Add obsm, etc to ExperimentAxisQuery

python-spec/src/somacore/query/query.py

@@ -236,18 +236,34 @@ def obsp(self, layer: str) -> data.SparseRead:
         return self._axisp_inner(_Axis.OBS, layer)
 
     def varp(self, layer: str) -> data.SparseRead:
-        """Returns an ``varp`` layer as a sparse read.
+        """Returns a ``varp`` layer as a sparse read.
 
         Lifecycle: maturing
         """
         return self._axisp_inner(_Axis.VAR, layer)
 
+    def obsm(self, layer: str) -> data.SparseRead:
+        """Returns an ``obsm`` layer as a sparse read.
+        Lifecycle: experimental
+        """
+        return self._axism_inner(_Axis.OBS, layer)
+
+    def varm(self, layer: str) -> data.SparseRead:
+        """Returns a ``varm`` layer as a sparse read.
+        Lifecycle: experimental
+        """
+        return self._axism_inner(_Axis.VAR, layer)
+
     def to_anndata(
         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] = (),
     ) -> anndata.AnnData:
         """
         Executes the query and return result as an ``AnnData`` in-memory object.
@@ -258,13 +274,25 @@ def to_anndata(
                 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.
 
         Lifecycle: maturing
         """
         return self._read(
             X_name,
             column_names=column_names or AxisColumnNames(obs=None, var=None),
             X_layers=X_layers,
+            obsm_layers=obsm_layers,
+            obsp_layers=obsp_layers,
+            varm_layers=varm_layers,
+            varp_layers=varp_layers,
         ).to_anndata()
 
     # Context management
@@ -306,19 +334,32 @@ def _read(
         *,
         column_names: AxisColumnNames,
         X_layers: Sequence[str],
+        obsm_layers: Sequence[str] = (),
+        obsp_layers: Sequence[str] = (),
+        varm_layers: Sequence[str] = (),
+        varp_layers: Sequence[str] = (),
     ) -> "_AxisQueryResult":
-        """Reads the entire query result into in-memory Arrow tables.
+        """Reads the entire query result in memory.
+
 
         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 Tables.
+        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.
         """
         x_collection = self._ms.X
         all_x_names = [X_name] + list(X_layers)
@@ -333,6 +374,22 @@ def _read(
                 raise NotImplementedError("Dense array unsupported")
             all_x_arrays[_xname] = x_array
 
+        def _read_axis_mappings(fn, axis, keys: Sequence[str]) -> Dict[str, np.ndarray]:
+            return {key: fn(axis, key) for key in keys}
+
+        obsm_ft = self._threadpool.submit(
+            _read_axis_mappings, self._axism_inner_ndarray, _Axis.OBS, obsm_layers
+        )
+        obsp_ft = self._threadpool.submit(
+            _read_axis_mappings, self._axisp_inner_ndarray, _Axis.OBS, obsp_layers
+        )
+        varm_ft = self._threadpool.submit(
+            _read_axis_mappings, self._axism_inner_ndarray, _Axis.VAR, varm_layers
+        )
+        varp_ft = self._threadpool.submit(
+            _read_axis_mappings, self._axisp_inner_ndarray, _Axis.VAR, varp_layers
+        )
+
         obs_table, var_table = self._read_both_axes(column_names)
 
         x_matrices = {
@@ -343,7 +400,23 @@ def _read(
         }
 
         x = x_matrices.pop(X_name)
-        return _AxisQueryResult(obs=obs_table, var=var_table, X=x, X_layers=x_matrices)
+
+        obs = obs_table.to_pandas()
+        obs.index = obs.index.astype(str)
+
+        var = var_table.to_pandas()
+        var.index = var.index.astype(str)
+
+        return _AxisQueryResult(
+            obs=obs,
+            var=var,
+            X=x,
+            obsm=obsm_ft.result(),
+            obsp=obsp_ft.result(),
+            varm=varm_ft.result(),
+            varp=varp_ft.result(),
+            X_layers=x_matrices,
+        )
 
     def _read_both_axes(
         self,
@@ -433,9 +506,64 @@ def _axisp_inner(
                 f" stored in {p_name} layer {layer!r}"
             )
 
-        joinids = getattr(self._joinids, axis.value)
+        joinids = axis.getattr_from(self._joinids)
         return ap_layer.read((joinids, joinids))
 
+    def _axism_inner(
+        self,
+        axis: "_Axis",
+        layer: str,
+    ) -> data.SparseRead:
+        m_name = f"{axis.value}m"
+
+        try:
+            axism = axis.getitem_from(self._ms, suf="m")
+        except KeyError:
+            raise ValueError(f"Measurement does not contain {m_name} data") from None
+
+        try:
+            axism_layer = axism[layer]
+        except KeyError as ke:
+            raise ValueError(f"layer {layer!r} is not available in {m_name}") from ke
+
+        if not isinstance(axism_layer, data.SparseNDArray):
+            raise TypeError(f"Unexpected SOMA type stored in '{m_name}' layer")
+
+        joinids = axis.getattr_from(self._joinids)
+        return axism_layer.read((joinids, slice(None)))
+
+    def _convert_to_ndarray(
+        self, axis: "_Axis", table: pa.Table, n_row: int, n_col: int
+    ) -> np.ndarray:
+        indexer: pd.Index = axis.getattr_from(self.indexer, pre="by_")
+        idx = indexer(table["soma_dim_0"])
+        z = np.zeros(n_row * n_col, dtype=np.float32)
+        np.put(z, idx * n_col + table["soma_dim_1"], table["soma_data"])
+        return z.reshape(n_row, n_col)
+
+    def _axisp_inner_ndarray(
+        self,
+        axis: "_Axis",
+        layer: str,
+    ) -> np.ndarray:
+        n_row = n_col = len(axis.getattr_from(self._joinids))
+
+        table = self._axisp_inner(axis, layer).tables().concat()
+        return self._convert_to_ndarray(axis, table, n_row, n_col)
+
+    def _axism_inner_ndarray(
+        self,
+        axis: "_Axis",
+        layer: str,
+    ) -> np.ndarray:
+        axism = axis.getitem_from(self._ms, suf="m")
+
+        _, n_col = axism[layer].shape
+        n_row = len(axis.getattr_from(self._joinids))
+
+        table = self._axism_inner(axis, layer).tables().concat()
+        return self._convert_to_ndarray(axis, table, n_row, n_col)
+
     @property
     def _obs_df(self) -> data.DataFrame:
         return self.experiment.obs
@@ -466,24 +594,33 @@ def _threadpool(self) -> futures.ThreadPoolExecutor:
 class _AxisQueryResult:
     """The result of running :meth:`ExperimentAxisQuery.read`. Private."""
 
-    obs: pa.Table
-    """Experiment.obs query slice, as an Arrow Table"""
-    var: pa.Table
-    """Experiment.ms[...].var query slice, as an Arrow Table"""
+    obs: pd.DataFrame
+    """Experiment.obs query slice, as a pandas DataFrame"""
+    var: pd.DataFrame
+    """Experiment.ms[...].var query slice, as a pandas DataFrame"""
     X: sparse.csr_matrix
     """Experiment.ms[...].X[...] query slice, as an SciPy sparse.csr_matrix """
     X_layers: Dict[str, sparse.csr_matrix] = attrs.field(factory=dict)
     """Any additional X layers requested, as SciPy sparse.csr_matrix(s)"""
+    obsm: Dict[str, np.ndarray] = attrs.field(factory=dict)
+    """Experiment.obsm query slice, as a numpy ndarray"""
+    obsp: Dict[str, np.ndarray] = attrs.field(factory=dict)
+    """Experiment.obsp query slice, as a numpy ndarray"""
+    varm: Dict[str, np.ndarray] = attrs.field(factory=dict)
+    """Experiment.varm query slice, as a numpy ndarray"""
+    varp: Dict[str, np.ndarray] = attrs.field(factory=dict)
+    """Experiment.varp query slice, as a numpy ndarray"""
 
     def to_anndata(self) -> anndata.AnnData:
-        obs = self.obs.to_pandas()
-        obs.index = obs.index.astype(str)
-
-        var = self.var.to_pandas()
-        var.index = var.index.astype(str)
-
         return anndata.AnnData(
-            X=self.X, obs=obs, var=var, layers=(self.X_layers or None)
+            X=self.X,
+            obs=self.obs,
+            var=self.var,
+            obsm=(self.obsm or None),
+            obsp=(self.obsp or None),
+            varm=(self.varm or None),
+            varp=(self.varp or None),
+            layers=(self.X_layers or None),
         )