73 lines
2.3 KiB
Python
73 lines
2.3 KiB
Python
# test_bridges.py - unit tests for bridge-finding algorithms
|
|
#
|
|
# Copyright 2004-2019 NetworkX developers.
|
|
#
|
|
# This file is part of NetworkX.
|
|
#
|
|
# NetworkX is distributed under a BSD license; see LICENSE.txt for more
|
|
# information.
|
|
"""Unit tests for bridge-finding algorithms."""
|
|
from unittest import TestCase
|
|
|
|
import networkx as nx
|
|
|
|
|
|
class TestBridges(TestCase):
|
|
"""Unit tests for the bridge-finding function."""
|
|
|
|
def test_single_bridge(self):
|
|
edges = [
|
|
# DFS tree edges.
|
|
(1, 2), (2, 3), (3, 4), (3, 5), (5, 6), (6, 7), (7, 8), (5, 9),
|
|
(9, 10),
|
|
# Nontree edges.
|
|
(1, 3), (1, 4), (2, 5), (5, 10), (6, 8)
|
|
]
|
|
G = nx.Graph(edges)
|
|
source = 1
|
|
bridges = list(nx.bridges(G, source))
|
|
self.assertEqual(bridges, [(5, 6)])
|
|
|
|
def test_barbell_graph(self):
|
|
# The (3, 0) barbell graph has two triangles joined by a single edge.
|
|
G = nx.barbell_graph(3, 0)
|
|
source = 0
|
|
bridges = list(nx.bridges(G, source))
|
|
self.assertEqual(bridges, [(2, 3)])
|
|
|
|
|
|
class TestLocalBridges(TestCase):
|
|
"""Unit tests for the local_bridge function."""
|
|
|
|
@classmethod
|
|
def setup_class(cls):
|
|
cls.BB = nx.barbell_graph(4, 0)
|
|
cls.square = nx.cycle_graph(4)
|
|
cls.tri = nx.cycle_graph(3)
|
|
|
|
def test_nospan(self):
|
|
expected = {(3, 4), (4, 3)}
|
|
assert next(nx.local_bridges(self.BB, with_span=False)) in expected
|
|
assert set(nx.local_bridges(self.square, with_span=False)) == self.square.edges
|
|
assert list(nx.local_bridges(self.tri, with_span=False)) == []
|
|
|
|
def test_no_weight(self):
|
|
inf = float('inf')
|
|
expected = {(3, 4, inf), (4, 3, inf)}
|
|
assert next(nx.local_bridges(self.BB)) in expected
|
|
expected = {(u, v, 3) for u, v, in self.square.edges}
|
|
assert set(nx.local_bridges(self.square)) == expected
|
|
assert list(nx.local_bridges(self.tri)) == []
|
|
|
|
def test_weight(self):
|
|
inf = float('inf')
|
|
G = self.square.copy()
|
|
|
|
G.edges[1, 2]['weight'] = 2
|
|
expected = {(u, v, 5 - wt) for u, v, wt in G.edges(data='weight', default=1)}
|
|
assert set(nx.local_bridges(G, weight='weight')) == expected
|
|
|
|
expected = {(u, v, 6) for u, v in G.edges}
|
|
lb = nx.local_bridges(G, weight=lambda u, v, d: 2)
|
|
assert set(lb) == expected
|