def clean_example(self):
tables = tskit.TableCollection(sequence_length=100)
tables.populations.add_row()
tables.populations.add_row()
tables.individuals.add_row()
tables.nodes.add_row(time=0, flags=tskit.NODE_IS_SAMPLE, population=1, individual=0)
tables.nodes.add_row(time=0, flags=tskit.NODE_IS_SAMPLE, population=1, individual=0)
pyslim.annotate_defaults_tables(tables, model_type='nonWF', slim_generation=1)
return tables
def test_inconsistent_nodes(self):
clean_tables = self.clean_example()
tables = clean_tables.copy()
tables.nodes.clear()
for j, n in enumerate(clean_tables.nodes):
tables.nodes.add_row(
time=n.time, flags=n.flags,
population=j,
individual=n.individual,
metadata=n.metadata)
with pytest.raises(ValueError):
pyslim.annotate_defaults_tables(tables, model_type='nonWF', slim_generation=1)
ts = tables.tree_sequence()
with pytest.raises(ValueError):
_ = pyslim.SlimTreeSequence(ts)
def test_dont_annotate_mutations(self, helper_functions):
# Test the option to not overwrite mutation annotations
ts = msprime.sim_ancestry(10)
ts = msprime.sim_mutations(ts, rate=5, random_seed=3)
assert ts.num_mutations > 0
tables = ts.dump_tables()
pre_mutations = tables.mutations.copy()
pyslim.annotate_defaults_tables(tables,
model_type="WF",
slim_generation=1,
annotate_mutations=False)
# this is necessary because b'' actually is decoded to
# an empty mutation_list by the schema
pre_mutations.metadata_schema = tables.mutations.metadata_schema
assert tables.mutations.equals(pre_mutations)
# Keywords: Python, nonWF, non-Wright-Fisher, tree-sequence recording, tree sequence recording
import msprime, pyslim, random
import numpy as np
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)
# add sexes and ages
individual_metadata = [ind.metadata for ind in tables.individuals]
for md in individual_metadata:
md["sex"] = random.choice(
[pyslim.INDIVIDUAL_TYPE_FEMALE, pyslim.INDIVIDUAL_TYPE_MALE])
md["age"] = random.choice([0, 1, 2, 3, 4])
ims = tables.individuals.metadata_schema
tables.individuals.packset_metadata(
[ims.validate_and_encode_row(md) for md in individual_metadata])
# add selected mutation
mut_ind_id = random.choice(range(tables.individuals.num_rows))
mut_node_id = random.choice(np.where(tables.nodes.individual == mut_ind_id)[0])
mut_node = tables.nodes[mut_node_id]
mut_metadata = {
# 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")
