#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in May 2023
"""
import numpy as np
from scipy import sparse
from sknetwork.path.distances import get_distances
[docs]def breadth_first_search(adjacency: sparse.csr_matrix, source: int):
"""Breadth-first ordering starting from some node.
Parameters
----------
adjacency :
Adjacency matrix of the graph.
source : int
Source node.
Returns
-------
index : np.ndarray
Node index corresponding to the breadth-first-search from the source.
The length of the vector is the number of nodes reachable from the source.
"""
distances = get_distances(adjacency, source)
indices = np.argsort(distances)
n = np.sum(distances < 0)
return indices[n:]