def test_simulateAlignment2(self): "Simulate alignment with dinucleotide model" al = LoadSeqs(data={'a': 'ggaatt', 'c': 'cctaat'}) t = LoadTree(treestring="(a,c);") sm = substitution_model.Dinucleotide(mprob_model='tuple') lf = sm.makeParamController(t) lf.setAlignment(al) simalign = lf.simulateAlignment() self.assertEqual(len(simalign), 6)
def use_root_seq(root_sequence): al = LoadSeqs(data={'a': 'ggaatt', 'c': 'cctaat'}) t = LoadTree(treestring="(a,c);") sm = substitution_model.Dinucleotide(mprob_model='tuple') lf = sm.makeParamController(t) lf.setAlignment(al) simalign = lf.simulateAlignment(exclude_internal=False, root_sequence=root_sequence) root = simalign.NamedSeqs['root'] self.assertEqual(str(root), str(root_sequence))
def test_dinucleotide(self): """test a dinucleotide model.""" submod = substitution_model.Dinucleotide( equal_motif_probs=True, do_scaling=False, motif_probs=None, predicates={'kappa': 'transition'}, mprob_model='tuple') likelihood_function = self._makeLikelihoodFunction(submod) evolve_lnL = likelihood_function.getLogLikelihood() self.assertFloatEqual(evolve_lnL, -102.48145536663735)
def test_dinucleotide(self): """test a dinucleotide model.""" submod = substitution_model.Dinucleotide( equal_motif_probs=True, do_scaling=False, motif_probs=None, predicates={'kappa': 'transition'}, mprob_model='tuple') likelihood_function = self._makeLikelihoodFunction( submod, self.alignment) for par, val in self.par_values.items(): likelihood_function.setpar(par, val) likelihood_function.setpar("length", self.length) evolve_lnL = likelihood_function.testfunction() self.assertFloatEqual(evolve_lnL, -102.48145536663735)
def test_asciiArt(self): model = substitution_model.Dinucleotide(mprob_model='tuple', predicates=['k:transition']) model.asciiArt() model = substitution_model.Dinucleotide(mprob_model='tuple') model.asciiArt()
def setUp(self): self.submodel = substitution_model.Dinucleotide(do_scaling=True, model_gaps=True, mprob_model='tuple')