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timtreistimtreis
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fix: full scanpy 1.13 compatibility layer
scanpy 1.13 reorganized its plotting internals, breaking spatialdata-plot on pre-release scanpy. Consolidate every reliance on scanpy internals into one version-tolerant module, _scanpy_compat, that imports each symbol from the new location with a fallback to the old: - palettes default_20/28/102 scanpy.plotting.palettes -> .legacy.palettes - _add_categorical_legend scanpy.plotting._tools... -> .legacy._tools... - add_colors_for_categorical_... scanpy.plotting._utils -> .legacy._utils - vector_friendly() settings._vector_friendly removed in 1.13; default False Route all call sites (render.py, utils.py, _color.py, _palette.py) through _scanpy_compat. Behaviour is unchanged: the relocated palettes/helpers are frozen copies (identical values and signatures), and vector_friendly keeps honouring sc.set_figure_params on older scanpy. scanpy public API still used directly (sc.get.obs_df, settings.figdir, set_figure_params) is unaffected. Verified: the full non-visual suite passes and no scanpy AttributeError/ ImportError occurs when resolved against scanpy 1.13.0a1.
1 parent 5627c9b commit 18069cb

6 files changed

Lines changed: 60 additions & 26 deletions

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‎src/spatialdata_plot/pl/_color.py‎

Lines changed: 6 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -28,7 +28,6 @@
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from numpy.random import default_rng
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from pandas.api.types import CategoricalDtype, is_bool_dtype, is_numeric_dtype, is_string_dtype
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from pandas.core.arrays.categorical import Categorical
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from scanpy.plotting._utils import add_colors_for_categorical_sample_annotation
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from skimage.color import label2rgb
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from skimage.morphology import erosion, footprint_rectangle
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from skimage.util import map_array
@@ -42,7 +41,12 @@
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)
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from spatialdata_plot._logging import logger
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from spatialdata_plot.pl._scanpy_palettes import default_20, default_28, default_102
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from spatialdata_plot.pl._scanpy_compat import (
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add_colors_for_categorical_sample_annotation,
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default_20,
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default_28,
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default_102,
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)
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from spatialdata_plot.pl.render_params import (
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CmapParams,
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Color,

‎src/spatialdata_plot/pl/_palette.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -21,7 +21,7 @@
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from matplotlib.colors import ListedColormap, to_hex, to_rgb
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from matplotlib.pyplot import colormaps as mpl_colormaps
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24-
from spatialdata_plot.pl._scanpy_palettes import default_20, default_28, default_102
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from spatialdata_plot.pl._scanpy_compat import default_20, default_28, default_102
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if TYPE_CHECKING:
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import spatialdata as sd

‎src/spatialdata_plot/pl/_scanpy_compat.py‎

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,46 @@
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"""Version-tolerant access to scanpy internals used by spatialdata-plot.
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scanpy 1.13 relocated the default palettes and several private plotting helpers from
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``scanpy.plotting.{palettes,_tools,_utils}`` to ``scanpy.plotting.legacy.*``, and dropped the
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``settings._vector_friendly`` flag. The values and behaviour are unchanged, so we import from
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whichever path the installed scanpy exposes and re-export from a single place. This keeps
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spatialdata-plot working on scanpy both < and >= 1.13 and confines the reliance on scanpy
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internals to one module.
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"""
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from scanpy._settings import settings as _sc_settings
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try: # scanpy >= 1.13
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from scanpy.plotting.legacy.palettes import default_20, default_28, default_102
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except ImportError: # scanpy < 1.13
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from scanpy.plotting.palettes import default_20, default_28, default_102
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try: # scanpy >= 1.13
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from scanpy.plotting.legacy._tools.scatterplots import _add_categorical_legend
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except ImportError: # scanpy < 1.13
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from scanpy.plotting._tools.scatterplots import _add_categorical_legend
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try: # scanpy >= 1.13
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from scanpy.plotting.legacy._utils import add_colors_for_categorical_sample_annotation
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except ImportError: # scanpy < 1.13
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from scanpy.plotting._utils import add_colors_for_categorical_sample_annotation
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def vector_friendly() -> bool:
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"""scanpy's rasterize-for-vector-output flag, read dynamically.
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Controls whether scatter/image artists are rasterized (so vector output stays small). scanpy
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1.13 removed the ``settings._vector_friendly`` attribute; default to ``False`` there (scanpy's
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historical default), while still honouring ``sc.set_figure_params(vector_friendly=...)`` on
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older scanpy.
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"""
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return bool(getattr(_sc_settings, "_vector_friendly", False))
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__all__ = [
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"_add_categorical_legend",
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"add_colors_for_categorical_sample_annotation",
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"default_20",
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"default_28",
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"default_102",
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"vector_friendly",
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]

‎src/spatialdata_plot/pl/_scanpy_palettes.py‎

Lines changed: 0 additions & 14 deletions
This file was deleted.

‎src/spatialdata_plot/pl/render.py‎

Lines changed: 6 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -20,8 +20,6 @@
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from matplotlib import patheffects
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from matplotlib.cm import ScalarMappable
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from matplotlib.colors import BoundaryNorm, Colormap, ListedColormap, Normalize, to_rgba_array
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from scanpy._settings import settings as sc_settings
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from scanpy.plotting._tools.scatterplots import _add_categorical_legend
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from spatialdata import get_extent, get_values
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from spatialdata.models import PointsModel, ShapesModel, get_table_keys
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from spatialdata.transformations import set_transformation
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_scale_geometries,
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_validate_polygons,
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)
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from spatialdata_plot.pl._scanpy_compat import _add_categorical_legend, vector_friendly
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from spatialdata_plot.pl._validate import (
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_check_obs_var_shadow,
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)
@@ -933,7 +932,7 @@ def _draw_centroids(xy: np.ndarray, radius: float | None = None) -> None:
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s=render_params.scale,
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c=np.array(["white"]), # hack, will be invisible bc fill_alpha=0
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render_params=render_params,
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rasterized=sc_settings._vector_friendly,
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rasterized=vector_friendly(),
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cmap=None,
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fill_alpha=0.0,
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outline_alpha=render_params.outline_alpha[0],
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s=render_params.scale,
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c=np.array(["white"]), # hack, will be invisible bc fill_alpha=0
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render_params=render_params,
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rasterized=sc_settings._vector_friendly,
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rasterized=vector_friendly(),
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cmap=None,
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fill_alpha=0.0,
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outline_alpha=render_params.outline_alpha[0],
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s=render_params.scale,
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c=np.array(["white"]), # hack, will be invisible bc fill_alpha=0
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render_params=render_params,
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rasterized=sc_settings._vector_friendly,
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rasterized=vector_friendly(),
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cmap=None,
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fill_alpha=0.0,
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outline_alpha=render_params.outline_alpha[1],
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c=color_spec.to_rgba(render_params.cmap_params),
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prebuilt_paths=prebuilt_paths,
986985
render_params=render_params,
987-
rasterized=sc_settings._vector_friendly,
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rasterized=vector_friendly(),
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cmap=render_params.cmap_params.cmap,
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fill_alpha=render_params.fill_alpha,
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outline_alpha=0.0,
@@ -1072,7 +1071,7 @@ def _scatter_points(
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# `size` at high dpi) only that ring survives, rendering markers as hollow outlines.
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# linewidths=0 keeps them solid fills whose radius honours `size`.
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linewidths=0,
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rasterized=sc_settings._vector_friendly,
1074+
rasterized=vector_friendly(),
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alpha=alpha,
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transform=trans_data,
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zorder=zorder,

‎src/spatialdata_plot/pl/utils.py‎

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -31,7 +31,6 @@
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from pandas.api.types import CategoricalDtype, is_numeric_dtype
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from pandas.core.arrays.categorical import Categorical
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from scanpy import settings
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from scanpy.plotting._tools.scatterplots import _add_categorical_legend
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from spatialdata import (
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SpatialData,
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get_element_annotators,
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from xarray import DataArray, DataTree
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from spatialdata_plot._logging import logger
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from spatialdata_plot.pl._scanpy_palettes import default_102
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from spatialdata_plot.pl._scanpy_compat import _add_categorical_legend, default_102
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from spatialdata_plot.pl.render_params import (
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Color,
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ColorbarSpec,

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