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src/p/y/pycogent-HEAD/tests/test_evolve/test_likelihood_function.py   pycogent(Download)
        # should fail for a discrete Markov model
        dm = substitution_model.DiscreteSubstitutionModel(DNA.Alphabet)
        lf = dm.makeLikelihoodFunction(self.tree)
        lf.setAlignment(self.data)
        self.assertRaises(Exception, lf.getRateMatrixForEdge, 'NineBande')
    def test_make_discrete_markov(self):
        """lf ignores tree lengths if a discrete Markov model"""
        t = LoadTree(treestring='(a:0.4,b:0.3,(c:0.15,d:0.2)edge.0:0.1)root;')
        dm = substitution_model.DiscreteSubstitutionModel(DNA.Alphabet)
        lf = dm.makeLikelihoodFunction(t)

src/c/o/cogent-1.5.3/tests/test_evolve/test_likelihood_function.py   cogent(Download)
        # should fail for a discrete Markov model
        dm = substitution_model.DiscreteSubstitutionModel(DNA.Alphabet)
        lf = dm.makeLikelihoodFunction(self.tree)
        lf.setAlignment(self.data)
        self.assertRaises(Exception, lf.getRateMatrixForEdge, 'NineBande')
    def test_make_discrete_markov(self):
        """lf ignores tree lengths if a discrete Markov model"""
        t = LoadTree(treestring='(a:0.4,b:0.3,(c:0.15,d:0.2)edge.0:0.1)root;')
        dm = substitution_model.DiscreteSubstitutionModel(DNA.Alphabet)
        lf = dm.makeLikelihoodFunction(t)