def test_trajectory_no_recomb(self):
trajectory = msprime.simulate_trajectory(start_frequency=0.1,
end_frequency=0.8,
alpha=0.1,
time_slice=0.01,
random_seed=32)
model = msprime.SingleSweep(position=0.5, trajectory=trajectory)
msprime.simulate(10, model=model, num_labels=2)
def test_incorrect_num_labels(self):
trajectory = msprime.SweepTrajectory([0, 0.1], [0.1, 0.11])
model = msprime.SingleSweep(position=0.5, trajectory=trajectory)
for num_labels in [1, 3, 10]:
with self.assertRaises(_msprime.LibraryError):
msprime.simulate(10,
recombination_rate=1,
model=model,
num_labels=num_labels)
def test_simple_example(self):
trajectory = msprime.SweepTrajectory([0, 0.1, 0.2, 0.3],
[0.95, 0.85, 0.75, 0.5])
recomb_map = msprime.RecombinationMap.uniform_map(length=100,
num_loci=100,
rate=0.1)
model = msprime.SingleSweep(population_size=100,
position=5,
trajectory=trajectory)
ts = msprime.simulate(sample_size=10,
recombination_map=recomb_map,
model=model,
num_labels=2,
demographic_events=[
msprime.SimulationModelChange(
0.3, msprime.StandardCoalescent(100))
])
for tree in ts.trees():
self.assertEqual(tree.num_roots, 1)
def test_simple_recomb(self):
trajectory = msprime.SweepTrajectory([0, 0.1], [0.1, 0.11])
model = msprime.SingleSweep(position=0.5, trajectory=trajectory)
msprime.simulate(10, recombination_rate=1, model=model, num_labels=2)