        sum1 = np.sum([w_i * (-0.5 * (theta_i - mu_new)[:,np.newaxis].T @ sigma_new_inv @ (theta_i -  mu_new)[:,np.newaxis] - 0.5 * logdet_sigma_new - 0.5 * c) for w_i, theta_i in zip(weights, theta)])
