def test_annotate_individuals(self):
for ts in self.get_msprime_examples():
slim_ts = pyslim.annotate_defaults(ts,
model_type="nonWF",
slim_generation=1)
tables = slim_ts.tables
metadata = list(pyslim.extract_individual_metadata(tables))
self.assertEqual(len(metadata), slim_ts.num_individuals)
sexes = [
random.choice([
pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE
]) for _ in metadata
]
for j in range(len(metadata)):
metadata[j].sex = sexes[j]
pyslim.annotate_individual_metadata(tables, metadata)
new_ts = pyslim.load_tables(tables)
for j, ind in enumerate(new_ts.individuals()):
md = ind.metadata
self.assertEqual(md.sex, sexes[j])
# try loading this into SLiM
loaded_ts = self.run_msprime_restart(new_ts, sex="A")
self.verify_annotated_tables(new_ts, slim_ts)
self.verify_annotated_trees(new_ts, slim_ts)
self.verify_haplotype_equality(new_ts, slim_ts)
def test_annotate_individuals(self):
for ts in self.get_slim_examples():
tables = ts.tables
new_tables = ts.tables
metadata = []
for md in tskit.unpack_bytes(tables.individuals.metadata,
tables.individuals.metadata_offset):
dm = pyslim.decode_individual(md)
edm = pyslim.encode_individual(dm)
self.assertEqual(md, edm)
metadata.append(dm)
pyslim.annotate_individual_metadata(new_tables, metadata)
self.assertEqual(tables, new_tables)
def test_annotate_individuals(self):
for ts in get_msprime_examples():
slim_ts = pyslim.annotate_defaults(ts, model_type="nonWF", slim_generation=1)
tables = slim_ts.tables
metadata = list(pyslim.extract_individual_metadata(tables))
self.assertEqual(len(metadata), slim_ts.num_individuals)
sexes = [random.choice([pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE])
for _ in metadata]
for j in range(len(metadata)):
metadata[j].sex = sexes[j]
pyslim.annotate_individual_metadata(tables, metadata)
new_ts = pyslim.load_tables(tables)
for j, ind in enumerate(new_ts.individuals()):
md = pyslim.decode_individual(ind.metadata)
self.assertEqual(md.sex, sexes[j])
def test_annotate_individuals(self):
for ts in self.get_slim_examples():
tables = ts.tables
new_tables = ts.tables
metadata = []
for md in tskit.unpack_bytes(tables.individuals.metadata,
tables.individuals.metadata_offset):
with self.assertWarns(DeprecationWarning):
dm = pyslim.decode_individual(md)
with self.assertWarns(DeprecationWarning):
edm = pyslim.encode_individual(dm)
self.assertEqual(md, edm)
metadata.append(dm)
with self.assertWarns(DeprecationWarning):
pyslim.annotate_individual_metadata(new_tables, metadata)
self.assertTableCollectionsEqual(tables, new_tables)
def test_annotate_XY(self):
for ts in self.get_msprime_examples():
for genome_type in ["X", "Y"]:
slim_ts = pyslim.annotate_defaults(ts,
model_type="nonWF",
slim_generation=1)
tables = slim_ts.tables
metadata = list(pyslim.extract_individual_metadata(tables))
self.assertEqual(len(metadata), slim_ts.num_individuals)
sexes = [
random.choice([
pyslim.INDIVIDUAL_TYPE_FEMALE,
pyslim.INDIVIDUAL_TYPE_MALE
]) for _ in metadata
]
for j in range(len(metadata)):
metadata[j].sex = sexes[j]
pyslim.annotate_individual_metadata(tables, metadata)
node_metadata = list(pyslim.extract_node_metadata(tables))
self.assertEqual(len(node_metadata), slim_ts.num_nodes)
for j in range(slim_ts.num_individuals):
nodes = slim_ts.individual(j).nodes
node_metadata[nodes[0]].genome_type = pyslim.GENOME_TYPE_X
node_metadata[nodes[0]].is_null = (genome_type != "X")
if sexes[j] == pyslim.INDIVIDUAL_TYPE_MALE:
node_metadata[
nodes[1]].genome_type = pyslim.GENOME_TYPE_Y
node_metadata[nodes[1]].is_null = (genome_type != "Y")
else:
node_metadata[
nodes[1]].genome_type = pyslim.GENOME_TYPE_X
node_metadata[nodes[1]].is_null = (genome_type != "X")
pyslim.annotate_node_metadata(tables, node_metadata)
new_ts = pyslim.load_tables(tables)
# try loading this into SLiM
loaded_ts = self.run_msprime_restart(new_ts, sex=genome_type)
self.verify_annotated_tables(new_ts, slim_ts)
self.verify_annotated_trees(new_ts, slim_ts)
self.verify_haplotype_equality(new_ts, slim_ts)
# Keywords: Python, nonWF, non-Wright-Fisher, tree-sequence recording, tree sequence recording
import msprime, pyslim, random
ts = msprime.simulate(sample_size=10000, Ne=5000, length=1e8,
mutation_rate=0.0, recombination_rate=1e-8)
tables = ts.dump_tables()
pyslim.annotate_defaults_tables(tables, model_type="nonWF", slim_generation=1)
individual_metadata = list(pyslim.extract_individual_metadata(tables))
for j in range(len(individual_metadata)):
individual_metadata[j].sex = random.choice([pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE])
individual_metadata[j].age = random.choice([0, 1, 2, 3, 4])
pyslim.annotate_individual_metadata(tables, individual_metadata)
slim_ts = pyslim.load_tables(tables)
slim_ts.dump("recipe_16.9.trees")
# Keywords: Python, nonWF, non-Wright-Fisher, tree-sequence recording, tree sequence recording
import msprime, pyslim, random
ts = msprime.simulate(sample_size=10000, Ne=5000, length=1e8,
mutation_rate=0.0, recombination_rate=1e-8)
tables = ts.dump_tables()
pyslim.annotate_defaults_tables(tables, model_type="nonWF", slim_generation=1)
individual_metadata = list(pyslim.extract_individual_metadata(tables))
for j in range(len(individual_metadata)):
individual_metadata[j].sex = random.choice([pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE])
individual_metadata[j].age = random.choice([0, 1, 2, 3, 4])
pyslim.annotate_individual_metadata(tables, individual_metadata)
slim_ts = pyslim.load_tables(tables)
slim_ts.dump("recipe_17.9.trees")
