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)