def test_small_smc(self):
base_ts = get_smc_simulation(5, L=1, recombination_rate=10, seed=111)
assert base_ts.num_trees > 1
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(base_ts,
engine=engine)
self.verify_perfect_inference(ts, inferred_ts)
def test_small_smc_no_time_chunking(self):
base_ts = get_smc_simulation(10, L=1, recombination_rate=10, seed=113)
self.assertGreater(base_ts.num_trees, 1)
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(
base_ts, engine=engine, time_chunking=False)
self.verify_perfect_inference(ts, inferred_ts)
def test_small_smc_threads(self):
base_ts = get_smc_simulation(5, L=1, recombination_rate=10, seed=112)
self.assertGreater(base_ts.num_trees, 1)
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(
base_ts, engine=engine, num_threads=4)
self.verify_perfect_inference(ts, inferred_ts)
def test_small_use_ts(self):
base_ts = msprime.simulate(5, recombination_rate=10, random_seed=112)
self.assertGreater(base_ts.num_trees, 1)
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(
base_ts, use_ts=True, engine=engine)
self.verify_perfect_inference(ts, inferred_ts)
def test_sample_20_use_ts(self):
base_ts = msprime.simulate(20,
length=5,
recombination_rate=10,
random_seed=111)
self.assertGreater(base_ts.num_trees, 5)
ts, inferred_ts = tsinfer.run_perfect_inference(base_ts, use_ts=True)
self.verify_perfect_inference(ts, inferred_ts)
def test_sample_20_smc_path_compression(self):
base_ts = get_smc_simulation(20, L=5, recombination_rate=10, seed=111)
self.assertGreater(base_ts.num_trees, 5)
ts, inferred_ts = tsinfer.run_perfect_inference(base_ts, path_compression=True)
# We can't just compare tables when doing path compression because
# we'll find different ways of expressing the same trees.
breakpoints, distances = tsinfer.compare(ts, inferred_ts)
self.assertTrue(np.all(distances == 0))
def test_small_use_ts_path_compression(self):
base_ts = msprime.simulate(5, recombination_rate=10, random_seed=112)
self.assertGreater(base_ts.num_trees, 1)
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(
base_ts, use_ts=True, path_compression=True, engine=engine)
# We can't just compare tables when doing path compression because
# we'll find different ways of expressing the same trees.
breakpoints, distances = tsinfer.compare(ts, inferred_ts)
self.assertTrue(np.all(distances == 0))
def test_small_smc_path_compression(self):
base_ts = get_smc_simulation(5, L=1, recombination_rate=10, seed=111)
assert base_ts.num_trees > 1
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(
base_ts, engine=engine, path_compression=True)
# We can't just compare tables when doing path compression because
# we'll find different ways of expressing the same trees.
breakpoints, distances = tsinfer.compare(ts, inferred_ts)
assert np.all(distances == 0)
def test_single_tree_defaults(self):
base_ts = msprime.simulate(5, random_seed=234)
for engine in [tsinfer.PY_ENGINE, tsinfer.C_ENGINE]:
ts, inferred_ts = tsinfer.run_perfect_inference(base_ts,
engine=engine)
self.verify_perfect_inference(ts, inferred_ts)
