Sep 13, 2024 · Oct 9, 2024 · Oct 21, 2024 · Oct 21, 2024 · Nov 5, 2024 · Nov 5, 2024
diff --git a/lib/matplotlib/patheffects.py b/lib/matplotlib/patheffects.py
        gc0.copy_properties(gc)

        if self._shadow_color is None:
            r, g, b = (gc0.get_foreground() or (1., 1., 1.))[:3]
            r, g, b = (gc0.get_rgb() or (1., 1., 1.))[:3]
            # Scale the colors by a factor to improve the shadow effect.
            shadow_rgbFace = (r * self._rho, g * self._rho, b * self._rho)
        else:
diff --git a/lib/matplotlib/tests/test_patheffects.py b/lib/matplotlib/tests/test_patheffects.py
 import platform

 import numpy as np

 from matplotlib.testing.decorators import image_comparison
 from matplotlib.testing.decorators import image_comparison, check_figures_equal
 import matplotlib.pyplot as plt
 import matplotlib.patheffects as path_effects
 from matplotlib.path import Path

    assert renderer.open_group('s') == "open_group overridden"
    assert renderer.close_group('s') == "close_group overridden"


 @check_figures_equal()
 def test_simpleLineShadow_plot(fig_test, fig_ref):
    # Create the plots
    ax_ref = fig_ref.add_subplot()
    ax_test = fig_test.add_subplot()

    # Generate Gaussian distribution data
    x = np.linspace(-5, 5, 500)
    y = np.exp(-x**2)

    # Plot the Gaussian line with the SimpleLineShadow path effect
    line, = ax_test.plot(x, y, linewidth=5)
    line.set_path_effects([path_effects.SimpleLineShadow(
                            offset=(0, 0), shadow_color='blue', rho=0.5)])

    # Plot the Gaussian line simply
    ax_ref.plot(x, y, linewidth=5, color='blue', alpha=0.3)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -325,7 +325,7 @@
		gc0.copy_properties(gc)

		if self._shadow_color is None:
		r, g, b = (gc0.get_foreground() or (1., 1., 1.))[:3]
		r, g, b = (gc0.get_rgb() or (1., 1., 1.))[:3]
Check warning on line 328 in lib/matplotlib/patheffects.py View check run for this annotation Codecov/ codecov/patch lib/matplotlib/patheffects.py#L328 `Added line #L328 was not covered by tests`
		# Scale the colors by a factor to improve the shadow effect.
		shadow_rgbFace = (r * self._rho, g * self._rho, b * self._rho)
		else:
Expand Down
Original file line number	Diff line number	Diff line change
		@@ -1,8 +1,7 @@
		import platform

		import numpy as np

		from matplotlib.testing.decorators import image_comparison
		from matplotlib.testing.decorators import image_comparison, check_figures_equal
		import matplotlib.pyplot as plt
		import matplotlib.patheffects as path_effects
		from matplotlib.path import Path
Expand DownExpand Up		@@ -214,3 +213,22 @@ def close_group(self, s):

		assert renderer.open_group('s') == "open_group overridden"
		assert renderer.close_group('s') == "close_group overridden"


		@check_figures_equal()
		def test_simpleLineShadow_plot(fig_test, fig_ref):
		# Create the plots
		ax_ref = fig_ref.add_subplot()
		ax_test = fig_test.add_subplot()

		# Generate Gaussian distribution data
		x = np.linspace(-5, 5, 500)
		y = np.exp(-x**2)

		# Plot the Gaussian line with the SimpleLineShadow path effect
		line, = ax_test.plot(x, y, linewidth=5)
		line.set_path_effects([path_effects.SimpleLineShadow(
		offset=(0, 0), shadow_color='blue', rho=0.5)])

		# Plot the Gaussian line simply
		ax_ref.plot(x, y, linewidth=5, color='blue', alpha=0.3)