image_comparer = <function image_comparer.<locals>.make_comparer at 0x7f16c0bc68b0>

    @needs("leidenalg")
    def test_pbmc3k(image_comparer):
        save_and_compare_images = image_comparer(ROOT, FIGS, tol=20)
    
        adata = sc.read(
            './data/pbmc3k_raw.h5ad', backup_url='http://falexwolf.de/data/pbmc3k_raw.h5ad'
        )
    
        # Preprocessing
    
        sc.pl.highest_expr_genes(adata, n_top=20, show=False)
        save_and_compare_images('highest_expr_genes')
    
        sc.pp.filter_cells(adata, min_genes=200)
        sc.pp.filter_genes(adata, min_cells=3)
    
        mito_genes = [name for name in adata.var_names if name.startswith('MT-')]
        # for each cell compute fraction of counts in mito genes vs. all genes
        # the `.A1` is only necessary as X is sparse to transform to a dense array after summing
        adata.obs['percent_mito'] = (
            np.sum(adata[:, mito_genes].X, axis=1).A1 / np.sum(adata.X, axis=1).A1
        )
        # add the total counts per cell as observations-annotation to adata
        adata.obs['n_counts'] = adata.X.sum(axis=1).A1
    
>       sc.pl.violin(
            adata,
            ['n_genes', 'n_counts', 'percent_mito'],
            jitter=False,
            multi_panel=True,
            show=False,
        )

scanpy/tests/notebooks/test_pbmc3k.py:54: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
scanpy/plotting/_anndata.py:793: in violin
    g = sns.catplot(
/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:2927: in catplot
    p.plot_violins(
/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:1145: in plot_violins
    self._configure_legend(ax, legend_artist, common_kws)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <seaborn.categorical._CategoricalPlotter object at 0x7f16c0c42460>
ax = None
func = <function _get_patch_legend_artist.<locals>.legend_artist at 0x7f16c15b5e50>
common_kws = {'edgecolor': (0.24823529411764705, 0.24823529411764705, 0.24823529411764705), 'linewidth': 1.25}
semantic_kws = None

    def _configure_legend(self, ax, func, common_kws=None, semantic_kws=None):
    
        if self.legend == "auto":
            show_legend = not self._redundant_hue and self.input_format != "wide"
        else:
            show_legend = bool(self.legend)
    
        if show_legend:
            self.add_legend_data(ax, func, common_kws, semantic_kws=semantic_kws)
>           handles, _ = ax.get_legend_handles_labels()
E           AttributeError: 'NoneType' object has no attribute 'get_legend_handles_labels'

/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:419: AttributeError

image_comparer = <function image_comparer.<locals>.make_comparer at 0x7f16c270fe50>

    def test_violin(image_comparer):
        save_and_compare_images = image_comparer(ROOT, FIGS, tol=40)
    
        with plt.rc_context():
            sc.pl.set_rcParams_defaults()
            sc.set_figure_params(dpi=50, color_map='viridis')
    
            pbmc = pbmc68k_reduced()
>           sc.pl.violin(
                pbmc,
                ['n_genes', 'percent_mito', 'n_counts'],
                stripplot=True,
                multi_panel=True,
                jitter=True,
                show=False,
            )

scanpy/tests/test_plotting.py:487: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
scanpy/plotting/_anndata.py:793: in violin
    g = sns.catplot(
/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:2927: in catplot
    p.plot_violins(
/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:1145: in plot_violins
    self._configure_legend(ax, legend_artist, common_kws)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <seaborn.categorical._CategoricalPlotter object at 0x7f16c14cbc70>
ax = None
func = <function _get_patch_legend_artist.<locals>.legend_artist at 0x7f16c1404ee0>
common_kws = {'edgecolor': (0.24823529411764705, 0.24823529411764705, 0.24823529411764705), 'linewidth': 1.25}
semantic_kws = None

    def _configure_legend(self, ax, func, common_kws=None, semantic_kws=None):
    
        if self.legend == "auto":
            show_legend = not self._redundant_hue and self.input_format != "wide"
        else:
            show_legend = bool(self.legend)
    
        if show_legend:
            self.add_legend_data(ax, func, common_kws, semantic_kws=semantic_kws)
>           handles, _ = ax.get_legend_handles_labels()
E           AttributeError: 'NoneType' object has no attribute 'get_legend_handles_labels'

/opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/seaborn/categorical.py:419: AttributeError