Contour labelling image test failing against Matplotlib main

Description

I just ran the tests against Matplotlib main, and got an image comparison failure because of the contour labels:

Expected

Actual

The test:

cartopy/lib/cartopy/tests/mpl/test_examples.py

Lines 33 to 72 in c4858e4

    
           @pytest.mark.natural_earth 
        
           @pytest.mark.mpl_image_compare(filename='contour_label.png', tolerance=0.5) 
        
           def test_contour_label(): 
        
               from cartopy.tests.mpl.test_caching import sample_data 
        
               fig = plt.figure() 
        
               # Setup a global EckertIII map with faint coastlines. 
        
               ax = fig.add_subplot(1, 1, 1, projection=ccrs.EckertIII()) 
        
               ax.set_global() 
        
               ax.coastlines('110m', alpha=0.1) 
        
               # Use the waves example to provide some sample data, but make it 
        
               # more dependent on y for more interesting contours. 
        
               x, y, z = sample_data((20, 40)) 
        
               z = z * -1.5 * y 
        
               # Add colourful filled contours. 
        
               filled_c = ax.contourf(x, y, z, transform=ccrs.PlateCarree()) 
        
               # And black line contours. 
        
               line_c = ax.contour(x, y, z, levels=filled_c.levels, 
        
                                   colors=['black'], 
        
                                   transform=ccrs.PlateCarree()) 
        
               # Uncomment to make the line contours invisible. 
        
               # plt.setp(line_c.collections, visible=False) 
        
               # Add a colorbar for the filled contour. 
        
               fig.colorbar(filled_c, orientation='horizontal') 
        
               # Use the line contours to place contour labels. 
        
               ax.clabel( 
        
                   line_c,  # Typically best results when labelling line contours. 
        
                   colors=['black'], 
        
                   manual=False,  # Automatic placement vs manual placement. 
        
                   inline=True,  # Cut the line where the label will be placed. 
        
                   fmt=' {:.0f} '.format,  # Labes as integers, with some extra space. 
        
               ) 
        
               return fig

I have two questions

Does anyone have a theory why inline=True does not seem to work any more? I cannot reproduce the problem with Matplotlib's Contour Label Demo.
How would you handle a genuine difference caused by different Matplotlib versions, so that both the main tests and the "minimum package versions" tests still pass?

Full environment definition

Operating system

RHEL7

Cartopy version

main

conda list


# Name                    Version                   Build  Channel
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attr                      2.5.1                h166bdaf_1    conda-forge
attrs                     22.2.0             pyh71513ae_0    conda-forge
backcall                  0.2.0              pyh9f0ad1d_0    conda-forge
backports                 1.0                pyhd8ed1ab_3    conda-forge
backports.functools_lru_cache 1.6.4              pyhd8ed1ab_0    conda-forge
beautifulsoup4            4.12.2             pyha770c72_0    conda-forge
black                     23.3.0          py311h38be061_0    conda-forge
bleach                    6.0.0              pyhd8ed1ab_0    conda-forge
brotli                    1.0.9                h166bdaf_8    conda-forge
brotli-bin                1.0.9                h166bdaf_8    conda-forge
brotlipy                  0.7.0           py311hd4cff14_1005    conda-forge
bzip2                     1.0.8                h7f98852_4    conda-forge
c-ares                    1.18.1               h7f98852_0    conda-forge
ca-certificates           2022.12.7            ha878542_0    conda-forge
cairo                     1.16.0            h35add3b_1015    conda-forge
cairocffi                 1.4.0              pyhd8ed1ab_0    conda-forge
cartopy                   0.21.1.dev109+g08ee0828.d20230414          pypi_0    pypi
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cffi                      1.15.1          py311h409f033_3    conda-forge
cfgv                      3.3.1              pyhd8ed1ab_0    conda-forge
charset-normalizer        3.1.0              pyhd8ed1ab_0    conda-forge
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colorama                  0.4.6              pyhd8ed1ab_0    conda-forge
comm                      0.1.3              pyhd8ed1ab_0    conda-forge
contourpy                 1.0.7           py311ha3edf6b_0    conda-forge
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6189
forge
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xorg-randrproto           1.5.0             h7f98852_1001    conda-forge
xorg-renderproto          0.11.1            h7f98852_1002    conda-forge
xorg-util-macros          1.19.3               h7f98852_0    conda-forge
xorg-xextproto            7.3.0             h0b41bf4_1003    conda-forge
xorg-xf86vidmodeproto     2.3.1             h7f98852_1002    conda-forge
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xorg-xproto               7.0.31            h7f98852_1007    conda-forge
xz                        5.2.6                h166bdaf_0    conda-forge
yaml                      0.2.5                h7f98852_2    conda-forge
zeromq                    4.3.4                h9c3ff4c_1    conda-forge
zipp                      3.15.0             pyhd8ed1ab_0    conda-forge
zlib                      1.2.13               h166bdaf_4    conda-forge
zstd                      1.5.2                h3eb15da_6    conda-forge

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	@pytest.mark.natural_earth
	@pytest.mark.mpl_image_compare(filename='contour_label.png', tolerance=0.5)
	def test_contour_label():
	from cartopy.tests.mpl.test_caching import sample_data
	fig = plt.figure()

	# Setup a global EckertIII map with faint coastlines.
	ax = fig.add_subplot(1, 1, 1, projection=ccrs.EckertIII())
	ax.set_global()
	ax.coastlines('110m', alpha=0.1)

	# Use the waves example to provide some sample data, but make it
	# more dependent on y for more interesting contours.
	x, y, z = sample_data((20, 40))
	z = z * -1.5 * y

	# Add colourful filled contours.
	filled_c = ax.contourf(x, y, z, transform=ccrs.PlateCarree())

	# And black line contours.
	line_c = ax.contour(x, y, z, levels=filled_c.levels,
	colors=['black'],
	transform=ccrs.PlateCarree())

	# Uncomment to make the line contours invisible.
	# plt.setp(line_c.collections, visible=False)

	# Add a colorbar for the filled contour.
	fig.colorbar(filled_c, orientation='horizontal')

	# Use the line contours to place contour labels.
	ax.clabel(
	line_c, # Typically best results when labelling line contours.
	colors=['black'],
	manual=False, # Automatic placement vs manual placement.
	inline=True, # Cut the line where the label will be placed.
	fmt=' {:.0f} '.format, # Labes as integers, with some extra space.
	)

	return fig

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