Improvements/fixes: merscope reader

src/spatialdata_io/_constants/_constants.py

@@ -174,11 +174,12 @@ class MerscopeKeys(ModeEnum):
     VPT_NAME_BOUNDARIES = "cell_boundaries"
 
     # metadata
-    INSTANCE_KEY = "EntityID"
+    METADATA_CELL_KEY = "EntityID"
     COUNTS_CELL_KEY = "cell"
     CELL_X = "center_x"
     CELL_Y = "center_y"
     GLOBAL_X = "global_x"
     GLOBAL_Y = "global_y"
     GLOBAL_Z = "global_z"
     Z_INDEX = "ZIndex"
+    REGION_KEY = "cells_region"

src/spatialdata_io/readers/merscope.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
 
 import re
+from collections.abc import Mapping
 from pathlib import Path
+from types import MappingProxyType
 from typing import Any
 
 import anndata
@@ -79,6 +81,8 @@ def merscope(
     z_layers: int | list[int] | None = 3,
     region_name: str | None = None,
     slide_name: str | None = None,
+    imread_kwargs: Mapping[str, Any] = MappingProxyType({}),
+    image_models_kwargs: Mapping[str, Any] = MappingProxyType({}),
 ) -> SpatialData:
     """
     Read *MERSCOPE* data from Vizgen.
@@ -115,21 +119,38 @@ def merscope(
         Name of the region of interest, e.g., `'region_0'`. If `None` then the name of the `path` directory is used.
     slide_name
         Name of the slide/run. If `None` then the name of the parent directory of `path` is used (whose name starts with a date).
+    imread_kwargs
+        Keyword arguments to pass to the image reader.
+    image_models_kwargs
+        Keyword arguments to pass to the image models.
 
     Returns
     -------
     :class:`spatialdata.SpatialData`
     """
+    if "chunks" not in image_models_kwargs:
+        if isinstance(image_models_kwargs, MappingProxyType):
+            image_models_kwargs = {}
+        assert isinstance(image_models_kwargs, dict)
+        image_models_kwargs["chunks"] = (1, 4096, 4096)
+    if "scale_factors" not in image_models_kwargs:
+        if isinstance(image_models_kwargs, MappingProxyType):
+            image_models_kwargs = {}
+        assert isinstance(image_models_kwargs, dict)
+        image_models_kwargs["scale_factors"] = [2, 2, 2, 2]
+
     path = Path(path)
     count_path, obs_path, boundaries_path = _get_file_paths(path, vpt_outputs)
     images_dir = path / MerscopeKeys.IMAGES_DIR
 
-    microns_to_pixels = np.genfromtxt(images_dir / MerscopeKeys.TRANSFORMATION_FILE)
-    microns_to_pixels = Affine(microns_to_pixels, input_axes=("x", "y"), output_axes=("x", "y"))
+    microns_to_pixels = Affine(
+        np.genfromtxt(images_dir / MerscopeKeys.TRANSFORMATION_FILE), input_axes=("x", "y"), output_axes=("x", "y")
+    )
 
-    region_name = path.name if region_name is None else region_name
+    vizgen_region = path.name if region_name is None else region_name
     slide_name = path.parent.name if slide_name is None else slide_name
-    dataset_id = f"{slide_name}_{region_name}"
+    dataset_id = f"{slide_name}_{vizgen_region}"
+    region = f"{dataset_id}_polygons"
 
     # Images
     images = {}
@@ -138,12 +159,16 @@ def merscope(
 
     stainings = _get_channel_names(images_dir)
     for z_layer in z_layers:
-        im = da.stack([imread(images_dir / f"mosaic_{stain}_z{z_layer}.tif").squeeze() for stain in stainings], axis=0)
+        im = da.stack(
+            [imread(images_dir / f"mosaic_{stain}_z{z_layer}.tif", **imread_kwargs).squeeze() for stain in stainings],
+            axis=0,
+        )
         parsed_im = Image2DModel.parse(
             im,
             dims=("c", "y", "x"),
-            transformations={"pixels": Identity()},
+            transformations={"microns": microns_to_pixels.inverse()},
             c_coords=stainings,
+            **image_models_kwargs,
         )
         images[f"{dataset_id}_z{z_layer}"] = parsed_im
 
@@ -152,7 +177,7 @@ def merscope(
     transcripts = PointsModel.parse(
         transcript_df,
         coordinates={"x": MerscopeKeys.GLOBAL_X, "y": MerscopeKeys.GLOBAL_Y},
-        transformations={"pixels": microns_to_pixels},
+        transformations={"microns": Identity()},
     )
     categories = transcripts["gene"].compute().astype("category")
     gene_categorical = dd.from_pandas(categories, npartitions=transcripts.npartitions).reset_index(drop=True)
@@ -164,31 +189,33 @@ def merscope(
     geo_df = geopandas.read_parquet(boundaries_path)
     geo_df = geo_df.rename_geometry("geometry")
     geo_df = geo_df[geo_df[MerscopeKeys.Z_INDEX] == 0]  # Avoid duplicate boundaries on all z-levels
-    geo_df.index = geo_df[MerscopeKeys.INSTANCE_KEY].astype(str)
+    geo_df.geometry = geo_df.geometry.map(lambda x: x.geoms[0])  # The MultiPolygons contain only one polygon
+    geo_df.index = geo_df[MerscopeKeys.METADATA_CELL_KEY].astype(str)
 
-    polygons = ShapesModel.parse(geo_df, transformations={"pixels": microns_to_pixels})
+    polygons = ShapesModel.parse(geo_df, transformations={"microns": Identity()})
 
     shapes = {f"{dataset_id}_polygons": polygons}
 
     # Table
     data = pd.read_csv(count_path, index_col=0, dtype={MerscopeKeys.COUNTS_CELL_KEY: str})
-    obs = pd.read_csv(obs_path, index_col=0, dtype={MerscopeKeys.INSTANCE_KEY: str})
+    obs = pd.read_csv(obs_path, index_col=0, dtype={MerscopeKeys.METADATA_CELL_KEY: str})
 
     is_gene = ~data.columns.str.lower().str.contains("blank")
     adata = anndata.AnnData(data.loc[:, is_gene], dtype=data.values.dtype, obs=obs)
 
     adata.obsm["blank"] = data.loc[:, ~is_gene]  # blank fields are excluded from adata.X
     adata.obsm["spatial"] = adata.obs[[MerscopeKeys.CELL_X, MerscopeKeys.CELL_Y]].values
-    adata.obs["region"] = pd.Series(region_name, index=adata.obs_names, dtype="category")
+    adata.obs["region"] = pd.Series(vizgen_region, index=adata.obs_names, dtype="category")
     adata.obs["slide"] = pd.Series(slide_name, index=adata.obs_names, dtype="category")
     adata.obs["dataset_id"] = pd.Series(dataset_id, index=adata.obs_names, dtype="category")
-    adata.obs[MerscopeKeys.INSTANCE_KEY] = adata.obs.index
+    adata.obs[MerscopeKeys.REGION_KEY] = pd.Series(region, index=adata.obs_names, dtype="category")
+    adata.obs[MerscopeKeys.METADATA_CELL_KEY] = adata.obs.index
 
     table = TableModel.parse(
         adata,
-        region_key="region",
-        region=adata.obs["region"].cat.categories.tolist(),
-        instance_key=MerscopeKeys.INSTANCE_KEY.value,
+        region_key=MerscopeKeys.REGION_KEY.value,
+        region=region,
+        instance_key=MerscopeKeys.METADATA_CELL_KEY.value,
     )
 
     return SpatialData(shapes=shapes, points=points, images=images, table=table)