Fix data type errors

HISTORY.rst

@@ -2,6 +2,15 @@
 History
 =======
 
+1.4.1 (2026-06-16)
+------------------
+* Improved speed of random spot generation used in permutation testing.
+
+API and Bug Fixes:
+* Fixed up docstring and types for various CCI methods.
+* Fixes for issues #350 and #300 with incorrect types.
+* Upgrade libraries: pillow>=12.0.0,<13.0
+
 1.4.0 (2026-05-01)
 ------------------
 * Removed tensorflow and keras and replaced with torch and torchvision.

docs/index.rst

@@ -38,6 +38,8 @@ undissociated tissue sample.
 Latest Additions
 ----------------
 
+.. include:: release_notes/1.4.1.rst
+
 .. include:: release_notes/1.4.0.rst
 
 .. include:: release_notes/1.3.0.rst

docs/release_notes/1.4.1.rst

@@ -0,0 +1,11 @@
+1.4.1 `2026-06-16`
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. rubric:: Features
+* Improved speed of random spot generation used in permutation testing.
+
+.. rubric:: Bugs
+
+* Fixed up docstring and types for various CCI methods.
+* Fixes for issues #350 and #300 with incorrect types.
+* Upgrade libraries: pillow>=12.0.0,<13.0

docs/release_notes/index.rst

@@ -1,6 +1,8 @@
 Release Notes
 ===================================================
 
+.. include:: 1.4.1.rst
+
 .. include:: 1.4.0.rst
 
 .. include:: 1.3.0.rst

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "stlearn"
-version = "1.4.0"
+version = "1.4.1"
 authors = [
     { name = "Genomics and Machine Learning Lab", email = "andrew.newman@uq.edu.au" },
 ]
@@ -20,7 +20,7 @@ dependencies = [
     "leidenalg>=0.11.0",
     "numba>=0.58.1",
     "numpy>=2.4.0",
-    "pillow>=11.0.0,<12.0",
+    "pillow>=12.0.0,<13.0",
     "scanpy>=1.12.0",
     "scikit-image>=0.22.0",
     "pandas>=2.3.0",

stlearn/__init__.py

@@ -2,7 +2,7 @@
 
 __author__ = """Genomics and Machine Learning Lab"""
 __email__ = "andrew.newman@uq.edu.au"
-__version__ = "1.4.0"
+__version__ = "1.4.1"
 
 from . import add, datasets, em, pl, pp, spatial, tl, types
 from ._settings import settings

stlearn/adds/add_mask.py

@@ -38,9 +38,11 @@ def add_mask(
         library_id = next(iter(adata.uns["spatial"].keys()))
         quality = adata.uns["spatial"][library_id]["use_quality"]
     except Exception as e:
-        raise KeyError("""\
+        raise KeyError(
+            """\
         Please read ST data first and try again
-        """) from e
+        """
+        ) from e
 
     if imgpath is not None and os.path.isfile(imgpath):
         try:
@@ -59,13 +61,17 @@ def add_mask(
             adata.uns["mask_image"][library_id][key][quality] = img
             print("Added tissue mask to the object!")
         except Exception as e:
-            raise ValueError(f"""\
+            raise ValueError(
+                f"""\
             {imgpath!r} does not end on a valid extension.
-            """) from e
+            """
+            ) from e
     else:
-        raise ValueError(f"""\
+        raise ValueError(
+            f"""\
         {imgpath!r} does not end on a valid extension.
-        """)
+        """
+        )
     return adata if copy else None
 
 
@@ -128,9 +134,11 @@ def apply_mask(
         library_id = next(iter(adata.uns["spatial"].keys()))
         quality = adata.uns["spatial"][library_id]["use_quality"]
     except Exception as e:
-        raise KeyError("""\
+        raise KeyError(
+            """\
         Please read ST data first and try again
-        """) from e
+        """
+        ) from e
 
     if masks == "all":
         masks = list(adata.uns["mask_image"][library_id].keys())
@@ -144,9 +152,11 @@ def apply_mask(
         try:
             mask_image = adata.uns["mask_image"][library_id][mask][quality]
         except Exception as e:
-            raise KeyError(f"""\
+            raise KeyError(
+                f"""\
             Please load mask {mask} images first and try again
-            """) from e
+            """
+            ) from e
 
         # Normalise to uint8 if the image is float in [0, 1]
         if mask_image.dtype.kind == "f" and mask_image.max() <= 1.0:
@@ -157,9 +167,11 @@ def apply_mask(
         elif select == "white":
             mask_image = np.where(mask_image >= 155, 1, 0)
         else:
-            raise ValueError("""\
+            raise ValueError(
+                """\
             Only support black and white mask yet.
-            """)
+            """
+            )
         mask_image_2d = mask_image.mean(axis=2)
 
         def apply_spot_mask(x, _mask=mask, _i=i, _mask_image_2d=mask_image_2d):

stlearn/adds/image.py

@@ -71,11 +71,15 @@ def image(
 
             print("Added tissue image to the object!")
         except Exception as e:
-            raise ValueError(f"""\
+            raise ValueError(
+                f"""\
             {imgpath!r} does not end on a valid extension.
-            """) from e
+            """
+            ) from e
     else:
-        raise ValueError(f"""\
+        raise ValueError(
+            f"""\
         {imgpath!r} does not end on a valid extension.
-        """)
+        """
+        )
     return adata if copy else None

stlearn/spatial/sme/_weighting_matrix.py

@@ -36,9 +36,11 @@ def row_col_by_platform(
         array_col = adata.obs_names.map(lambda x: x.split("x")[0])
         rate = 1.5
     else:
-        raise ValueError(f"""\
+        raise ValueError(
+            f"""\
                 {platform!r} does not support.
-                """)
+                """
+        )
     regression = LinearRegression()
     reg_row: LinearRegression = regression.fit(array_row.values.reshape(-1, 1), img_row)  # type: ignore
     reg_col: LinearRegression = regression.fit(array_col.values.reshape(-1, 1), img_col)  # type: ignore

stlearn/spatial/sme/pseudo_spot.py

@@ -172,9 +172,11 @@ def pseudo_spot(
         ).reset_index()
         obs_df.drop_duplicates(subset=["array_row", "array_col"], keep="last")
     else:
-        raise ValueError(f"""\
+        raise ValueError(
+            f"""\
                 {platform!r} does not support.
-                """)
+                """
+        )
 
     reg_row = LinearRegression().fit(array_row.values.reshape(-1, 1), img_row)
 

stlearn/spatial/sme/sme_impute0.py

@@ -61,9 +61,11 @@ def sme_impute0(
         elif isinstance(adata.X, pd.Dataframe):
             count_embed = adata.X.values
         else:
-            raise ValueError(f"""\
+            raise ValueError(
+                f"""\
                     {type(adata.X)} is not a valid type.
-                    """)
+                    """
+            )
     else:
         count_embed = adata.obsm[use_data]
 

stlearn/spatial/sme/sme_normalize.py

@@ -61,9 +61,11 @@ def sme_normalize(
         elif isinstance(adata.X, pd.Dataframe):
             count_embed = adata.X.values
         else:
-            raise ValueError(f"""\
+            raise ValueError(
+                f"""\
                     {type(adata.X)} is not a valid type.
-                    """)
+                    """
+            )
     else:
         count_embed = adata.obsm[use_data]