def test_drop_obs_column():
    adata = ad.AnnData(np.array(X_list), obs=obs_dict, dtype="int32")

    subset = adata[:2]
    assert subset.is_view
    # returns a copy of obs
    assert subset.obs.drop(columns=["oanno1"]).columns.tolist() == ["oanno2", "oanno3"]
    assert subset.is_view
    # would modify obs, so it should actualize subset and not modify adata
    subset.obs.drop(columns=["oanno1"], inplace=True)
    assert not subset.is_view
    assert subset.obs.columns.tolist() == ["oanno2", "oanno3"]

    assert adata.obs.columns.tolist() == ["oanno1", "oanno2", "oanno3"]
def __getitem__(self, index):

        img1 = self._read_img(self._image_list[index][0])
        img2 = self._read_img(self._image_list[index][1])

        if self._flow_list:  # it will be empty for some dataset when split="test"
            flow = self._read_flow(self._flow_list[index])
            if self._has_builtin_flow_mask:
                flow, valid_flow_mask = flow
            else:
                valid_flow_mask = None
        else:
            flow = valid_flow_mask = None

        if self.transforms is not None:
            img1, img2, flow, valid_flow_mask = self.transforms(img1, img2, flow, valid_flow_mask)

        if self._has_builtin_flow_mask or valid_flow_mask is not None:
            # The `or valid_flow_mask is not None` part is here because the mask can be generated within a transform
            return img1, img2, flow, valid_flow_mask
        else:
            return img1, img2, flow