def test_undirected_graph_dijkstra(self):
""" Perform Dijkstra's algorithm on an undirected graph """
""" 1_ E 1_ E
| / | /
A- 1 -B- 5 -D A- 3 -B- 5 -D
\ | \ |
2 0 2 -2
\ | \ |
C C
"""
g = UndirectedGraph()
g.add_vertex(v_val='A')
g.add_vertex(v_val='B')
g.add_vertex(v_val='C')
g.add_vertex(v_val='D')
g.add_vertex(v_val='E')
g.add_edge(('A', 'A'), attrs={'weight': 1})
g.add_edge(('A', 'B'), attrs={'weight': 1})
g.add_edge(('A', 'C'), attrs={'weight': 2})
g.add_edge(('B', 'C'), attrs={'weight': 0})
g.add_edge(('B', 'D'), attrs={'weight': 5})
negative_weight_g = g.clone()
negative_weight_g.get_edge(('A', 'B')).set('weight', 3)
negative_weight_g.get_edge(('B', 'C')).set('weight', -2)
missing_weight_g = g.clone()
missing_weight_g.get_edge(('A', 'B')).set('weight', None)
self.assertEqual(g.dijkstra('A', goal_val='A'), ['A'])
self.assertEqual(g.dijkstra('A', goal_val='B'), ['A', 'B'])
self.assertEqual(g.dijkstra('A', goal_val='C'), ['A', 'B', 'C'])
self.assertEqual(g.dijkstra('A', goal_val='D'), ['A', 'B', 'D'])
self.assertIsNone(g.dijkstra('A', goal_val='E'))
# when returning all paths (no goal specified), paths aren't evaluated
# until requested, to avoid the O(|V|^2) cost of backtracking |V| paths
A_paths = g.dijkstra('A')
# request each key
_ = [A_paths[v.val] for v in g]
self.assertEqual(dict(A_paths), {'A': ['A'],
'B': ['A', 'B'],
'C': ['A', 'B', 'C'],
'D': ['A', 'B', 'D'],
'E': None})
self.assertEqual(g.dijkstra('A', goal_val='A', return_distances=True),
0)
self.assertEqual(g.dijkstra('A', goal_val='B', return_distances=True),
1)
self.assertEqual(g.dijkstra('A', goal_val='C', return_distances=True),
1)
self.assertEqual(g.dijkstra('A', goal_val='D', return_distances=True),
6)
self.assertEqual(g.dijkstra('A', goal_val='E', return_distances=True),
float('inf'))
self.assertEqual(g.dijkstra('A', return_distances=True),
{'A': 0, 'B': 1, 'C': 1, 'D': 6, 'E': float('inf')})
with self.assertRaises(ValueError):
negative_weight_g.dijkstra('A')
with self.assertRaises(ValueError):
missing_weight_g.dijkstra('A')
