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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 calc_neg_log_likelihood_and_neg_gradient(self, params):
 """ Calculates and returns the negative of the log-likelihood and the negative of the gradient. This function is used as the objective function in scipy.optimize.minimize. """

        neg_log_likelihood = -1 * self.convenience_calc_log_likelihood(params)
        neg_gradient = -1 * self.convenience_calc_gradient(params)

        if self.constrained_pos is not None:
            neg_gradient[self.constrained_pos] = 0

        return neg_log_likelihood, neg_gradient