def test_pedigree_sanity_checks(self):
individual = np.array([1, 2, 3, 4])
parents = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 2)
time = np.array([0, 0, 1, 1])
is_sample = np.array([1, 1, 0, 0])
with pytest.raises(NotImplementedError):
pedigrees.Pedigree(
individual=individual,
parents=parents,
time=time,
ploidy=1,
)
bad_parents = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 4)
with pytest.raises(ValueError):
pedigrees.Pedigree(
individual=individual,
parents=bad_parents,
time=time,
)
bad_individual = np.array([-1, 2, 3, 4])
with pytest.raises(ValueError):
pedigrees.Pedigree(
individual=bad_individual,
parents=parents,
time=time,
)
bad_times = np.array([1, 1, 1, 1])
ped = pedigrees.Pedigree(individual,
parents,
bad_times,
is_sample,
sex=None,
ploidy=2)
with pytest.raises(ValueError):
ped.check_times(
individual=ped.individual,
parents=ped.parents,
time=ped.time,
)
ped = pedigrees.Pedigree(individual, parents, time, sex=None, ploidy=2)
with pytest.raises(ValueError):
ped.set_samples()
with pytest.raises(ValueError):
ped.set_samples(num_samples=10)
with pytest.raises(ValueError):
ped.set_samples(num_samples=2, sample_IDs=[1, 2])
with pytest.raises(ValueError):
ped.get_times(individual=ped.individual)
def test_pedigree_samples(self):
individual = np.array([1, 2, 3, 4])
parents = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 2)
time = np.array([0, 0, 1, 1])
ped = pedigrees.Pedigree(individual, parents, time)
# This interface is pretty poor - what we want is for the
# samples argument to simulate to be interpreted as individual
# IDs. For now, let's just leave it as it is, though.
ped.set_samples(2)
ts = msprime.simulate(2, pedigree=ped, model="wf_ped")
assert ts.num_edges > 0
ped.set_samples(sample_IDs=[1, 2])
ts = msprime.simulate(2, pedigree=ped, model="wf_ped")
assert ts is not None
with pytest.raises(ValueError):
ped.set_samples(sample_IDs=[1, 1])
with pytest.raises(ValueError):
ped.set_samples(sample_IDs=[1, 3])
with pytest.raises(NotImplementedError):
ped.set_samples(sample_IDs=[1, 3], probands_only=False)
ped.set_samples(sample_IDs=[1, 2])
assert ped.get_proband_indices() == [0, 1]
def test_ped_wf_recombination(self):
inds = np.array([1, 2, 3, 4, 5, 6])
parent_indices = np.array([4, 5, 4, 5, 4, 5, 4, 5, -1, -1, -1,
-1]).reshape(-1, 2)
times = np.array([0, 0, 0, 0, 1, 1])
is_sample = np.array([1, 1, 1, 1, 0, 0])
t = max(times)
model = msprime.WrightFisherPedigree()
ped = pedigrees.Pedigree(inds,
parent_indices,
times,
is_sample,
sex=None,
ploidy=2)
ts = msprime.simulate(
sample_size=4,
pedigree=ped,
recombination_rate=0.1,
model=model,
demographic_events=[
msprime.SimulationModelChange(time=1, model="dtwf")
],
)
tree = ts.first()
assert tree.num_roots == 1
all_times = ts.tables.nodes.time
ped_times = all_times[np.logical_and(all_times > 0, all_times <= t)]
assert ped_times.shape[0] > 0
assert np.all(ped_times == np.floor(ped_times))
wf_times = all_times[all_times > t]
assert wf_times.shape[0] > 0
def test_pedigree_unsupported_events(self):
inds = np.array([1, 2, 3, 4, 5, 6])
parent_indices = np.array([4, 5, 4, 5, 4, 5, 4, 5, -1, -1, -1,
-1]).reshape(-1, 2)
times = np.array([0, 0, 0, 0, 1, 1])
is_sample = np.array([1, 1, 1, 1, 0, 0])
t = max(times)
ped = pedigrees.Pedigree(inds,
parent_indices,
times,
is_sample,
sex=None,
ploidy=2)
bad_model_change = msprime.SimulationModelChange(
0.5, msprime.DiscreteTimeWrightFisher())
with pytest.raises(RuntimeError, match="not support interruption"):
msprime.simulate(
4,
pedigree=ped,
demographic_events=[bad_model_change],
model="wf_ped",
)
bad_demographic_event = msprime.PopulationParametersChange(
t, initial_size=2)
with pytest.raises(_msprime.LibraryError):
msprime.simulate(
4,
pedigree=ped,
demographic_events=[bad_demographic_event],
model="wf_ped",
)
def test_wf_ped(self):
inds = np.array([1, 2, 3, 4])
parent_indices = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 2)
times = np.array([0, 0, 1, 1])
is_sample = np.array([1, 1, 0, 0])
model = msprime.WrightFisherPedigree()
ped = pedigrees.Pedigree(inds,
parent_indices,
times,
is_sample,
sex=None,
ploidy=2)
ts = msprime.simulate(2, pedigree=ped, model=model)
assert ts is not None
def test_pedigree_replicates(self):
individual = np.array([1, 2, 3, 4])
parents = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 2)
time = np.array([0, 0, 1, 1])
is_sample = np.array([1, 1, 0, 0])
model = msprime.WrightFisherPedigree()
ped = pedigrees.Pedigree(individual,
parents,
time,
is_sample,
sex=None,
ploidy=2)
replicates = msprime.simulate(2,
pedigree=ped,
model=model,
recombination_rate=1,
num_replicates=100)
for ts in replicates:
assert ts is not None
def test_pedigree(self):
with tempfile.TemporaryDirectory() as tmpdir:
ped_path = pathlib.Path(tmpdir) / "tmp.ped"
individual = np.array([1, 2, 3, 4], dtype=int)
parents = np.array([2, 3, 2, 3, -1, -1, -1, -1],
dtype=int).reshape(-1, 2)
time = np.array([0, 0, 1, 1])
is_sample = np.array([1, 1, 0, 0], dtype=int)
ped = pedigrees.Pedigree(individual,
parents,
time,
is_sample,
sex=None,
ploidy=2)
ped.save_txt(ped_path)
ts = self.run_script(
f"2 --pedigree-file {ped_path} --model=wf_ped")
for tree in ts.trees():
assert tree.num_roots > 1
assert ts.num_individuals == len(individual)
assert ts.num_samples == 4
def test_simple_case(self):
# Simple test to check that the current code is still roughly working.
# Should be replace by better tests.
individual = np.array([1, 2, 3, 4])
parents = np.array([-1, -1, -1, -1, 0, 1, 1, 0]).reshape(-1, 2)
time = np.array([1, 1, 0, 0])
is_sample = np.array([0, 0, 1, 1])
model = msprime.WrightFisherPedigree()
ped = pedigrees.Pedigree(individual,
parents,
time,
is_sample,
sex=None,
ploidy=2)
ts = msprime.simulate(2,
pedigree=ped,
model=model,
recombination_rate=1)
table = ts.tables.individuals
assert np.all(table[0].parents == [-1, -1])
assert np.all(table[1].parents == [-1, -1])
def test_pedigree_read_write(self):
individual = np.array([1, 2, 3, 4])
parents = np.array([2, 3, 2, 3, -1, -1, -1, -1]).reshape(-1, 2)
time = np.array([0, 0, 1, 1])
is_sample = np.array([1, 1, 0, 0])
ped = pedigrees.Pedigree(individual,
parents,
time,
is_sample,
sex=None,
ploidy=2)
ped.save_txt(self.temp_pedigree_text_file)
with pytest.raises(NotImplementedError):
pedigrees.Pedigree.read_txt(
self.temp_pedigree_text_file,
sex_col=4,
)
# FIXME
# The compute_times should be done automatically in this case .
# ped_from_txt = pedigrees.Pedigree.read_txt(
# self.temp_pedigree_text_file, time_col=None
# )
# ts = msprime.simulate(2, pedigree=ped_from_txt, model="wf_ped")
# self.assertTrue(ts is not None)
# ped_from_txt = pedigrees.Pedigree.read_txt(
# self.temp_pedigree_text_file, time_col=3
# )
# ts = msprime.simulate(2, pedigree=ped_from_txt, model="wf_ped")
# self.assertTrue(ts is not None)
ped.save_npy(self.temp_pedigree_array_file)
ped_from_npy = pedigrees.Pedigree.read_npy(
self.temp_pedigree_array_file)
# TODO compre this to the file above.
assert isinstance(ped_from_npy, pedigrees.Pedigree)
def test_pedigree(self):
inds = np.array([1, 2, 3, 4, 5, 6])
parent_indices = np.array([4, 5, 4, 5, 4, 5, 4, 5, -1, -1, -1,
-1]).reshape(-1, 2)
times = np.array([0, 0, 0, 0, 1, 1])
is_sample = np.array([1, 1, 1, 1, 0, 0])
t = max(times)
model = msprime.WrightFisherPedigree()
ped = pedigrees.Pedigree(inds,
parent_indices,
times,
is_sample,
sex=None,
ploidy=2)
ts = msprime.simulate(
sample_size=4,
pedigree=ped,
demographic_events=[
msprime.SimulationModelChange(
t, msprime.DiscreteTimeWrightFisher())
],
model=model,
)
self.verify(ts)
