code: def mix2PL_mse(mean, estimator, m):
      
      mse1 = mse(mean, estimator)
      estimator = np.hstack((1 - estimator[0], estimator[m+1:], estimator[1:m+1]))
      mse2 = mse(mean, estimator)
      return min(mse1, mse2)
docs: Description:
          Calculates the Mean Squared Error (MSE) of an
          estimator of a mixture of 2 Plackett-Luce models,
          on flat numpy ndarrays, where the first element is
          the mixing proportion of the first model defined
          as the minimum MSE over the inverse permutations of
          the estimator.
      Parameters:
          mean:      actual value (numpy ndarray)
          estimator: estimated value of the mean (numpy ndarray)
          m:         number of alternatives in each of the two models