def predictive_log_likelihood(self, X_test):
        assert X_test.shape >= (self.N, self.K)
        ll = 0
        ll += gammaln(X_test.sum(axis=1)+1).sum() - gammaln(X_test+1).sum()
        ll += np.nansum(X_test * np.log(self.pi))
        return ll
dataset/ETHPy150Open HIPS/pgmult/pgmult/distributions.py/IndependentMultinomialsModel.predictive_log_likelihood/operator `==` -> `>=`