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# ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
# ----------------------------------------------------------------------------
import io
from unittest import TestCase, main
import numpy as np
from skbio import TreeNode
from skbio.tree import majority_rule
from skbio.tree._majority_rule import (_walk_clades, _filter_clades,
_build_trees)
class MajorityRuleTests(TestCase):
def test_majority_rule(self):
trees = [
TreeNode.read(
io.StringIO("(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(D,((J,H),(((G,E),(F,I)),C)))));")),
TreeNode.read(
io.StringIO("(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,(G,((F,I),(((J,H),D),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,((F,I),(G,((J,(H,D)),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,((F,I),(G,(((J,H),D),C))))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));")),
TreeNode.read(
io.StringIO("(A,(B,(E,((G,(F,I)),(((J,H),D),C)))));"))]
exp = TreeNode.read(io.StringIO("(((E,(G,(F,I),(C,(D,J,H)))),B),A);"))
obs = majority_rule(trees)
self.assertEqual(exp.compare_subsets(obs[0]), 0.0)
self.assertEqual(len(obs), 1)
tree = obs[0]
exp_supports = sorted([9.0, 9.0, 9.0, 6.0, 6.0, 6.0])
obs_supports = sorted([n.support for n in tree.non_tips()])
self.assertEqual(obs_supports, exp_supports)
obs = majority_rule(trees, weights=np.ones(len(trees)) * 2)
self.assertEqual(exp.compare_subsets(obs[0]), 0.0)
self.assertEqual(len(obs), 1)
tree = obs[0]
exp_supports = sorted([18.0, 18.0, 12.0, 18.0, 12.0, 12.0])
obs_supports = sorted([n.support for n in tree.non_tips()])
with self.assertRaises(ValueError):
majority_rule(trees, weights=[1, 2])
def test_majority_rule_multiple_trees(self):
trees = [
TreeNode.read(io.StringIO("((a,b),(c,d),(e,f));")),
TreeNode.read(io.StringIO("(a,(c,d),b,(e,f));")),
TreeNode.read(io.StringIO("((c,d),(e,f),b);")),
TreeNode.read(io.StringIO("(a,(c,d),(e,f));"))]
trees = majority_rule(trees)
self.assertEqual(len(trees), 4)
for tree in trees:
self.assertIs(type(tree), TreeNode)
exp = set([
frozenset(['a']),
frozenset(['b']),
frozenset([None, 'c', 'd']),
frozenset([None, 'e', 'f'])])
obs = set([frozenset([n.name for n in t.traverse()]) for t in trees])
self.assertEqual(obs, exp)
def test_majority_rule_tree_node_class(self):
class TreeNodeSubclass(TreeNode):
pass
trees = [
TreeNode.read(io.StringIO("((a,b),(c,d),(e,f));")),
TreeNode.read(io.StringIO("(a,(c,d),b,(e,f));")),
TreeNode.read(io.StringIO("((c,d),(e,f),b);")),
TreeNode.read(io.StringIO("(a,(c,d),(e,f));"))]
trees = majority_rule(trees, tree_node_class=TreeNodeSubclass)
self.assertEqual(len(trees), 4)
for tree in trees:
self.assertIs(type(tree), TreeNodeSubclass)
exp = set([
frozenset(['a']),
frozenset(['b']),
frozenset([None, 'c', 'd']),
frozenset([None, 'e', 'f'])])
obs = set([frozenset([n.name for n in t.traverse()]) for t in trees])
self.assertEqual(obs, exp)
def test_walk_clades(self):
trees = [TreeNode.read(io.StringIO("((A,B),(D,E));")),
TreeNode.read(io.StringIO("((A,B),(D,(E,X)));"))]
exp_clades = [
(frozenset(['A']), 2.0),
(frozenset(['B']), 2.0),
(frozenset(['A', 'B']), 2.0),
(frozenset(['D', 'E']), 1.0),
(frozenset(['D', 'E', 'A', 'B']), 1.0),
(frozenset(['D']), 2.0),
(frozenset(['E']), 2.0),
(frozenset(['X']), 1.0),
(frozenset(['E', 'X']), 1.0),
(frozenset(['D', 'E', 'X']), 1.0),
(frozenset(['A', 'B', 'D', 'E', 'X']), 1.0)]
exp_lengths_nolength = {
frozenset(['A']): None,
frozenset(['B']): None,
frozenset(['A', 'B']): None,
frozenset(['D', 'E']): None,
frozenset(['D', 'E', 'A', 'B']): None,
frozenset(['D']): None,
frozenset(['E']): None,
frozenset(['X']): None,
frozenset(['E', 'X']): None,
frozenset(['D', 'E', 'X']): None,
frozenset(['A', 'B', 'D', 'E', 'X']): None}
exp_lengths = {
frozenset(['A']): 2.0,
frozenset(['B']): 2.0,
frozenset(['A', 'B']): 2.0,
frozenset(['D', 'E']): 1.0,
frozenset(['D', 'E', 'A', 'B']): 1.0,
frozenset(['D']): 2.0,
frozenset(['E']): 2.0,
frozenset(['X']): 1.0,
frozenset(['E', 'X']): 1.0,
frozenset(['D', 'E', 'X']): 1.0,
frozenset(['A', 'B', 'D', 'E', 'X']): 1.0}
obs_clades, obs_lengths = _walk_clades(trees, np.ones(len(trees)))
self.assertEqual(set(obs_clades), set(exp_clades))
self.assertEqual(obs_lengths, exp_lengths_nolength)
for t in trees:
for n in t.traverse(include_self=True):
n.length = 2.0
obs_clades, obs_lengths = _walk_clades(trees, np.ones(len(trees)))
self.assertEqual(set(obs_clades), set(exp_clades))
self.assertEqual(obs_lengths, exp_lengths)
def test_filter_clades(self):
clade_counts = [(frozenset(['A', 'B']), 8),
(frozenset(['A', 'C']), 7),
(frozenset(['A']), 6),
(frozenset(['B']), 5)]
obs = _filter_clades(clade_counts, 2)
exp = {frozenset(['A', 'B']): 8,
frozenset(['A']): 6,
frozenset(['B']): 5}
self.assertEqual(obs, exp)
clade_counts = [(frozenset(['A']), 8),
(frozenset(['B']), 7),
(frozenset(['C']), 7),
(frozenset(['A', 'B']), 6),
(frozenset(['A', 'B', 'C']), 5),
(frozenset(['D']), 2)]
obs = _filter_clades(clade_counts, 4)
exp = {frozenset(['A']): 8,
frozenset(['B']): 7,
frozenset(['C']): 7,
frozenset(['A', 'B']): 6,
frozenset(['A', 'B', 'C']): 5}
self.assertEqual(obs, exp)
def test_build_trees(self):
clade_counts = {frozenset(['A', 'B']): 6,
frozenset(['A']): 7,
frozenset(['B']): 8}
edge_lengths = {frozenset(['A', 'B']): 1,
frozenset(['A']): 2,
frozenset(['B']): 3}
tree = _build_trees(clade_counts, edge_lengths, 'foo', TreeNode)[0]
self.assertEqual(tree.foo, 6)
tree_foos = set([c.foo for c in tree.children])
tree_lens = set([c.length for c in tree.children])
self.assertEqual(tree_foos, set([7, 8]))
self.assertEqual(tree_lens, set([2, 3]))
if __name__ == '__main__':
main()
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