--- Begin Message ---
Source: seaborn
Version: 0.11.2-2
Severity: important
Justification: FTBFS
Tags: bookworm sid ftbfs
User: [email protected]
Usertags: ftbfs-matplotlib35
Hi,
During a rebuild of all packages in sid, your package failed to build
on amd64, using matplotlib 3.5 currently in experimental. This version
will soon be uploaded to unstable.
If you have questions about this, please contact Sandro Tosi
<[email protected]>.
Relevant part (hopefully):
> make[1]: Entering directory '/<<PKGBUILDDIR>>'
> xvfb-run --auto-servernum --server-num=20 dh_auto_test override_dh_auto_test
> I: pybuild base:232: cd /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build;
> python3.9 -m pytest
> ============================= test session starts
> ==============================
> platform linux -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-0.13.0
> rootdir: /<<PKGBUILDDIR>>, configfile: pytest.ini
> collected 1048 items
>
> seaborn/tests/test_algorithms.py ............ssssss [
> 1%]
> seaborn/tests/test_axisgrid.py ......................................... [
> 5%]
> ........................................................................ [
> 12%]
> . [
> 12%]
> seaborn/tests/test_categorical.py ................................F.FF.. [
> 16%]
> ...................................................................F.... [
> 23%]
> ..................................s [
> 26%]
> seaborn/tests/test_core.py ............................................. [
> 30%]
> ...sss............ [
> 32%]
> seaborn/tests/test_decorators.py ... [
> 32%]
> seaborn/tests/test_distributions.py .................................... [
> 36%]
> ...........................F..FFFFFFF..F................................ [
> 43%]
> ........................................................................ [
> 49%]
> ..........................................FFF...........F.. [
> 55%]
> seaborn/tests/test_docstrings.py .... [
> 55%]
> seaborn/tests/test_matrix.py ........................................... [
> 60%]
> ..ss.......................................... [
> 64%]
> seaborn/tests/test_miscplot.py .s [
> 64%]
> seaborn/tests/test_palettes.py ..................................... [
> 68%]
> seaborn/tests/test_rcmod.py ....................s.s [
> 70%]
> seaborn/tests/test_regression.py ................ss.ss.........ssss..... [
> 74%]
> ..............s.. [
> 75%]
> seaborn/tests/test_relational.py ....................................... [
> 79%]
> ........................................................................ [
> 86%]
> ............................................. [
> 90%]
> seaborn/tests/test_statistics.py ....................................... [
> 94%]
> ......s.. [
> 95%]
> seaborn/tests/test_utils.py ssss........................................ [
> 99%]
> .......
> [100%]
>
> =================================== FAILURES
> ===================================
> ________________________ TestBoxPlotter.test_axes_data
> _________________________
>
> self = <seaborn.tests.test_categorical.TestBoxPlotter object at
> 0x7f3e7111f220>
>
> def test_axes_data(self):
>
> ax = cat.boxplot(x="g", y="y", data=self.df)
> > assert len(ax.artists) == 3
> E AssertionError: assert 0 == 3
> E + where 0 = len(<Axes.ArtistList of 0 artists>)
> E + where <Axes.ArtistList of 0 artists> = <AxesSubplot:xlabel='g',
> ylabel='y'>.artists
>
> seaborn/tests/test_categorical.py:775: AssertionError
> ____________________ TestBoxPlotter.test_draw_missing_boxes
> ____________________
>
> self = <seaborn.tests.test_categorical.TestBoxPlotter object at
> 0x7f3e70a04700>
>
> 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
> E AssertionError: assert 0 == 3
> E + where 0 = len(<Axes.ArtistList of 0 artists>)
> E + where <Axes.ArtistList of 0 artists> = <AxesSubplot:xlabel='g',
> ylabel='y'>.artists
>
> seaborn/tests/test_categorical.py:804: AssertionError
> _______________________ TestBoxPlotter.test_missing_data
> _______________________
>
> self = <seaborn.tests.test_categorical.TestBoxPlotter object at
> 0x7f3e6ace7220>
>
> def test_missing_data(self):
>
> x = ["a", "a", "b", "b", "c", "c", "d", "d"]
> h = ["x", "y", "x", "y", "x", "y", "x", "y"]
> y = self.rs.randn(8)
> y[-2:] = np.nan
>
> ax = cat.boxplot(x=x, y=y)
> > assert len(ax.artists) == 3
> E assert 0 == 3
> E + where 0 = len(<Axes.ArtistList of 0 artists>)
> E + where <Axes.ArtistList of 0 artists> = <AxesSubplot:>.artists
>
> seaborn/tests/test_categorical.py:814: AssertionError
> ________________________ TestCatPlot.test_plot_elements
> ________________________
>
> self = <seaborn.tests.test_categorical.TestCatPlot object at 0x7f3e6abe7220>
>
> def test_plot_elements(self):
>
> g = cat.catplot(x="g", y="y", data=self.df, kind="point")
> assert len(g.ax.collections) == 1
> want_lines = self.g.unique().size + 1
> assert len(g.ax.lines) == want_lines
>
> g = cat.catplot(x="g", y="y", hue="h", data=self.df, kind="point")
> want_collections = self.h.unique().size
> assert len(g.ax.collections) == want_collections
> want_lines = (self.g.unique().size + 1) * self.h.unique().size
> assert len(g.ax.lines) == want_lines
>
> g = cat.catplot(x="g", y="y", data=self.df, kind="bar")
> want_elements = self.g.unique().size
> assert len(g.ax.patches) == want_elements
> assert len(g.ax.lines) == want_elements
>
> g = cat.catplot(x="g", y="y", hue="h", data=self.df, kind="bar")
> want_elements = self.g.unique().size * self.h.unique().size
> assert len(g.ax.patches) == want_elements
> assert len(g.ax.lines) == want_elements
>
> g = cat.catplot(x="g", data=self.df, kind="count")
> want_elements = self.g.unique().size
> assert len(g.ax.patches) == want_elements
> assert len(g.ax.lines) == 0
>
> g = cat.catplot(x="g", hue="h", data=self.df, kind="count")
> want_elements = self.g.unique().size * self.h.unique().size
> assert len(g.ax.patches) == want_elements
> assert len(g.ax.lines) == 0
>
> 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
> E AssertionError: assert 0 == 3
> E + where 0 = len(<Axes.ArtistList of 0 artists>)
> E + where <Axes.ArtistList of 0 artists> = <AxesSubplot:xlabel='g',
> ylabel='y'>.artists
> E + where <AxesSubplot:xlabel='g', ylabel='y'> =
> <seaborn.axisgrid.FacetGrid object at 0x7f3e716b3790>.ax
>
> seaborn/tests/test_categorical.py:2507: AssertionError
> ______________________ TestKDEPlotUnivariate.test_legend
> _______________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotUnivariate object at
> 0x7f3e70831a00>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
>
> def test_legend(self, long_df):
>
> ax = kdeplot(data=long_df, x="x", hue="a")
>
> assert ax.legend_.get_title().get_text() == "a"
>
> legend_labels = ax.legend_.get_texts()
> order = categorical_order(long_df["a"])
> for label, level in zip(legend_labels, order):
> assert label.get_text() == level
>
> legend_artists = ax.legend_.findobj(mpl.lines.Line2D)[::2]
> palette = color_palette()
> for artist, color in zip(legend_artists, palette):
> > assert to_rgb(artist.get_color()) == to_rgb(color)
> E assert (0.3333333333...4313725490196) ==
> (0.8666666666...5686274509804)
> E At index 0 diff: 0.3333333333333333 != 0.8666666666666667
> E Use -v to get the full diff
>
> seaborn/tests/test_distributions.py:809: AssertionError
> ____________________ TestKDEPlotBivariate.test_fill_artists
> ____________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e70923550>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
>
> def test_fill_artists(self, long_df):
>
> for fill in [True, False]:
> f, ax = plt.subplots()
> kdeplot(data=long_df, x="x", y="y", hue="c", fill=fill)
> for c in ax.collections:
> if fill:
> assert isinstance(c, mpl.collections.PathCollection)
> else:
> > assert isinstance(c, mpl.collections.LineCollection)
> E AssertionError: assert False
> E + where False =
> isinstance(<matplotlib.collections.PathCollection object at 0x7f3e70bfb460>,
> <class 'matplotlib.collections.LineCollection'>)
> E + where <class
> 'matplotlib.collections.LineCollection'> = <module 'matplotlib.collections'
> from
> '/usr/lib/python3/dist-packages/matplotlib/collections.py'>.LineCollection
> E + where <module 'matplotlib.collections' from
> '/usr/lib/python3/dist-packages/matplotlib/collections.py'> = mpl.collections
>
> seaborn/tests/test_distributions.py:860: AssertionError
> ____________________ TestKDEPlotBivariate.test_common_norm
> _____________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e70ab5340>
> rng = RandomState(MT19937) at 0x7F3E71434340
>
> def test_common_norm(self, rng):
>
> hue = np.repeat(["a", "a", "a", "b"], 40)
> x, y = rng.multivariate_normal([0, 0], [(.2, .5), (.5, 2)],
> len(hue)).T
> x[hue == "a"] -= 2
> x[hue == "b"] += 2
>
> f, (ax1, ax2) = plt.subplots(ncols=2)
> 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])
>
> seaborn/tests/test_distributions.py:873:
> _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> _
>
> .0 = <generator object _AxesBase.ArtistList.__iter__ at 0x7f3e70932ba0>
>
> > n_seg_1 = sum([len(c.get_segments()) > 0 for c in ax1.collections])
> E AttributeError: 'PathCollection' object has no attribute 'get_segments'
>
> seaborn/tests/test_distributions.py:873: AttributeError
> _____________________ TestKDEPlotBivariate.test_log_scale
> ______________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e7145d490>
> rng = RandomState(MT19937) at 0x7F3E70857540
>
> def test_log_scale(self, rng):
>
> x = rng.lognormal(0, 1, 100)
> y = rng.uniform(0, 1, 100)
>
> levels = .2, .5, 1
>
> f, ax = plt.subplots()
> kdeplot(x=x, y=y, log_scale=True, levels=levels, ax=ax)
> assert ax.get_xscale() == "log"
> assert ax.get_yscale() == "log"
>
> f, (ax1, ax2) = plt.subplots(ncols=2)
> kdeplot(x=x, y=y, log_scale=(10, False), levels=levels, ax=ax1)
> assert ax1.get_xscale() == "log"
> assert ax1.get_yscale() == "linear"
>
> p = _DistributionPlotter()
> kde = KDE()
> density, (xx, yy) = kde(np.log10(x), y)
> levels = p._quantile_to_level(density, levels)
> 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())
> E AttributeError: 'PathCollection' object has no attribute
> 'get_segments'
>
> seaborn/tests/test_distributions.py:901: AttributeError
> _____________________ TestKDEPlotBivariate.test_bandwidth
> ______________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e708a8700>
> rng = RandomState(MT19937) at 0x7F3E71434640
>
> def test_bandwidth(self, rng):
>
> n = 100
> x, y = rng.multivariate_normal([0, 0], [(.2, .5), (.5, 2)], n).T
>
> f, (ax1, ax2) = plt.subplots(ncols=2)
>
> kdeplot(x=x, y=y, ax=ax1)
> 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()
> E AttributeError: 'PathCollection' object has no attribute
> 'get_segments'
>
> seaborn/tests/test_distributions.py:914: AttributeError
> ______________________ TestKDEPlotBivariate.test_weights
> _______________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e711a5040>
> rng = RandomState(MT19937) at 0x7F3E70857540
>
> @pytest.mark.skipif(
> LooseVersion(scipy.__version__) < "1.2.0",
> reason="Weights require scipy >= 1.2.0"
> )
> def test_weights(self, rng):
>
> import warnings
> warnings.simplefilter("error", np.VisibleDeprecationWarning)
>
> n = 100
> x, y = rng.multivariate_normal([1, 3], [(.2, .5), (.5, 2)], n).T
> hue = np.repeat([0, 1], n // 2)
> weights = rng.uniform(0, 1, n)
>
> f, (ax1, ax2) = plt.subplots(ncols=2)
> kdeplot(x=x, y=y, hue=hue, ax=ax1)
> 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():
> E AttributeError: 'PathCollection' object has no attribute
> 'get_segments'
>
> seaborn/tests/test_distributions.py:939: AttributeError
> __________________ TestKDEPlotBivariate.test_hue_ignores_cmap
> __________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e71181520>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
>
> 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")
>
> > color = tuple(ax.collections[0].get_color().squeeze())
> E AttributeError: 'PathCollection' object has no attribute 'get_color'
>
> seaborn/tests/test_distributions.py:949: AttributeError
> ________________ TestKDEPlotBivariate.test_contour_line_colors
> _________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e70f6d3a0>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
>
> 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 tuple(c.get_color().squeeze()) == color
> E AttributeError: 'PathCollection' object has no attribute
> 'get_color'
>
> seaborn/tests/test_distributions.py:958: AttributeError
> _________________ TestKDEPlotBivariate.test_levels_and_thresh
> __________________
>
> self = <seaborn.tests.test_distributions.TestKDEPlotBivariate object at
> 0x7f3e707e27c0>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
>
> def test_levels_and_thresh(self, long_df):
>
> f, (ax1, ax2) = plt.subplots(ncols=2)
>
> n = 8
> thresh = .1
> plot_kws = dict(data=long_df, x="x", y="y")
> kdeplot(**plot_kws, levels=n, thresh=thresh, ax=ax1)
> 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())
> E AttributeError: 'PathCollection' object has no attribute
> 'get_segments'
>
> seaborn/tests/test_distributions.py:990: AttributeError
> ______________________ TestDisPlot.test_with_rug[kwargs0]
> ______________________
>
> self = <seaborn.tests.test_distributions.TestDisPlot object at 0x7f3e71290400>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
> kwargs = {'x': 'x'}
>
> @pytest.mark.parametrize(
> "kwargs", [
> dict(x="x"),
> dict(x="x", y="y"),
> dict(x="x", hue="a"),
> ]
> )
> def test_with_rug(self, long_df, kwargs):
>
> ax = rugplot(data=long_df, **kwargs)
> g = displot(long_df, rug=True, **kwargs)
> > g.ax.patches = []
> E AttributeError: can't set attribute
>
> seaborn/tests/test_distributions.py:2166: AttributeError
> ______________________ TestDisPlot.test_with_rug[kwargs1]
> ______________________
>
> self = <seaborn.tests.test_distributions.TestDisPlot object at 0x7f3e71357850>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
> kwargs = {'x': 'x', 'y': 'y'}
>
> @pytest.mark.parametrize(
> "kwargs", [
> dict(x="x"),
> dict(x="x", y="y"),
> dict(x="x", hue="a"),
> ]
> )
> def test_with_rug(self, long_df, kwargs):
>
> ax = rugplot(data=long_df, **kwargs)
> g = displot(long_df, rug=True, **kwargs)
> > g.ax.patches = []
> E AttributeError: can't set attribute
>
> seaborn/tests/test_distributions.py:2166: AttributeError
> ______________________ TestDisPlot.test_with_rug[kwargs2]
> ______________________
>
> self = <seaborn.tests.test_distributions.TestDisPlot object at 0x7f3e70a9fa90>
> long_df = x y z a b c t s f a_cat s_cat
> s_str
> 0 12 0.449243 6.611886 b p 0 2004-01-0...0.3 a 8 8
> 99 15 0.073484 1.036343 c p 0 2005-01-01 2 0.3 c 2 2
>
> [100 rows x 12 columns]
> kwargs = {'hue': 'a', 'x': 'x'}
>
> @pytest.mark.parametrize(
> "kwargs", [
> dict(x="x"),
> dict(x="x", y="y"),
> dict(x="x", hue="a"),
> ]
> )
> def test_with_rug(self, long_df, kwargs):
>
> ax = rugplot(data=long_df, **kwargs)
> g = displot(long_df, rug=True, **kwargs)
> > g.ax.patches = []
> E AttributeError: can't set attribute
>
> seaborn/tests/test_distributions.py:2166: AttributeError
> _____________________ TestDisPlot.test_bivariate_kde_norm
> ______________________
>
> self = <seaborn.tests.test_distributions.TestDisPlot object at 0x7f3e7058f8b0>
> rng = RandomState(MT19937) at 0x7F3E70857540
>
> def test_bivariate_kde_norm(self, rng):
>
> x, y = rng.normal(0, 1, (2, 100))
> 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)
>
> seaborn/tests/test_distributions.py:2249:
> _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> _
>
> .0 = <generator object _AxesBase.ArtistList.__iter__ at 0x7f3e70869040>
>
> > l1 = sum(bool(c.get_segments()) for c in g.axes.flat[0].collections)
> E AttributeError: 'PathCollection' object has no attribute 'get_segments'
>
> seaborn/tests/test_distributions.py:2249: AttributeError
> =============================== warnings summary
> ===============================
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_axisgrid.py: 15
> warnings
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py: 42
> warnings
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/distributions.py:849:
> MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and
> pcolormesh() is deprecated since 3.5 and will be removed two minor releases
> later; please call grid(False) first.
> mesh = ax.pcolormesh(
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_colorbar
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/distributions.py:1224:
> MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and
> pcolormesh() is deprecated since 3.5 and will be removed two minor releases
> later; please call grid(False) first.
> ax.figure.colorbar(cset, cbar_ax, ax, **cbar_kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotUnivariate::test_discrete_categorical_default
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotUnivariate::test_categorical_yaxis_inversion
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotUnivariate::test_auto_linewidth[True]
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestDisPlot::test_versus_single_histplot[kwargs3]
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/distributions.py:516:
> MatplotlibDeprecationWarning: Support for passing numbers through unit
> converters is deprecated since 3.5 and support will be removed two minor
> releases later; use Axis.convert_units instead.
> scout = self.ax.fill_between([], [], color=color, **plot_kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotUnivariate::test_auto_linewidth[False]
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/distributions.py:521:
> MatplotlibDeprecationWarning: Support for passing numbers through unit
> converters is deprecated since 3.5 and support will be removed two minor
> releases later; use Axis.convert_units instead.
> scout, = self.ax.plot([], [], color=color, **plot_kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotBivariate::test_colorbar
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_distributions.py::TestHistPlotBivariate::test_colorbar
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/distributions.py:867:
> MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and
> pcolormesh() is deprecated since 3.5 and will be removed two minor releases
> later; please call grid(False) first.
> ax.figure.colorbar(mesh, cbar_ax, ax, **cbar_kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_matrix.py: 77 warnings
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/matrix.py:302:
> MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and
> pcolormesh() is deprecated since 3.5 and will be removed two minor releases
> later; please call grid(False) first.
> mesh = ax.pcolormesh(self.plot_data, cmap=self.cmap, **kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_matrix.py: 47 warnings
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/matrix.py:312:
> MatplotlibDeprecationWarning: Auto-removal of grids by pcolor() and
> pcolormesh() is deprecated since 3.5 and will be removed two minor releases
> later; please call grid(False) first.
> cb = ax.figure.colorbar(mesh, cax, ax, **self.cbar_kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestLinePlotter::test_lineplot_vs_relplot[long_semantics2]
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestLinePlotter::test_lineplot_vs_relplot[long_semantics2]
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/relational.py:436:
> MatplotlibDeprecationWarning: Support for passing numbers through unit
> converters is deprecated since 3.5 and support will be removed two minor
> releases later; use Axis.convert_units instead.
> scout, = ax.plot([], [], **kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestLinePlotter::test_lineplot_vs_relplot[long_semantics2]
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestLinePlotter::test_lineplot_vs_relplot[long_semantics2]
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/relational.py:514:
> MatplotlibDeprecationWarning: Support for passing numbers through unit
> converters is deprecated since 3.5 and support will be removed two minor
> releases later; use Axis.convert_units instead.
> line, = ax.plot([], [], **kws)
>
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestScatterPlotter::test_scatterplot_vs_relplot[long_semantics2]
> .pybuild/cpython3_3.9_seaborn/build/seaborn/tests/test_relational.py::TestScatterPlotter::test_scatterplot_vs_relplot[long_semantics2]
>
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build/seaborn/relational.py:608:
> MatplotlibDeprecationWarning: Support for passing numbers through unit
> converters is deprecated since 3.5 and support will be removed two minor
> releases later; use Axis.convert_units instead.
> scout = ax.scatter(scout_x, scout_y, **kws)
>
> -- Docs: https://docs.pytest.org/en/stable/warnings.html
> =========================== short test summary info
> ============================
> FAILED seaborn/tests/test_categorical.py::TestBoxPlotter::test_axes_data -
> As...
> FAILED
> seaborn/tests/test_categorical.py::TestBoxPlotter::test_draw_missing_boxes
> FAILED seaborn/tests/test_categorical.py::TestBoxPlotter::test_missing_data
> FAILED seaborn/tests/test_categorical.py::TestCatPlot::test_plot_elements -
> A...
> FAILED seaborn/tests/test_distributions.py::TestKDEPlotUnivariate::test_legend
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_fill_artists
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_common_norm
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_log_scale
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_bandwidth
> FAILED seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_weights
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_hue_ignores_cmap
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_contour_line_colors
> FAILED
> seaborn/tests/test_distributions.py::TestKDEPlotBivariate::test_levels_and_thresh
> FAILED
> seaborn/tests/test_distributions.py::TestDisPlot::test_with_rug[kwargs0]
> FAILED
> seaborn/tests/test_distributions.py::TestDisPlot::test_with_rug[kwargs1]
> FAILED
> seaborn/tests/test_distributions.py::TestDisPlot::test_with_rug[kwargs2]
> FAILED
> seaborn/tests/test_distributions.py::TestDisPlot::test_bivariate_kde_norm
> ==== 17 failed, 1002 passed, 29 skipped, 195 warnings in 193.55s (0:03:13)
> =====
> E: pybuild pybuild:354: test: plugin distutils failed with: exit code=1: cd
> /<<PKGBUILDDIR>>/.pybuild/cpython3_3.9_seaborn/build; python3.9 -m pytest
> dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p 3.9
> returned exit code 13
The full build log is available from:
http://qa-logs.debian.net/http://qa-logs.debian.net/2021/11/numpy-matplotlib/matplotlib-exp/seaborn_0.11.2-2_unstable_matplotlib-exp.log
If you reassign this bug to another package, please marking it as 'affects'-ing
this package. See https://www.debian.org/Bugs/server-control#affects
If you fail to reproduce this, please provide a build log and diff it with mine
so that we can identify if something relevant changed in the meantime.
--- End Message ---
