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')