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3.2.1 ▾
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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,
_bidirectional_shortest_path,
)
from networkx.utils import arbitrary_element, 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_missing_starting_node(self):
G = nx.path_graph(2)
assert not nx.is_simple_path(G, [2, 0])
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(p) for p in paths] == []
paths = nx.all_simple_paths(nx.MultiGraph(G), 0, 3, cutoff=0)
assert [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) == 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(p) for p in paths] == []
paths = nx.all_simple_edge_paths(nx.MultiGraph(G), 0, 3, cutoff=0)
assert [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 list(paths) == [[0, 1, 2, 3]]
def test_shortest_simple_paths_directed_with_weight_function():
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_function():
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 list(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_dijkstra_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]
)