code: def committor_sensitivity(T, A, B, i, forward=True):
      r
      # check inputs
      T = _types.ensure_ndarray_or_sparse(T, ndim=2, uniform=True, kind='numeric')
      A = _types.ensure_int_vector(A)
      B = _types.ensure_int_vector(B)
      if _issparse(T):
          _showSparseConversionWarning()
          committor_sensitivity(T.todense(), A, B, i, forward)
      else:
          if forward:
              return dense.sensitivity.forward_committor_sensitivity(T, A, B, i)
          else:
              return dense.sensitivity.backward_committor_sensitivity(T, A, B, i)
docs: r"""Sensitivity matrix of a specified committor entry.
  
      Parameters
      ----------
  
      T : (M, M) ndarray
          Transition matrix
      A : array_like
          List of integer state labels for set A
      B : array_like
          List of integer state labels for set B
      i : int
          Compute the sensitivity for committor entry `i`
      forward : bool (optional)
          Compute the forward committor. If forward
          is False compute the backward committor.
  
      Returns
      -------
      S : (M, M) ndarray
          Sensitivity matrix of the specified committor entry.