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_ancestral(self):
"""recon ancestral states works"""
_data = {
"Human": "ATGCGGCTCGCGGAGGCCGCGCTCGCGGAG",
"Mouse": "ATGCCCGGCGCCAAGGCAGCGCTGGCGGAG",
"Opossum": "ATGCCAGTGAAAGTGGCGGCGGTGGCTGAG",
}
aln = make_aligned_seqs(data=_data, moltype="dna")
mod = evo_app.model("GN",
opt_args=dict(max_evaluations=25,
limit_action="ignore"))
anc = evo_app.ancestral_states()
result = anc(mod(aln))
self.assertEqual(result["root"].shape, (len(aln), 4))
assert_allclose(result["root"].row_sum(), 1)
