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All Samples(8)  |  Call(6)  |  Derive(0)  |  Import(2)

src/c/o/cogent-1.5.3/cogent/evolve/discrete_markov.py   cogent(Download)
        "cogent.evolve.substitution_model.DiscreteSubstitutionModel",
        '1.6')
    from cogent.evolve.substitution_model import DiscreteSubstitutionModel
    return DiscreteSubstitutionModel(*args, **kw)
 

src/p/y/pycogent-HEAD/cogent/evolve/discrete_markov.py   pycogent(Download)
        "cogent.evolve.substitution_model.DiscreteSubstitutionModel",
        '1.6')
    from cogent.evolve.substitution_model import DiscreteSubstitutionModel
    return DiscreteSubstitutionModel(*args, **kw)
 

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)
    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/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)
    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)