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Fix: Change alpha application for RGBA from overwrite to multiply #30523

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Fix: Change alpha application for RGBA from overwrite to multiply #30523

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6 changes: 4 additions & 2 deletions lib/matplotlib/image.py
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Original file line number Diff line number Diff line change
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: # image has no alpha channel
A = np.dstack([A, alpha])
else: # blend with existing alpha channel
A = np.dstack([A[..., :3], A[..., 3:] * alpha[..., np.newaxis]])
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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20 changes: 11 additions & 9 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -1809,19 +1809,21 @@ 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
# scalar alpha param, or blend it with the array alpha param
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)
axs_ref[1][1].imshow(
np.concatenate( # combine rgb channels with scaled array alpha
(im_rgb, scalar_alpha * array_alpha.reshape((ny, nx, 1))), axis=-1
), interpolation_stage=intp_stage
)
np.concatenate(
(im_rgb,
(scalar_alpha * array_alpha).reshape((ny, nx, 1))),
axis=-1),
interpolation_stage=intp_stage)
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@rcomer rcomer Nov 23, 2025

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This looks like a style-only change. Please revert.

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
), interpolation_stage=intp_stage
)
np.concatenate(
(im_rgb,
(array_alpha * new_array_alpha).reshape((ny, nx, 1))),
axis=-1),
interpolation_stage=intp_stage)
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