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Fix array alpha to multiply (not replace) existing RGBA alpha #30795

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Fix array alpha to multiply (not replace) existing RGBA alpha #30795

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7401f07
Fix array alpha to multiply (not replace) existing RGBA alpha
FazeelUsmani Nov 28, 2025
4653910
Fix line too long linting error
FazeelUsmani Nov 28, 2025
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10 changes: 6 additions & 4 deletions doc/api/next_api_changes/behavior/28437-CH.rst
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Original file line number Diff line number Diff line change
@@ -1,8 +1,10 @@
*alpha* parameter handling on images
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

When passing and array to ``imshow(..., alpha=...)``, the parameter was silently ignored
if the image data was a RGB or RBGA image or if :rc:`interpolation_state`
resolved to "rbga".
When passing an array to ``imshow(..., alpha=...)``, the parameter was silently ignored
if the image data was a RGB or RGBA image or if :rc:`interpolation_stage`
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@rcomer rcomer Dec 17, 2025

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This is not quite right - for RGBA the alpha parameter replaced the image alpha channel. So alpha was not ignored.

resolved to "rgba".

This is now fixed, and the alpha array overwrites any previous transparency information.
This is now fixed. For RGB images, the alpha array is used directly as the alpha channel.
For RGBA images, the alpha array is multiplied with the existing alpha channel, consistent
with how scalar alpha values are handled.
6 changes: 4 additions & 2 deletions lib/matplotlib/image.py
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Expand Up @@ -512,8 +512,10 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
if A.shape[2] == 3: # image has no alpha channel
A = np.dstack([A, np.ones(A.shape[:2])])
elif np.ndim(alpha) > 0: # Array alpha
# user-specified array alpha overrides the existing alpha channel
A = np.dstack([A[..., :3], alpha])
if A.shape[2] == 3: # RGB: use array alpha directly
A = np.dstack([A, alpha])
else: # RGBA: multiply existing alpha by array alpha
A = np.dstack([A[..., :3], A[..., 3] * alpha])
else: # Scalar alpha
if A.shape[2] == 3: # broadcast scalar alpha
A = np.dstack([A, np.full(A.shape[:2], alpha, np.float32)])
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7 changes: 4 additions & 3 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -1841,7 +1841,7 @@ def test_interpolation_stage_rgba_respects_alpha_param(fig_test, fig_ref, intp_s
axs_ref[0][2].imshow(im_rgba, interpolation_stage=intp_stage)

# When the image already has an alpha channel, multiply it by the
# scalar alpha param, or replace it by the array alpha param
# alpha param (both scalar and array alpha multiply the existing alpha)
axs_tst[1][0].imshow(im_rgba)
axs_ref[1][0].imshow(im_rgb, alpha=array_alpha)
axs_tst[1][1].imshow(im_rgba, interpolation_stage=intp_stage, alpha=scalar_alpha)
Expand All @@ -1853,7 +1853,8 @@ def test_interpolation_stage_rgba_respects_alpha_param(fig_test, fig_ref, intp_s
new_array_alpha = np.random.rand(ny, nx)
axs_tst[1][2].imshow(im_rgba, interpolation_stage=intp_stage, alpha=new_array_alpha)
axs_ref[1][2].imshow(
np.concatenate( # combine rgb channels with new array alpha
(im_rgb, new_array_alpha.reshape((ny, nx, 1))), axis=-1
np.concatenate( # combine rgb channels with multiplied array alpha
(im_rgb, array_alpha.reshape((ny, nx, 1))
* new_array_alpha.reshape((ny, nx, 1))), axis=-1
), interpolation_stage=intp_stage
)
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