Nov 28, 2025 · Nov 28, 2025
diff --git a/doc/api/next_api_changes/behavior/28437-CH.rst b/doc/api/next_api_changes/behavior/28437-CH.rst
 *alpha* parameter handling on images
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 When passingand array to ``imshow(..., alpha=...)``, the parameter was silently ignored
 if the image data was a RGB orRBGA image or if :rc:`interpolation_state`
 resolved to "rbga".
 When passingan array to ``imshow(..., alpha=...)``, the parameter was silently ignored
 if the image data was a RGB orRGBA image or if :rc:`interpolation_stage`
 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.
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
                    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)])
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
    axs_ref[0][2].imshow(im_rgba, interpolation_stage=intp_stage)

    # When the image already has an alpha channel, multiply it by the
    #scalaralpha param, or replace it bythearray alpha param
    # alpha param (both scalar and array alpha multiplytheexisting 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)
    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
    )
Original file line number	Diff line number	Diff line change
		@@ -1,8 +1,10 @@
		alpha parameter handling on images
		~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

		When passingand array to ``imshow(..., alpha=...)``, the parameter was silently ignored
		if the image data was a RGB orRBGA image or if :rc:`interpolation_state`
		resolved to "rbga".
		When passingan array to ``imshow(..., alpha=...)``, the parameter was silently ignored
		if the image data was a RGB orRGBA image or if :rc:`interpolation_stage`
		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.
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: # 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)])
Expand Down
Original file line number	Diff line number	Diff line change
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
		#scalaralpha param, or replace it bythearray alpha param
		# alpha param (both scalar and array alpha multiplytheexisting 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
		)