def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
def __init__(self, train_x, train_y, likelihood):
        super(GPRegressionModel, self).__init__(train_x, train_y, likelihood)
        self.mean_module = ConstantMean(prior=SmoothedBoxPrior(-1e-5, 1e-5))
        self.base_covar_module = ScaleKernel(RBFKernel(lengthscale_prior=SmoothedBoxPrior(exp(-5), exp(6), sigma=0.1)))
        self.covar_module = InducingPointKernel(
            self.base_covar_module, inducing_points=torch.linspace(0, 1, 32), likelihood=likelihood
        )