def test_two(self):
text = "((1, 2), 3);"
enewick_graph = enewick_to_digraph(text)
clusters = [(1, 2), (3,)]
gold = construct(clusters)
GM = GraphMatcher(enewick_graph, gold)
self.assertTrue(GM.is_isomorphic())
def test_one(self):
text = "(1, 2);"
enewick_graph = enewick_to_digraph(text)
clusters = [('1', '2'),]
gold = construct(clusters)
GM = GraphMatcher(enewick_graph, gold)
self.assertTrue(GM.is_isomorphic())
def test_five(self):
text = "((1, (2)h#H1)x,(h#H1,3)y)r;"
clusters = [(1, 2), (2, 3)]
enewick_graph = enewick_to_digraph(text)
self.assertEqual(len(enewick_graph.nodes()), 7)
gold = construct(clusters)
GM = GraphMatcher(enewick_graph, gold)
self.assertTrue(GM.is_isomorphic())
def test_three(self):
text = "((4, 5#1)2, (#1, 6)3);"
enewick_graph = enewick_to_digraph(text)
self.assertEqual(len(enewick_graph.nodes()), 6)
enewick_graph = calc_hybrid(enewick_graph)
leafs = get_leaf_nodes(enewick_graph)
gold_leafs = ['1', '4', '6', ]
self.assertItemsEqual(leafs, gold_leafs)
clusters = ["1,2", "2,3"]
gold = construct(clusters)
g = enewick_to_phylonet(text)
GM = GraphMatcher(g, gold)
self.assertTrue(GM.is_isomorphic())
def test_two(self):
text = "((4, 5#1)2, (#1, 6)3);"
enewick_graph = enewick_to_digraph(text)
self.assertEqual(len(enewick_graph.nodes()), 6)
enewick_phylo = enewick_to_phylonet(text)
gold_hard = "1,4 1,4,6 1,6 4 6".split()
hard = cluster_hard(enewick_graph)
self.assertItemsEqual(hard, gold_hard)
self.assertEqual(len(enewick_phylo.nodes()), 7)
clusters = [(1, 2), (2, 3),]
gold = construct(clusters)
GM = GraphMatcher(enewick_phylo, gold)
self.assertTrue(GM.is_isomorphic())
def test_one(self):
text = "((MOUSE,(HUMAN,RAT)),CIOIN);"
enewick_graph = enewick_to_digraph(text)
self.assertEqual(len(enewick_graph.nodes()), 7)
enewick_graph = enewick_to_phylonet(text)
self.assertEqual(len(enewick_graph.nodes()), 7)
clusters = [(1, 2, 3), (2, 3), (4,)]
gold = construct(clusters)
GM = GraphMatcher(enewick_graph, gold)
self.assertTrue(GM.is_isomorphic())
gold_hard = [
'CIOIN,HUMAN,MOUSE,RAT',
'CIOIN', 'HUMAN', 'MOUSE', 'RAT',
'HUMAN,MOUSE,RAT',
'HUMAN,RAT',
]
hard = cluster_hard(enewick_graph)
self.assertEqual(len(hard), 7)
self.assertItemsEqual(hard, gold_hard)
def hypergraphs_are_equivalent(graph1, graph2, isomorphy=True):
if graph1 is None or graph2 is None:
return None
graph1 = put_parent_node_first(graph1)
graph2 = put_parent_node_first(graph2)
if len(graph1) != len(graph2):
return None
# index_cache_1 = {}
# index_cache_2 = {}
if not isomorphy:
# node type must match as well as node ordering, nx is just needed to check that the edges also align
edge2nodes1 = graph1.node_ids_by_edge_id()
edge2nodes2 = graph2.node_ids_by_edge_id()
def other_node1(node_id, edge_id):
nodes = edge2nodes1[edge_id]
tmp = [n for n in nodes if n != node_id]
assert len(tmp) == 1, "This node is not connected to this edge!"
return tmp[0]
def other_node2(node_id, edge_id):
nodes = edge2nodes2[edge_id]
tmp = [n for n in nodes if n != node_id]
assert len(tmp) == 1, "This node is not connected to this edge!"
return tmp[0]
mapping = {
id1: id2
for id1, id2 in zip(graph1.node.keys(), graph2.node.keys())
}
for i, (node1_id, node1), (node2_id,
node2) in zip(range(len(graph1)),
graph1.node.items(),
graph2.node.items()):
if not (graph1.is_parent_node(node1)
== graph2.is_parent_node(node2)):
return None
elif str(node1) != str(node2) or len(node1.edges) != len(
node2.edges):
return None
else:
for edge1_id, edge2_id in zip(node1.edge_ids, node2.edge_ids):
edge1 = graph1.edges[edge1_id]
edge2 = graph2.edges[edge2_id]
if edge1.type != edge2.type or edge1.data != edge2.data:
return None
# now test that matching edges lead to matching nodes
candidate_node_id1 = other_node1(node1_id, edge1_id)
candidate_node_id2 = other_node2(node2_id, edge2_id)
if mapping[candidate_node_id1] != candidate_node_id2:
return None
return mapping
else:
def nodes_match(node1, node2):
# parent nodes must be aligned
if not graph1.is_parent_node(
node1['node']) == graph2.is_parent_node(node2['node']):
return False
# and for all nodes the content must match as well as the ordering
return str(node1['node']) == str(node2['node'])
def edges_match(edge1, edge2):
return edge1['data'].type == edge2['data'].type and edge1[
'data'].data == edge2['data'].data
from networkx.algorithms.isomorphism import GraphMatcher
graph1_nx = graph1.to_nx()
graph2_nx = graph2.to_nx()
GM = GraphMatcher(graph1_nx,
graph2_nx,
edge_match=edges_match,
node_match=nodes_match)
if GM.is_isomorphic():
# assert str(graph1) == str(graph2)
# for id1, id2
# test = {id1: id2 for id1, id2 in zip(graph1.node.keys(), graph2.node.keys())}
# for id1 in test:
# if test[id1] != GM.mapping[id1]:
# print("what?")
assert graph1.parent_node_id is None or GM.mapping[
graph1.parent_node_id] == graph2.parent_node_id
return GM.mapping
else:
return None
