def tree_sequence(self, strategy):
"""Create a sequence of mixed trees with associated maps. Depending on the given strategy,
the algorithm 2 or 4 will be computed. The given tree `self.mixed_tree` must be *consistent*
and have only *undirected* edges.
Args:
strategy: a list of the functions needed, depending on which algorithm we want to execute (2 or 4)
Returns:
seq (list): a sequence ((T_0, S_0), ..., (T_i, S_i)...) of mixed trees and there maps
"""
strategy.algo = self
current_tree = self.mixed_tree
current_map = s_0(current_tree)
self.maps = current_map
seq = [(current_tree, current_map)]
while len(current_tree) > 1:
current_tree, current_map = self.step(strategy)
seq.append((current_tree, current_map))
return seq
def test_tree_sequence(self):
g = BinaryMixedTree(MixedGraph({0, 1}, [(0, 1)]))
g2 = BinaryMixedTree(MixedGraph())
g2.add(frozenset([0, 1]))
expected = [
(g, s_0(g)),
(g2, {
frozenset([1]): {frozenset([1])},
frozenset([0]): {frozenset([0])},
frozenset([0, 1]): {frozenset([0]), frozenset([1])}
}
)
]
value = BasicTreeConstruction(g, s_0(g)).tree_sequence(StratAlgo1())
self.assertEqual(value, expected)
def test_A_set(self):
t = BinaryMixedTree(MixedGraph({1, 2, 3}))
t.add(frozenset([1, 3]))
t.add_directed(frozenset([1]), frozenset([2]))
t.add_directed(frozenset([1]), frozenset([1, 3]))
s = s_0(t)
s[frozenset([1, 3])] = {frozenset([3]), frozenset([1])}
delta_plus = t(frozenset([1]), undirected=False, begin=True, end=False, closed=False)
A = line_14(delta_plus, s, frozenset([1]))
self.assertEqual(A, {frozenset([2]), frozenset([3])})
def test_one_edge_available(self):
h = HyperGraph(frozenset([frozenset([1]), frozenset([2]), frozenset([3])]),
frozenset([frozenset([frozenset([1])]),
frozenset([frozenset([2])]),
frozenset([frozenset([3])]),
frozenset([frozenset([1]), frozenset([2])]),
frozenset([frozenset([2]), frozenset([3])]),
frozenset([frozenset([i + 1]) for i in range(3)])
]))
t = BinaryMixedTree(MixedGraph({1, 2, 3}, [(1, 3)]))
t.add_directed(frozenset([1]), frozenset([2]))
self.assertEqual(edge_choice_for_algo3(BasicTreeConstruction(t, s_0(t), h)),
frozenset([frozenset([1]), frozenset([3])]))
def test_one_undirected(self):
g = BinaryMixedTree(MixedGraph({0, 1, 2}, [(0, 1)]))
g.add_directed(frozenset([1]), frozenset([2]))
value_graph_2, value_map_2 = BasicTreeConstruction(g, s_0(g)).step(StratAlgo1())
expected_graph = BinaryMixedTree(MixedGraph({2}))
expected_graph.add(frozenset([0, 1]))
expected_graph.add_undirected(frozenset([2]), frozenset([0, 1]))
expected_map = {frozenset([0]): {frozenset([0])}, frozenset([1]): {frozenset([1])},
frozenset([2]): {frozenset([2])}, frozenset([0, 1]): {frozenset([0]), frozenset([1])}}
self.assertEqual(value_graph_2, expected_graph)
self.assertEqual(value_map_2, expected_map)
def test_empty_delta_z(self):
h = HyperGraph(frozenset([frozenset([1]), frozenset([2]), frozenset([3])]),
frozenset([frozenset([frozenset([1])]),
frozenset([frozenset([2])]),
frozenset([frozenset([3])]),
frozenset([frozenset([1]), frozenset([2])]),
frozenset([frozenset([2]), frozenset([3])]),
frozenset([frozenset([i + 1]) for i in range(3)])
]))
t = BinaryMixedTree(MixedGraph({1, 2, 3}))
t.add(frozenset([1, 3]))
t.add_directed(frozenset([1]), frozenset([2]))
self.assertEqual(
delta_z_subset_algo3(BasicTreeConstruction(t, s_0(t), h), set(), frozenset([1, 3]), frozenset([1])), set())
def test_line_16_2(self):
t = BinaryMixedTree(MixedGraph({1, 2, 3, 4, 5, 6}, [(3, 6)]))
t.add(frozenset([1, 3]))
t.add_directed(frozenset([1]), frozenset([2]))
t.add_directed(frozenset([3]), frozenset([4]))
t.add_directed(frozenset([1]), frozenset([1, 3]))
t.add_undirected(frozenset([1, 3]), frozenset([5]))
s = s_0(t)
s[frozenset([1, 3])] = {frozenset([1]), frozenset([3])}
delta_plus = t(frozenset([1]), undirected=False, begin=True, end=False, closed=False)
A = line_14(delta_plus, s, frozenset([1]))
dict_s = line_16(A, delta_plus, s)
self.assertEqual(dict_s, {frozenset([2]): frozenset([2]), frozenset([3]): frozenset([1, 3])})
def test_edge_choice(self):
g = HyperGraph(frozenset([frozenset([i]) for i in range(1, 7)]))
for i in range(1, 7):
g.add_edge(frozenset([frozenset([i])]))
g.add_edge(frozenset([frozenset([i]) for i in range(1, 7)]))
g.add_edge(frozenset([frozenset([1]), frozenset([2])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([1]), frozenset([2]), frozenset([3]), frozenset([4]), frozenset([5])]))
t = BinaryMixedTree(MixedGraph({1, 2, 3, 4, 5, 6}, [(1, 3), (3, 6), (1, 5)]))
t.add_directed(frozenset([1]), frozenset([2]))
t.add_directed(frozenset([3]), frozenset([4]))
self.assertEqual(edges_in_homogeneous_subset(t, t.homogeneous_subset()), list(t.edges[0]))
value = edge_choice_for_algo3(BasicTreeConstruction(t, s_0(t), g))
self.assertEqual(value, frozenset([frozenset([1]), frozenset([3])]))
def test_edge_choice_for_algo3(self):
h = HyperGraph(
frozenset([frozenset([1]), frozenset([2]), frozenset([3]), frozenset([4]), frozenset([5]), frozenset([6])]),
frozenset([frozenset([frozenset([1])]),
frozenset([frozenset([2])]),
frozenset([frozenset([3])]),
frozenset([frozenset([4])]),
frozenset([frozenset([5])]),
frozenset([frozenset([6])]),
frozenset([frozenset([4]), frozenset([5])]),
frozenset([frozenset([5]), frozenset([6])]),
frozenset([frozenset([1]), frozenset([2]), frozenset([3]), frozenset([4]), frozenset([5]),
frozenset([6])])]))
g = BinaryMixedTree(MixedGraph({1, 2, 3, 4, 5, 6}, [(1, 2), (2, 4), (4, 3), (4, 5), (5, 6)]))
map = s_0(g)
value = edge_choice_for_algo3(BasicTreeConstruction(g, map, h))
expected = frozenset({frozenset([4]), frozenset([5])})
self.assertEqual(list(g.edges[0]), edges_in_homogeneous_subset(g, g.homogeneous_subset()))
self.assertEqual(expected, value)
def test_delta_z(self):
g = HyperGraph(frozenset([frozenset([i]) for i in range(1, 7)]))
for i in range(1, 7):
g.add_edge(frozenset([frozenset([i])]))
g.add_edge(frozenset([frozenset([i]) for i in range(1, 7)]))
g.add_edge(frozenset([frozenset([1]), frozenset([2])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([1]), frozenset([2]), frozenset([3]), frozenset([4]), frozenset([5])]))
t = BinaryMixedTree(MixedGraph({1, 2, 3, 4, 5, 6}, [(3, 6), (1, 5)]))
s = s_0(t)
s[frozenset([1, 3])] = {frozenset([1]), frozenset([3])}
t.add(frozenset([1, 3]))
t.add_directed(frozenset([1]), frozenset([2]))
t.add_directed(frozenset([3]), frozenset([4]))
expected = {frozenset([5])}
value = delta_z_subset_algo3(BasicTreeConstruction(t, s, g), frozenset([frozenset([5])]),
frozenset([1, 3]), frozenset([1]))
self.assertEqual(expected, value)
def test_hypergraph_2(self):
g = HyperGraph(frozenset([frozenset([i]) for i in range(1, 7)]))
for i in range(1, 7):
g.add_edge(frozenset([frozenset([i])]))
g.add_edge(frozenset([frozenset([i]) for i in range(1, 7)]))
g.add_edge(frozenset([frozenset([1]), frozenset([2])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5])]))
g.add_edge(frozenset([frozenset([3]), frozenset([4]), frozenset([5]), frozenset([6])]))
g.add_edge(frozenset([frozenset([1]), frozenset([2]), frozenset([3]), frozenset([4]), frozenset([5])]))
t = BinaryMixedTree(MixedGraph({1, 2, 3, 4, 5, 6}, [(3, 6), (1, 5), (1, 3)]))
t.add_directed(frozenset([1]), frozenset([2]))
t.add_directed(frozenset([3]), frozenset([4]))
next_tree, next_map = BasicTreeConstruction(t, s_0(t), g).step(StratAlgo3())
self.assertEqual({frozenset([1]): {frozenset([1])},
frozenset([2]): {frozenset([2])},
frozenset([3]): {frozenset([3])},
frozenset([4]): {frozenset([4])},
frozenset([5]): {frozenset([5])},
frozenset([6]): {frozenset([6])},
frozenset([1, 3]): {frozenset([1]), frozenset([3])}
}, next_map)
expected_tree = BinaryMixedTree(MixedGraph({2, 5, 3, 4, 6}, [(3, 6)]))
expected_tree.add(frozenset([1, 3]))
expected_tree.add_undirected(frozenset([1, 3]), frozenset([5]))
expected_tree.add_undirected(frozenset([1, 3]), frozenset([2]))
expected_tree.add_directed(frozenset([3]), frozenset([1, 3]))
expected_tree.add_directed(frozenset([3]), frozenset([4]))
self.assertEqual(expected_tree, next_tree)
def test_hypergraph_1(self):
h = HyperGraph(frozenset([frozenset([1]), frozenset([2]), frozenset([3])]),
frozenset([frozenset([frozenset([1])]),
frozenset([frozenset([2])]),
frozenset([frozenset([3])]),
frozenset([frozenset([1]), frozenset([2])]),
frozenset([frozenset([2]), frozenset([3])]),
frozenset([frozenset([i + 1]) for i in range(3)])
]))
t = BinaryMixedTree(MixedGraph({1, 2, 3}, [(1, 3)]))
t.add_directed(frozenset([1]), frozenset([2]))
maps = s_0(t)
next_tree, next_map = BasicTreeConstruction(t, maps, h).step(StratAlgo3())
self.assertEqual(
{frozenset([1]): {frozenset([1])}, frozenset([2]): {frozenset([2])}, frozenset([3]): {frozenset([3])},
frozenset([1, 3]): {frozenset([1]), frozenset([3])}}, next_map)
expected_graph = BinaryMixedTree(MixedGraph({2}))
expected_graph.add(frozenset([1, 3]))
expected_graph.add_undirected(frozenset([2]), frozenset([1, 3]))
self.assertEqual(expected_graph, next_tree)