def prob_t(self, seq_p, seq_ch, t, pattern_multiplicity = None,<EOL>return_log=False, ignore_gaps=True):
seq_pair, multiplicity = self.compress_sequence_pair(seq_p, seq_ch,<EOL>pattern_multiplicity=pattern_multiplicity, ignore_gaps=ignore_gaps)<EOL>return self.prob_t_compressed(seq_pair, multiplicity, t, return_log=return_log)<EOL>
Compute the probability to observe seq_ch (child sequence) after time t starting from seq_p
(parent sequence).

Parameters
----------

 seq_p : character array
    Parent sequence

 seq_c : character array
    Child sequence

 t : double
    Time (branch len) separating the profiles.

 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.

 return_log : bool
    It True, return log-probability.

Returns
-------
 prob : np.array
    Resulting probability