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Fix array alpha to multiply with existing RGBA alpha in imshow #31180

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Fix array alpha to multiply with existing RGBA alpha in imshow #31180

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7 changes: 5 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 +512,11 @@ 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 array alpha with existing 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
42 changes: 39 additions & 3 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -304,6 +304,7 @@ def test_imshow_alpha(fig_test, fig_ref):

@pytest.mark.parametrize('n_channels, is_int, alpha_arr, opaque',
[(3, False, False, False), # RGB float
(3, False, True, False), # RGB float with alpha array
(4, False, False, False), # RGBA float
(4, False, True, False), # RGBA float with alpha array
(4, False, False, True), # RGBA float with solid color
Expand Down Expand Up @@ -1223,6 +1224,41 @@ def test_image_array_alpha(fig_test, fig_ref):
ax.imshow(rgba, interpolation='nearest')


@check_figures_equal(extensions=['png'])
def test_image_array_alpha_rgb(fig_test, fig_ref):
"""Array alpha should work with RGB images (not just 2D colormapped)."""
np.random.seed(19680801)
rgb = np.random.rand(6, 6, 3).astype(np.float32)
alpha = np.random.rand(6, 6).astype(np.float32)

ax_test = fig_test.add_subplot()
ax_test.imshow(rgb, alpha=alpha, interpolation='nearest')

# Reference: manually construct RGBA with the same alpha
rgba = np.dstack([rgb, alpha])
ax_ref = fig_ref.add_subplot()
ax_ref.imshow(rgba, interpolation='nearest')


@check_figures_equal(extensions=['png'])
def test_image_array_alpha_rgba(fig_test, fig_ref):
"""Array alpha should multiply with existing RGBA alpha channel."""
np.random.seed(19680801)
rgb = np.random.rand(6, 6, 3).astype(np.float32)
existing_alpha = np.random.rand(6, 6).astype(np.float32)
rgba = np.dstack([rgb, existing_alpha])

user_alpha = np.random.rand(6, 6).astype(np.float32)

ax_test = fig_test.add_subplot()
ax_test.imshow(rgba, alpha=user_alpha, interpolation='nearest')

# Reference: RGBA with alpha = existing_alpha * user_alpha
blended_rgba = np.dstack([rgb, existing_alpha * user_alpha])
ax_ref = fig_ref.add_subplot()
ax_ref.imshow(blended_rgba, interpolation='nearest')


def test_image_array_alpha_validation():
with pytest.raises(TypeError, match="alpha must be a float, two-d"):
plt.imshow(np.zeros((2, 2)), alpha=[1, 1])
Expand Down Expand Up @@ -1855,7 +1891,7 @@ 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
# scalar alpha param or 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)
Expand All @@ -1867,7 +1903,7 @@ 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 * new_array_alpha).reshape((ny, nx, 1))), axis=-1
), interpolation_stage=intp_stage
)
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