fix: don't enforce identical df index on {obs,var}m

src/anndata/_core/aligned_mapping.py

@@ -22,7 +22,6 @@
     axis_len,
     convert_to_dict,
     deprecation_msg,
-    raise_value_error_if_multiindex_columns,
     warn,
     warn_once,
 )
@@ -351,24 +350,6 @@ def to_df(self) -> pd.DataFrame:
                 df[f"{key}{icolumn + 1}"] = column
         return df
 
-    def _validate_value(self, val: _AlignedAny, key: str) -> V:
-        if isinstance(val, pd.DataFrame):
-            raise_value_error_if_multiindex_columns(val, f"{self.attrname}[{key!r}]")
-            if not val.index.equals(self.dim_names):
-                # Could probably also re-order index if it’s contained
-                try:
-                    pd.testing.assert_index_equal(val.index, self.dim_names)
-                except AssertionError as e:
-                    msg = f"value.index does not match parent’s {self.dim} names:\n{e}"
-                    raise ValueError(msg) from None
-                else:
-                    msg = "Index.equals and pd.testing.assert_index_equal disagree"
-                    raise AssertionError(msg)
-            val.index.name = (
-                self.dim_names.name
-            )  # this is consistent with AnnData.obsm.setter and AnnData.varm.setter
-        return super()._validate_value(val, key)
-
     @property
     def dim_names(self) -> pd.Index:
         return (self.parent.obs_names, self.parent.var_names)[self._axis]

tests/test_obsmvarm.py

@@ -1,18 +1,24 @@
 from __future__ import annotations
 
 from functools import partial
+from typing import TYPE_CHECKING
 
 import joblib
 import numpy as np
 import pandas as pd
 import pytest
 from scipy import sparse
 
+import anndata as ad
 from anndata import AnnData
 from anndata.compat import CupyArray
-from anndata.tests.helpers import as_cupy, get_multiindex_columns_df, jnp
+from anndata.tests.helpers import as_cupy, assert_equal, get_multiindex_columns_df, jnp
 from anndata.utils import asarray
 
+if TYPE_CHECKING:
+    from pathlib import Path
+    from typing import Literal
+
 M, N = (100, 100)
 
 
@@ -81,26 +87,6 @@ def test_setting_ndarray(adata: AnnData):
     assert h == joblib.hash(adata)
 
 
-def test_setting_dataframe(adata: AnnData):
-    obsm_df = pd.DataFrame(dict(b_1=np.ones(M), b_2=["a"] * M), index=adata.obs_names)
-    varm_df = pd.DataFrame(dict(b_1=np.ones(N), b_2=["a"] * N), index=adata.var_names)
-
-    adata.obsm["b"] = obsm_df
-    assert np.all(adata.obsm["b"] == obsm_df)
-    adata.varm["b"] = varm_df
-    assert np.all(adata.varm["b"] == varm_df)
-
-    bad_obsm_df = obsm_df.copy()
-    bad_obsm_df.reset_index(inplace=True)
-    with pytest.raises(ValueError, match=r"index does not match.*obs names"):
-        adata.obsm["c"] = bad_obsm_df
-
-    bad_varm_df = varm_df.copy()
-    bad_varm_df.reset_index(inplace=True)
-    with pytest.raises(ValueError, match=r"index does not match.*var names"):
-        adata.varm["c"] = bad_varm_df
-
-
 def test_setting_sparse(adata: AnnData):
     obsm_sparse = sparse.random(M, 100, format="csr")
     assert isinstance(obsm_sparse, sparse.csr_matrix)
@@ -182,3 +168,15 @@ def test_1d_declaration(array_type):
 def test_1d_set(adata, array_type):
     adata.varm["1d-array"] = array_type(np.ones(adata.shape[1]))
     assert adata.varm["1d-array"].shape == (adata.shape[1], 1)
+
+
+@pytest.mark.parametrize("axis", ["obs", "var"])
+def test_roundtrips_df_with_different_index(
+    tmp_path: Path, adata: AnnData, axis: Literal["obs", "var"]
+):
+    getattr(adata, f"{axis}m")["df"] = pd.DataFrame(
+        index=[f"not_{i}" for i in range(getattr(adata, axis).shape[0])]
+    )
+    adata.write_h5ad(tmp_path / "foo.h5ad")
+    roundtripped = ad.read_h5ad(tmp_path / "foo.h5ad")
+    assert_equal(adata, roundtripped)