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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 prox_max_entropy(X, step, gamma=1):
 """Proximal operator for maximum entropy regularization. g(x) = gamma \sum_i x_i ln(x_i) has the analytical solution of gamma W(1/gamma exp((X-gamma)/gamma)), where W is the Lambert W function. """

    from scipy.special import lambertw
    gamma_ = _step_gamma(step, gamma)
    # minimize entropy: return gamma_ * np.real(lambertw(np.exp((X - gamma_) / gamma_) / gamma_))
    above = X > 0
    X[above] = gamma_ * np.real(lambertw(np.exp(X[above]/gamma_ - 1) / gamma_))
    return X