treetime/clock_tree.py
def setup_TreeRegression(self, covariation=True):
        """instantiate a TreeRegression object and set its tip_value and branch_value function
        to defaults that are sensible for treetime instances.

        Parameters
        ----------
        covariation : bool, optional
            account for phylogenetic covariation
        Returns
        -------
        TreeRegression
            a TreeRegression instance with self.tree attached as tree.
        """
        from .treeregression import TreeRegression
        tip_value = lambda x:np.mean(x.raw_date_constraint) if (x.is_terminal() and (x.bad_branch is False)) else None
        branch_value = lambda x:x.mutation_length
        if covariation:
            om = self.one_mutation
            branch_variance = lambda x:((x.clock_length if hasattr(x,'clock_length') else x.mutation_length)
                                        +(self.tip_slack**2*om if x.is_terminal() else 0.0))*om
        else:
            branch_variance = lambda x:1.0 if x.is_terminal() else 0.0

        Treg = TreeRegression(self.tree, tip_value=tip_value,
                             branch_value=branch_value, branch_variance=branch_variance)
        Treg.valid_confidence = covariation
        return Treg
def setup_TreeRegression(self, covariation=True):
        from .treeregression import TreeRegression
        tip_value = lambda x:np.mean(x.raw_date_constraint) if (x.is_terminal() and (x.bad_branch is False)) else None
        branch_value = lambda x:x.mutation_length
        if covariation:
            om = self.one_mutation
            branch_variance = lambda x:((x.clock_length if hasattr(x,'clock_length') else x.mutation_length)
                                        +(self.tip_slack**2*om if x.is_terminal() else 0.0))*om
        else:
            branch_variance = lambda x:1.0 if x.is_terminal() else 0.0

        Treg = TreeRegression(self.tree, tip_value=tip_value,
                             branch_value=branch_value, branch_variance=branch_variance)
        Treg.valid_confidence = covariation
        return Treg
def setup_TreeRegression ( self , covariation = True ) : from . treeregression import TreeRegression tip_value = lambda x : np . mean ( x . raw_date_constraint ) if ( x . is_terminal ( ) and ( x . bad_branch is False ) ) else None branch_value = lambda x : x . mutation_length if covariation : om = self . one_mutation branch_variance = lambda x : ( ( x . clock_length if hasattr ( x , 'clock_length' ) else x . mutation_length ) + ( self . tip_slack ** 2 * om if x . is_terminal ( ) else 0.0 ) ) * om else : branch_variance = lambda x : 1.0 if x . is_terminal ( ) else 0.0 Treg = TreeRegression ( self . tree , tip_value = tip_value , branch_value = branch_value , branch_variance = branch_variance ) Treg . valid_confidence = covariation return Treg
instantiate a TreeRegression object and set its tip_value and branch_value function
        to defaults that are sensible for treetime instances.

        Parameters
        ----------
        covariation : bool, optional
            account for phylogenetic covariation
        Returns
        -------
        TreeRegression
            a TreeRegression instance with self.tree attached as tree.
instantiate a TreeRegression object and set its tip_value and branch_value function to defaults that are sensible for treetime instances .