treetime/gtr.py
def optimal_t(self, seq_p, seq_ch, pattern_multiplicity=None, ignore_gaps=False):
        '''
        Find the optimal distance between the two sequences

        Parameters
        ----------

         seq_p : character array
            Parent sequence

         seq_c : character array
            Child sequence

         pattern_multiplicity : numpy array
            If sequences are reduced by combining identical alignment patterns,
            these multplicities need to be accounted for when counting the number
            of mutations across a branch. If None, all pattern are assumed to
            occur exactly once.

         ignore_gaps : bool
            If True, ignore gaps in distance calculations

        '''
        seq_pair, multiplicity = self.compress_sequence_pair(seq_p, seq_ch,
                                                            pattern_multiplicity = pattern_multiplicity,
                                                            ignore_gaps=ignore_gaps)
        return self.optimal_t_compressed(seq_pair, multiplicity)
def optimal_t(self, seq_p, seq_ch, pattern_multiplicity=None, ignore_gaps=False):
        '''
        Find the optimal distance between the two sequences

        Parameters
        ----------

         seq_p : character array
            Parent sequence

         seq_c : character array
            Child sequence

         pattern_multiplicity : numpy array
            If sequences are reduced by combining identical alignment patterns,
            these multplicities need to be accounted for when counting the number
            of mutations across a branch. If None, all pattern are assumed to
            occur exactly once.

         ignore_gaps : bool
            If True, ignore gaps in distance calculations

        '''
        seq_pair, multiplicity = self.compress_sequence_pair(seq_p, seq_ch,
                                                            pattern_multiplicity = pattern_multiplicity,
                                                            ignore_gaps=ignore_gaps)
        return self.optimal_t_compressed(seq_pair, multiplicity)
Find the optimal distance between the two sequences

        Parameters
        ----------

         seq_p : character array
            Parent sequence

         seq_c : character array
            Child sequence

         pattern_multiplicity : numpy array
            If sequences are reduced by combining identical alignment patterns,
            these multplicities need to be accounted for when counting the number
            of mutations across a branch. If None, all pattern are assumed to
            occur exactly once.

         ignore_gaps : bool
            If True, ignore gaps in distance calculations