code: def sample_path(alpha, A, pobs, T=None):
      
      if __impl__ == __IMPL_PYTHON__:
          return ip.sample_path(alpha, A, pobs, T=T, dtype=config.dtype)
      elif __impl__ == __IMPL_C__:
          return ic.sample_path(alpha, A, pobs, T=T, dtype=config.dtype)
      else:
          raise RuntimeError('Nonexisting implementation selected: '+str(__impl__))
docs: Sample the hidden pathway S from the conditional distribution P ( S | Parameters, Observations )
  
      Parameters
      ----------
      alpha : ndarray((T,N), dtype = float), optional, default = None
          alpha[t,i] is the ith forward coefficient of time t.
      A : ndarray((N,N), dtype = float)
          transition matrix of the hidden states
      pobs : ndarray((T,N), dtype = float)
          pobs[t,i] is the observation probability for observation at time t given hidden state i
      T : int
          number of time steps
  
      Returns
      -------
      S : numpy.array shape (T)
          maximum likelihood hidden path