def test_tree_unweighted_normalized_pairwise_distance_query(self):
num_edges_on_tree = combinatorics.num_edges_on_tree(num_leaves=len(self.tree.taxon_namespace), is_rooted=True)
for taxon1 in self.tree.taxon_namespace:
for taxon2 in self.tree.taxon_namespace:
exp = self.reference_pdm_unweighted_table[taxon1.label, taxon2.label] / num_edges_on_tree
obs2 = self.pdm.path_edge_count(taxon1, taxon2, is_normalize_by_tree_size=True)
self.assertAlmostEqual(obs2, exp, 6)
obs3 = self.pdm.distance(
taxon1, taxon2, is_weighted_edge_distances=False, is_normalize_by_tree_size=True
)
self.assertAlmostEqual(obs3, exp, 6)
def test_tree_unweighted_normalized_pairwise_distance_collection(self):
# this test relies on populating the expected result list
# in the *same order* as the function it is testing
num_edges_on_tree = combinatorics.num_edges_on_tree(num_leaves=len(self.tree.taxon_namespace), is_rooted=True)
exp_list = []
for taxon1, taxon2 in self.pdm.distinct_taxon_pair_iter():
exp = self.reference_pdm_unweighted_table[taxon1.label, taxon2.label] / num_edges_on_tree
exp_list.append(exp)
obs = self.pdm.distances(is_weighted_edge_distances=False, is_normalize_by_tree_size=True)
self.assertEqual(len(obs), len(exp_list))
for obs, exp in zip(obs, exp_list):
self.assertAlmostEqual(obs, exp, 6)
self.assertAlmostEqual(
self.pdm.sum_of_distances(is_weighted_edge_distances=False, is_normalize_by_tree_size=True),
sum(exp_list),
6,
)
def test_tree_num_edges(self):
self.assertEqual(
self.pdm._num_edges,
combinatorics.num_edges_on_tree(num_leaves=len(self.tree.taxon_namespace), is_rooted=True),
)
