def _get_all_composables(tmp_dir_name):
test_model1 = evo.model("HKY85")
test_model2 = evo.model("GN")
test_hyp = evo.hypothesis(test_model1, test_model2)
test_num_reps = 100
applications = [
align.align_to_ref(),
align.progressive_align(model="GY94"),
evo.ancestral_states(),
evo.bootstrap(hyp=test_hyp, num_reps=test_num_reps),
evo.hypothesis(test_model1, test_model2),
evo.model("GN"),
evo.tabulate_stats(),
sample.fixed_length(100),
sample.min_length(100),
io.write_db(tmp_dir_name, create=True),
io.write_json(tmp_dir_name, create=True),
io.write_seqs(tmp_dir_name, create=True),
sample.omit_bad_seqs(),
sample.omit_degenerates(),
sample.omit_duplicated(),
sample.take_codon_positions(1),
sample.take_named_seqs(),
sample.trim_stop_codons(gc=1),
translate.select_translatable(),
tree.quick_tree(),
tree.scale_branches(),
tree.uniformize_tree(),
]
return applications
def test_bootstrap_composability(self):
"""can be composed with load_db and write_db"""
m1 = evo_app.model("F81")
m2 = evo_app.model("HKY85")
hyp = evo_app.hypothesis(m1, m2)
with TemporaryDirectory(dir=".") as dirname:
path = join(dirname, "delme.tinydb")
_ = io.load_db() + evo_app.bootstrap(
hyp, num_reps=2) + io.write_db(path)
def test_bstrap_parallel(self):
"""exercising bootstrap with parallel"""
aln = load_aligned_seqs(join(data_dir, "brca1.fasta"), moltype="dna")
aln = aln.take_seqs(aln.names[:3])
aln = aln.omit_gap_pos(allowed_gap_frac=0)
opt_args = dict(max_evaluations=20, limit_action="ignore")
m1 = evo_app.model("F81", opt_args=opt_args)
m2 = evo_app.model("HKY85", opt_args=opt_args)
hyp = evo_app.hypothesis(m1, m2)
strapper = evo_app.bootstrap(hyp, num_reps=2, parallel=True)
result = strapper(aln)
self.assertIsInstance(result, evo_app.bootstrap_result)
def test_bstrap(self):
"""exercising bootstrap with simple hypothesis"""
aln = load_aligned_seqs(join(data_dir, "brca1.fasta"), moltype="dna")
aln = aln.take_seqs(aln.names[:3])
aln = aln.omit_gap_pos(allowed_gap_frac=0)
opt_args = dict(max_evaluations=20, limit_action="ignore")
m1 = evo_app.model("F81", opt_args=opt_args)
m2 = evo_app.model("HKY85", opt_args=opt_args)
hyp = evo_app.hypothesis(m1, m2)
strapper = evo_app.bootstrap(hyp, num_reps=2, parallel=False)
result = strapper(aln)
nd = result.null_dist
self.assertTrue(set(type(v) for v in nd), {float})
json = result.to_json()
got = deserialise_object(json)
self.assertIsInstance(got, evo_app.bootstrap_result)