Backport PR #4091 on branch 1.12.x (test: fix matplotlib deprecations) (#4092)

Author: flying-sheep

pyproject.toml

@@ -57,7 +57,8 @@ dependencies = [
     "h5py>=3.11",
     "joblib",
     "legacy-api-wrap>=1.5",                     # for positional API deprecations
-    "matplotlib>=3.9",
+    # skip 3.11.0rc1 for now: https://github.com/matplotlib/matplotlib/issues/31575
+    "matplotlib>=3.9,!=3.11.0rc1",
     "natsort",
     "networkx>=2.8.8",
     "numba>=0.60",
@@ -259,8 +260,11 @@ filterwarnings = [
     "error",
     # Umap warns when tensorflow isn’t installed.
     "ignore::ImportWarning:umap",
+    # matplotlib<3.10.7 uses old pyparsing APIs
+    "ignore::pyparsing.warnings.PyparsingDeprecationWarning",
     # seaborn≤0.13.2 causes some matplotlib warnings
     "ignore::PendingDeprecationWarning:seaborn",
+    "ignore:vert.*bool was deprecated:matplotlib.MatplotlibDeprecationWarning:seaborn",
     # matplotlib<3.10.4 causes a Pillow warning
     "ignore:.*Pillow:DeprecationWarning",
     # networkx 2.x warns about scipy.sparse changes
@@ -273,9 +277,7 @@ filterwarnings = [
     "ignore:FNV hashing is not implemented in Numba.*:UserWarning",
     # we want to see and eventually fix these
     "default::numba.core.errors.NumbaPerformanceWarning",
-    "default:.*TSNE.*random.*to.*pca:FutureWarning",                       # we should set init=obsm["X_pca"] or so
-    # matplotlib <3.11 uses old pyparsing APIs
-    "ignore::pyparsing.warnings.PyparsingDeprecationWarning",
+    "default:.*TSNE.*random.*to.*pca:FutureWarning",                                    # we should set init=obsm["X_pca"] or so
     # igraph vs leidenalg warning
     "ignore:The `igraph` implementation of leiden clustering:UserWarning",
     # everybody uses this zarr 3 feature, including us, XArray, lots of data out there …

src/scanpy/plotting/_tools/paga.py

@@ -1358,8 +1358,7 @@ def moving_average(a):
             cmap=matplotlib.colors.ListedColormap(
                 # the following line doesn't work because of normalization
                 # adata.uns['paga_groups_colors'])
-                palette_groups[np.min(groups).astype(int) :],
-                N=int(np.max(groups) + 1 - np.min(groups)),
+                palette_groups[int(np.min(groups)) : int(np.max(groups)) + 1]
             ),
         )
         if show_yticks:

src/scanpy/plotting/_tools/scatterplots.py

@@ -4,7 +4,6 @@
 import re
 import textwrap
 from collections.abc import Sequence
-from copy import copy
 from functools import cache, partial
 from itertools import combinations, product
 from numbers import Integral
@@ -169,8 +168,7 @@ def embedding(  # noqa: PLR0912, PLR0913, PLR0915
             raise ValueError(msg)
         else:
             cmap = color_map
-    cmap = copy(colormaps.get_cmap(cmap))
-    cmap.set_bad(na_color)
+    cmap = colormaps.get_cmap(cmap).with_extremes(bad=na_color)
     # Prevents warnings during legend creation
     na_color = colors.to_hex(na_color, keep_alpha=True)