import random import pytest import networkx as nx from networkx import convert_node_labels_to_integers as cnlti from networkx.algorithms.simple_paths import _bidirectional_dijkstra from networkx.algorithms.simple_paths import _bidirectional_shortest_path from networkx.utils import arbitrary_element from networkx.utils import pairwise class TestIsSimplePath: """Unit tests for the :func:`networkx.algorithms.simple_paths.is_simple_path` function. """ def test_empty_list(self): """Tests that the empty list is not a valid path, since there should be a one-to-one correspondence between paths as lists of nodes and paths as lists of edges. """ G = nx.trivial_graph() assert not nx.is_simple_path(G, []) def test_trivial_path(self): """Tests that the trivial path, a path of length one, is considered a simple path in a graph. """ G = nx.trivial_graph() assert nx.is_simple_path(G, [0]) def test_trivial_nonpath(self): """Tests that a list whose sole element is an object not in the graph is not considered a simple path. """ G = nx.trivial_graph() assert not nx.is_simple_path(G, ["not a node"]) def test_simple_path(self): G = nx.path_graph(2) assert nx.is_simple_path(G, [0, 1]) def test_non_simple_path(self): G = nx.path_graph(2) assert not nx.is_simple_path(G, [0, 1, 0]) def test_cycle(self): G = nx.cycle_graph(3) assert not nx.is_simple_path(G, [0, 1, 2, 0]) def test_missing_node(self): G = nx.path_graph(2) assert not nx.is_simple_path(G, [0, 2]) def test_directed_path(self): G = nx.DiGraph([(0, 1), (1, 2)]) assert nx.is_simple_path(G, [0, 1, 2]) def test_directed_non_path(self): G = nx.DiGraph([(0, 1), (1, 2)]) assert not nx.is_simple_path(G, [2, 1, 0]) def test_directed_cycle(self): G = nx.DiGraph([(0, 1), (1, 2), (2, 0)]) assert not nx.is_simple_path(G, [0, 1, 2, 0]) def test_multigraph(self): G = nx.MultiGraph([(0, 1), (0, 1)]) assert nx.is_simple_path(G, [0, 1]) def test_multidigraph(self): G = nx.MultiDiGraph([(0, 1), (0, 1), (1, 0), (1, 0)]) assert nx.is_simple_path(G, [0, 1]) # Tests for all_simple_paths def test_all_simple_paths(): G = nx.path_graph(4) paths = nx.all_simple_paths(G, 0, 3) assert {tuple(p) for p in paths} == {(0, 1, 2, 3)} def test_all_simple_paths_with_two_targets_emits_two_paths(): G = nx.path_graph(4) G.add_edge(2, 4) paths = nx.all_simple_paths(G, 0, [3, 4]) assert {tuple(p) for p in paths} == {(0, 1, 2, 3), (0, 1, 2, 4)} def test_digraph_all_simple_paths_with_two_targets_emits_two_paths(): G = nx.path_graph(4, create_using=nx.DiGraph()) G.add_edge(2, 4) paths = nx.all_simple_paths(G, 0, [3, 4]) assert {tuple(p) for p in paths} == {(0, 1, 2, 3), (0, 1, 2, 4)} def test_all_simple_paths_with_two_targets_cutoff(): G = nx.path_graph(4) G.add_edge(2, 4) paths = nx.all_simple_paths(G, 0, [3, 4], cutoff=3) assert {tuple(p) for p in paths} == {(0, 1, 2, 3), (0, 1, 2, 4)} def test_digraph_all_simple_paths_with_two_targets_cutoff(): G = nx.path_graph(4, create_using=nx.DiGraph()) G.add_edge(2, 4) paths = nx.all_simple_paths(G, 0, [3, 4], cutoff=3) assert {tuple(p) for p in paths} == {(0, 1, 2, 3), (0, 1, 2, 4)} def test_all_simple_paths_with_two_targets_in_line_emits_two_paths(): G = nx.path_graph(4) paths = nx.all_simple_paths(G, 0, [2, 3]) assert {tuple(p) for p in paths} == {(0, 1, 2), (0, 1, 2, 3)} def test_all_simple_paths_ignores_cycle(): G = nx.cycle_graph(3, create_using=nx.DiGraph()) G.add_edge(1, 3) paths = nx.all_simple_paths(G, 0, 3) assert {tuple(p) for p in paths} == {(0, 1, 3)} def test_all_simple_paths_with_two_targets_inside_cycle_emits_two_paths(): G = nx.cycle_graph(3, create_using=nx.DiGraph()) G.add_edge(1, 3) paths = nx.all_simple_paths(G, 0, [2, 3]) assert {tuple(p) for p in paths} == {(0, 1, 2), (0, 1, 3)} def test_all_simple_paths_source_target(): G = nx.path_graph(4) paths = nx.all_simple_paths(G, 1, 1) assert list(paths) == [] def test_all_simple_paths_cutoff(): G = nx.complete_graph(4) paths = nx.all_simple_paths(G, 0, 1, cutoff=1) assert {tuple(p) for p in paths} == {(0, 1)} paths = nx.all_simple_paths(G, 0, 1, cutoff=2) assert {tuple(p) for p in paths} == {(0, 1), (0, 2, 1), (0, 3, 1)} def test_all_simple_paths_on_non_trivial_graph(): """you may need to draw this graph to make sure it is reasonable""" G = nx.path_graph(5, create_using=nx.DiGraph()) G.add_edges_from([(0, 5), (1, 5), (1, 3), (5, 4), (4, 2), (4, 3)]) paths = nx.all_simple_paths(G, 1, [2, 3]) assert {tuple(p) for p in paths} == { (1, 2), (1, 3, 4, 2), (1, 5, 4, 2), (1, 3), (1, 2, 3), (1, 5, 4, 3), (1, 5, 4, 2, 3), } paths = nx.all_simple_paths(G, 1, [2, 3], cutoff=3) assert {tuple(p) for p in paths} == { (1, 2), (1, 3, 4, 2), (1, 5, 4, 2), (1, 3), (1, 2, 3), (1, 5, 4, 3), } paths = nx.all_simple_paths(G, 1, [2, 3], cutoff=2) assert {tuple(p) for p in paths} == {(1, 2), (1, 3), (1, 2, 3)} def test_all_simple_paths_multigraph(): G = nx.MultiGraph([(1, 2), (1, 2)]) paths = nx.all_simple_paths(G, 1, 1) assert list(paths) == [] nx.add_path(G, [3, 1, 10, 2]) paths = list(nx.all_simple_paths(G, 1, 2)) assert len(paths) == 3 assert {tuple(p) for p in paths} == {(1, 2), (1, 2), (1, 10, 2)} def test_all_simple_paths_multigraph_with_cutoff(): G = nx.MultiGraph([(1, 2), (1, 2), (1, 10), (10, 2)]) paths = list(nx.all_simple_paths(G, 1, 2, cutoff=1)) assert len(paths) == 2 assert {tuple(p) for p in paths} == {(1, 2), (1, 2)} def test_all_simple_paths_directed(): G = nx.DiGraph() nx.add_path(G, [1, 2, 3]) nx.add_path(G, [3, 2, 1]) paths = nx.all_simple_paths(G, 1, 3) assert {tuple(p) for p in paths} == {(1, 2, 3)} def test_all_simple_paths_empty(): G = nx.path_graph(4) paths = nx.all_simple_paths(G, 0, 3, cutoff=2) assert list(paths) == [] def test_all_simple_paths_corner_cases(): assert list(nx.all_simple_paths(nx.empty_graph(2), 0, 0)) == [] assert list(nx.all_simple_paths(nx.empty_graph(2), 0, 1)) == [] assert list(nx.all_simple_paths(nx.path_graph(9), 0, 8, 0)) == [] def hamiltonian_path(G, source): source = arbitrary_element(G) neighbors = set(G[source]) - {source} n = len(G) for target in neighbors: for path in nx.all_simple_paths(G, source, target): if len(path) == n: yield path def test_hamiltonian_path(): from itertools import permutations G = nx.complete_graph(4) paths = [list(p) for p in hamiltonian_path(G, 0)] exact = [[0] + list(p) for p in permutations([1, 2, 3], 3)] assert sorted(paths) == sorted(exact) def test_cutoff_zero(): G = nx.complete_graph(4) paths = nx.all_simple_paths(G, 0, 3, cutoff=0) assert list(list(p) for p in paths) == [] paths = nx.all_simple_paths(nx.MultiGraph(G), 0, 3, cutoff=0) assert list(list(p) for p in paths) == [] def test_source_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.all_simple_paths(nx.MultiGraph(G), 0, 3)) def test_target_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.all_simple_paths(nx.MultiGraph(G), 1, 4)) # Tests for all_simple_edge_paths def test_all_simple_edge_paths(): G = nx.path_graph(4) paths = nx.all_simple_edge_paths(G, 0, 3) assert {tuple(p) for p in paths} == {((0, 1), (1, 2), (2, 3))} def test_all_simple_edge_paths_with_two_targets_emits_two_paths(): G = nx.path_graph(4) G.add_edge(2, 4) paths = nx.all_simple_edge_paths(G, 0, [3, 4]) assert {tuple(p) for p in paths} == { ((0, 1), (1, 2), (2, 3)), ((0, 1), (1, 2), (2, 4)), } def test_digraph_all_simple_edge_paths_with_two_targets_emits_two_paths(): G = nx.path_graph(4, create_using=nx.DiGraph()) G.add_edge(2, 4) paths = nx.all_simple_edge_paths(G, 0, [3, 4]) assert {tuple(p) for p in paths} == { ((0, 1), (1, 2), (2, 3)), ((0, 1), (1, 2), (2, 4)), } def test_all_simple_edge_paths_with_two_targets_cutoff(): G = nx.path_graph(4) G.add_edge(2, 4) paths = nx.all_simple_edge_paths(G, 0, [3, 4], cutoff=3) assert {tuple(p) for p in paths} == { ((0, 1), (1, 2), (2, 3)), ((0, 1), (1, 2), (2, 4)), } def test_digraph_all_simple_edge_paths_with_two_targets_cutoff(): G = nx.path_graph(4, create_using=nx.DiGraph()) G.add_edge(2, 4) paths = nx.all_simple_edge_paths(G, 0, [3, 4], cutoff=3) assert {tuple(p) for p in paths} == { ((0, 1), (1, 2), (2, 3)), ((0, 1), (1, 2), (2, 4)), } def test_all_simple_edge_paths_with_two_targets_in_line_emits_two_paths(): G = nx.path_graph(4) paths = nx.all_simple_edge_paths(G, 0, [2, 3]) assert {tuple(p) for p in paths} == {((0, 1), (1, 2)), ((0, 1), (1, 2), (2, 3))} def test_all_simple_edge_paths_ignores_cycle(): G = nx.cycle_graph(3, create_using=nx.DiGraph()) G.add_edge(1, 3) paths = nx.all_simple_edge_paths(G, 0, 3) assert {tuple(p) for p in paths} == {((0, 1), (1, 3))} def test_all_simple_edge_paths_with_two_targets_inside_cycle_emits_two_paths(): G = nx.cycle_graph(3, create_using=nx.DiGraph()) G.add_edge(1, 3) paths = nx.all_simple_edge_paths(G, 0, [2, 3]) assert {tuple(p) for p in paths} == {((0, 1), (1, 2)), ((0, 1), (1, 3))} def test_all_simple_edge_paths_source_target(): G = nx.path_graph(4) paths = nx.all_simple_edge_paths(G, 1, 1) assert list(paths) == [] def test_all_simple_edge_paths_cutoff(): G = nx.complete_graph(4) paths = nx.all_simple_edge_paths(G, 0, 1, cutoff=1) assert {tuple(p) for p in paths} == {((0, 1),)} paths = nx.all_simple_edge_paths(G, 0, 1, cutoff=2) assert {tuple(p) for p in paths} == {((0, 1),), ((0, 2), (2, 1)), ((0, 3), (3, 1))} def test_all_simple_edge_paths_on_non_trivial_graph(): """you may need to draw this graph to make sure it is reasonable""" G = nx.path_graph(5, create_using=nx.DiGraph()) G.add_edges_from([(0, 5), (1, 5), (1, 3), (5, 4), (4, 2), (4, 3)]) paths = nx.all_simple_edge_paths(G, 1, [2, 3]) assert {tuple(p) for p in paths} == { ((1, 2),), ((1, 3), (3, 4), (4, 2)), ((1, 5), (5, 4), (4, 2)), ((1, 3),), ((1, 2), (2, 3)), ((1, 5), (5, 4), (4, 3)), ((1, 5), (5, 4), (4, 2), (2, 3)), } paths = nx.all_simple_edge_paths(G, 1, [2, 3], cutoff=3) assert {tuple(p) for p in paths} == { ((1, 2),), ((1, 3), (3, 4), (4, 2)), ((1, 5), (5, 4), (4, 2)), ((1, 3),), ((1, 2), (2, 3)), ((1, 5), (5, 4), (4, 3)), } paths = nx.all_simple_edge_paths(G, 1, [2, 3], cutoff=2) assert {tuple(p) for p in paths} == {((1, 2),), ((1, 3),), ((1, 2), (2, 3))} def test_all_simple_edge_paths_multigraph(): G = nx.MultiGraph([(1, 2), (1, 2)]) paths = nx.all_simple_edge_paths(G, 1, 1) assert list(paths) == [] nx.add_path(G, [3, 1, 10, 2]) paths = list(nx.all_simple_edge_paths(G, 1, 2)) assert len(paths) == 3 assert {tuple(p) for p in paths} == { ((1, 2, 0),), ((1, 2, 1),), ((1, 10, 0), (10, 2, 0)), } def test_all_simple_edge_paths_multigraph_with_cutoff(): G = nx.MultiGraph([(1, 2), (1, 2), (1, 10), (10, 2)]) paths = list(nx.all_simple_edge_paths(G, 1, 2, cutoff=1)) assert len(paths) == 2 assert {tuple(p) for p in paths} == {((1, 2, 0),), ((1, 2, 1),)} def test_all_simple_edge_paths_directed(): G = nx.DiGraph() nx.add_path(G, [1, 2, 3]) nx.add_path(G, [3, 2, 1]) paths = nx.all_simple_edge_paths(G, 1, 3) assert {tuple(p) for p in paths} == {((1, 2), (2, 3))} def test_all_simple_edge_paths_empty(): G = nx.path_graph(4) paths = nx.all_simple_edge_paths(G, 0, 3, cutoff=2) assert list(paths) == [] def test_all_simple_edge_paths_corner_cases(): assert list(nx.all_simple_edge_paths(nx.empty_graph(2), 0, 0)) == [] assert list(nx.all_simple_edge_paths(nx.empty_graph(2), 0, 1)) == [] assert list(nx.all_simple_edge_paths(nx.path_graph(9), 0, 8, 0)) == [] def hamiltonian_edge_path(G, source): source = arbitrary_element(G) neighbors = set(G[source]) - {source} n = len(G) for target in neighbors: for path in nx.all_simple_edge_paths(G, source, target): if len(path) == n - 1: yield path def test_hamiltonian__edge_path(): from itertools import permutations G = nx.complete_graph(4) paths = hamiltonian_edge_path(G, 0) exact = [list(pairwise([0] + list(p))) for p in permutations([1, 2, 3], 3)] assert sorted(exact) == [p for p in sorted(paths)] def test_edge_cutoff_zero(): G = nx.complete_graph(4) paths = nx.all_simple_edge_paths(G, 0, 3, cutoff=0) assert list(list(p) for p in paths) == [] paths = nx.all_simple_edge_paths(nx.MultiGraph(G), 0, 3, cutoff=0) assert list(list(p) for p in paths) == [] def test_edge_source_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.all_simple_edge_paths(nx.MultiGraph(G), 0, 3)) def test_edge_target_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.all_simple_edge_paths(nx.MultiGraph(G), 1, 4)) # Tests for shortest_simple_paths def test_shortest_simple_paths(): G = cnlti(nx.grid_2d_graph(4, 4), first_label=1, ordering="sorted") paths = nx.shortest_simple_paths(G, 1, 12) assert next(paths) == [1, 2, 3, 4, 8, 12] assert next(paths) == [1, 5, 6, 7, 8, 12] assert [len(path) for path in nx.shortest_simple_paths(G, 1, 12)] == sorted( len(path) for path in nx.all_simple_paths(G, 1, 12) ) def test_shortest_simple_paths_directed(): G = nx.cycle_graph(7, create_using=nx.DiGraph()) paths = nx.shortest_simple_paths(G, 0, 3) assert [path for path in paths] == [[0, 1, 2, 3]] def test_shortest_simple_paths_directed_with_weight_fucntion(): def cost(u, v, x): return 1 G = cnlti(nx.grid_2d_graph(4, 4), first_label=1, ordering="sorted") paths = nx.shortest_simple_paths(G, 1, 12) assert next(paths) == [1, 2, 3, 4, 8, 12] assert next(paths) == [1, 5, 6, 7, 8, 12] assert [ len(path) for path in nx.shortest_simple_paths(G, 1, 12, weight=cost) ] == sorted(len(path) for path in nx.all_simple_paths(G, 1, 12)) def test_shortest_simple_paths_with_weight_fucntion(): def cost(u, v, x): return 1 G = nx.cycle_graph(7, create_using=nx.DiGraph()) paths = nx.shortest_simple_paths(G, 0, 3, weight=cost) assert [path for path in paths] == [[0, 1, 2, 3]] def test_Greg_Bernstein(): g1 = nx.Graph() g1.add_nodes_from(["N0", "N1", "N2", "N3", "N4"]) g1.add_edge("N4", "N1", weight=10.0, capacity=50, name="L5") g1.add_edge("N4", "N0", weight=7.0, capacity=40, name="L4") g1.add_edge("N0", "N1", weight=10.0, capacity=45, name="L1") g1.add_edge("N3", "N0", weight=10.0, capacity=50, name="L0") g1.add_edge("N2", "N3", weight=12.0, capacity=30, name="L2") g1.add_edge("N1", "N2", weight=15.0, capacity=42, name="L3") solution = [["N1", "N0", "N3"], ["N1", "N2", "N3"], ["N1", "N4", "N0", "N3"]] result = list(nx.shortest_simple_paths(g1, "N1", "N3", weight="weight")) assert result == solution def test_weighted_shortest_simple_path(): def cost_func(path): return sum(G.adj[u][v]["weight"] for (u, v) in zip(path, path[1:])) G = nx.complete_graph(5) weight = {(u, v): random.randint(1, 100) for (u, v) in G.edges()} nx.set_edge_attributes(G, weight, "weight") cost = 0 for path in nx.shortest_simple_paths(G, 0, 3, weight="weight"): this_cost = cost_func(path) assert cost <= this_cost cost = this_cost def test_directed_weighted_shortest_simple_path(): def cost_func(path): return sum(G.adj[u][v]["weight"] for (u, v) in zip(path, path[1:])) G = nx.complete_graph(5) G = G.to_directed() weight = {(u, v): random.randint(1, 100) for (u, v) in G.edges()} nx.set_edge_attributes(G, weight, "weight") cost = 0 for path in nx.shortest_simple_paths(G, 0, 3, weight="weight"): this_cost = cost_func(path) assert cost <= this_cost cost = this_cost def test_weighted_shortest_simple_path_issue2427(): G = nx.Graph() G.add_edge("IN", "OUT", weight=2) G.add_edge("IN", "A", weight=1) G.add_edge("IN", "B", weight=2) G.add_edge("B", "OUT", weight=2) assert list(nx.shortest_simple_paths(G, "IN", "OUT", weight="weight")) == [ ["IN", "OUT"], ["IN", "B", "OUT"], ] G = nx.Graph() G.add_edge("IN", "OUT", weight=10) G.add_edge("IN", "A", weight=1) G.add_edge("IN", "B", weight=1) G.add_edge("B", "OUT", weight=1) assert list(nx.shortest_simple_paths(G, "IN", "OUT", weight="weight")) == [ ["IN", "B", "OUT"], ["IN", "OUT"], ] def test_directed_weighted_shortest_simple_path_issue2427(): G = nx.DiGraph() G.add_edge("IN", "OUT", weight=2) G.add_edge("IN", "A", weight=1) G.add_edge("IN", "B", weight=2) G.add_edge("B", "OUT", weight=2) assert list(nx.shortest_simple_paths(G, "IN", "OUT", weight="weight")) == [ ["IN", "OUT"], ["IN", "B", "OUT"], ] G = nx.DiGraph() G.add_edge("IN", "OUT", weight=10) G.add_edge("IN", "A", weight=1) G.add_edge("IN", "B", weight=1) G.add_edge("B", "OUT", weight=1) assert list(nx.shortest_simple_paths(G, "IN", "OUT", weight="weight")) == [ ["IN", "B", "OUT"], ["IN", "OUT"], ] def test_weight_name(): G = nx.cycle_graph(7) nx.set_edge_attributes(G, 1, "weight") nx.set_edge_attributes(G, 1, "foo") G.adj[1][2]["foo"] = 7 paths = list(nx.shortest_simple_paths(G, 0, 3, weight="foo")) solution = [[0, 6, 5, 4, 3], [0, 1, 2, 3]] assert paths == solution def test_ssp_source_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.shortest_simple_paths(G, 0, 3)) def test_ssp_target_missing(): with pytest.raises(nx.NodeNotFound): G = nx.Graph() nx.add_path(G, [1, 2, 3]) list(nx.shortest_simple_paths(G, 1, 4)) def test_ssp_multigraph(): with pytest.raises(nx.NetworkXNotImplemented): G = nx.MultiGraph() nx.add_path(G, [1, 2, 3]) list(nx.shortest_simple_paths(G, 1, 4)) def test_ssp_source_missing2(): with pytest.raises(nx.NetworkXNoPath): G = nx.Graph() nx.add_path(G, [0, 1, 2]) nx.add_path(G, [3, 4, 5]) list(nx.shortest_simple_paths(G, 0, 3)) def test_bidirectional_shortest_path_restricted_cycle(): cycle = nx.cycle_graph(7) length, path = _bidirectional_shortest_path(cycle, 0, 3) assert path == [0, 1, 2, 3] length, path = _bidirectional_shortest_path(cycle, 0, 3, ignore_nodes=[1]) assert path == [0, 6, 5, 4, 3] def test_bidirectional_shortest_path_restricted_wheel(): wheel = nx.wheel_graph(6) length, path = _bidirectional_shortest_path(wheel, 1, 3) assert path in [[1, 0, 3], [1, 2, 3]] length, path = _bidirectional_shortest_path(wheel, 1, 3, ignore_nodes=[0]) assert path == [1, 2, 3] length, path = _bidirectional_shortest_path(wheel, 1, 3, ignore_nodes=[0, 2]) assert path == [1, 5, 4, 3] length, path = _bidirectional_shortest_path( wheel, 1, 3, ignore_edges=[(1, 0), (5, 0), (2, 3)] ) assert path in [[1, 2, 0, 3], [1, 5, 4, 3]] def test_bidirectional_shortest_path_restricted_directed_cycle(): directed_cycle = nx.cycle_graph(7, create_using=nx.DiGraph()) length, path = _bidirectional_shortest_path(directed_cycle, 0, 3) assert path == [0, 1, 2, 3] pytest.raises( nx.NetworkXNoPath, _bidirectional_shortest_path, directed_cycle, 0, 3, ignore_nodes=[1], ) length, path = _bidirectional_shortest_path( directed_cycle, 0, 3, ignore_edges=[(2, 1)] ) assert path == [0, 1, 2, 3] pytest.raises( nx.NetworkXNoPath, _bidirectional_shortest_path, directed_cycle, 0, 3, ignore_edges=[(1, 2)], ) def test_bidirectional_shortest_path_ignore(): G = nx.Graph() nx.add_path(G, [1, 2]) nx.add_path(G, [1, 3]) nx.add_path(G, [1, 4]) pytest.raises( nx.NetworkXNoPath, _bidirectional_shortest_path, G, 1, 2, ignore_nodes=[1] ) pytest.raises( nx.NetworkXNoPath, _bidirectional_shortest_path, G, 1, 2, ignore_nodes=[2] ) G = nx.Graph() nx.add_path(G, [1, 3]) nx.add_path(G, [1, 4]) nx.add_path(G, [3, 2]) pytest.raises( nx.NetworkXNoPath, _bidirectional_shortest_path, G, 1, 2, ignore_nodes=[1, 2] ) def validate_path(G, s, t, soln_len, path): assert path[0] == s assert path[-1] == t assert soln_len == sum( G[u][v].get("weight", 1) for u, v in zip(path[:-1], path[1:]) ) def validate_length_path(G, s, t, soln_len, length, path): assert soln_len == length validate_path(G, s, t, length, path) def test_bidirectional_dijksta_restricted(): XG = nx.DiGraph() XG.add_weighted_edges_from( [ ("s", "u", 10), ("s", "x", 5), ("u", "v", 1), ("u", "x", 2), ("v", "y", 1), ("x", "u", 3), ("x", "v", 5), ("x", "y", 2), ("y", "s", 7), ("y", "v", 6), ] ) XG3 = nx.Graph() XG3.add_weighted_edges_from( [[0, 1, 2], [1, 2, 12], [2, 3, 1], [3, 4, 5], [4, 5, 1], [5, 0, 10]] ) validate_length_path(XG, "s", "v", 9, *_bidirectional_dijkstra(XG, "s", "v")) validate_length_path( XG, "s", "v", 10, *_bidirectional_dijkstra(XG, "s", "v", ignore_nodes=["u"]) ) validate_length_path( XG, "s", "v", 11, *_bidirectional_dijkstra(XG, "s", "v", ignore_edges=[("s", "x")]) ) pytest.raises( nx.NetworkXNoPath, _bidirectional_dijkstra, XG, "s", "v", ignore_nodes=["u"], ignore_edges=[("s", "x")], ) validate_length_path(XG3, 0, 3, 15, *_bidirectional_dijkstra(XG3, 0, 3)) validate_length_path( XG3, 0, 3, 16, *_bidirectional_dijkstra(XG3, 0, 3, ignore_nodes=[1]) ) validate_length_path( XG3, 0, 3, 16, *_bidirectional_dijkstra(XG3, 0, 3, ignore_edges=[(2, 3)]) ) pytest.raises( nx.NetworkXNoPath, _bidirectional_dijkstra, XG3, 0, 3, ignore_nodes=[1], ignore_edges=[(5, 4)], ) def test_bidirectional_dijkstra_no_path(): with pytest.raises(nx.NetworkXNoPath): G = nx.Graph() nx.add_path(G, [1, 2, 3]) nx.add_path(G, [4, 5, 6]) _bidirectional_dijkstra(G, 1, 6) def test_bidirectional_dijkstra_ignore(): G = nx.Graph() nx.add_path(G, [1, 2, 10]) nx.add_path(G, [1, 3, 10]) pytest.raises(nx.NetworkXNoPath, _bidirectional_dijkstra, G, 1, 2, ignore_nodes=[1]) pytest.raises(nx.NetworkXNoPath, _bidirectional_dijkstra, G, 1, 2, ignore_nodes=[2]) pytest.raises( nx.NetworkXNoPath, _bidirectional_dijkstra, G, 1, 2, ignore_nodes=[1, 2] )