Mar 18, 2025 · Feb 5, 2025 · Feb 5, 2025 · Feb 5, 2025 · Mar 3, 2025 · Mar 16, 2025
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
 import matplotlib.cbook as cbook
 import matplotlib.patches as mpatches
 import matplotlib.transforms as mtransforms
 from . import artist


 def _contour_labeler_event_handler(cs, inline, inline_spacing, event):
                edgecolor="none",
                # Default zorder taken from Collection
                zorder=kwargs.pop("zorder", 1),
                rasterized=kwargs.pop("rasterized", False),
            )

        else:

        return (i_level, segment, index, xmin, ymin, d2)

    @artist.allow_rasterization
    def draw(self, renderer):
        paths = self._paths
        n_paths = len(paths)
 data : indexable object, optional
    DATA_PARAMETER_PLACEHOLDER

 rasterized : bool, optional
    *Only applies to* `.contourf`.
    Rasterize the contour plot when drawing vector graphics.  This can
    speed up rendering and produce smaller files for large data sets.
    See also :doc:`/gallery/misc/rasterization_demo`.


 Notes
 -----
 1. `.contourf` differs from the MATLAB version in that it does not draw
diff --git a/lib/matplotlib/tests/baseline_images/test_contour/contour_rasterization.pdf b/lib/matplotlib/tests/baseline_images/test_contour/contour_rasterization.pdf
diff --git a/lib/matplotlib/tests/test_contour.py b/lib/matplotlib/tests/test_contour.py
        assert len(result) == 2
        assert len(result[0]) == 5
        assert len(result[1]) == 4


 @image_comparison(baseline_images=['contour_rasterization'],
                  extensions=['pdf'], style='mpl20', savefig_kwarg={'dpi': 25})
 def test_contourf_rasterize():
    fig, ax = plt.subplots()
    data = [[0, 1], [1, 0]]
    circle = mpatches.Circle([0.5, 0.5], 0.5, transform=ax.transAxes)
    cs = ax.contourf(data, clip_path=circle, rasterized=True)
    assert cs._rasterized
Original file line number	Diff line number	Diff line change
Expand Up		@@ -24,6 +24,7 @@
		import matplotlib.cbook as cbook
		import matplotlib.patches as mpatches
		import matplotlib.transforms as mtransforms
		from . import artist


		def _contour_labeler_event_handler(cs, inline, inline_spacing, event):
Expand DownExpand Up		@@ -767,6 +768,7 @@ def __init__(self, ax, *args,
		edgecolor="none",
		# Default zorder taken from Collection
		zorder=kwargs.pop("zorder", 1),
		rasterized=kwargs.pop("rasterized", False),
		)

		else:
Expand DownExpand Up		@@ -1254,6 +1256,7 @@ def find_nearest_contour(self, x, y, indices=None, pixel=True):

		return (i_level, segment, index, xmin, ymin, d2)

		@artist.allow_rasterization
		def draw(self, renderer):
		paths = self._paths
		n_paths = len(paths)
Expand DownExpand Up		@@ -1681,6 +1684,13 @@ def _initialize_x_y(self, z):
		data : indexable object, optional
		DATA_PARAMETER_PLACEHOLDER

		rasterized : bool, optional
		Only applies to `.contourf`.
		Rasterize the contour plot when drawing vector graphics. This can
		speed up rendering and produce smaller files for large data sets.
		See also :doc:`/gallery/misc/rasterization_demo`.


		Notes
		-----
		1. `.contourf` differs from the MATLAB version in that it does not draw
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -837,3 +837,13 @@ def test_allsegs_allkinds():
		assert len(result) == 2
		assert len(result[0]) == 5
		assert len(result[1]) == 4


		@image_comparison(baseline_images=['contour_rasterization'],
		extensions=['pdf'], style='mpl20', savefig_kwarg={'dpi': 25})
		def test_contourf_rasterize():
		fig, ax = plt.subplots()
		data = [[0, 1], [1, 0]]
		circle = mpatches.Circle([0.5, 0.5], 0.5, transform=ax.transAxes)
		cs = ax.contourf(data, clip_path=circle, rasterized=True)
		assert cs._rasterized
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