Exemple #1
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 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)
Exemple #2
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 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])
Exemple #3
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 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)
Exemple #4
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 def verify_defaults(self, ts):
     '''
     Verify the default values have been entered into metadata.
     '''
     mut_md = pyslim.extract_mutation_metadata(ts.tables)
     for md in mut_md:
         self.assertEqual(md.mutation_type, 1)
         self.assertEqual(md.selection_coeff, 0.0)
         self.assertEqual(md.population, tskit.NULL)
         self.assertEqual(md.slim_time, 0)
     node_md = pyslim.extract_node_metadata(ts.tables)
     for md, node in zip(node_md, ts.nodes()):
         if not node.is_sample():
             self.assertEqual(md, None)
         else:
             self.assertEqual(md.is_null, False)
             self.assertEqual(md.genome_type, pyslim.GENOME_TYPE_AUTOSOME)
     for ind in ts.individuals():
         self.assertArrayEqual(ind.location, [0, 0, 0])
         self.assertEqual(ind.flags, pyslim.INDIVIDUAL_ALIVE)
     ind_md = pyslim.extract_individual_metadata(ts.tables)
     for md in ind_md:
         self.assertEqual(md.sex, pyslim.INDIVIDUAL_TYPE_HERMAPHRODITE)
         self.assertEqual(md.flags, 0)
     pop_md = pyslim.extract_population_metadata(ts.tables)
     for md in pop_md:
         self.assertEqual(md.selfing_fraction, 0.0)
         self.assertEqual(md.female_cloning_fraction, 0.0)
         self.assertEqual(md.male_cloning_fraction, 0.0)
         self.assertEqual(md.sex_ratio, 0.5)
         self.assertEqual(md.bounds_x0, 0.0)
         self.assertEqual(md.bounds_x1, 0.0)
         self.assertEqual(md.bounds_y0, 0.0)
         self.assertEqual(md.bounds_y1, 0.0)
         self.assertEqual(md.bounds_z0, 0.0)
         self.assertEqual(md.bounds_z1, 0.0)
         self.assertEqual(len(md.migration_records), 0)
Exemple #5
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# 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")