Update tests for compatability with matplotlib 3.5.0

doc/requirements.txt

@@ -1,3 +1,4 @@
+docutils<=0.17  # https://sourceforge.net/p/docutils/bugs/431/
 sphinx==3.3.1
 sphinx_bootstrap_theme==0.7.1
 numpydoc

seaborn/tests/test_categorical.py

@@ -110,6 +110,14 @@ class CategoricalFixture:
     df = pd.DataFrame(dict(y=y, g=g, h=h, u=u))
     x_df["W"] = g
 
+    def get_box_artists(self, ax):
+
+        if Version(mpl.__version__) < Version("3.5.0b0"):
+            return ax.artists
+        else:
+            # Exclude labeled patches, which are for the legend
+            return [p for p in ax.patches if not p.get_label()]
+
 
 class TestCategoricalPlotter(CategoricalFixture):
 
@@ -855,27 +863,27 @@ def test_hue_offsets(self):
     def test_axes_data(self):
 
         ax = cat.boxplot(x="g", y="y", data=self.df)
-        assert len(ax.artists) == 3
+        assert len(self.get_box_artists(ax)) == 3
 
         plt.close("all")
 
         ax = cat.boxplot(x="g", y="y", hue="h", data=self.df)
-        assert len(ax.artists) == 6
+        assert len(self.get_box_artists(ax)) == 6
 
         plt.close("all")
 
     def test_box_colors(self):
 
         ax = cat.boxplot(x="g", y="y", data=self.df, saturation=1)
         pal = palettes.color_palette(n_colors=3)
-        for patch, color in zip(ax.artists, pal):
+        for patch, color in zip(self.get_box_artists(ax), pal):
             assert patch.get_facecolor()[:3] == color
 
         plt.close("all")
 
         ax = cat.boxplot(x="g", y="y", hue="h", data=self.df, saturation=1)
         pal = palettes.color_palette(n_colors=2)
-        for patch, color in zip(ax.artists, pal * 2):
+        for patch, color in zip(self.get_box_artists(ax), pal * 2):
             assert patch.get_facecolor()[:3] == color
 
         plt.close("all")
@@ -884,7 +892,7 @@ def test_draw_missing_boxes(self):
 
         ax = cat.boxplot(x="g", y="y", data=self.df,
                          order=["a", "b", "c", "d"])
-        assert len(ax.artists) == 3
+        assert len(self.get_box_artists(ax)) == 3
 
     def test_missing_data(self):
 
@@ -894,13 +902,13 @@ def test_missing_data(self):
         y[-2:] = np.nan
 
         ax = cat.boxplot(x=x, y=y)
-        assert len(ax.artists) == 3
+        assert len(self.get_box_artists(ax)) == 3
 
         plt.close("all")
 
         y[-1] = 0
         ax = cat.boxplot(x=x, y=y, hue=h)
-        assert len(ax.artists) == 7
+        assert len(self.get_box_artists(ax)) == 7
 
         plt.close("all")
 
@@ -2766,11 +2774,11 @@ def test_plot_elements(self):
 
         g = cat.catplot(x="g", y="y", data=self.df, kind="box")
         want_artists = self.g.unique().size
-        assert len(g.ax.artists) == want_artists
+        assert len(self.get_box_artists(g.ax)) == want_artists
 
         g = cat.catplot(x="g", y="y", hue="h", data=self.df, kind="box")
         want_artists = self.g.unique().size * self.h.unique().size
-        assert len(g.ax.artists) == want_artists
+        assert len(self.get_box_artists(g.ax)) == want_artists
 
         g = cat.catplot(x="g", y="y", data=self.df,
                         kind="violin", inner=None)
@@ -3137,14 +3145,14 @@ def test_box_colors(self):
 
         ax = cat.boxenplot(x="g", y="y", data=self.df, saturation=1)
         pal = palettes.color_palette(n_colors=3)
-        for patch, color in zip(ax.artists, pal):
+        for patch, color in zip(self.get_box_artists(ax), pal):
             assert patch.get_facecolor()[:3] == color
 
         plt.close("all")
 
         ax = cat.boxenplot(x="g", y="y", hue="h", data=self.df, saturation=1)
         pal = palettes.color_palette(n_colors=2)
-        for patch, color in zip(ax.artists, pal * 2):
+        for patch, color in zip(self.get_box_artists(ax), pal * 2):
             assert patch.get_facecolor()[:3] == color
 
         plt.close("all")

seaborn/tests/test_distributions.py

@@ -39,6 +39,27 @@
 )
 
 
+def get_contour_coords(c):
+    """Provide compatability for change in contour artist type in mpl3.5."""
+    # See https://github.com/matplotlib/matplotlib/issues/20906
+    if isinstance(c, mpl.collections.LineCollection):
+        return c.get_segments()
+    elif isinstance(c, mpl.collections.PathCollection):
+        return [p.vertices[:np.argmax(p.codes) + 1] for p in c.get_paths()]
+
+
+def get_contour_color(c):
+    """Provide compatability for change in contour artist type in mpl3.5."""
+    # See https://github.com/matplotlib/matplotlib/issues/20906
+    if isinstance(c, mpl.collections.LineCollection):
+        return c.get_color()
+    elif isinstance(c, mpl.collections.PathCollection):
+        if c.get_facecolor().size:
+            return c.get_facecolor()
+        else:
+            return c.get_edgecolor()
+
+
 class TestDistPlot(object):
 
     rs = np.random.RandomState(0)
@@ -851,7 +872,10 @@ def test_legend(self, long_df):
         for label, level in zip(legend_labels, order):
             assert label.get_text() == level
 
-        legend_artists = ax.legend_.findobj(mpl.lines.Line2D)[::2]
+        legend_artists = ax.legend_.findobj(mpl.lines.Line2D)
+        if Version(mpl.__version__) < Version("3.5.0b0"):
+            # https://github.com/matplotlib/matplotlib/pull/20699
+            legend_artists = legend_artists[::2]
         palette = color_palette()
         for artist, color in zip(legend_artists, palette):
             assert_colors_equal(artist.get_color(), color)
@@ -902,7 +926,7 @@ def test_fill_artists(self, long_df):
             f, ax = plt.subplots()
             kdeplot(data=long_df, x="x", y="y", hue="c", fill=fill)
             for c in ax.collections:
-                if fill:
+                if fill or Version(mpl.__version__) >= Version("3.5.0b0"):
                     assert isinstance(c, mpl.collections.PathCollection)
                 else:
                     assert isinstance(c, mpl.collections.LineCollection)
@@ -918,8 +942,8 @@ def test_common_norm(self, rng):
         kdeplot(x=x, y=y, hue=hue, common_norm=True, ax=ax1)
         kdeplot(x=x, y=y, hue=hue, common_norm=False, ax=ax2)
 
-        n_seg_1 = sum([len(c.get_segments()) > 0 for c in ax1.collections])
-        n_seg_2 = sum([len(c.get_segments()) > 0 for c in ax2.collections])
+        n_seg_1 = sum([len(get_contour_coords(c)) > 0 for c in ax1.collections])
+        n_seg_2 = sum([len(get_contour_coords(c)) > 0 for c in ax2.collections])
         assert n_seg_2 > n_seg_1
 
     def test_log_scale(self, rng):
@@ -946,7 +970,7 @@ def test_log_scale(self, rng):
         ax2.contour(10 ** xx, yy, density, levels=levels)
 
         for c1, c2 in zip(ax1.collections, ax2.collections):
-            assert_array_equal(c1.get_segments(), c2.get_segments())
+            assert_array_equal(get_contour_coords(c1), get_contour_coords(c2))
 
     def test_bandwidth(self, rng):
 
@@ -959,7 +983,7 @@ def test_bandwidth(self, rng):
         kdeplot(x=x, y=y, bw_adjust=2, ax=ax2)
 
         for c1, c2 in zip(ax1.collections, ax2.collections):
-            seg1, seg2 = c1.get_segments(), c2.get_segments()
+            seg1, seg2 = get_contour_coords(c1), get_contour_coords(c2)
             if seg1 + seg2:
                 x1 = seg1[0][:, 0]
                 x2 = seg2[0][:, 0]
@@ -980,25 +1004,25 @@ def test_weights(self, rng):
         kdeplot(x=x, y=y, hue=hue, weights=weights, ax=ax2)
 
         for c1, c2 in zip(ax1.collections, ax2.collections):
-            if c1.get_segments() and c2.get_segments():
-                seg1 = np.concatenate(c1.get_segments(), axis=0)
-                seg2 = np.concatenate(c2.get_segments(), axis=0)
+            if get_contour_coords(c1) and get_contour_coords(c2):
+                seg1 = np.concatenate(get_contour_coords(c1), axis=0)
+                seg2 = np.concatenate(get_contour_coords(c2), axis=0)
                 assert not np.array_equal(seg1, seg2)
 
     def test_hue_ignores_cmap(self, long_df):
 
         with pytest.warns(UserWarning, match="cmap parameter ignored"):
             ax = kdeplot(data=long_df, x="x", y="y", hue="c", cmap="viridis")
 
-        assert_colors_equal(ax.collections[0].get_color(), "C0")
+        assert_colors_equal(get_contour_color(ax.collections[0]), "C0")
 
     def test_contour_line_colors(self, long_df):
 
         color = (.2, .9, .8, 1)
         ax = kdeplot(data=long_df, x="x", y="y", color=color)
 
         for c in ax.collections:
-            assert_colors_equal(c.get_color(), color)
+            assert_colors_equal(get_contour_color(c), color)
 
     def test_contour_fill_colors(self, long_df):
 
@@ -1030,7 +1054,7 @@ def test_levels_and_thresh(self, long_df):
         kdeplot(**plot_kws, levels=np.linspace(thresh, 1, n), ax=ax2)
 
         for c1, c2 in zip(ax1.collections, ax2.collections):
-            assert_array_equal(c1.get_segments(), c2.get_segments())
+            assert_array_equal(get_contour_coords(c1), get_contour_coords(c2))
 
         with pytest.raises(ValueError):
             kdeplot(**plot_kws, levels=[0, 1, 2])
@@ -1042,7 +1066,7 @@ def test_levels_and_thresh(self, long_df):
         kdeplot(**plot_kws, levels=n, thresh=0, ax=ax2)
 
         for c1, c2 in zip(ax1.collections, ax2.collections):
-            assert_array_equal(c1.get_segments(), c2.get_segments())
+            assert_array_equal(get_contour_coords(c1), get_contour_coords(c2))
         for c1, c2 in zip(ax1.collections, ax2.collections):
             assert_array_equal(c1.get_facecolors(), c2.get_facecolors())
 
@@ -2322,13 +2346,13 @@ def test_bivariate_kde_norm(self, rng):
         z = [0] * 80 + [1] * 20
 
         g = displot(x=x, y=y, col=z, kind="kde", levels=10)
-        l1 = sum(bool(c.get_segments()) for c in g.axes.flat[0].collections)
-        l2 = sum(bool(c.get_segments()) for c in g.axes.flat[1].collections)
+        l1 = sum(bool(get_contour_coords(c)) for c in g.axes.flat[0].collections)
+        l2 = sum(bool(get_contour_coords(c)) for c in g.axes.flat[1].collections)
         assert l1 > l2
 
         g = displot(x=x, y=y, col=z, kind="kde", levels=10, common_norm=False)
-        l1 = sum(bool(c.get_segments()) for c in g.axes.flat[0].collections)
-        l2 = sum(bool(c.get_segments()) for c in g.axes.flat[1].collections)
+        l1 = sum(bool(get_contour_coords(c)) for c in g.axes.flat[0].collections)
+        l2 = sum(bool(get_contour_coords(c)) for c in g.axes.flat[1].collections)
         assert l1 == l2
 
     def test_bivariate_hist_norm(self, rng):