docs: def steadystate(A, max_iter=100):
      """
      Empirically determine the steady state probabilities from a stochastic matrix
      """
      P = np.linalg.matrix_power(A, max_iter)
  
      # Determine the unique rows in A
      v = []
      for i in range(len(P)):
          if not np.any([np.allclose(P[i], vi, ) for vi in v]):
              v.append(P[i])
  
      return normalize(np.sum(v, axis=0))