Files
2026-07-13 12:36:30 +08:00

177 lines
5.7 KiB
Python

import unittest
import easygraph as eg
class test_mst(unittest.TestCase):
def setUp(self):
self.g1 = eg.get_graph_karateclub()
# source graph: https://zh.wikipedia.org/zh-cn/%E6%88%B4%E5%85%8B%E6%96%AF%E7%89%B9%E6%8B%89%E7%AE%97%E6%B3%95#/media/File:Dijkstra_Animation.gif
edges = [(1, 2), (1, 3), (1, 6), (2, 3), (2, 4), (3, 4), (3, 6), (4, 5), (5, 6)]
self.g2 = eg.Graph(edges)
self.g2.add_edges(
edges,
edges_attr=[
{"weight": 7},
{"weight": 9},
{"weight": 14},
{"weight": 10},
{"weight": 15},
{"weight": 11},
{"weight": 2},
{"weight": 6},
{"weight": 9},
],
)
# source graph: https://static.javatpoint.com/tutorial/daa/images/dijkstra-algorithm.png
self.g3 = eg.Graph()
edges = [
(0, 1),
(0, 4),
(1, 4),
(1, 2),
(4, 5),
(4, 8),
(2, 3),
(2, 6),
(2, 8),
(5, 6),
(5, 8),
(3, 6),
(3, 7),
(6, 7),
]
self.g3.add_edges(
edges,
edges_attr=[
{"weight": 4},
{"weight": 1},
{"weight": 11},
{"weight": 8},
{"weight": 1},
{"weight": 7},
{"weight": 7},
{"weight": 4},
{"weight": 2},
{"weight": 2},
{"weight": 6},
{"weight": 14},
{"weight": 9},
{"weight": 10},
],
)
self.g4 = eg.DiGraph()
edges = [(0, 1), (1, 2), (2, 3), (3, 0), (0, 2), (1, 3)]
self.g4.add_edges(
edges,
edges_attr=[
{"weight": -1},
{"weight": -2},
{"weight": -3},
{"weight": -4},
{"weight": -5},
{"weight": -6},
],
)
self.nan_graph = eg.Graph()
self.nan_graph.add_edges(
[(0, 1), (1, 2)], edges_attr=[{"weight": float("nan")}, {"weight": 1}]
)
self.no_weight_graph = eg.Graph()
self.no_weight_graph.add_edges([(0, 1), (1, 2)])
self.equal_weight_graph = eg.Graph()
self.equal_weight_graph.add_edges(
[(0, 1), (1, 2), (2, 0)],
edges_attr=[{"weight": 1}, {"weight": 1}, {"weight": 1}],
)
self.negative_weight_graph = eg.Graph()
self.negative_weight_graph.add_edges(
[(0, 1), (1, 2), (2, 3)],
edges_attr=[{"weight": -1}, {"weight": -2}, {"weight": -3}],
)
self.disconnected_graph = eg.Graph()
self.disconnected_graph.add_edges(
[(0, 1), (2, 3)], edges_attr=[{"weight": 1}, {"weight": 2}]
)
self.G = eg.Graph()
self.G.add_edges(
[(0, 1), (1, 2), (2, 3), (3, 0)],
edges_attr=[{"weight": 1}, {"weight": 2}, {"weight": 3}, {"weight": 4}],
)
def helper(self, g: eg.Graph, func):
result = func(g)
if isinstance(result, eg.Graph):
print("nodes: " + str(result.nodes))
print("edges: " + str(result.edges))
else:
for i in result:
print(i)
def test_minimum_spanning_edges(self):
print("test_minimum_spanning_edges")
self.helper(self.g2, eg.minimum_spanning_edges)
self.helper(self.g2, eg.minimum_spanning_edges)
self.helper(self.g4, eg.minimum_spanning_edges)
def test_maximum_spanning_edges(self):
print("test_maximum_spanning_edges")
self.helper(self.g2, eg.maximum_spanning_edges)
self.helper(self.g2, eg.maximum_spanning_edges)
self.helper(self.g4, eg.maximum_spanning_edges)
def test_minimum_spanning_tree(self):
print("test_minimum_spanning_tree")
self.helper(self.g2, eg.minimum_spanning_tree)
self.helper(self.g2, eg.minimum_spanning_tree)
self.helper(self.g4, eg.minimum_spanning_tree)
def test_maximum_spanning_tree(self):
print("test_maximum_spanning_tree")
self.helper(self.g2, eg.maximum_spanning_tree)
self.helper(self.g2, eg.maximum_spanning_tree)
self.helper(self.g4, eg.maximum_spanning_tree)
def test_nan_handling(self):
with self.assertRaises(ValueError):
list(eg.minimum_spanning_edges(self.nan_graph))
edges = list(eg.minimum_spanning_edges(self.nan_graph, ignore_nan=True))
self.assertEqual(len(edges), 1)
def test_missing_weight_defaults_to_one(self):
edges = list(eg.minimum_spanning_edges(self.no_weight_graph))
self.assertEqual(len(edges), 2)
def test_negative_weights(self):
edges = list(eg.minimum_spanning_edges(self.negative_weight_graph))
weights = [attr["weight"] for _, _, attr in edges]
self.assertIn(-3, weights)
self.assertEqual(len(edges), 3)
def test_disconnected_graph(self):
edges = list(eg.minimum_spanning_edges(self.disconnected_graph))
self.assertEqual(len(edges), 2)
def test_maximum_vs_minimum_edges(self):
min_edges = list(eg.minimum_spanning_edges(self.G))
max_edges = list(eg.maximum_spanning_edges(self.G))
min_set = {(min(u, v), max(u, v)) for u, v, _ in min_edges}
max_set = {(min(u, v), max(u, v)) for u, v, _ in max_edges}
self.assertNotEqual(min_set, max_set)
def test_invalid_algorithm_name(self):
with self.assertRaises(ValueError):
list(eg.minimum_spanning_edges(self.G, algorithm="invalid_algo"))
if __name__ == "__main__":
unittest.main()