ... [2, 0, 0, 3], ... [0, 0, 0, 0] ... ] graph = csr_array(graph) print(graph) <Compressed Sparse Row sparse array of dtype 'int64' with 5 stored elements and shape (4, 4)> Coords Values (0, 1) 1 (0, 2) 2 (1, 3) 1 (2, 0) 2 (2, 3) 3

breadth_first_order(graph,0) (array([0, 1, 2, 3], dtype=int32), array([-9999, 0, 0, 1], dtype=int32))