def MutsFromTrees(Trees):
print('read trees')
ts = pyslim.load(Trees).simplify()
variants = []
# for variant in pyslim.extract_mutation_metadata(ts.tables):
# print(variant)
# return
for variant, mut, node in zip(ts.variants(),
pyslim.extract_mutation_metadata(ts.tables),
pyslim.extract_node_metadata(ts.tables)):
# print ()
# print (variant)
# print (mut)
# print (node)
freq = sum(variant.genotypes) / len(variant.genotypes)
# print (freq)
if freq >= 1: continue
if len(mut) > 1: pass
variants.append([variant.site.position, freq, mut[0].selection_coeff])
return variants
def test_reload_annotate(self):
"""
Test the ability of SLiM to load our files after annotation.
"""
for ts, basename in self.get_slim_restarts():
tables = ts.tables
metadata = list(pyslim.extract_mutation_metadata(tables))
has_nucleotides = (metadata[0][0].nucleotide >= 0)
if has_nucleotides:
nucs = [random.choice([0, 1, 2, 3]) for _ in metadata]
refseq = "".join(
random.choices(pyslim.NUCLEOTIDES,
k=int(ts.sequence_length)))
for n, md in zip(nucs, metadata):
for j in range(len(md)):
md[j].nucleotide = n
else:
refseq = None
for md in metadata:
for j in range(len(md)):
md[j].selection_coeff = random.random()
pyslim.annotate_mutation_metadata(tables, metadata)
in_ts = pyslim.load_tables(tables, reference_sequence=refseq)
# put it through SLiM (which just reads in and writes out)
out_ts = self.run_slim_restart(in_ts, basename)
# check for equality, in everything but the last provenance
self.verify_slim_restart_equality(in_ts, out_ts)
def test_annotate_mutations(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_mutation_metadata(tables))
self.assertEqual(len(metadata), slim_ts.num_mutations)
selcoefs = [random.uniform(0, 1) for _ in metadata]
for j in range(len(metadata)):
metadata[j].selection_coeff = selcoefs[j]
pyslim.annotate_mutation_metadata(tables, metadata)
new_ts = pyslim.load_tables(tables)
for j, x in enumerate(new_ts.mutations()):
md = pyslim.decode_mutation(x.metadata)
self.assertEqual(md.selection_coeff, selcoefs[j])
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)