docs: def hitting_probability(T, target):
      """
      Computes the hitting probabilities for all states to the target states.
  
      The hitting probability of state i to the target set A is defined as the minimal,
      non-negative solution of:
  
      .. math::
          h_i^A &= 1                    \:\:\:\:  i\in A \\
          h_i^A &= \sum_j p_{ij} h_i^A  \:\:\:\:  i \notin A
  
      Parameters
      ----------
      T : (M, M) ndarray or scipy.sparse matrix
          Transition matrix
      B : array_like
          List of integer state labels for the target set
  
      Returns
      -------
      h : ndarray(n)
          a vector with hitting probabilities
      """
      T = _types.ensure_ndarray_or_sparse(T, ndim=2, uniform=True, kind='numeric')
      target = _types.ensure_int_vector(target)
      if _issparse(T):
          _showSparseConversionWarning()  # currently no sparse implementation!
          return dense.hitting_probability.hitting_probability(T.toarray(), target)
      else:
          return dense.hitting_probability.hitting_probability(T, target)