def test_transpose(self):
vertices = range(5)
edge_list = [(0, 1), (1, 2), (2, 3), (3, 0), (4, 3)]
graph = Graph(vertices, edge_list)
trans_graph = graph.transpose()
self.assertEqual(trans_graph.get_edges(0), [3])
self.assertEqual(trans_graph.get_edges(1), [0])
self.assertEqual(trans_graph.get_edges(2), [1])
self.assertEqual(trans_graph.get_edges(3), [2, 4])
def test_neg_cycle(self):
vertices = range(4)
edge_list = [(0, 1, 1), (0, 3, 1), (1, 2, 2), (2, 0, -10), (3, 1, 3)]
graph = Graph(vertices, edge_list)
with self.assertRaises(NegativeCycleError):
min_path, parents = shortest_paths(graph, 0)
def test_strong_conn_comps(self):
vertices = range(10)
edge_list = [(0, 1), (1, 2), (2, 3), (3, 0), (3, 4), (4, 5), (5, 6),
(6, 4), (6, 7), (7, 8), (8, 7), (8, 9)]
graph = Graph(vertices, edge_list)
comps = strongly_connected_components(graph)
self.assertEqual(comps, [[0, 1, 2, 3], [4, 5, 6], [7, 8], [9]])
def test_bfs_clr(self):
"""
Example from Intro To Algorithms Figure 23.3
"""
vertices = range(8)
edge_list = [(0, 1), (0, 4), (1, 5), (2, 3), (2, 5), (2, 6), (3, 7),
(5, 6), (6, 7)]
graph = Graph(vertices, edge_list, undirected=True)
bfs = BFS(graph)
bfs.search(1)
self.assertEqual(len(bfs.vertex_queue), 0)
self.assertEqual(bfs.level, [1, 0, 2, 3, 2, 1, 2, 3])
self.assertEqual(bfs.parent, [1, -1, 5, 2, 0, 1, 5, 6])
def test_dfs_clr(self):
"""
Example from Intro To Algorithms Fig 23.4
"""
vertices = range(6)
edge_list = [(0, 1), (0, 3), (1, 4), (2, 4), (2, 5), (3, 1), (4, 3),
(5, 5)]
graph = Graph(vertices, edge_list)
dfs = DFS(graph)
dfs.search()
self.assertTrue(np.all(np.array(dfs.entered) < np.array(dfs.exited)))
self.assertEqual(dfs.entered, [1, 2, 9, 4, 3, 10])
self.assertEqual(dfs.exited, [8, 7, 12, 5, 6, 11])
def test_full_tree(self):
vertices = range(7)
edge_list = [
(0, 1),
(0, 2),
(1, 3),
(1, 4),
(2, 5),
(2, 6),
]
graph = Graph(vertices, edge_list)
bfs = BFS(graph)
bfs.search(0)
self.assertEqual(bfs.level, [0, 1, 1, 2, 2, 2, 2])
self.assertEqual(bfs.parent, [-1, 0, 0, 1, 1, 2, 2])
def test_dfs(self):
"""
Random DFS I made up
"""
vertices = range(10)
edge_list = [
(0, 1),
(0, 4),
(0, 6),
(0, 9),
(1, 0),
(1, 2),
(1, 3),
(1, 4),
(1, 5),
(2, 5),
(2, 9),
(3, 3),
(3, 6),
(3, 9),
(4, 5),
(4, 6),
(4, 8),
(5, 1),
(5, 2),
(5, 4),
(6, 1),
(6, 7),
(7, 8),
(7, 9),
(8, 9),
(9, 0),
(9, 8),
]
graph = Graph(vertices, edge_list)
dfs = DFS(graph)
dfs.search()
# Check that all vertexes are entered before exiting
self.assertTrue(np.all(np.array(dfs.entered) < np.array(dfs.exited)))
self.assertEqual(dfs.entered, [1, 2, 3, 17, 5, 4, 6, 7, 8, 9])
self.assertEqual(dfs.exited, [20, 19, 16, 18, 14, 15, 13, 12, 11, 10])
def test_min_span_tree(self):
vertices = range(5)
edge_list = [
(0, 1, 1),
(0, 4, 100),
(0, 2, 102),
(0, 3, 103),
(1, 2, 2),
(1, 4, 105),
(2, 3, 3),
(2, 4, 106),
(3, 4, 4),
(3, 1, 104),
]
graph = Graph(vertices, edge_list)
edge_list = calc_min_spanning_tree(graph)
self.assertEqual(set(edge_list), {(0, 1), (1, 2), (2, 3), (3, 4)})
self.assertTrue(graph.is_valid)
def test_shortest_path(self):
vertices = range(6)
edge_list = [
(0, 1, 1),
(0, 3, 10),
(1, 2, 2),
(1, 3, 20),
(2, 3, 3),
(2, 0, 30),
(3, 4, 4),
(3, 5, 40),
(4, 5, 5),
(4, 2, 50),
(5, 1, -1),
]
graph = Graph(vertices, edge_list)
min_path, parents = shortest_paths(graph, 0)
self.assertEqual(min_path, [0, 1, 3, 6, 10, 15])
self.assertEqual(parents, [-6, 0, 1, 2, 3, 4])