def test_weighted_trees_satisyfing_cutoff(self):
"""build consensus tree from those satisfying cutoff"""
sct = LogLikelihoodScoredTreeCollection(self.scored_trees)
cts = sct.getWeightedTrees(cutoff=0.8)
for weight, tree in cts:
self.assertTrue(tree.sameTopology(Tree('((a,b),c,d);')))
ct = cts.getConsensusTree()
self.assertTrue(ct.sameTopology(Tree("((a,b),c,d);")))
def test_weighted_trees_satisyfing_cutoff(self):
"""build consensus tree from those satisfying cutoff"""
sct = LogLikelihoodScoredTreeCollection(self.scored_trees)
cts = sct.getWeightedTrees(cutoff=0.8)
for weight, tree in cts:
self.assertTrue(tree.sameTopology(Tree('((a,b),c,d);')))
ct = cts.getConsensusTree()
self.assertTrue(ct.sameTopology(Tree("((a,b),c,d);")))
def test_weighted_trees_satisyfing_cutoff(self):
"""build consensus tree from those satisfying cutoff"""
sct = LogLikelihoodScoredTreeCollection(self.scored_trees)
cts = sct.getWeightedTrees(cutoff=0.8)
expected_trees = [Tree(t) for t in "((a,b),(c,d));", "((a,b),(c,d));",
"((a,b),c,d);"]
for i in range(len(cts)):
cts[i][1].sameTopology(expected_trees[i])
ct = cts.getConsensusTree()
self.assertTrue(ct.sameTopology(Tree("((a,b),(c,d));")))
def test_weighted_trees_satisyfing_cutoff(self):
"""build consensus tree from those satisfying cutoff"""
sct = LogLikelihoodScoredTreeCollection(self.scored_trees)
cts = sct.getWeightedTrees(cutoff=0.8)
expected_trees = [Tree(t) for t in "((a,b),(c,d));", "((a,b),(c,d));",
"((a,b),c,d);"]
for i in range(len(cts)):
cts[i][1].sameTopology(expected_trees[i])
ct = cts.getConsensusTree()
self.assertTrue(ct.sameTopology(Tree("((a,b),(c,d));")))