def test_invalid_missing(self):
test_data = [
['(A,(B,(H,(D,(J,(((G,E),(F,I,K,L)),C))))));'],
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data]
with self.assertRaisesRegex(ValueError, "not-an-option"):
robinson_foulds(trees, missing_tips="not-an-option")
def test_labels_too_short(self):
test_data = [
['(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));'],
['(A,(B,(D,((J,H),(((G,E),(F,I)),C)))));'],
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data]
with self.assertRaisesRegex(ValueError, 'number.*match'):
robinson_foulds(trees, labels=['A'])
def test_missing_all_tips(self):
test_data = [
['(A,(B,(H,(D,(J,(((G,E),(F,I,K,L)),C))))));'],
['(,(,((,),(((,),(,)),))));'],
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data]
with self.assertRaisesRegex(ValueError, "No tip names.*shared"):
robinson_foulds(trees)
def test_missing_single_tip(self):
test_data = [
['(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));'],
['((B,(D,((J,H),(((G,E),(F,I)),C)))));'],
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data]
with self.assertRaisesRegex(ValueError, "tips.*shared.*'A'"):
robinson_foulds(trees)
def test_single_tree_and_label(self):
trees = [skbio.TreeNode.read(['(A:0.2, B:1.5, C, (E, F));'])]
expected = skbio.DistanceMatrix([[0]], ids=['foo'])
result = robinson_foulds(trees, labels=['foo'])
self.assertEqual(result, expected)
def test_missing_intersect_all(self):
test_data = [
['(A,(B,(H,(J,(((G,E),(F,I)),C)))));'],
['(B,((J,H),(((G,E),(F,I)),C)));'],
['(B,(D,(H,(J,(((G,E),(F,I)),C)))));'],
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data]
expected = skbio.DistanceMatrix([[0, 2, 0], [2, 0, 2], [0, 2, 0]])
result = robinson_foulds(trees, labels=['0', '1', '2'],
missing_tips='intersect-all')
self.assertEqual(result, expected)
def test_expected(self):
# Using Felsenstein's test data set from here:
# http://evolution.genetics.washington.edu/phylip/doc/treedist.html
test_data_set_1 = [ # name from original source
['(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));'],
['(A,(B,(D,((J,H),(((G,E),(F,I)),C)))));'],
['(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));'],
['(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));'],
['(A,(B,(E,(G,((F,I),(((J,H),D),C))))));'],
['(A,(B,(E,((F,I),(G,((J,(H,D)),C))))));'],
['(A,(B,(E,((F,I),(G,(((J,H),D),C))))));'],
['(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));'],
['(A,(B,(E,((G,(F,I)),(((J,H),D),C)))));'],
['(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));'],
['(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));'],
['(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));']
]
trees = [skbio.TreeNode.read(nwk) for nwk in test_data_set_1]
expected = skbio.DistanceMatrix(
[
[0, 4, 2, 10, 10, 10, 10, 10, 10, 10, 2, 10],
[4, 0, 2, 10, 8, 10, 8, 10, 8, 10, 2, 10],
[2, 2, 0, 10, 10, 10, 10, 10, 10, 10, 0, 10],
[10, 10, 10, 0, 2, 2, 4, 2, 4, 0, 10, 2],
[10, 8, 10, 2, 0, 4, 2, 4, 2, 2, 10, 4],
[10, 10, 10, 2, 4, 0, 2, 2, 4, 2, 10, 2],
[10, 8, 10, 4, 2, 2, 0, 4, 2, 4, 10, 4],
[10, 10, 10, 2, 4, 2, 4, 0, 2, 2, 10, 0],
[10, 8, 10, 4, 2, 4, 2, 2, 0, 4, 10, 2],
[10, 10, 10, 0, 2, 2, 4, 2, 4, 0, 10, 2],
[2, 2, 0, 10, 10, 10, 10, 10, 10, 10, 0, 10],
[10, 10, 10, 2, 4, 2, 4, 0, 2, 2, 10, 0]
], ids=['tree_%d' % d for d in range(1, 13)])
result = robinson_foulds(trees)
self.assertEqual(result, expected)