Merge branch 'main' into feature/202306_support_multipolygons

Author: timtreis

.pre-commit-config.yaml

@@ -13,21 +13,21 @@ repos:
       hooks:
           - id: black
     - repo: https://github.com/pre-commit/mirrors-prettier
-      rev: v3.0.0-alpha.6
+      rev: v3.0.0-alpha.9-for-vscode
       hooks:
           - id: prettier
     - repo: https://github.com/asottile/blacken-docs
       rev: 1.13.0
       hooks:
           - id: blacken-docs
     - repo: https://github.com/pre-commit/mirrors-mypy
-      rev: v1.2.0
+      rev: v1.3.0
       hooks:
           - id: mypy
             additional_dependencies: [numpy, types-requests]
             exclude: tests/|docs/
     - repo: https://github.com/charliermarsh/ruff-pre-commit
-      rev: v0.0.261
+      rev: v0.0.272
       hooks:
           - id: ruff
             args: [--fix, --exit-non-zero-on-fix]

pyproject.toml

@@ -161,6 +161,3 @@ target-version = "py39"
     "src/spatialdata_plot/pl/utils.py"= ["PGH003"]
 [tool.ruff.pydocstyle]
 convention = "numpy"
-[tool.ruff.pyupgrade]
-# Preserve types, even if a file imports `from __future__ import annotations`.
-keep-runtime-typing = true

src/spatialdata_plot/pl/basic.py

@@ -4,7 +4,7 @@
 from collections import OrderedDict
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Any, Optional, Union
+from typing import Any
 
 import matplotlib.pyplot as plt
 import scanpy as sc
@@ -82,11 +82,11 @@ def __init__(self, sdata: sd.SpatialData) -> None:
 
     def _copy(
         self,
-        images: Union[None, dict[str, Union[SpatialImage, MultiscaleSpatialImage]]] = None,
-        labels: Union[None, dict[str, Union[SpatialImage, MultiscaleSpatialImage]]] = None,
-        points: Union[None, dict[str, DaskDataFrame]] = None,
-        shapes: Union[None, dict[str, GeoDataFrame]] = None,
-        table: Union[None, AnnData] = None,
+        images: None | dict[str, SpatialImage | MultiscaleSpatialImage] = None,
+        labels: None | dict[str, SpatialImage | MultiscaleSpatialImage] = None,
+        points: None | dict[str, DaskDataFrame] = None,
+        shapes: None | dict[str, GeoDataFrame] = None,
+        table: None | AnnData = None,
     ) -> sd.SpatialData:
         """Copy the current `SpatialData` object, optionally modifying some of its attributes.
 
@@ -150,7 +150,7 @@ def render_shapes(
         layer: str | None = None,
         palette: Palette_t = None,
         cmap: Colormap | str | None = None,
-        norm: Optional[Normalize] = None,
+        norm: None | Normalize = None,
         na_color: str | tuple[float, ...] | None = "lightgrey",
         outline_alpha: float = 1.0,
         fill_alpha: float = 1.0,
@@ -232,7 +232,7 @@ def render_points(
         size: float = 1.0,
         palette: Palette_t = None,
         cmap: Colormap | str | None = None,
-        norm: Optional[Normalize] = None,
+        norm: None | Normalize = None,
         na_color: str | tuple[float, ...] | None = (0.0, 0.0, 0.0, 0.0),
         alpha: float = 1.0,
         **kwargs: Any,
@@ -296,7 +296,7 @@ def render_images(
         elements: str | list[str] | None = None,
         channel: list[str] | list[int] | int | str | None = None,
         cmap: Colormap | str | None = None,
-        norm: Optional[Normalize] = None,
+        norm: None | Normalize = None,
         na_color: str | tuple[float, ...] | None = (0.0, 0.0, 0.0, 0.0),
         palette: Palette_t = None,
         alpha: float = 1.0,
@@ -358,7 +358,7 @@ def render_labels(
         layer: str | None = None,
         palette: Palette_t = None,
         cmap: Colormap | str | None = None,
-        norm: Optional[Normalize] = None,
+        norm: None | Normalize = None,
         na_color: str | tuple[float, ...] | None = (0.0, 0.0, 0.0, 0.0),
         outline_alpha: float = 1.0,
         fill_alpha: float = 0.3,
@@ -452,11 +452,11 @@ def show(
         figsize: tuple[float, float] | None = None,
         dpi: int | None = None,
         fig: Figure | None = None,
-        title: Optional[Union[str, Sequence[str]]] = None,
+        title: None | str | Sequence[str] = None,
         share_extent: bool = True,
         ax: Axes | Sequence[Axes] | None = None,
         return_ax: bool = False,
-        save: Optional[Union[str, Path]] = None,
+        save: None | str | Path = None,
     ) -> sd.SpatialData:
         """
         Plot the images in the SpatialData object.
@@ -517,7 +517,7 @@ def show(
             if isinstance(title, str):
                 title = [title]
 
-            if not all([isinstance(t, str) for t in title]):
+            if not all(isinstance(t, str) for t in title):
                 raise TypeError("All titles must be strings.")
 
         # Simplicstic solution: If the images are multiscale, just use the first

src/spatialdata_plot/pl/render.py

@@ -115,8 +115,8 @@ def _get_collection_shape(
         c: Any,
         s: float,
         norm: Any,
-        fill_alpha: Optional[float] = None,
-        outline_alpha: Optional[float] = None,
+        fill_alpha: None | float = None,
+        outline_alpha: None | float = None,
         **kwargs: Any,
     ) -> PatchCollection:
         polygon_df = shapes[shapes["geometry"].apply(lambda geom: geom.geom_type == "Polygon")]

src/spatialdata_plot/pl/utils.py

@@ -112,7 +112,7 @@ def _prepare_params_plot(
         fig, grid = _panel_grid(
             num_panels=num_panels, hspace=hspace, wspace=wspace, ncols=ncols, dpi=dpi, figsize=figsize
         )
-        axs: Union[Sequence[Axes], None] = [plt.subplot(grid[c]) for c in range(num_panels)]
+        axs: None | Sequence[Axes] = [plt.subplot(grid[c]) for c in range(num_panels)]
     elif num_panels > 1 and ax is not None:
         if len(ax) != num_panels:
             raise ValueError(f"Len of `ax`: {len(ax)} is not equal to number of panels: {num_panels}.")
@@ -151,10 +151,10 @@ def _get_cs_contents(sdata: sd.SpatialData) -> pd.DataFrame:
 
     for cs_name, element_ids in cs_mapping.items():
         # determine if coordinate system has the respective elements
-        cs_has_images = bool(any([(e in sdata.images) for e in element_ids]))
-        cs_has_labels = bool(any([(e in sdata.labels) for e in element_ids]))
-        cs_has_points = bool(any([(e in sdata.points) for e in element_ids]))
-        cs_has_shapes = bool(any([(e in sdata.shapes) for e in element_ids]))
+        cs_has_images = bool(any((e in sdata.images) for e in element_ids))
+        cs_has_labels = bool(any((e in sdata.labels) for e in element_ids))
+        cs_has_points = bool(any((e in sdata.points) for e in element_ids))
+        cs_has_shapes = bool(any((e in sdata.shapes) for e in element_ids))
 
         cs_contents = pd.concat(
             [
@@ -181,7 +181,7 @@ def _get_cs_contents(sdata: sd.SpatialData) -> pd.DataFrame:
 
 def _get_extent(
     sdata: sd.SpatialData,
-    coordinate_systems: Optional[Union[str, Sequence[str]]] = None,
+    coordinate_systems: None | str | Sequence[str] = None,
     has_images: bool = True,
     has_labels: bool = True,
     has_points: bool = True,
@@ -480,7 +480,7 @@ class OutlineParams:
     gap_size: float
     gap_color: str
     bg_size: float
-    bg_color: Union[str, tuple[float, ...]]
+    bg_color: str | tuple[float, ...]
 
 
 def _set_outline(
@@ -504,7 +504,7 @@ def _set_outline(
     return OutlineParams(outline, gap_size, gap_color, bg_size, bg_color)
 
 
-def _get_subplots(num_images: int, ncols: int = 4, width: int = 4, height: int = 3) -> Union[plt.Figure, plt.Axes]:
+def _get_subplots(num_images: int, ncols: int = 4, width: int = 4, height: int = 3) -> plt.Figure | plt.Axes:
     """Set up the axs objects.
 
     Parameters
@@ -630,7 +630,7 @@ def _normalize(
     return norm
 
 
-def _get_colors_for_categorical_obs(categories: Sequence[Union[str, int]], palette: Palette_t = None) -> list[str]:
+def _get_colors_for_categorical_obs(categories: Sequence[str | int], palette: Palette_t = None) -> list[str]:
     """
     Return a list of colors for a categorical observation.
 
@@ -771,7 +771,7 @@ def _map_color_seg(
 def _get_palette(
     categories: Sequence[Any],
     adata: AnnData | None = None,
-    cluster_key: Optional[str] | None = None,
+    cluster_key: None | str = None,
     palette: Palette_t = None,
     alpha: float = 1.0,
 ) -> Mapping[str, str] | None:
@@ -1082,7 +1082,7 @@ def _flatten_transformation_sequence(
         transformations = list(transformation_sequence.transformations)
         found_bottom_of_tree = False
         while not found_bottom_of_tree:
-            if all([not isinstance(t, sd.transformations.transformations.Sequence) for t in transformations]):
+            if all(not isinstance(t, sd.transformations.transformations.Sequence) for t in transformations):
                 found_bottom_of_tree = True
             else:
                 for idx, t in enumerate(transformations):

src/spatialdata_plot/pp/basic.py

@@ -116,7 +116,7 @@ def get_elements(self, elements: Union[str, list[str]]) -> sd.SpatialData:
         if not isinstance(elements, (str, list)):
             raise TypeError("Parameter 'elements' must be a string or a list of strings.")
 
-        if not all([isinstance(e, str) for e in elements]):
+        if not all(isinstance(e, str) for e in elements):
             raise TypeError("When parameter 'elements' is a list, all elements must be strings.")
 
         if isinstance(elements, str):