def testCanonicalizeByNumberOfTipsAheadOfName(self):
"""
In forming a canonical tree, child nodes must be sorted by number of
tips in preference to name.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='a',
children=[
TreeNode(),
TreeNode(),
TreeNode(),
]),
TreeNode(name='b',
children=[
TreeNode(),
]),
TreeNode(name='c',
children=[
TreeNode(),
TreeNode(),
]),
])
self.assertEqual(
['a', 'b', 'c'],
[child.name for child in njtree.tree.children])
self.assertEqual(
['b', 'c', 'a'],
[child.name for child in njtree.canonicalize().tree.children])
def testCountCladesEmptyTree(self):
"""
In a tree with no children, there are no clades.
"""
njtree = NJTree()
njtree.tree = TreeNode()
self.assertEqual(Counter(), njtree.countClades())
def testCanonicalizeByNameAheadOfNamesOfDescendants(self):
"""
In forming a canonical tree, child nodes must be sorted by name in
preference to the sorted names of all their descendants.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='b',
children=[
TreeNode(name='e'),
TreeNode(name='f'),
TreeNode(name='g'),
]),
TreeNode(name='c',
children=[
TreeNode(name='h'),
TreeNode(name='i'),
TreeNode(name='j'),
]),
TreeNode(name='a',
children=[
TreeNode(name='k'),
TreeNode(name='l'),
TreeNode(name='m'),
]),
])
self.assertEqual(
['b', 'c', 'a'],
[child.name for child in njtree.tree.children])
self.assertEqual(
['a', 'b', 'c'],
[child.name for child in njtree.canonicalize().tree.children])
def testCanonicalizeByTipSubset(self):
"""
In forming a canonical tree, child nodes must be sorted by the names of
the set of tips they lead to, if all else is equal.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(children=[
TreeNode(name='d'),
TreeNode(name='e'),
TreeNode(name='f'),
]),
TreeNode(children=[
TreeNode(name='g'),
TreeNode(name='h'),
TreeNode(name='i'),
]),
TreeNode(children=[
TreeNode(name='a'),
TreeNode(name='b'),
TreeNode(name='c'),
]),
])
self.assertEqual(
['d', 'e', 'f', 'g', 'h', 'i', 'a', 'b', 'c'],
[grandchild.name for child in njtree.tree.children
for grandchild in child.children])
self.assertEqual(
['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i'],
[grandchild.name for child in njtree.canonicalize().tree.children
for grandchild in child.children])
def testCanonicalizeByNumberOfTips(self):
"""
In forming a canonical tree, child nodes must be sorted by number
of tips (assuming child lengths are all equal).
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(children=[
TreeNode(),
TreeNode(),
TreeNode(),
]),
TreeNode(children=[
TreeNode(),
TreeNode(),
TreeNode(),
TreeNode(),
TreeNode(),
]),
TreeNode(children=[
TreeNode(),
TreeNode(),
]),
])
self.assertEqual(
[3, 5, 2],
[len(child.children) for child in njtree.tree.children])
self.assertEqual(
[2, 3, 5],
[len(child.children)
for child in njtree.canonicalize().tree.children])
def testCountCladesOneChild(self):
"""
In a tree with one child, there is one clade.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='a'),
])
self.assertEqual(
{
frozenset(['a']): 1,
},
njtree.countClades()
)
def testRootByOneNodeName(self):
"""
Rooting by one node name must work.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='c'),
TreeNode(name='d'),
TreeNode(name='b'),
TreeNode(name='a')])
self.assertEqual(
['c', 'd', 'b', 'a'],
[child.name for child in njtree.root(['a']).tree.children])
def testRootByInexistentNodeNameMustRaiseError(self):
"""
Rooting by an inexistent node name must raise an exception.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='c'),
TreeNode(name='d'),
TreeNode(name='b'),
TreeNode(name='a')])
error = 'Node f is not in self'
six.assertRaisesRegex(self, MissingNodeError, error, njtree.root,
['f'])
def testTreeSampleSortedCounts(self):
"""
The treeSample method returns a list of tuples, the second element of
which is a count. The counts must be sorted from highest to lowest.
"""
distance = [
[0, 1, 1, 1, 1],
[1, 0, 1, 1, 1],
[1, 1, 0, 1, 1],
[1, 1, 1, 0, 1],
[1, 1, 1, 1, 0],
]
labels = ['a', 'b', 'c', 'd', 'e']
njtree = NJTree.fromDistanceMatrix(labels, distance)
# This test is not 100% reliable because there is a tiny chance the
# treeSample method will repeatedly generate the same tree, even
# though we make 50 trees and pass a high (0.3) standard deviation.
# It is also possible that the counts come back sorted just by
# chance even if the treeSample method does not sort them (in which
# case the test will pass even though the treeSample code is wrong).
#
# To make these errors even more unlikely, I have put in an assert
# on the number of trees that come back and I do the test multiple
# times. If the assert fails it doesn't mean that treeSample is
# broken, but it's highly likely that it is! It's also extremely
# unlikely that the counts could be sorted correctly by chance on
# every run. So if the test passes it doesn't mean that treeSample
# isn't broken, but it's highly unlikely that it is! Phew.
for _ in range(10):
counts = [count for (tree, count) in njtree.treeSample(50, 0.3)]
self.assertTrue(len(counts) > 2)
self.assertEqual(sorted(counts, reverse=True), counts)
def testFromThreeSequences(self):
"""
If three sequences with no features are used to create an NJTree
instance, the instance must 1) have a distance matrix that is zero
on the diagonal and ones elsewhere, 2) save the labels, and 3) produce
a simple tree with three children.
"""
sequences = Reads()
sequences.add(AARead('id1', 'A'))
sequences.add(AARead('id2', 'A'))
sequences.add(AARead('id3', 'A'))
labels = ['x', 'y', 'z']
njtree = NJTree.fromSequences(labels, sequences,
landmarks=['AlphaHelix'])
self.assertTrue(np.array_equal(
[
[0, 1, 1],
[1, 0, 1],
[1, 1, 0],
],
njtree.distance))
self.assertIs(labels, njtree.labels)
self.assertEqual(['x:0.5;\n', 'y:0.5;\n', 'z:0.5;\n'],
sorted(str(child) for child in njtree.tree.children))
def testCanonicalizeByNodeLength(self):
"""
In forming a canonical tree, child nodes must be sorted by length.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(length=13),
TreeNode(length=11),
TreeNode(length=18),
TreeNode(length=14)])
self.assertEqual(
[13, 11, 18, 14],
[child.length for child in njtree.tree.children])
self.assertEqual(
[11, 13, 14, 18],
[child.length for child in njtree.canonicalize().tree.children])
def testRootByTwoTreeNodes(self):
"""
Rooting by two TreeNodes must work.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='c'),
TreeNode(name='d'),
TreeNode(name='b'),
TreeNode(name='a')])
node1 = njtree.tree.find('a')
node2 = njtree.tree.find('b')
self.assertEqual(
['c', 'd', 'b', 'a'],
[child.name for child in
njtree.root([node1, node2]).tree.children])
def testCanonicalizeByNodeName(self):
"""
In forming a canonical tree, child nodes must be sorted by name if node
lengths and number of tips are equal.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(name='c'),
TreeNode(name='d'),
TreeNode(name='b'),
TreeNode(name='a')])
self.assertEqual(
['c', 'd', 'b', 'a'],
[child.name for child in njtree.tree.children])
self.assertEqual(
['a', 'b', 'c', 'd'],
[child.name for child in njtree.canonicalize().tree.children])
def testNewTreeHasExpectedAttributes(self):
"""
A new NJTree instance must have the expected attributes.
"""
njtree = NJTree()
self.assertEqual(0, njtree.supportIterations)
self.assertIs(None, njtree.sequences)
self.assertIs(None, njtree.distance)
self.assertIs(None, njtree.tree)
self.assertIs(None, njtree.labels)
def testCountCladesTwoChildren(self):
"""
In a tree with two children, one of which has two children, there are
two clades.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(children=[
TreeNode(name='a'),
TreeNode(name='b'),
]),
TreeNode(name='c'),
])
self.assertEqual(
{
frozenset(['a', 'b']): 1,
frozenset(['a', 'b', 'c']): 1,
},
njtree.countClades()
)
def testWithNoSupportAllNodesHaveSupportOfZero(self):
"""
If three sequences with no features are used to create an NJTree
the child nodes in the resulting tree must all have support of 0.0.
"""
distance = [[0, 1, 1], [1, 0, 1], [1, 1, 0]]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
self.assertEqual(
[0.0, 0.0, 0.0],
[njtree.supportForNode(child) for child in njtree.tree.children])
def testRobinsonFoulds(self):
"""
The correct Robinson Foulds distance must be calculated.
"""
njtree1 = NJTree()
njtree2 = NJTree()
njtree1.tree = TreeNode.read(StringIO('((a,b),(c,d));'))
njtree2.tree = TreeNode.read(StringIO('(((a,b),c),d);'))
distance = njtree1.robinsonFoulds(njtree2)
self.assertEqual(2.0, distance)
def testCanonicalizeByLengthAheadOfNumberOfTips(self):
"""
In forming a canonical tree, child nodes must be sorted by length
in preference to number of tips.
"""
njtree = NJTree()
njtree.tree = TreeNode(children=[
TreeNode(
length=13,
children=[
TreeNode(),
TreeNode(),
TreeNode(),
],
),
TreeNode(
length=11,
children=[
TreeNode(),
TreeNode(),
TreeNode(),
TreeNode(),
],
),
TreeNode(
length=12,
children=[
TreeNode(),
TreeNode(),
],
),
])
self.assertEqual(
[13, 11, 12],
[child.length for child in njtree.tree.children])
self.assertEqual(
[11, 12, 13],
[child.length for child in njtree.canonicalize().tree.children])
def testTreeSampleZero(self):
"""
When treeSample is called with a zero argument, it should return an
empty list.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
self.assertEqual([], njtree.treeSample(0))
def testGenerateTreesZero(self):
"""
When generateTrees is called with a zero argument, it should return an
empty list.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
self.assertEqual([], list(njtree.generateTrees(0)))
def testRobinsonFouldsCompareAgainstItself(self):
"""
If a tree is compared against itself, the Robinson Foulds distance must
be 0.0.
"""
njtree1 = NJTree()
njtree2 = NJTree()
njtree1.tree = TreeNode.read(StringIO('((a,b),(c,d));'))
njtree2.tree = TreeNode.read(StringIO('((a,b),(c,d));'))
distance = njtree1.robinsonFoulds(njtree2)
self.assertEqual(0.0, distance)
def testRobinsonFouldsProportionTrueReversed(self):
"""
The correct Robinson Foulds distance must be calculated with
proportion=True, if the trees are passed in reverse order.
"""
njtree1 = NJTree()
njtree2 = NJTree()
njtree1.tree = TreeNode.read(StringIO('((a,b),(c,d));'))
njtree2.tree = TreeNode.read(StringIO('(((a,b),c),d);'))
distance = njtree2.robinsonFoulds(njtree1, proportion=True)
self.assertEqual(0.5, distance)
def testOnlyOneConsensusTreeWithZeroIterations(self):
"""
When consensusTrees is passed an iteration count of zero, only one
consensus tree must be returned.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
consensusTrees = njtree.consensusTrees(0)
self.assertEqual(1, len(consensusTrees))
def testAddSupportIncrementsSupportIterations(self):
"""
When support has been added to a tree, its supportIterations attribute
must be incremented correctly.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
njtree.addSupport(2)
self.assertEqual(2, njtree.supportIterations)
def testSupportForNodeIsOneAtRoot(self):
"""
When support has been added to a tree, the root node must have support
of 1.0. This is because all trees will have all tips under their root,
regardless of their topologies.
"""
distance = [
[0.0, 0.5, 0.4],
[0.5, 0.0, 0.1],
[0.4, 0.1, 0.0],
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
njtree.addSupport(10)
self.assertEqual(1.0, njtree.supportForNode(njtree.tree))
def testSupportForNodeWhenNoSuppportAdded(self):
"""
If no support has been added to a tree, supportForNode must return
zero for all nodes.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
self.assertEqual(0, njtree.supportForNode(njtree.tree))
self.assertEqual([0, 0, 0],
[njtree.supportForNode(child)
for child in njtree.tree.children])
def testTreeSampleReturnType(self):
"""
The treeSample method must return a list of tuples, each containing
an NJTree and a count.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
result = njtree.treeSample(10)
for tree, count in result:
self.assertTrue(isinstance(tree, NJTree))
self.assertTrue(isinstance(count, int))
def testGenerateTreesMultiple(self):
"""
When generateTrees is called with a non-zero argument, it should
return a list with the expected number of items, which must all
be instances of NJTree.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
result = list(njtree.generateTrees(5))
self.assertEqual(5, len(result))
self. assertTrue(all(isinstance(t, NJTree) for t in result))
def testConsensusTreeWithZeroIterationsHasSupportOneForAllChildren(self):
"""
When consensusTrees is passed an iteration count of zero, all children
in the consensus tree must have support of zero.
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
consensusTrees = njtree.consensusTrees(0)
self.assertEqual([0, 0, 0],
[njtree.supportForNode(child)
for child in consensusTrees[0].tree.children])
def testNewickWithNoSuppportAdded(self):
"""
If no support has been added to a tree, newick must return the expected
string (with no support values).
"""
distance = [
[0, 1, 1],
[1, 0, 1],
[1, 1, 0]
]
labels = ['x', 'y', 'z']
njtree = NJTree.fromDistanceMatrix(labels, distance)
# The order in the Newick string seems deterministic, and according
# to the skbio docs this is the case.
self.assertEqual('(y:0.500000,x:0.500000,z:0.500000);\n',
njtree.newick())
