code: def _initial_guess(self, countsmat):
          
  
          if self.theta_ is not None:
              return self.theta_
  
          if self.guess == 'log':
              transmat, pi = _transmat_mle_prinz(countsmat)
              K = np.real(scipy.linalg.logm(transmat)) / self.lag_time
  
          elif self.guess == 'pseudo':
              transmat, pi = _transmat_mle_prinz(countsmat)
              K = (transmat - np.eye(self.n_states_)) / self.lag_time
  
          elif isinstance(self.guess, np.ndarray):
              pi = _solve_ratemat_eigensystem(self.guess)[1][:, 0]
              K = self.guess
  
          S = np.multiply(np.sqrt(np.outer(pi, 1/pi)), K)
          sflat = np.maximum(S[np.triu_indices_from(countsmat, k=1)], 0)
          theta0 = np.concatenate((sflat, np.log(pi)))
          return theta0
docs: Generate an initial guess for \theta.