fix: ci's and scanpy 1.13 plot compat

.github/workflows/test.yaml

@@ -153,7 +153,16 @@ jobs:
         env:
           PLATFORM: ${{ matrix.os }}
           DISPLAY: :42
-        run: uvx hatch run ${{ matrix.env.name }}:run -v --color=yes -n auto
+        # The stable environments run the spatialdata-plot tests as part of the suite.
+        # The pre-release one leaves them to the dedicated `spatialdata-plot` job below.
+        # Two mechanisms are needed: `-m` deselects after collection, which is too late
+        # for tests/experimental/plotting, whose modules import spatialdata-plot at module
+        # level and so fail during collection; `--ignore` keeps them from being imported
+        # at all. The marker then covers tests that only reach spatialdata-plot at call
+        # time, through squidpy's own lazy import.
+        run: |
+          uvx hatch run ${{ matrix.env.name }}:run -v --color=yes -n auto \
+            ${{ contains(matrix.env.name, 'pre') && '--ignore=tests/experimental/plotting -m "not spatialdata_plot"' || '' }}
 
       - name: Archive figures generated during testing
         if: always()
@@ -219,6 +228,71 @@ jobs:
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: true
 
+  # Everything marked `spatialdata_plot` renders through `spatialdata-plot`, whose own
+  # pre-release compatibility is out of our hands -- its failures would mask squidpy's in
+  # the pre-release environment. So the pre-release run of those tests is carved out here:
+  # still visible (and still failing) on its own line, without turning the whole
+  # pre-release environment red. The stable environments keep running these tests as part
+  # of the suite in the `test` and `coverage` jobs above.
+  spatialdata-plot:
+    name: spatialdata-plot tests (PRE-RELEASE DEPENDENCIES) (ubuntu-latest)
+    needs: [ensure-data-is-cached]
+    runs-on: ubuntu-latest
+    continue-on-error: true
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          filter: blob:none
+          fetch-depth: 0
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
+        with:
+          python-version: "3.14"
+          cache-dependency-glob: pyproject.toml
+
+      - name: Ensure figure directory exists
+        run: mkdir -p "$GITHUB_WORKSPACE/tests/figures"
+
+      - name: Restore data cache
+        id: data-cache
+        uses: actions/cache@v4
+        with:
+          path: data # IMPORTANT: this will fail if scanpy.settings.datasetdir default changes
+          key: data-${{ hashFiles('**/download_data.py') }}
+          restore-keys: |
+            data-
+          enableCrossOsArchive: true
+
+      - name: System dependencies (Linux)
+        run: |
+          sudo apt-get update -y
+          sudo apt-get install automake -y
+
+          # PyQt5 related
+          sudo apt install libxkbcommon-x11-0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-randr0 libxcb-render-util0 libxcb-xinerama0 libxcb-xfixes0 -y
+          sudo Xvfb :42 -screen 0 1920x1080x24 -ac +extension GLX </dev/null &
+
+      - name: create hatch environment
+        run: uvx hatch env create hatch-test.py3.14-pre
+
+      - name: run tests using hatch
+        env:
+          PLATFORM: ubuntu-latest
+          DISPLAY: :42
+        # No coverage upload: the stable `coverage` job above already covers these tests.
+        # `--continue-on-collection-errors` so the marked tests still run and report even
+        # though tests/experimental/plotting fails to import -- both halves of the picture
+        # in one place. This job is expected to be red whenever the stack is broken.
+        run: uvx hatch run hatch-test.py3.14-pre:run -v --color=yes -n auto -m spatialdata_plot --continue-on-collection-errors
+
+      - name: Archive figures generated during testing
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: visual_test_results_Linux_hatch-test.py3.14-pre_spatialdata-plot
+          path: ${{ github.workspace }}/tests/figures/*
+
 
   # Check that all tests defined above pass. This makes it easy to set a single "required" test in branch
   # protection instead of having to update it frequently. See https://github.com/re-actors/alls-green#why.
@@ -229,6 +303,7 @@ jobs:
       - get-environments
       - test
       - coverage
+      - spatialdata-plot
     runs-on: ubuntu-latest
     steps:
       - uses: re-actors/alls-green@release/v1

pyproject.toml

@@ -279,6 +279,7 @@ addopts = [
 ]
 markers = [
   "internet: tests that require internet",
+  "spatialdata_plot: tests that render through spatialdata-plot",
   # the below markers are just there because we import from anndata.tests.helpers,
   # which means pytest sees them despite us not using them.
   "gpu: tests that require GPU",

src/squidpy/_compat.py

@@ -3,29 +3,71 @@
 from importlib.metadata import version
 
 from packaging.version import Version
-from scanpy.plotting._tools.scatterplots import _add_categorical_legend as add_categorical_legend
-from scanpy.plotting._tools.scatterplots import _panel_grid as panel_grid
-from scanpy.plotting._utils import add_colors_for_categorical_sample_annotation
 
 __all__ = [
     # scanpy
     "set_default_colors_for_categorical_obs",
     "add_categorical_legend",
     "panel_grid",
     "add_colors_for_categorical_sample_annotation",
+    "default_palette",
+    "default_frameon",
+    "vector_friendly",
     # anndata
     "ArrayView",
     "SparseCSCView",
     "SparseCSRView",
 ]
 
-# See https://github.com/scverse/squidpy/issues/1061 for more details.
-# Scanpy 0.11.x-0.12.x renamed set_default_colors_for_categorical_obs to _set_default_colors_for_categorical_obs
-# and then changed it back. Try underscore version first, fall back to non-underscore.
+# Scanpy 1.13 moved the pre-v2 plotting internals under ``scanpy.plotting.legacy``.
+# ``scanpy.plotting.__getattr__`` forwards attribute access there, but submodule
+# imports such as ``scanpy.plotting.palettes`` are not covered by it.
 try:
-    from scanpy.plotting._utils import _set_default_colors_for_categorical_obs as set_default_colors_for_categorical_obs
+    from scanpy.plotting.legacy._tools.scatterplots import _add_categorical_legend as add_categorical_legend
+    from scanpy.plotting.legacy._tools.scatterplots import _panel_grid as panel_grid
+    from scanpy.plotting.legacy._utils import (
+        add_colors_for_categorical_sample_annotation,
+        set_default_colors_for_categorical_obs,
+    )
+    from scanpy.plotting.legacy.palettes import default_102 as default_palette
 except ImportError:
-    from scanpy.plotting._utils import set_default_colors_for_categorical_obs
+    from scanpy.plotting._tools.scatterplots import _add_categorical_legend as add_categorical_legend
+    from scanpy.plotting._tools.scatterplots import _panel_grid as panel_grid
+    from scanpy.plotting._utils import add_colors_for_categorical_sample_annotation
+    from scanpy.plotting.palettes import default_102 as default_palette
+
+    # See https://github.com/scverse/squidpy/issues/1061 for more details.
+    # Scanpy 0.11.x-0.12.x renamed set_default_colors_for_categorical_obs to _set_default_colors_for_categorical_obs
+    # and then changed it back. Try underscore version first, fall back to non-underscore.
+    try:
+        from scanpy.plotting._utils import (
+            _set_default_colors_for_categorical_obs as set_default_colors_for_categorical_obs,
+        )
+    except ImportError:
+        from scanpy.plotting._utils import set_default_colors_for_categorical_obs
+
+
+# Scanpy 1.13 also moved these two plotting defaults off ``Settings``, where they were the
+# private ``_frameon`` / ``_vector_friendly`` class attributes, and onto module-level
+# globals in ``scanpy.plotting.legacy.mpl_settings``. ``scanpy.set_figure_params`` rebinds
+# them in either layout, so they must be read at call time rather than imported once.
+try:
+    from scanpy.plotting.legacy import mpl_settings as _mpl_settings
+
+    def default_frameon() -> bool:
+        return _mpl_settings.FRAMEON
+
+    def vector_friendly() -> bool:
+        return _mpl_settings.VECTOR_FRIENDLY
+
+except ImportError:
+    from scanpy import settings as _sc_settings
+
+    def default_frameon() -> bool:
+        return _sc_settings._frameon
+
+    def vector_friendly() -> bool:
+        return _sc_settings._vector_friendly
 
 
 CAN_USE_SPARSE_ARRAY = Version(version("anndata")) >= Version("0.11.0rc1")

src/squidpy/im/_container.py

@@ -19,10 +19,10 @@
 from dask import delayed
 from matplotlib.colors import ListedColormap
 from scanpy import logging as logg
-from scanpy.plotting.palettes import default_102 as default_palette
 from skimage.transform import rescale
 from skimage.util import img_as_float
 
+from squidpy._compat import default_palette
 from squidpy._constants._constants import InferDimensions
 from squidpy._constants._pkg_constants import Key
 from squidpy._docs import d, inject_docs

src/squidpy/pl/_spatial_utils.py

@@ -29,13 +29,12 @@
 from matplotlib_scalebar.scalebar import ScaleBar
 from pandas import CategoricalDtype
 from scanpy import logging as logg
-from scanpy import settings as sc_settings
 from skimage.color import label2rgb
 from skimage.morphology import erosion, square
 from skimage.segmentation import find_boundaries
 from skimage.util import map_array
 
-from squidpy._compat import add_categorical_legend
+from squidpy._compat import add_categorical_legend, default_frameon, vector_friendly
 from squidpy._constants._constants import ScatterShape
 from squidpy._constants._pkg_constants import Key
 from squidpy._utils import NDArrayA
@@ -569,7 +568,7 @@ def _plot_edges(
         ax=ax,
         **kwargs,
     )
-    edge_collection.set_rasterized(sc_settings._vector_friendly)
+    edge_collection.set_rasterized(vector_friendly())
     ax.add_collection(edge_collection)
 
 
@@ -904,7 +903,7 @@ def _panel_grid(
 
 def _set_ax_title(fig_params: FigParams, count: int, value_to_plot: str | None = None) -> Axes:
     ax = fig_params.axs[count] if fig_params.axs is not None else fig_params.ax
-    if not (sc_settings._frameon if fig_params.frameon is None else fig_params.frameon):
+    if not (default_frameon() if fig_params.frameon is None else fig_params.frameon):
         ax.axis("off")
 
     if fig_params.title is None:
@@ -959,7 +958,7 @@ def _plot_scatter(
             coords[:, 1],
             s=outline_params.bg_size,
             c=outline_params.bg_color,
-            rasterized=sc_settings._vector_friendly,
+            rasterized=vector_friendly(),
             cmap=cmap_params.cmap,
             norm=norm,
             **kwargs,
@@ -970,7 +969,7 @@ def _plot_scatter(
             coords[:, 1],
             s=outline_params.gap_size,
             c=outline_params.gap_color,
-            rasterized=sc_settings._vector_friendly,
+            rasterized=vector_friendly(),
             cmap=cmap_params.cmap,
             norm=norm,
             **kwargs,
@@ -981,7 +980,7 @@ def _plot_scatter(
         coords[:, 1],
         c=np.array(color_vector),
         s=size,
-        rasterized=sc_settings._vector_friendly,
+        rasterized=vector_friendly(),
         cmap=cmap_params.cmap,
         norm=norm,
         **kwargs,

tests/experimental/plotting/conftest.py

@@ -0,0 +1,17 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+HERE = Path(__file__).parent
+
+
+def pytest_collection_modifyitems(items):
+    """Mark everything in this directory as requiring spatialdata-plot.
+
+    Every module here imports ``spatialdata_plot`` at module level, so applying the
+    marker from the directory keeps it in one place and covers files added later.
+    The hook is session-wide even though this conftest is not, hence the path filter.
+    """
+    for item in items:
+        if item.path.is_relative_to(HERE):
+            item.add_marker("spatialdata_plot")

tests/experimental/plotting/test_stain_normalize.py

@@ -0,0 +1,37 @@
+from __future__ import annotations
+
+import matplotlib.pyplot as plt
+import spatialdata_plot as sdp
+import xarray as xr
+from spatialdata.models import Image2DModel
+
+import squidpy as sq
+from squidpy.experimental.im import fit_stain_reference, normalize_stains
+from squidpy.experimental.im._utils import get_element_data
+from tests.conftest import PlotTester, PlotTesterMeta
+
+_ = sdp  # registers the `.pl` spatialdata accessor
+
+
+class TestStainNormalizationVisual(PlotTester, metaclass=PlotTesterMeta):
+    def test_plot_reinhard_before_after(self, sdata_hne) -> None:
+        """Visual: a re-stained source (left) normalized back to the H&E reference (right)."""
+        image_key = next(iter(sdata_hne.images))
+        sq.experimental.im.detect_tissue(sdata_hne, image_key)
+        reference = fit_stain_reference(sdata_hne, image_key, method="reinhard")
+
+        # Deterministically warm/cool the channels to simulate a different
+        # staining batch, so the before/after panels are visibly distinct.
+        da_rgb = get_element_data(sdata_hne.images[image_key], "auto", "image", image_key).astype("float32")
+        weights = xr.DataArray([1.4, 1.0, 0.6], dims="c", coords={"c": da_rgb.coords["c"]})
+        shifted = (da_rgb * weights).clip(0, 255).astype("uint8")
+        sdata_hne.images["hne_shifted"] = Image2DModel.parse(shifted.data, dims=shifted.dims)
+
+        # `hne_shifted` shares geometry with `image_key`; reuse its tissue mask.
+        normalize_stains(
+            sdata_hne, "hne_shifted", reference, image_key_added="hne_normalized", tissue_mask_key=f"{image_key}_tissue"
+        )
+
+        _, axes = plt.subplots(1, 2, figsize=(8, 4))
+        sdata_hne.pl.render_images("hne_shifted").pl.show(ax=axes[0], title="before")
+        sdata_hne.pl.render_images("hne_normalized").pl.show(ax=axes[1], title="after")

tests/experimental/test_stain_normalize.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 
 import dask.array as da
-import matplotlib.pyplot as plt
 import numpy as np
 import pytest
 import spatialdata as sd
-import spatialdata_plot as sdp
 import xarray as xr
 from spatialdata.models import Image2DModel, Labels2DModel
 from spatialdata.transformations import Scale, get_transformation, set_transformation
@@ -18,9 +16,6 @@
     normalize_stains,
 )
 from squidpy.experimental.im._utils import get_element_data
-from tests.conftest import PlotTester, PlotTesterMeta
-
-_ = sdp  # registers the `.pl` spatialdata accessor
 
 
 def _make_sdata(
@@ -227,27 +222,3 @@ def test_fit_apply_smoke(self, sdata_hne) -> None:
         out = sq.experimental.im.normalize_stains(sdata_hne, image_key, ref, inplace=False)
         assert "c" in out.dims
         assert out.sizes["c"] == 3
-
-
-class TestStainNormalizationVisual(PlotTester, metaclass=PlotTesterMeta):
-    def test_plot_reinhard_before_after(self, sdata_hne) -> None:
-        """Visual: a re-stained source (left) normalized back to the H&E reference (right)."""
-        image_key = next(iter(sdata_hne.images))
-        sq.experimental.im.detect_tissue(sdata_hne, image_key)
-        reference = fit_stain_reference(sdata_hne, image_key, method="reinhard")
-
-        # Deterministically warm/cool the channels to simulate a different
-        # staining batch, so the before/after panels are visibly distinct.
-        da_rgb = get_element_data(sdata_hne.images[image_key], "auto", "image", image_key).astype("float32")
-        weights = xr.DataArray([1.4, 1.0, 0.6], dims="c", coords={"c": da_rgb.coords["c"]})
-        shifted = (da_rgb * weights).clip(0, 255).astype("uint8")
-        sdata_hne.images["hne_shifted"] = Image2DModel.parse(shifted.data, dims=shifted.dims)
-
-        # `hne_shifted` shares geometry with `image_key`; reuse its tissue mask.
-        normalize_stains(
-            sdata_hne, "hne_shifted", reference, image_key_added="hne_normalized", tissue_mask_key=f"{image_key}_tissue"
-        )
-
-        _, axes = plt.subplots(1, 2, figsize=(8, 4))
-        sdata_hne.pl.render_images("hne_shifted").pl.show(ax=axes[0], title="before")
-        sdata_hne.pl.render_images("hne_normalized").pl.show(ax=axes[1], title="after")

tests/experimental/test_tiling_qc.py

@@ -366,6 +366,9 @@ def sdata_with_qc(sdata_tile_boundary):
     return sdata
 
 
+# `sq.experimental.pl.tiling_qc` imports spatialdata-plot lazily, so this module
+# imports cleanly and only these tests need excluding when that stack is broken.
+@pytest.mark.spatialdata_plot
 class TestTilingQCVisual(PlotTester, metaclass=PlotTesterMeta):
     def test_plot_tiling_qc_cut_score(self, sdata_with_qc):
         """Visual: labels coloured by cut_score."""