docs: def transition_matrix_non_reversible(C):
      r"""
      Estimates a non-reversible transition matrix from count matrix C
  
      T_ij = c_ij / c_i where c_i = sum_j c_ij
  
      Parameters
      ----------
      C: ndarray, shape (n,n)
          count matrix
  
      Returns
      -------
      T: Estimated transition matrix
  
      """
      # multiply by 1.0 to make sure we're not doing integer division
      rowsums = 1.0 * np.sum(C, axis=1)
      if np.min(rowsums) <= 0:
          raise ValueError(
              "Transition matrix has row sum of " + str(np.min(rowsums)) + ". Must have strictly positive row sums.")
      return np.divide(C, rowsums[:, np.newaxis])