[Backport release-1.15][python] Rename to_spatial_data -> to_spatialdata

apis/python/src/tiledbsoma/_query.py

@@ -6,6 +6,7 @@
 """Implementation of a SOMA Experiment.
 """
 import enum
+import warnings
 from concurrent.futures import ThreadPoolExecutor
 from typing import (
     TYPE_CHECKING,
@@ -54,6 +55,7 @@
 
 if TYPE_CHECKING:
     from ._experiment import Experiment
+from ._constants import SPATIAL_DISCLAIMER
 from ._fastercsx import CompressedMatrix
 from ._measurement import Measurement
 from ._sparse_nd_array import SparseNDArray
@@ -407,9 +409,14 @@
         try:
             obs_scene = self.experiment.obs_spatial_presence
         except KeyError as ke:
-            raise KeyError("Missing obs_scene") from ke
+            raise KeyError(
+                "No obs_spatial_presence dataframe in this experiment."
+            ) from ke
         if not isinstance(obs_scene, DataFrame):
-            raise TypeError("obs_scene must be a dataframe.")
+            raise TypeError(
+                f"obs_spatial_presence must be a dataframe; got "
+                f"{type(obs_scene).__name__}."
+            )
 
         full_table = obs_scene.read(
             coords=((Axis.OBS.getattr_from(self._joinids), slice(None))),
@@ -428,12 +435,18 @@
         try:
             var_scene = self._ms.var_spatial_presence
         except KeyError as ke:
-            raise KeyError("Missing var_scene") from ke
+            raise KeyError(
+                f"No var_spatial_presence dataframe in measurement "
+                f"'{self.measurement_name}'."
+            ) from ke
         if not isinstance(var_scene, DataFrame):
-            raise TypeError("var_scene must be a dataframe.")
+            raise TypeError(
+                f"var_spatial_presence must be a dataframe; got "
+                f"{type(var_scene).__name__}."
+            )
 
         full_table = var_scene.read(
-            coords=((Axis.OBS.getattr_from(self._joinids), slice(None))),
+            coords=((Axis.VAR.getattr_from(self._joinids), slice(None))),
             result_order=ResultOrder.COLUMN_MAJOR,
             value_filter="data != 0",
         ).concat()
@@ -473,6 +486,85 @@
 
         return ad
 
+    def to_spatialdata(  # type: ignore[no-untyped-def]
+        self,
+        X_name: str,
+        *,
+        column_names: Optional[AxisColumnNames] = None,
+        X_layers: Sequence[str] = (),
+        obsm_layers: Sequence[str] = (),
+        obsp_layers: Sequence[str] = (),
+        varm_layers: Sequence[str] = (),
+        varp_layers: Sequence[str] = (),
+        drop_levels: bool = False,
+        scene_presence_mode: str = "obs",
+    ):
+        """Returns a SpatialData object containing the query results
+
+        This is a low-level routine intended to be used by loaders for other
+        in-core formats, such as AnnData, which can be created from the
+        resulting objects.
+
+        Args:
+            X_name: The X layer to read and return in the ``X`` slot.
+            column_names: The columns in the ``var`` and ``obs`` dataframes
+                to read.
+            X_layers: Additional X layers to read and return in the ``layers`` slot.
+            obsm_layers: Additional obsm layers to read and return in the obsm slot.
+            obsp_layers: Additional obsp layers to read and return in the obsp slot.
+            varm_layers: Additional varm layers to read and return in the varm slot.
+            varp_layers: Additional varp layers to read and return in the varp slot.
+            drop_levels: If ``True`` remove unused categories from the AnnData table
+                with the measurement data.
+            scene_presence_mode: Method for determining what scenes to return data
+                from. Valid options are ``obs`` (use ``obs_spatial_presence``
+                dataframe) and ``var`` (use ``var_spatial_presence`` dataframe).
+                Defaults to ``obs``.
+        """
+
+        from spatialdata import SpatialData
+
+        from .io.spatial.outgest import _add_scene_to_spatialdata
+
+        warnings.warn(SPATIAL_DISCLAIMER)
+
+        # Get a list of scenes to add to SpatialData object.
+        if scene_presence_mode == "obs":
+            scene_ids = self.obs_scene_ids()
+        elif scene_presence_mode == "var":
+            scene_ids = self.var_scene_ids()
+        else:
+            raise ValueError(
+                f"Invalid scene presence mode '{scene_presence_mode}'. Valid options "
+                f"are 'obs' and 'var'."
+            )
+
+        # Get the anndata table.
+        ad = self.to_anndata(
+            X_name,
+            column_names=column_names,
+            X_layers=X_layers,
+            obsm_layers=obsm_layers,
+            obsp_layers=obsp_layers,
+            varm_layers=varm_layers,
+            varp_layers=varp_layers,
+            drop_levels=drop_levels,
+        )
+        sdata = SpatialData(tables={self.measurement_name: ad})
+
+        for scene_id in scene_ids:
+            scene = self.experiment.spatial[str(scene_id)]
+            _add_scene_to_spatialdata(
+                sdata,
+                scene_id=str(scene_id),
+                scene=scene,
+                obs_id_name="soma_joinid",
+                var_id_name="soma_joinid",
+                measurement_names=(self.measurement_name,),
+            )
+
+        return sdata
+
     # Context management
 
     def __enter__(self) -> Self:

apis/python/src/tiledbsoma/io/spatial/__init__.py

@@ -5,6 +5,6 @@
 """
 
 from .ingest import VisiumPaths, from_visium
-from .outgest import to_spatial_data
+from .outgest import to_spatialdata
 
-__all__ = ["to_spatial_data", "from_visium", "VisiumPaths"]
+__all__ = ["to_spatialdata", "from_visium", "VisiumPaths"]

apis/python/src/tiledbsoma/io/spatial/outgest.py

@@ -69,7 +69,7 @@ def _convert_axis_names(
     return spatial_data_axes, soma_dim_map
 
 
-def _transform_to_spatial_data(
+def _transform_to_spatialdata(
     transform: somacore.CoordinateTransform,
     input_dim_map: Dict[str, str],
     output_dim_map: Dict[str, str],
@@ -102,7 +102,7 @@ def _transform_to_spatial_data(
     )
 
 
-def to_spatial_data_points(
+def to_spatialdata_points(
     points: PointCloudDataFrame,
     *,
     key: str,
@@ -135,7 +135,7 @@ def to_spatial_data_points(
         transforms = {key: sd.transformations.Identity()}
     else:
         transforms = {
-            scene_id: _transform_to_spatial_data(
+            scene_id: _transform_to_spatialdata(
                 transform.inverse_transform(), points_dim_map, scene_dim_map
             )
         }
@@ -146,7 +146,7 @@ def to_spatial_data_points(
     return sd.models.PointsModel.parse(df, transformations=transforms)
 
 
-def to_spatial_data_shapes(
+def to_spatialdata_shapes(
     points: PointCloudDataFrame,
     *,
     key: str,
@@ -197,7 +197,7 @@ def to_spatial_data_shapes(
         transforms = {key: sd.transformations.Identity()}
     else:
         transforms = {
-            scene_id: _transform_to_spatial_data(
+            scene_id: _transform_to_spatialdata(
                 transform.inverse_transform(), points_dim_map, scene_dim_map
             )
         }
@@ -220,7 +220,7 @@ def to_spatial_data_shapes(
     return df
 
 
-def to_spatial_data_image(
+def to_spatialdata_image(
     image: MultiscaleImage,
     level: Optional[Union[str, int]] = None,
     *,
@@ -272,7 +272,7 @@ def to_spatial_data_image(
     if transform is None:
         # Get the transformation from the image level to the highest resolution of the multiscale image.
         scale_transform = image.get_transform_from_level(level)
-        sd_transform = _transform_to_spatial_data(
+        sd_transform = _transform_to_spatialdata(
             scale_transform, image_dim_map, image_dim_map
         )
         transformations = {key: sd_transform}
@@ -287,14 +287,14 @@ def to_spatial_data_image(
             scale_transform, somacore.IdentityTransform
         ):
             # inv_transform @ scale_transform -> applies scale_transform first
-            sd_transform = _transform_to_spatial_data(
+            sd_transform = _transform_to_spatialdata(
                 inv_transform @ scale_transform, image_dim_map, scene_dim_map
             )
         else:
-            sd_transform1 = _transform_to_spatial_data(
+            sd_transform1 = _transform_to_spatialdata(
                 scale_transform, image_dim_map, image_dim_map
             )
-            sd_transform2 = _transform_to_spatial_data(
+            sd_transform2 = _transform_to_spatialdata(
                 inv_transform, image_dim_map, scene_dim_map
             )
             # Sequence([sd_transform1, sd_transform2]) -> applies sd_transform1 first
@@ -310,7 +310,7 @@ def to_spatial_data_image(
     )
 
 
-def to_spatial_data_multiscale_image(
+def to_spatialdata_multiscale_image(
     image: MultiscaleImage,
     *,
     key: str,
@@ -350,7 +350,7 @@ def to_spatial_data_multiscale_image(
 
     if transform is None:
         spatial_data_transformations = tuple(
-            _transform_to_spatial_data(
+            _transform_to_spatialdata(
                 image.get_transform_from_level(level),
                 image_dim_map,
                 image_dim_map,
@@ -366,7 +366,7 @@ def to_spatial_data_multiscale_image(
         if isinstance(transform, somacore.ScaleTransform):
             # inv_transform @ scale_transform -> applies scale_transform first
             spatial_data_transformations = tuple(
-                _transform_to_spatial_data(
+                _transform_to_spatialdata(
                     inv_transform @ image.get_transform_from_level(level),
                     image_dim_map,
                     scene_dim_map,
@@ -375,12 +375,12 @@ def to_spatial_data_multiscale_image(
             )
         else:
             sd_scale_transforms = tuple(
-                _transform_to_spatial_data(
+                _transform_to_spatialdata(
                     image.get_transform_from_level(level), image_dim_map, image_dim_map
                 )
                 for level in range(1, image.level_count)
             )
-            sd_inv_transform = _transform_to_spatial_data(
+            sd_inv_transform = _transform_to_spatialdata(
                 inv_transform, image_dim_map, scene_dim_map
             )
 
@@ -420,7 +420,7 @@ def _get_transform_from_collection(
     return None
 
 
-def _add_scene_to_spatial_data(
+def _add_scene_to_spatialdata(
     sdata: sd.SpatialData,
     scene_id: str,
     scene: Scene,
@@ -456,7 +456,7 @@ def _add_scene_to_spatial_data(
             transform = _get_transform_from_collection(key, scene.obsl.metadata)
             if isinstance(df, PointCloudDataFrame):
                 if "soma_geometry" in df.metadata:
-                    sdata.shapes[output_key] = to_spatial_data_shapes(
+                    sdata.shapes[output_key] = to_spatialdata_shapes(
                         df,
                         key=output_key,
                         scene_id=scene_id,
@@ -465,7 +465,7 @@ def _add_scene_to_spatial_data(
                         soma_joinid_name=obs_id_name,
                     )
                 else:
-                    sdata.points[output_key] = to_spatial_data_points(
+                    sdata.points[output_key] = to_spatialdata_points(
                         df,
                         key=output_key,
                         scene_id=scene_id,
@@ -492,7 +492,7 @@ def _add_scene_to_spatial_data(
                 transform = _get_transform_from_collection(key, subcoll.metadata)
                 if isinstance(df, PointCloudDataFrame):
                     if "soma_geometry" in df.metadata:
-                        sdata.shapes[output_key] = to_spatial_data_shapes(
+                        sdata.shapes[output_key] = to_spatialdata_shapes(
                             df,
                             key=output_key,
                             scene_id=scene_id,
@@ -501,7 +501,7 @@ def _add_scene_to_spatial_data(
                             soma_joinid_name=var_id_name,
                         )
                     else:
-                        sdata.points[output_key] = to_spatial_data_points(
+                        sdata.points[output_key] = to_spatialdata_points(
                             df,
                             key=output_key,
                             scene_id=scene_id,
@@ -526,7 +526,7 @@ def _add_scene_to_spatial_data(
                     f"datatype {type(image).__name__}."
                 )
             if image.level_count == 1:
-                sdata.images[output_key] = to_spatial_data_image(
+                sdata.images[output_key] = to_spatialdata_image(
                     image,
                     0,
                     key=output_key,
@@ -535,7 +535,7 @@ def _add_scene_to_spatial_data(
                     transform=transform,
                 )
             else:
-                sdata.images[f"{scene_id}_{key}"] = to_spatial_data_multiscale_image(
+                sdata.images[f"{scene_id}_{key}"] = to_spatialdata_multiscale_image(
                     image,
                     key=output_key,
                     scene_id=scene_id,
@@ -544,7 +544,7 @@ def _add_scene_to_spatial_data(
                 )
 
 
-def to_spatial_data(
+def to_spatialdata(
     experiment: Experiment,
     *,
     measurement_names: Optional[Sequence[str]] = None,
@@ -614,7 +614,7 @@ def to_spatial_data(
 
     for scene_id in scene_names:
         scene = experiment.spatial[scene_id]
-        _add_scene_to_spatial_data(
+        _add_scene_to_spatialdata(
             sdata=sdata,
             scene_id=scene_id,
             scene=scene,

apis/python/tests/test_basic_spatialdata_io.py

@@ -26,7 +26,7 @@ def sample_2d_data():
 
 @pytest.fixture(scope="module")
 def experiment_with_single_scene(tmp_path_factory, sample_2d_data) -> soma.Experiment:
-    uri = tmp_path_factory.mktemp("experiment_with_spatial_data").as_uri()
+    uri = tmp_path_factory.mktemp("experiment_with_spatialdata").as_uri()
     with soma.Experiment.create(uri) as exp:
         assert exp.uri == uri
         # Create spatial folder.
@@ -173,7 +173,7 @@ def test_outgest_no_spatial(tmp_path, conftest_pbmc_small):
 
     # Read full experiment into SpatialData.
     with _factory.open(output_path) as exp:
-        sdata = spatial_outgest.to_spatial_data(exp)
+        sdata = spatial_outgest.to_spatialdata(exp)
 
     # Check the number of assets (exactly 1 table) is as expected.
     assert len(sdata.tables) == 2
@@ -204,7 +204,7 @@ def test_outgest_no_spatial(tmp_path, conftest_pbmc_small):
 
 def test_outgest_spatial_only(experiment_with_single_scene, sample_2d_data):
     # Export to SpatialData.
-    sdata = spatial_outgest.to_spatial_data(experiment_with_single_scene)
+    sdata = spatial_outgest.to_spatialdata(experiment_with_single_scene)
 
     # Check the number of assets is correct.
     assert len(sdata.tables) == 0