test_kernel.py 文件源码

def test_gradXY_sum(self):
        n = 11
        with util.NumpySeedContext(seed=12):
            for d in [3, 1]:
                X = np.random.randn(n, d)
                sigma2 = 1.4
                k = kernel.KGauss(sigma2=sigma2)

                # n x n
                myG = np.zeros((n, n))
                K = k.eval(X, X)
                for i in range(n):
                    for j in range(n):
                        diffi2 = np.sum( (X[i, :] - X[j, :])**2 )
                        #myG[i, j] = -diffi2*K[i, j]/(sigma2**2)+ d*K[i, j]/sigma2
                        myG[i, j] = K[i, j]/sigma2*(d - diffi2/sigma2)

                # check correctness 
                G = k.gradXY_sum(X, X)

                self.assertEqual(G.shape, myG.shape)
                testing.assert_almost_equal(G, myG)