def test_double_index(subset_func, subset_func2):
    adata = gen_adata((10, 10))
    obs_subset = subset_func(adata.obs_names)
    var_subset = subset_func2(adata.var_names)
    v1 = adata[obs_subset, var_subset]
    v2 = adata[obs_subset, :][:, var_subset]

    assert np.all(asarray(v1.X) == asarray(v2.X))
    assert np.all(v1.obs == v2.obs)
    assert np.all(v1.var == v2.var)
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
        )