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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def mbar_W_nk(u_kn, N_k, f_k):
 """Calculate the weight matrix. Parameters u_kn : np.ndarray, shape=(n_states, n_samples), dtype='float' The reduced potential energies, i.e. -log unnormalized probabilities N_k : np.ndarray, shape=(n_states), dtype='int' The number of samples in each state f_k : np.ndarray, shape=(n_states), dtype='float' The reduced free energies of each state Returns ------- W_nk : np.ndarray, dtype='float', shape=(n_samples, n_states) The normalized weights. Notes ----- Equation (9) in JCP MBAR paper. """

    return np.exp(mbar_log_W_nk(u_kn, N_k, f_k))