test_kernel.py 文件源码

def test_gradX_y(self):
        n = 10
        with util.NumpySeedContext(seed=10):
            for d in [1, 3]:
                y = np.random.randn(d)*2
                X = np.random.rand(n, d)*3

                sigma2 = 1.3
                k = kernel.KGauss(sigma2=sigma2)
                # n x d
                G = k.gradX_y(X, y)
                # check correctness 
                K = k.eval(X, y[np.newaxis, :])
                myG = -K/sigma2*(X-y)

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