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Merge pull request #2643 from Billyzhang1229/feature/rf_distance
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Add unweighted_rf_distance (symmetric_distance) function and tests
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benjeffery authored Sep 24, 2024
2 parents 8a958e9 + 3a11d75 commit 860a9c5
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215 changes: 215 additions & 0 deletions python/tests/test_distance_metrics.py
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# MIT License
#
# Copyright (c) 2023 Tskit Developers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
"""
Tests for tree distance metrics.
"""
import dendropy
import msprime
import pytest
from dendropy.calculate import treecompare

import tests
import tskit


class TestTreeSameSamples:
# Tree1
# 2.00┊ 6 ┊
# ┊ ┏━┻━┓ ┊
# 1.00┊ 4 5 ┊
# ┊ ┏┻┓ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 ┊
# 0 1
#
# Tree2
# 3.00┊ 6 ┊
# ┊ ┏━┻━┓ ┊
# 2.00┊ ┃ 5 ┊
# ┊ ┃ ┏━┻┓ ┊
# 1.00┊ ┃ ┃ 4 ┊
# ┊ ┃ ┃ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 ┊
# 0 1

@tests.cached_example
def tree(self):
return tskit.Tree.generate_balanced(4)

@tests.cached_example
def tree_other(self):
return tskit.Tree.generate_comb(4)

def test_rf_distance(self):
assert self.tree().rf_distance(self.tree_other()) == 2


class TestTreeDifferentSamples:
# Tree1
# 2.00┊ 6 ┊
# ┊ ┏━┻━┓ ┊
# 1.00┊ 4 5 ┊
# ┊ ┏┻┓ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 ┊
# 0 1
#
# Tree2
# 4.00┊ 8 ┊
# ┊ ┏━┻━┓ ┊
# 3.00┊ ┃ 7 ┊
# ┊ ┃ ┏━┻━┓ ┊
# 2.00┊ ┃ ┃ 6 ┊
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# 1.00┊ ┃ ┃ ┃ 5 ┊
# ┊ ┃ ┃ ┃ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 4 ┊
# 0 1

@tests.cached_example
def tree(self):
return tskit.Tree.generate_balanced(4)

@tests.cached_example
def tree_other(self):
return tskit.Tree.generate_comb(5)

def test_rf_distance(self):
assert self.tree().rf_distance(self.tree_other()) == 8


class TestTreeMultiRoots:
# Tree1
# 4.00┊ 15 ┊
# ┊ ┏━━━┻━━━┓ ┊
# 3.00┊ ┃ 14 ┊
# ┊ ┃ ┏━┻━┓ ┊
# 2.00┊ 12 ┃ 13 ┊
# ┊ ┏━┻━┓ ┃ ┏┻┓ ┊
# 1.00┊ 9 10 ┃ ┃ 11 ┊
# ┊ ┏┻┓ ┏┻┓ ┏┻┓ ┃ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 4 5 6 7 8 ┊
# 0 1
#
# Tree2
# 3.00┊ 15 ┊
# ┊ ┏━━┻━┓ ┊
# 2.00┊ 11 ┃ 14 ┊
# ┊ ┏━┻━┓ ┃ ┏━┻┓ ┊
# 1.00┊ 9 10 12 ┃ 13 ┊
# ┊ ┏┻┓ ┏┻┓ ┏┻┓ ┃ ┏┻┓ ┊
# 0.00┊ 0 1 2 3 4 5 6 7 8 ┊
# 0 1

@tests.cached_example
def tree(self):
return tskit.Tree.generate_balanced(9)

@tests.cached_example
def tree_other(self):
tables = tskit.Tree.generate_balanced(9, arity=2).tree_sequence.dump_tables()
edges = tables.edges.copy()
tables.edges.clear()
for edge in edges:
if edge.parent != 16:
tables.edges.append(edge)
return tables.tree_sequence().first()

def test_rf_distance(self):
with pytest.raises(ValueError):
self.tree().rf_distance(self.tree_other())


class TestEmpty:
@tests.cached_example
def tree(self):
tables = tskit.TableCollection(1)
return tables.tree_sequence().first()

@tests.cached_example
def tree_other(self):
tables = tskit.TableCollection(1)
return tables.tree_sequence().first()

def test_rf_distance(self):
with pytest.raises(ValueError):
self.tree().rf_distance(self.tree_other())


class TestTreeInNullState:
@tests.cached_example
def tsk_tree1(self):
tree = tskit.Tree.generate_comb(5)
tree.clear()
return tree

@tests.cached_example
def tree_other(self):
tree = tskit.Tree.generate_comb(5)
tree.clear()
return tree

def test_rf_distance(self):
with pytest.raises(ValueError):
self.tsk_tree1().rf_distance(self.tree_other())


class TestAllRootsN5:
@tests.cached_example
def tree(self):
tables = tskit.TableCollection(1)
for _ in range(5):
tables.nodes.add_row(flags=tskit.NODE_IS_SAMPLE, time=0)
return tables.tree_sequence().first()

def test_rf_distance(self):
with pytest.raises(ValueError):
self.tree().rf_distance(self.tree())


class TestWithPackages:
def to_dendropy(self, newick_data, tns):
return dendropy.Tree.get(
data=newick_data,
schema="newick",
rooting="force-rooted",
taxon_namespace=tns,
)

def dendropy_rf_distance(self, tree1, tree2, weighted=False):
tns = dendropy.TaxonNamespace()
tree1 = self.to_dendropy(tree1.as_newick(), tns)
tree2 = self.to_dendropy(tree2.as_newick(), tns)
tree1.encode_bipartitions()
tree2.encode_bipartitions()
if weighted:
return treecompare.weighted_robinson_foulds_distance(tree1, tree2)
else:
return treecompare.unweighted_robinson_foulds_distance(tree1, tree2)

@pytest.mark.parametrize("n", [2, 3, 5, 10, 20])
def test_rf_distance_against_dendropy(self, n):
trees = []
for seed in [42, 43]:
ts = msprime.sim_ancestry(n, ploidy=1, random_seed=seed)
trees.append(ts.first())
rf1 = trees[0].rf_distance(trees[1])
rf2 = self.dendropy_rf_distance(trees[0], trees[1])
assert rf1 == rf2
31 changes: 31 additions & 0 deletions python/tskit/trees.py
Original file line number Diff line number Diff line change
Expand Up @@ -2937,6 +2937,37 @@ def kc_distance(self, other, lambda_=0.0):
"""
return self._ll_tree.get_kc_distance(other._ll_tree, lambda_)

def _get_sample_sets(self):
ret = {}
for u in self.nodes(order="postorder"):
u_sample_set = set()
if self.is_sample(u):
u_sample_set.add(u)
for v in self.children(u):
u_sample_set |= ret[v]
ret[u] = frozenset(u_sample_set)
return ret

def rf_distance(self, other):
"""
Returns the Robinson-Foulds distance between the specified pair of trees.
.. seealso::
See `Robinson & Foulds (1981)
<https://doi.org/10.1016/0025-5564(81)90043-2>`_ for more details.
:param Tree other: The other tree to compare to.
:return: The computed Robinson-Foulds distance between this tree and other.
:rtype: int
"""
if self.num_roots != 1 or other.num_roots != 1:
raise ValueError("Trees must have a single root")

s1 = set(self._get_sample_sets().values())
s2 = set(other._get_sample_sets().values())

return len(s1.symmetric_difference(s2))

def path_length(self, u, v):
"""
Returns the path length between two nodes
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