def test_3prism(self):
N = 6
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(1, 2),
Edge(2, 3),
Edge(3, 4),
Edge(4, 5),
Edge(0, 5),
Edge(1, 4),
Edge(2, 0),
Edge(3, 5)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "3prism"
algorithm = HalinNodeColoring(G, outer=set([0, 2, 3, 5]))
#algorithm = HalinNodeColoring(G, outer=set([0, 1, 4, 5]))
#algorithm = HalinNodeColoring(G, outer=set([1, 2, 3, 4]))
algorithm.run()
#print "3prism outer", algorithm.outer
parent = {0: 1, 1: None, 2: 1, 3: 4, 4: 1, 5: 4}
self.assertEqual(algorithm.parent, parent)
for node in G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
all_colors = set(algorithm.color[node] for node in G.iternodes())
self.assertEqual(len(all_colors), 3)
class TestStronglyConnectedComponents(unittest.TestCase):
def setUp(self):
self.N = 8 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1), Edge(1, 4), Edge(4, 0), Edge(4, 5), Edge(1, 5),
Edge(1, 2), Edge(5, 6), Edge(6, 5), Edge(2, 6), Edge(2, 3),
Edge(3, 2), Edge(6, 7), Edge(3, 7)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
self.expected_scc = {0: 0, 1: 0, 2: 1, 3: 1, 4: 0, 5: 2, 6: 2, 7: 3}
self.expected_n_scc = 4
def test_scc(self):
algorithm = StronglyConnectedComponents(self.G)
algorithm.run()
self.assertEqual(algorithm.n_scc, self.expected_n_scc)
self.assertEqual(algorithm.scc, self.expected_scc)
self.assertRaises(
ValueError, StronglyConnectedComponents, Graph(1, False))
def tearDown(self): pass
class TestMatching3(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(1, 2),
Edge(2, 3),
Edge(3, 4),
Edge(4, 5)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_matching(self):
algorithm = BorieMatching(self.G)
algorithm.run()
expected1 = set([Edge(0, 1), Edge(2, 3), Edge(4, 5)])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.mate_set, expected1)
# Testing matching.
S = set()
for edge in algorithm.mate_set:
S.add(edge.source)
S.add(edge.target)
self.assertEqual(len(S), 2 * len(algorithm.mate_set))
def tearDown(self):
pass
class TestMatchingWithWeights(unittest.TestCase):
def setUp(self):
# Graf pelny z kolejnymi wagami.
self.N = 4
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [Edge(0, 1, 5), Edge(0, 2, 7), Edge(0, 3, 2),
Edge(1, 2, 3), Edge(1, 3, 6), Edge(2, 3, 4)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_min_weight_matching(self):
algorithm = MinimumWeightMatchingWithEdges(self.G)
algorithm.run()
expected_cardinality = 2
expected_weight = 5
expected_mate = {0: Edge(0, 3, 2), 1: Edge(1, 2, 3),
2: Edge(2, 1, 3), 3: Edge(3, 0, 2)}
self.assertEqual(algorithm.cardinality, expected_cardinality)
# Krawedzie sa po dwa razy w slowniku.
weight = sum(algorithm.mate[node].weight
for node in algorithm.mate if algorithm.mate[node]) / 2
self.assertEqual(weight, expected_weight)
self.assertEqual(algorithm.mate, expected_mate)
# Is it matching?
for source in algorithm.mate:
if algorithm.mate[source] is not None:
edge = algorithm.mate[source]
self.assertEqual(algorithm.mate[edge.target], ~edge)
def tearDown(self): pass
class TestFloydWarshallAllGraphs(unittest.TestCase):
def setUp(self):
self.N = 5 # number of nodes
self.G = Graph(self.N, directed=False)
self.nodes = range(self.N)
self.edges = [
Edge(0, 2, 6), Edge(0, 3, 3), Edge(1, 0, 3), Edge(2, 3, 2),
Edge(3, 1, 1), Edge(4, 1, 4), Edge(4, 3, 2)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_floydwarshall(self):
algorithm = FloydWarshallAllGraphs(self.G)
algorithm.run()
expected_distance = {
0: {0: 0, 1: 3, 2: 5, 3: 3, 4: 5},
1: {0: 3, 1: 0, 2: 3, 3: 1, 4: 3},
2: {0: 5, 1: 3, 2: 0, 3: 2, 4: 4},
3: {0: 3, 1: 1, 2: 2, 3: 0, 4: 2},
4: {0: 5, 1: 3, 2: 4, 3: 2, 4: 0}}
self.assertEqual(algorithm.distance, expected_distance)
def test_negative_edge(self):
# An edge with the negative weight gives a negative cycle.
self.G.add_edge(Edge(2, 4, -1))
algorithm = FloydWarshallAllGraphs(self.G)
self.assertRaises(ValueError, algorithm.run)
class TestFordFulkerson(unittest.TestCase):
def setUp(self):
self.N = 4 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [Edge(0, 1, 10), Edge(0, 2, 10), Edge(1, 2, 1), Edge(1, 3, 10), Edge(2, 3, 10)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
# self.G.show()
def test_fordfulkerson(self):
algorithm = FordFulkerson(self.G)
algorithm.run(0, 3)
expected_max_flow = 20
expected_flow = {
0: {0: 0, 2: 10, 1: 10, 3: 0},
1: {0: -10, 2: 0, 1: 0, 3: 10},
2: {0: -10, 2: 0, 1: 0, 3: 10},
3: {0: 0, 2: -10, 1: -10, 3: 0},
}
self.assertEqual(algorithm.max_flow, expected_max_flow)
self.assertEqual(algorithm.flow, expected_flow)
def test_fordfulkerson_sparse(self):
algorithm = FordFulkersonSparse(self.G)
algorithm.run(0, 3)
expected_max_flow = 20
expected_flow = {0: {2: 10, 1: 10}, 1: {0: -10, 3: 10}, 2: {0: -10, 3: 10}, 3: {2: -10, 1: -10}}
self.assertEqual(algorithm.max_flow, expected_max_flow)
self.assertEqual(algorithm.flow, expected_flow)
class TestNodeColoring(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1), Edge(0, 3), Edge(1, 3), Edge(1, 4), Edge(1, 2),
Edge(2, 4), Edge(2, 5), Edge(3, 4), Edge(4, 5)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_us_node_coloring(self):
algorithm = UnorderedSequentialNodeColoring(self.G)
algorithm.run()
for node in self.G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in self.G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
#print algorithm.color
all_colors = set(algorithm.color[node] for node in self.G.iternodes())
self.assertEqual(len(all_colors), 4)
def test_exceptions(self):
self.assertRaises(ValueError, UnorderedSequentialNodeColoring,
Graph(5, directed=True))
def tearDown(self): pass
def test_3prism(self):
N = 6
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(1, 2),
Edge(2, 3),
Edge(3, 4),
Edge(4, 5),
Edge(0, 5),
Edge(1, 4),
Edge(2, 0),
Edge(3, 5)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "3prism ..."
algorithm = HalinGraphTreeDecomposition(G, outer=set([0, 2, 3, 5]))
#algorithm = HalinGraphTreeDecomposition(G, outer=set([0, 1, 4, 5]))
#algorithm = HalinGraphTreeDecomposition(G, outer=set([1, 2, 3, 4]))
algorithm.run()
#print "3prism outer", algorithm.outer
parent = {0: 1, 1: None, 2: 1, 3: 4, 4: 1, 5: 4}
self.assertEqual(algorithm.parent, parent)
#order = [1, 0, 2, 3, 5, 4]
order = [4, 0, 2, 3, 5, 1]
self.assertEqual(algorithm.order, order)
self.assertEqual(len(algorithm.cliques), G.v() - 3)
class TestMatching3(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [Edge(0, 1), Edge(1, 2), Edge(2, 3),
Edge(3, 4), Edge(4, 5)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_matching(self):
algorithm = BorieMatching(self.G)
algorithm.run()
expected1 = set([Edge(0, 1), Edge(2, 3), Edge(4, 5)])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.mate_set, expected1)
# Testing matching.
S = set()
for edge in algorithm.mate_set:
S.add(edge.source)
S.add(edge.target)
self.assertEqual(len(S), 2 * len(algorithm.mate_set))
def tearDown(self): pass
def test_halin8c(self):
N = 8
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 5),
Edge(0, 7),
Edge(1, 2),
Edge(1, 7),
Edge(2, 3),
Edge(2, 6),
Edge(3, 4),
Edge(3, 6),
Edge(4, 5),
Edge(4, 6),
Edge(5, 6),
Edge(6, 7)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
algorithm = HalinNodeColoring(G, outer=set([0, 1, 2, 3, 4, 5]))
algorithm.run()
#print "halin8c outer", algorithm.outer
parent = {0: 7, 1: 7, 2: 6, 3: 6, 4: 6, 5: 6, 6: None, 7: 6}
self.assertEqual(algorithm.parent, parent)
for node in G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
all_colors = set(algorithm.color[node] for node in G.iternodes())
self.assertEqual(len(all_colors), 3)
def test_frucht12(self):
N = 10
G = Graph(N, False)
edges = [Edge(0, 1), Edge(0, 4), Edge(0, 11), Edge(1, 2),
Edge(1, 10), Edge(2, 3), Edge(2, 7), Edge(3, 4),
Edge(3, 5), Edge(4, 5), Edge(5, 6), Edge(6, 7),
Edge(6, 8), Edge(7, 8), Edge(8, 9), Edge(9, 10),
Edge(9, 11), Edge(10, 11)]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "frucht12"
algorithm = HalinNodeColoring(G, outer=set([0, 4, 5, 6, 8, 9, 11]))
algorithm.run()
#print "frucht12 outer", algorithm.outer
parent = {0: 1, 1: None, 2: 1, 3: 2, 4: 3, 5: 3, 6: 7, 7: 2, 8: 7, 9: 10, 10: 1, 11: 10}
self.assertEqual(algorithm.parent, parent)
for node in G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
all_colors = set(algorithm.color[node] for node in G.iternodes())
self.assertEqual(len(all_colors), 3)
class TestBoruvkaDisconnectedGraph(unittest.TestCase):
def setUp(self):
# The modified graph (unique weights) from Cormen.
self.N = 9 # number of nodes
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 4), Edge(0, 7, 8), Edge(1, 7, 11), Edge(1, 2, 12),
Edge(7, 8, 7), Edge(8, 2, 2), Edge(8, 6, 6), Edge(7, 6, 1),
Edge(3, 5, 14), Edge(3, 4, 9), Edge(5, 4, 10)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#print self.G
def test_boruvka(self):
self.assertEqual(self.G.v(), self.N)
algorithm = BoruvkaMST(self.G)
algorithm.run()
self.assertEqual(algorithm.mst.v(), self.N)
self.assertEqual(algorithm.mst.e(), self.N-2) # 2 components
mst_weight_expected = 40
mst_weight = sum(edge.weight for edge in algorithm.mst.iteredges())
self.assertEqual(mst_weight, mst_weight_expected)
mst_edges_expected = [
Edge(0, 1, 4), Edge(0, 7, 8), Edge(8, 2, 2), Edge(7, 6, 1),
Edge(6, 8, 6), Edge(3, 4, 9), Edge(5, 4, 10)]
for edge in mst_edges_expected:
self.assertTrue(algorithm.mst.has_edge(edge))
def tearDown(self): pass
class TestBellmanFord(unittest.TestCase):
def setUp(self):
self.N = 4 # number of nodes
self.G = Graph(self.N, directed=True) # directed graph
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 1), Edge(0, 2, 5), Edge(1, 2, 1), Edge(1, 3, 3),
Edge(2, 3, 1)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_shortest_path(self):
source = 0
target = 3
algorithm = BellmanFord(self.G)
algorithm.run(source)
distance_expected = {0: 0, 2: 2, 1: 1, 3: 3}
self.assertEqual(algorithm.distance, distance_expected)
parent_expected = {0: None, 2: 1, 1: 0, 3: 2}
self.assertEqual(algorithm.parent, parent_expected)
path_expected = [0, 1, 2, 3]
self.assertEqual(algorithm.path(target), path_expected)
def tearDown(self): pass
class TestEdmondsKarpWiki(unittest.TestCase):
def setUp(self):
self.N = 7 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 3), Edge(0, 3, 3), Edge(1, 2, 4), Edge(2, 0, 3),
Edge(2, 3, 1), Edge(2, 4, 2), Edge(3, 4, 2), Edge(3, 5, 6),
Edge(4, 1, 1), Edge(4, 6, 1), Edge(5, 6, 9)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_wiki_sparse(self):
algorithm = EdmondsKarpSparse(self.G)
algorithm.run(0, 6)
expected_max_flow = 5
expected_flow = {
0: {1: 2, 3: 3},
1: {0: -2, 2: 2},
2: {1: -2, 4: 1, 3: 1},
3: {0: -3, 2: -1, 4: 0, 5: 4},
4: {2: -1, 3: 0, 6: 1},
5: {3: -4, 6: 4},
6: {4: -1, 5: -4}}
self.assertEqual(algorithm.max_flow, expected_max_flow)
self.assertEqual(algorithm.flow, expected_flow)
def tearDown(self): pass
def make_random_spgraph(n):
"""Make a series-parallel graph with n vertices."""
if n < 2:
raise ValueError("bad n")
graph = Graph(n)
for node in xrange(n):
graph.add_node(node)
source = 0
sink = n - 1
edge_list = [Edge(source, sink)]
node = n - 2
while node > 0:
# Losowanie krawedzi na ktorej bedzie operacja.
i = random.randrange(0, len(edge_list))
swap(edge_list, i, -1)
edge = edge_list[-1]
# Losowanie operacji.
if edge.target == sink:
action = random.choice(["series", "parallel", "jackknife"])
else:
action = random.choice(["series", "parallel"])
if action == "series":
edge_list.pop()
edge_list.append(Edge(edge.source, node))
edge_list.append(Edge(node, edge.target))
elif action == "parallel":
edge_list.append(Edge(edge.source, node))
edge_list.append(Edge(node, edge.target))
elif action == "jackknife":
edge_list.append(Edge(edge.target, node))
node -= 1
for edge in edge_list:
graph.add_edge(edge)
return graph
class TestTransitiveClosure(unittest.TestCase):
def setUp(self):
self.N = 4 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [Edge(0, 1), Edge(1, 2), Edge(2, 3)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
self.expected_T = {
0: {
0: True,
1: True,
2: True,
3: True
},
1: {
0: False,
1: True,
2: True,
3: True
},
2: {
0: False,
1: False,
2: True,
3: True
},
3: {
0: False,
1: False,
2: False,
3: True
}
}
def test_closure(self):
algorithm = TransitiveClosure(self.G)
algorithm.run()
self.assertEqual(algorithm.T, self.expected_T)
def test_closure_simple(self):
algorithm = TransitiveClosureSimple(self.G)
algorithm.run()
self.assertEqual(algorithm.T, self.expected_T)
def test_closure_bfs(self):
algorithm = TransitiveClosureBFS(self.G)
algorithm.run()
self.assertEqual(algorithm.T, self.expected_T)
def test_closure_dfs(self):
algorithm = TransitiveClosureDFS(self.G)
algorithm.run()
self.assertEqual(algorithm.T, self.expected_T)
def tearDown(self):
pass
def test_halin8c(self):
N = 8
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 5),
Edge(0, 7),
Edge(1, 2),
Edge(1, 7),
Edge(2, 3),
Edge(2, 6),
Edge(3, 4),
Edge(3, 6),
Edge(4, 5),
Edge(4, 6),
Edge(5, 6),
Edge(6, 7)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "halin8c ..."
algorithm = HalinGraphTreeDecomposition(G,
outer=set([0, 1, 2, 3, 4, 5]))
algorithm.run()
#print "halin8c outer", algorithm.outer
parent = {0: 7, 1: 7, 2: 6, 3: 6, 4: 6, 5: 6, 6: None, 7: 6}
self.assertEqual(algorithm.parent, parent)
#order = [7, 0, 1, 2, 3, 4, 5, 6] # wersja z indeksami
order = [3, 4, 6, 0, 1, 2, 5, 7] # wersja z linkami
self.assertEqual(algorithm.order, order)
self.assertEqual(len(algorithm.cliques), G.v() - 3)
def test_wheel5(self):
N = 5
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 2),
Edge(0, 3),
Edge(0, 4),
Edge(1, 2),
Edge(2, 3),
Edge(3, 4),
Edge(4, 1)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "wheel5 ..."
algorithm = HalinGraphTreeDecomposition(G, outer=set([1, 2, 3, 4]))
algorithm.run()
#print "wheel5 outer", algorithm.outer
#print "wheel5 cycle", algorithm.cycle
parent = {0: None, 1: 0, 2: 0, 3: 0, 4: 0}
self.assertEqual(algorithm.parent, parent)
order = [1, 2, 3, 4, 0]
self.assertEqual(algorithm.order, order)
self.assertEqual(len(algorithm.cliques), G.v() - 3)
class TestBellmanFordCormen(unittest.TestCase):
def setUp(self):
# The graph from Cormen p.666, negative weights.
self.N = 5 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 6), Edge(0, 3, 7), Edge(1, 3, 8), Edge(1, 2, 5),
Edge(1, 4, -4), Edge(2, 1, -2), Edge(3, 2, -3), Edge(3, 4, 9),
Edge(4, 0, 2), Edge(4, 2, 7)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_shortest_path_cormen(self):
source = 0
target = 4
algorithm = BellmanFord(self.G)
algorithm.run(source)
distance_expected = {3: 7, 2: 4, 0: 0, 4: -2, 1: 2}
self.assertEqual(algorithm.distance, distance_expected)
parent_expected = {3: 0, 2: 3, 0: None, 4: 1, 1: 2}
self.assertEqual(algorithm.parent, parent_expected)
path_expected = [0, 3, 2, 1, 4]
self.assertEqual(algorithm.path(target), path_expected)
def tearDown(self): pass
def test_halin8a(self):
N = 8
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 2),
Edge(0, 7),
Edge(1, 2),
Edge(1, 5),
Edge(2, 3),
Edge(3, 4),
Edge(3, 7),
Edge(4, 5),
Edge(4, 6),
Edge(5, 6),
Edge(6, 7)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "halin8a ..."
algorithm = HalinGraphTreeDecomposition(G, outer=set([0, 7, 6, 5, 1]))
algorithm.run()
#print "halin8a outer", algorithm.outer
parent = {0: 2, 1: 2, 2: None, 3: 2, 4: 3, 5: 4, 6: 4, 7: 3}
self.assertEqual(algorithm.parent, parent)
#order = [2, 4, 0, 1, 5, 6, 7, 3]
order = [4, 2, 0, 1, 5, 6, 7, 3]
self.assertEqual(algorithm.order, order)
self.assertEqual(len(algorithm.cliques), G.v() - 3)
class TestJohnsonWiki(unittest.TestCase):
def setUp(self):
self.N = 4 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 3), Edge(0, 3, 6), Edge(1, 3, 4), Edge(1, 2, 5),
Edge(3, 2, 2), Edge(2, 0, -7), Edge(2, 1, -3)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
def test_johnson(self):
algorithm = Johnson(self.G)
algorithm.run()
expected_distance = {
0: {1: 3, 0: 0, 2: 8, 3: 6},
1: {1: 0, 0: -2, 2: 5, 3: 4},
2: {1: -4, 0: -7, 2: 0, 3: -1},
3: {1: -2, 0: -5, 2: 2, 3: 0}}
self.assertEqual(algorithm.distance, expected_distance)
def test_johnson_faster(self):
algorithm = JohnsonFaster(self.G)
algorithm.run()
expected_distance = {
0: {1: 3, 0: 0, 2: 8, 3: 6},
1: {1: 0, 0: -2, 2: 5, 3: 4},
2: {1: -4, 0: -7, 2: 0, 3: -1},
3: {1: -2, 0: -5, 2: 2, 3: 0}}
self.assertEqual(algorithm.distance, expected_distance)
class TestDAGShortestPath(unittest.TestCase):
def setUp(self):
self.N = 6 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
for node in self.nodes:
self.G.add_node(node)
self.G.add_edge(Edge(0, 1, 5))
self.G.add_edge(Edge(0, 2, 3))
self.G.add_edge(Edge(1, 3, 6))
self.G.add_edge(Edge(1, 2, 2))
self.G.add_edge(Edge(2, 4, 4))
self.G.add_edge(Edge(2, 3, 7))
self.G.add_edge(Edge(2, 5, 2))
self.G.add_edge(Edge(3, 4, -1))
self.G.add_edge(Edge(3, 5, 1))
self.G.add_edge(Edge(4, 5, -2))
def test_shortest_path(self):
source = 0
target = 5
algorithm = DAGShortestPath(self.G)
algorithm.run(source)
distance_expected = {0: 0, 1: 5, 2: 3, 3: 10, 4: 7, 5: 5}
self.assertEqual(algorithm.distance, distance_expected)
parent_expected = {1: 0, 0: None, 2: 0, 4: 2, 3: 2, 5: 2}
self.assertEqual(algorithm.parent, parent_expected)
path_expected = [0, 2, 5]
self.assertEqual(algorithm.path(target), path_expected)
def tearDown(self): pass
def test_halin16(self):
N = 16
G = Graph(N, False)
edges = [Edge(0, 1), Edge(0, 2), Edge(0, 15), Edge(1, 2),
Edge(1, 6), Edge(2, 3), Edge(3, 4), Edge(3, 5),
Edge(4, 5), Edge(4, 10), Edge(5, 6), Edge(6, 7),
Edge(7, 8), Edge(7, 15), Edge(8, 9), Edge(8, 13),
Edge(9, 10), Edge(9, 11), Edge(10, 11), Edge(11, 12),
Edge(12, 13), Edge(12, 14), Edge(13, 14), Edge(14, 15)]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "halin16"
algorithm = HalinNodeColoring(G, outer=set([0, 2, 3, 4, 10, 11, 12, 14, 15]))
algorithm.run()
#print "halin16 outer", algorithm.outer
parent = {0: 1, 1: None, 2: 1, 3: 5, 4: 5, 5: 6, 6: 1, 7: 6,
8: 7, 9: 8, 10: 9, 11: 9, 12: 13, 13: 8, 14: 13, 15: 7}
self.assertEqual(algorithm.parent, parent)
for node in G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
all_colors = set(algorithm.color[node] for node in G.iternodes())
self.assertEqual(len(all_colors), 3)
def test_wheel5(self):
N = 5
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 2),
Edge(0, 3),
Edge(0, 4),
Edge(1, 2),
Edge(2, 3),
Edge(3, 4),
Edge(4, 1)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
algorithm = HalinNodeColoring(G, outer=set([1, 2, 3, 4]))
algorithm.run()
#print "wheel5 outer", algorithm.outer
#print "wheel5 cycle", algorithm.cycle
parent = {0: None, 1: 0, 2: 0, 3: 0, 4: 0}
self.assertEqual(algorithm.parent, parent)
for node in G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
all_colors = set(algorithm.color[node] for node in G.iternodes())
self.assertEqual(len(all_colors), 3)
def test_halin16(self):
N = 16
G = Graph(N, False)
edges = [
Edge(0, 1),
Edge(0, 2),
Edge(0, 15),
Edge(1, 2),
Edge(1, 6),
Edge(2, 3),
Edge(3, 4),
Edge(3, 5),
Edge(4, 5),
Edge(4, 10),
Edge(5, 6),
Edge(6, 7),
Edge(7, 8),
Edge(7, 15),
Edge(8, 9),
Edge(8, 13),
Edge(9, 10),
Edge(9, 11),
Edge(10, 11),
Edge(11, 12),
Edge(12, 13),
Edge(12, 14),
Edge(13, 14),
Edge(14, 15)
]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#print "halin16 ..."
algorithm = HalinGraphTreeDecomposition(
G, outer=set([0, 2, 3, 4, 10, 11, 12, 14, 15]))
algorithm.run()
#print "halin16 outer", algorithm.outer
parent = {
0: 1,
1: None,
2: 1,
3: 5,
4: 5,
5: 6,
6: 1,
7: 6,
8: 7,
9: 8,
10: 9,
11: 9,
12: 13,
13: 8,
14: 13,
15: 7
}
self.assertEqual(algorithm.parent, parent)
order = [5, 9, 13, 1, 11, 12, 8, 2, 3, 6, 0, 4, 10, 14, 15, 7]
self.assertEqual(algorithm.order, order)
self.assertEqual(len(algorithm.cliques), G.v() - 3)
class TestBoruvkaWiki(unittest.TestCase):
def setUp(self):
# The graph (unique weights) from
# http://en.wikipedia.org/wiki/Boruvka's_algorithm
self.N = 7 # number of nodes
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 7), Edge(1, 2, 11), Edge(0, 3, 4), Edge(3, 1, 9),
Edge(4, 1, 10), Edge(2, 4, 5), Edge(3, 4, 15), Edge(3, 5, 6),
Edge(5, 4, 12), Edge(5, 6, 13), Edge(4, 6, 8)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#print self.G
def test_boruvka(self):
self.assertEqual(self.G.v(), self.N)
algorithm = BoruvkaMST(self.G)
algorithm.run()
self.assertEqual(algorithm.mst.v(), self.N)
self.assertEqual(algorithm.mst.e(), self.N-1)
mst_weight_expected = 40
mst_weight = sum(edge.weight for edge in algorithm.mst.iteredges())
self.assertEqual(mst_weight, mst_weight_expected)
mst_edges_expected = [
Edge(0, 1, 7), Edge(0, 3, 4), Edge(2, 4, 5), Edge(1, 4, 10),
Edge(4, 6, 8), Edge(3, 5, 6)]
for edge in mst_edges_expected:
self.assertTrue(algorithm.mst.has_edge(edge))
def tearDown(self): pass
class TestDAGShortestPath(unittest.TestCase):
def setUp(self):
self.N = 6 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
for node in self.nodes:
self.G.add_node(node)
self.G.add_edge(Edge(0, 1, 5))
self.G.add_edge(Edge(0, 2, 3))
self.G.add_edge(Edge(1, 3, 6))
self.G.add_edge(Edge(1, 2, 2))
self.G.add_edge(Edge(2, 4, 4))
self.G.add_edge(Edge(2, 3, 7))
self.G.add_edge(Edge(2, 5, 2))
self.G.add_edge(Edge(3, 4, -1))
self.G.add_edge(Edge(3, 5, 1))
self.G.add_edge(Edge(4, 5, -2))
def test_shortest_path(self):
source = 0
target = 5
algorithm = DAGShortestPath(self.G)
algorithm.run(source)
distance_expected = {0: 0, 1: 5, 2: 3, 3: 10, 4: 7, 5: 5}
self.assertEqual(algorithm.distance, distance_expected)
parent_expected = {1: 0, 0: None, 2: 0, 4: 2, 3: 2, 5: 2}
self.assertEqual(algorithm.parent, parent_expected)
path_expected = [0, 2, 5]
self.assertEqual(algorithm.path(target), path_expected)
def tearDown(self):
pass
class TestHamiltonianCycleDirected(unittest.TestCase):
def setUp(self):
# 3-prism graph, Halin graph
self.N = 6 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(2, 0),
Edge(0, 5),
Edge(2, 1),
Edge(1, 4),
Edge(3, 2),
Edge(3, 4),
Edge(5, 3),
Edge(4, 5)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
def test_hamilton(self):
algorithm = HamiltonianCycleDFS(self.G)
algorithm.run(0)
expected_cycle = [0, 1, 4, 5, 3, 2, 0]
self.assertEqual(algorithm.hamiltonian_cycle, expected_cycle)
def test_hamilton_with_edges(self):
algorithm = HamiltonianCycleDFSWithEdges(self.G)
algorithm.run(0)
expected_cycle = [
Edge(0, 1),
Edge(1, 4),
Edge(4, 5),
Edge(5, 3),
Edge(3, 2),
Edge(2, 0)
]
self.assertEqual(algorithm.hamiltonian_cycle, expected_cycle)
def test_hamilton_with_cycle_graph(self):
algorithm = HamiltonianCycleDFSWithGraph(self.G)
algorithm.run(0)
# 5 solutions
expected_cycle = [
Edge(0, 1),
Edge(1, 4),
Edge(4, 5),
Edge(5, 3),
Edge(3, 2),
Edge(2, 0)
]
#print "directed", list(algorithm.hamiltonian_cycle.iteredges())
for edge in expected_cycle:
self.assertTrue(algorithm.hamiltonian_cycle.has_edge(edge))
def tearDown(self):
pass
def test_tree_three_nodes(self):
T = Graph(3)
for node in (0, 1, 2):
T.add_node(node)
for edge in (Edge(0, 1), Edge(1, 2)):
T.add_edge(edge)
algorithm = TreePlot(T)
algorithm.run()
self.assertEqual(len(algorithm.point_dict), 3)
class TestNodeCover3(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [Edge(0, 1), Edge(1, 2), Edge(2, 3),
Edge(3, 4), Edge(4, 5)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_borie_node_cover(self):
algorithm = BorieNodeCover(self.G)
algorithm.run()
expected1 = set([1, 2, 4])
expected2 = set([1, 3, 4])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.node_cover, expected3)
# Testing cover.
for edge in self.G.iteredges():
self.assertTrue(edge.source in algorithm.node_cover or
edge.target in algorithm.node_cover)
def test_tree_node_cover1(self):
algorithm = TreeNodeCover1(self.G)
algorithm.run()
expected1 = set([1, 2, 4])
expected2 = set([1, 3, 4])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.node_cover, expected2)
# Testing cover.
for edge in self.G.iteredges():
self.assertTrue(edge.source in algorithm.node_cover or
edge.target in algorithm.node_cover)
def test_tree_node_cover2(self):
algorithm = TreeNodeCover2(self.G)
algorithm.run()
expected1 = set([1, 2, 4])
expected2 = set([1, 3, 4])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.node_cover, expected2)
# Testing cover.
for edge in self.G.iteredges():
self.assertTrue(edge.source in algorithm.node_cover or
edge.target in algorithm.node_cover)
def tearDown(self): pass
def test_tree_three_nodes(self):
T = Graph(3)
for node in (0, 1, 2):
T.add_node(node)
for edge in (Edge(0, 1), Edge(1, 2)):
T.add_edge(edge)
algorithm = TreePlot(T)
algorithm.run()
self.assertEqual(len(algorithm.point_dict), 3)
class TestNodeColoring(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(0, 3),
Edge(1, 3),
Edge(1, 4),
Edge(1, 2),
Edge(2, 4),
Edge(2, 5),
Edge(3, 4),
Edge(4, 5)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_brooks_node_coloring(self):
algorithm = BrooksNodeColoring(self.G)
algorithm.run()
for node in self.G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in self.G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
#print algorithm.color
all_colors = set(algorithm.color[node] for node in self.G.iternodes())
self.assertEqual(len(all_colors), 4)
def test_brooks_node_coloring_regular(self):
# Buduje graf 4-regularny planarny z Delta=4.
# Graf jest 3-connected, dlatego algorytm dziala.
self.G.add_edge(Edge(0, 2))
self.G.add_edge(Edge(3, 5))
self.G.add_edge(Edge(0, 5))
algorithm = BrooksNodeColoring(self.G)
algorithm.run()
for node in self.G.iternodes():
self.assertNotEqual(algorithm.color[node], None)
for edge in self.G.iteredges():
self.assertNotEqual(algorithm.color[edge.source],
algorithm.color[edge.target])
#print algorithm.color
all_colors = set(algorithm.color[node] for node in self.G.iternodes())
self.assertEqual(len(all_colors), 3) # best
def test_exceptions(self):
self.assertRaises(ValueError, BrooksNodeColoring,
Graph(5, directed=True))
def tearDown(self):
pass
class TestIndependentSet3(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [Edge(0, 1), Edge(1, 2), Edge(2, 3),
Edge(3, 4), Edge(4, 5)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_borie_iset(self):
algorithm = BorieIndependentSet(self.G)
algorithm.run()
expected1 = set([0, 2, 5])
expected2 = set([0, 3, 5])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected3)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def test_tree_iset1(self):
algorithm = TreeIndependentSet1(self.G)
algorithm.run()
expected1 = set([0, 2, 5])
expected2 = set([0, 3, 5])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected1)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def test_tree_iset2(self):
algorithm = TreeIndependentSet2(self.G)
algorithm.run()
expected1 = set([0, 2, 5])
expected2 = set([0, 3, 5])
expected3 = set([0, 2, 4])
expected4 = set([1, 3, 5])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected1)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def tearDown(self): pass
class TestIndependentSet1(unittest.TestCase):
def setUp(self):
self.N = 7
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(0, 3),
Edge(1, 2),
Edge(1, 4),
Edge(2, 5),
Edge(2, 6)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_borie_iset(self):
algorithm = BorieIndependentSet(self.G)
algorithm.run()
expected1 = set([3, 4, 5, 6])
expected2 = set([0, 4, 5, 6])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected2)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def test_tree_iset1(self):
algorithm = TreeIndependentSet1(self.G)
algorithm.run()
expected1 = set([3, 4, 5, 6])
expected2 = set([0, 4, 5, 6])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected1)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def test_tree_iset2(self):
algorithm = TreeIndependentSet2(self.G)
algorithm.run()
expected1 = set([3, 4, 5, 6])
expected2 = set([0, 4, 5, 6])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.independent_set, expected1)
# Testing iset.
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
def tearDown(self):
pass
class TestDominatingSet2(unittest.TestCase):
def setUp(self):
self.N = 7
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(1, 3),
Edge(1, 2),
Edge(1, 4),
Edge(2, 5),
Edge(2, 6)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_borie_dset(self):
algorithm = BorieDominatingSet(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def test_tree_dset1(self):
algorithm = TreeDominatingSet1(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def test_tree_dset2(self):
algorithm = TreeDominatingSet2(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def tearDown(self):
pass
class TestFleuryDirectedGraph(unittest.TestCase):
def setUp(self):
self.N = 6 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1), Edge(3, 0), Edge(1, 4), Edge(4, 3), Edge(2, 4),
Edge(4, 5), Edge(5, 2)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
def test_fleury_dfs(self):
algorithm = FleuryDFS(self.G)
algorithm.run(0)
expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges) + 1)
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_bfs(self):
algorithm = FleuryBFS(self.G)
algorithm.run(0)
expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges) + 1)
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_dfs_with_edges(self):
algorithm = FleuryDFSWithEdges(self.G)
algorithm.run(0)
#expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
expected_cycle = [
Edge(0, 1), Edge(1, 4), Edge(4, 5), Edge(5, 2), Edge(2, 4),
Edge(4, 3), Edge(3, 0)]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges))
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_bfs_with_edges(self):
algorithm = FleuryBFSWithEdges(self.G)
algorithm.run(0)
#expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
expected_cycle = [
Edge(0, 1), Edge(1, 4), Edge(4, 5), Edge(5, 2), Edge(2, 4),
Edge(4, 3), Edge(3, 0)]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges))
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_eulerian(self):
self.G.add_edge(Edge(1, 2))
self.assertRaises(ValueError, FleuryDFS, self.G)
self.assertRaises(ValueError, FleuryBFS, self.G)
self.assertRaises(ValueError, FleuryDFSWithEdges, self.G)
self.assertRaises(ValueError, FleuryBFSWithEdges, self.G)
def tearDown(self): pass
class TestFleuryDirectedGraph(unittest.TestCase):
def setUp(self):
self.N = 6 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1), Edge(3, 0), Edge(1, 4), Edge(4, 3), Edge(2, 4),
Edge(4, 5), Edge(5, 2)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
def test_fleury_dfs(self):
algorithm = FleuryDFS(self.G)
algorithm.run(0)
expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges) + 1)
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_bfs(self):
algorithm = FleuryBFS(self.G)
algorithm.run(0)
expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges) + 1)
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_dfs_with_edges(self):
algorithm = FleuryDFSWithEdges(self.G)
algorithm.run(0)
#expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
expected_cycle = [
Edge(0, 1), Edge(1, 4), Edge(4, 5), Edge(5, 2), Edge(2, 4),
Edge(4, 3), Edge(3, 0)]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges))
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_fleury_bfs_with_edges(self):
algorithm = FleuryBFSWithEdges(self.G)
algorithm.run(0)
#expected_cycle = [0, 1, 4, 5, 2, 4, 3, 0]
expected_cycle = [
Edge(0, 1), Edge(1, 4), Edge(4, 5), Edge(5, 2), Edge(2, 4),
Edge(4, 3), Edge(3, 0)]
self.assertEqual(len(algorithm.eulerian_cycle), len(self.edges))
self.assertEqual(algorithm.eulerian_cycle, expected_cycle)
def test_eulerian(self):
self.G.add_edge(Edge(1, 2))
self.assertRaises(ValueError, FleuryDFS, self.G)
self.assertRaises(ValueError, FleuryBFS, self.G)
self.assertRaises(ValueError, FleuryDFSWithEdges, self.G)
self.assertRaises(ValueError, FleuryBFSWithEdges, self.G)
def tearDown(self): pass
def test_add_graph_undirected(self):
T = Graph(self.N)
for node in self.nodes:
T.add_node(node)
T.add_edge(Edge("A", "D", 9))
self.assertEqual(T.v(), self.N)
self.assertEqual(T.e(), 1)
self.G.add_graph(T)
self.assertEqual(self.G.v(), self.N)
self.assertEqual(self.G.e(), 6)
def test_add_graph_undirected(self):
T = Graph(self.N)
for node in self.nodes:
T.add_node(node)
T.add_edge(Edge("A", "D", 9))
self.assertEqual(T.v(), self.N)
self.assertEqual(T.e(), 1)
self.G.add_graph(T)
self.assertEqual(self.G.v(), self.N)
self.assertEqual(self.G.e(), 6)
class TestIndependentSet(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1), Edge(0, 3), Edge(1, 3), Edge(1, 4),
Edge(1, 2), Edge(2, 5), Edge(3, 4), Edge(4, 5)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_us_independent_set1(self):
algorithm = UnorderedSequentialIndependentSet1(self.G)
#algorithm.run() # przypadkiem znajduje najlepsze rozwiazanie
algorithm.run(3) # znajduje set([2, 3])
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
self.assertEqual(algorithm.cardinality, len(algorithm.independent_set))
#print algorithm.independent_set
def test_us_independent_set2(self):
algorithm = UnorderedSequentialIndependentSet2(self.G)
#algorithm.run() # przypadkiem znajduje najlepsze rozwiazanie
algorithm.run(3) # znajduje set([2, 3])
for edge in self.G.iteredges():
self.assertFalse(edge.source in algorithm.independent_set
and edge.target in algorithm.independent_set)
self.assertEqual(algorithm.cardinality, len(algorithm.independent_set))
#print algorithm.independent_set
def test_us_independent_set3(self):
algorithm = UnorderedSequentialIndependentSet3(self.G)
#algorithm.run() # przypadkiem znajduje najlepsze rozwiazanie
algorithm.run(3) # znajduje set([2, 3])
for edge in self.G.iteredges():
self.assertFalse(algorithm.independent_set[edge.source]
and algorithm.independent_set[edge.target])
cardinality = sum(1 for node in self.G if algorithm.independent_set[node])
self.assertEqual(algorithm.cardinality, cardinality)
#print algorithm.independent_set
def test_exceptions(self):
self.assertRaises(ValueError, UnorderedSequentialIndependentSet1,
Graph(5, directed=True))
self.assertRaises(ValueError, UnorderedSequentialIndependentSet2,
Graph(5, directed=True))
self.assertRaises(ValueError, UnorderedSequentialIndependentSet3,
Graph(5, directed=True))
def tearDown(self): pass
def make_halin_outer(n=4):
"""Create a random weighted Halin graph with the set of outer nodes."""
if n < 4:
raise ValueError("number of nodes must be greater than 3")
graph = Graph(n)
weights = list(range(1, 1 + 2 * n - 2))
random.shuffle(weights)
for node in xrange(n):
graph.add_node(node)
# Teraz trzeba dodawac krawedzie, ale nie moze zostac wierzcholek
# stopnia 2. Startuje od gwiazdy.
graph.add_edge(Edge(1, 0, weights.pop()))
graph.add_edge(Edge(2, 0, weights.pop()))
graph.add_edge(Edge(3, 0, weights.pop()))
nodes = set([0, 1, 2, 3])
node = 4
while node < n:
parent = random.sample(nodes, 1)[0]
if graph.degree(parent) == 1: # leaf, we must add two edges
if node + 1 == n:
continue
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
else: # degree > 2
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
# Method 1. Finding root without TreeCenter.
for node in graph.iternodes():
if graph.degree(node) > 1: # always present
root = node
break
# Method 2. Finding root with TreeCenter.
# TreeCenter reduces floating point errors for points.
#algorithm = TreeCenter(graph)
#algorithm.run()
#root = algorithm.tree_center[0]
# Wyznaczam slownik z punktami.
algorithm = TreePlotRadiusAngle(graph)
algorithm.run(root)
L = list() # for leafs
for node in algorithm.point_dict:
if graph.degree(node) == 1: # leafs
L.append(node)
# Sortowanie lisci ze wzgledu na kat.
L.sort(key=lambda node: algorithm.point_dict[node][1])
n_leafs = len(L)
for i in range(n_leafs):
graph.add_edge(Edge(L[i], L[(i + 1) % n_leafs], weights.pop()))
return graph, set(L)
def make_halin_outer(n=4):
"""Create a random weighted Halin graph with the set of outer nodes."""
if n < 4:
raise ValueError("number of nodes must be greater than 3")
graph = Graph(n)
weights = list(range(1, 1 + 2 * n - 2))
random.shuffle(weights)
for node in xrange(n):
graph.add_node(node)
# Teraz trzeba dodawac krawedzie, ale nie moze zostac wierzcholek
# stopnia 2. Startuje od gwiazdy.
graph.add_edge(Edge(1, 0, weights.pop()))
graph.add_edge(Edge(2, 0, weights.pop()))
graph.add_edge(Edge(3, 0, weights.pop()))
nodes = set([0, 1, 2, 3])
node = 4
while node < n:
parent = random.sample(nodes, 1)[0]
if graph.degree(parent) == 1: # leaf, we must add two edges
if node + 1 == n:
continue
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
else: # degree > 2
nodes.add(node)
graph.add_edge(Edge(parent, node, weights.pop()))
node += 1
# Method 1. Finding root without TreeCenter.
for node in graph.iternodes():
if graph.degree(node) > 1: # always present
root = node
break
# Method 2. Finding root with TreeCenter.
# TreeCenter reduces floating point errors for points.
#algorithm = TreeCenter(graph)
#algorithm.run()
#root = algorithm.tree_center[0]
# Wyznaczam slownik z punktami.
algorithm = TreePlotRadiusAngle(graph)
algorithm.run(root)
L = list() # for leafs
for node in algorithm.point_dict:
if graph.degree(node) == 1: # leafs
L.append(node)
# Sortowanie lisci ze wzgledu na kat.
L.sort(key=lambda node: algorithm.point_dict[node][1])
n_leafs = len(L)
for i in range(n_leafs):
graph.add_edge(Edge(L[i], L[(i + 1) % n_leafs], weights.pop()))
return graph, set(L)
class TestTSP(unittest.TestCase):
def setUp(self):
self.N = 4
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 20),
Edge(0, 3, 35),
Edge(0, 2, 42),
Edge(1, 2, 30),
Edge(1, 3, 34),
Edge(2, 3, 12)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
self.best_weight = 97
#self.G.show()
def test_nearest_neighbor_with_edges(self):
algorithm = NearestNeighborTSPWithEdges(self.G)
algorithm.run(0)
expected_hamiltonian_cycle = [
Edge(0, 1, 20),
Edge(1, 2, 30),
Edge(2, 3, 12),
Edge(3, 0, 35)
]
self.assertEqual(algorithm.hamiltonian_cycle,
expected_hamiltonian_cycle)
weight = sum(edge.weight for edge in algorithm.hamiltonian_cycle)
self.assertEqual(weight, self.best_weight)
def test_nearest_neighbor_with_cycle_graph(self):
algorithm = NearestNeighborTSPWithGraph(self.G)
algorithm.run(0)
weight = sum(edge.weight
for edge in algorithm.hamiltonian_cycle.iteredges())
self.assertEqual(weight, self.best_weight)
#algorithm.hamiltonian_cycle.show()
self.assertEqual(algorithm.hamiltonian_cycle.e(),
algorithm.hamiltonian_cycle.v())
for node in algorithm.hamiltonian_cycle.iternodes():
self.assertEqual(algorithm.hamiltonian_cycle.degree(node), 2)
def test_exceptions(self):
self.assertRaises(ValueError, NearestNeighborTSPWithEdges,
Graph(5, True))
self.assertRaises(ValueError, NearestNeighborTSPWithGraph,
Graph(5, True))
def tearDown(self):
pass
class TestAcyclicUdirectedGraph(unittest.TestCase):
def setUp(self):
# The graph from Cormen p.607 changed.
self.N = 8 # number of nodes
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 4),
Edge(0, 1),
Edge(1, 5),
Edge(5, 2),
Edge(2, 6),
Edge(6, 3),
Edge(6, 7)
]
self.cycle_edges = [Edge(5, 6), Edge(2, 3), Edge(3, 7)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#print self.G
#self.G.show()
def test_detect_no_cycles(self):
self.assertEqual(self.G.v(), self.N)
algorithm = AcyclicGraphDFS(self.G)
algorithm.run(1) # it is safe, because G is connected
parent_expected = {1: None, 0: 1, 3: 6, 2: 5, 5: 1, 4: 0, 7: 6, 6: 2}
self.assertEqual(algorithm.parent, parent_expected)
self.assertTrue(is_acyclic(self.G))
def test_detect_cycle1(self):
self.assertEqual(self.G.v(), self.N)
self.G.add_edge(self.cycle_edges[0])
algorithm = AcyclicGraphDFS(self.G)
self.assertRaises(ValueError, algorithm.run)
self.assertFalse(is_acyclic(self.G))
def test_detect_cycle2(self):
self.assertEqual(self.G.v(), self.N)
self.G.add_edge(self.cycle_edges[1])
algorithm = AcyclicGraphDFS(self.G)
self.assertRaises(ValueError, algorithm.run)
self.assertFalse(is_acyclic(self.G))
def test_detect_cycle3(self):
self.assertEqual(self.G.v(), self.N)
self.G.add_edge(self.cycle_edges[2])
algorithm = AcyclicGraphDFS(self.G)
self.assertRaises(ValueError, algorithm.run)
self.assertFalse(is_acyclic(self.G))
def tearDown(self):
pass
def test_wheel_true(self):
v = 10
G = Graph(v, False)
for node in range(v):
G.add_node(node)
hub = 0
for node in range(1, v):
G.add_edge(Edge(hub, node))
G.add_edge(Edge(node, node+1 if node < v-1 else 1))
self.assertTrue(is_wheel(G))
algorithm = WheelGraph(G)
algorithm.run()
self.assertEqual(algorithm.hub, hub)
def test_4prism(self):
N = 8
G = Graph(N, False)
edges = [Edge(0, 1), Edge(1, 2), Edge(2, 3), Edge(3, 0),
Edge(4, 5), Edge(5, 6), Edge(6, 7), Edge(7, 4),
Edge(0, 4), Edge(1, 5), Edge(2, 6), Edge(3, 7)]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
#G.show()
algorithm = HalinGraph(G)
self.assertRaises(ValueError, algorithm.run)
class TestMatching(unittest.TestCase):
def setUp(self):
# Wilson, ex. 25.1, bipartite graph
# 0 : 4 5 6
# 1 : 3 5
# 2 : 3 4
# ...
self.N = 7
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 4), Edge(0, 5), Edge(0, 6),
Edge(1, 3), Edge(1, 5), Edge(2, 3), Edge(2, 4)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_maximal_matching(self):
algorithm = MaximalMatching(self.G)
algorithm.run()
# 5 solutions
expected_cardinality = 2 # max 3
expected_mate = {0: 4, 4: 0, 1: 3, 3: 1, 2: None, 5: None, 6: None}
self.assertEqual(algorithm.cardinality, expected_cardinality)
self.assertEqual(algorithm.mate, expected_mate)
# Is it matching?
for source in algorithm.mate:
if algorithm.mate[source] is not None:
target = algorithm.mate[source]
self.assertEqual(algorithm.mate[target], source)
def test_maximal_matching_with_edges(self):
algorithm = MaximalMatchingWithEdges(self.G)
algorithm.run()
# 5 solutions
expected_cardinality = 2 # max 3
expected_mate = {0: Edge(0, 4), 1: Edge(1, 3), 2: None,
3: Edge(3, 1), 4: Edge(4, 0), 5: None, 6: None}
self.assertEqual(algorithm.cardinality, expected_cardinality)
self.assertEqual(algorithm.mate, expected_mate)
# Is it matching?
for source in algorithm.mate:
if algorithm.mate[source] is not None:
edge = algorithm.mate[source]
self.assertEqual(algorithm.mate[edge.target], ~edge)
def tearDown(self): pass
def test_wheel5(self):
N = 5
G = Graph(N, False)
edges = [Edge(0, 1), Edge(0, 2), Edge(0, 3), Edge(0, 4),
Edge(1, 2), Edge(2, 3), Edge(3, 4), Edge(4, 1)]
for node in range(N):
G.add_node(node)
for edge in edges:
G.add_edge(edge)
algorithm = HalinGraph(G)
algorithm.run()
#print "wheel5 outer", algorithm.outer
self.assertEqual(algorithm.outer, set([1, 2, 3, 4]))
self.assertTrue(algorithm.is_outer_k4())
class TestTSP(unittest.TestCase):
def setUp(self):
self.N = 4
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1, 20), Edge(0, 3, 35), Edge(0, 2, 42),
Edge(1, 2, 30), Edge(1, 3, 34), Edge(2, 3, 12)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
self.best_weight = 97
#self.G.show()
def test_brute_force_with_edges(self):
algorithm = BruteForceTSPWithEdges(self.G)
algorithm.run(2)
# Cycles for different starting nodes.
expected_hamiltonian_cycle0 = [
Edge(0, 1, 20), Edge(1, 2, 30), Edge(2, 3, 12), Edge(3, 0, 35)]
expected_hamiltonian_cycle1 = [
Edge(1, 0, 20), Edge(0, 3, 35), Edge(3, 2, 12), Edge(2, 1, 30)]
expected_hamiltonian_cycle2 = [
Edge(2, 1, 30), Edge(1, 0, 20), Edge(0, 3, 35), Edge(3, 2, 12)]
expected_hamiltonian_cycle3 = [
Edge(3, 0, 35), Edge(0, 1, 20), Edge(1, 2, 30), Edge(2, 3, 12)]
expected_hamiltonian_cycle = expected_hamiltonian_cycle2
self.assertEqual(algorithm.hamiltonian_cycle, expected_hamiltonian_cycle)
weight = sum(edge.weight for edge in algorithm.hamiltonian_cycle)
self.assertEqual(weight, self.best_weight)
def test_brute_force_with_cycle_graph(self):
algorithm = BruteForceTSPWithGraph(self.G)
algorithm.run(2)
# Hamiltonian cycle as a graph.
weight = sum(edge.weight for edge in algorithm.hamiltonian_cycle.iteredges())
self.assertEqual(weight, self.best_weight)
#algorithm.hamiltonian_cycle.show()
self.assertEqual(algorithm.hamiltonian_cycle.e(),
algorithm.hamiltonian_cycle.v())
for node in algorithm.hamiltonian_cycle.iternodes():
self.assertEqual(algorithm.hamiltonian_cycle.degree(node), 2)
def test_exceptions(self):
self.assertRaises(ValueError, BruteForceTSPWithEdges, Graph(5, True))
self.assertRaises(ValueError, BruteForceTSPWithGraph, Graph(5, True))
def tearDown(self): pass
def test_tree_three_nodes_radius_angle(self):
T = Graph(3)
for node in (0, 1, 2):
T.add_node(node)
for edge in (Edge(0, 1), Edge(1, 2)):
T.add_edge(edge)
algorithm = TreePlotRadiusAngle(T)
algorithm.run()
self.assertEqual(len(algorithm.point_dict), 3)
#print algorithm.point_dict
self.assertEqual(algorithm.point_dict,
{0: (1, Fraction(3, 2)),
1: (0, Fraction(3, 1)),
2: (1, Fraction(9, 2))})
class TestFloydWarshall(unittest.TestCase):
def setUp(self):
self.N = 5 # number of nodes
self.G = Graph(self.N, directed=True)
self.nodes = range(self.N)
self.edges = [
Edge(0, 2, 6), Edge(0, 3, 3), Edge(1, 0, 3), Edge(2, 3, 2),
Edge(3, 1, 1), Edge(3, 2, 1), Edge(4, 1, 4), Edge(4, 3, 2)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_floydwarshall(self):
algorithm = FloydWarshall(self.G)
algorithm.run()
expected_distance = {
0: {0: 0, 1: 4, 2: 4, 3: 3, 4: float("inf")},
1: {0: 3, 1: 0, 2: 7, 3: 6, 4: float("inf")},
2: {0: 6, 1: 3, 2: 0, 3: 2, 4: float("inf")},
3: {0: 4, 1: 1, 2: 1, 3: 0, 4: float("inf")},
4: {0: 6, 1: 3, 2: 3, 3: 2, 4: 0}}
self.assertEqual(algorithm.distance, expected_distance)
def test_floydwarshall_paths(self):
algorithm = FloydWarshallPaths(self.G)
algorithm.run()
expected_distance = {
0: {0: 0, 1: 4, 2: 4, 3: 3, 4: float("inf")},
1: {0: 3, 1: 0, 2: 7, 3: 6, 4: float("inf")},
2: {0: 6, 1: 3, 2: 0, 3: 2, 4: float("inf")},
3: {0: 4, 1: 1, 2: 1, 3: 0, 4: float("inf")},
4: {0: 6, 1: 3, 2: 3, 3: 2, 4: 0}}
expected_parent = {
0: {0: None, 2: 3, 1: 3, 4: None, 3: 0},
1: {0: 1, 2: 3, 1: None, 4: None, 3: 0},
2: {0: 1, 2: None, 1: 3, 4: None, 3: 2},
3: {0: 1, 2: 3, 1: 3, 4: None, 3: None},
4: {0: 1, 2: 3, 1: 3, 4: None, 3: 4}}
self.assertEqual(algorithm.distance, expected_distance)
self.assertEqual(algorithm.parent, expected_parent)
self.assertEqual(algorithm.path(0, 1), [0, 3, 1])
def test_floydwarshall_negative_cycle(self):
self.G.add_edge(Edge(1, 3, -2))
algorithm = FloydWarshall(self.G)
self.assertRaises(ValueError, algorithm.run)
class TestNodeCover(unittest.TestCase):
def setUp(self):
self.N = 5
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [Edge(0, 1), Edge(0, 2), Edge(1, 2),
Edge(1, 3), Edge(1, 4)]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
node1 = Node(0, 1, "edge")
node2 = Node(0, 2, "edge")
node3 = Node(2, 1, "edge")
node4 = Node(1, 3, "edge")
node5 = Node(1, 4, "edge")
node6 = Node(0, 1, "series", node2, node3)
node7 = Node(0, 1, "parallel", node1, node6)
node8 = Node(0, 1, "jackknife", node7, node4)
node9 = Node(0, 1, "jackknife", node8, node5)
self.root = node9
def test_spgraph_node_cover(self):
algorithm = SPGraphNodeCover(self.G, self.root)
algorithm.run()
expected1 = set([0, 1])
expected2 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.node_cover, expected2)
# Testing cover.
for edge in self.G.iteredges():
self.assertTrue(edge.source in algorithm.node_cover
or edge.target in algorithm.node_cover)
def test_sptree_node_cover(self):
algorithm = SPTreeNodeCover(self.root)
algorithm.run()
expected1 = set([0, 1])
expected2 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.node_cover, expected2)
# Testing cover.
for edge in self.G.iteredges():
self.assertTrue(edge.source in algorithm.node_cover
or edge.target in algorithm.node_cover)
def tearDown(self): pass
