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Commit44770ae

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Merge pull request#28437 from chaoyihu/imshow-alpha-not-respected
Respect array alpha with interpolation_stage='rgba' in _Imagebase::_make_image
2 parents177f28c +8a032c1 commit44770ae

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+75
-11
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3 files changed

+75
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lines changed
Lines changed: 8 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,8 @@
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*alpha* parameter handling on images
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When passing and array to ``imshow(..., alpha=...)``, the parameter was silently ignored
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if the image data was a RGB or RBGA image or if:rc:`interpolation_state`
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resolved to "rbga".
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This is now fixed, and the alpha array overwrites any previous transparency information.

‎lib/matplotlib/image.py

Lines changed: 21 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -501,17 +501,27 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
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ifA.ndim==2:# interpolation_stage = 'rgba'
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self.norm.autoscale_None(A)
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A=self.to_rgba(A)
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alpha=self._get_scalar_alpha()
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ifA.shape[2]==3:
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# No need to resample alpha or make a full array; NumPy will expand
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# this out and cast to uint8 if necessary when it's assigned to the
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# alpha channel below.
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output_alpha= (255*alpha)ifA.dtype==np.uint8elsealpha
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else:
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output_alpha=_resample(# resample alpha channel
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self,A[...,3],out_shape,t,alpha=alpha)
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output=_resample(# resample rgb channels
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self,_rgb_to_rgba(A[..., :3]),out_shape,t,alpha=alpha)
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alpha=self.get_alpha()
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ifalphaisNone:# alpha parameter not specified
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ifA.shape[2]==3:# image has no alpha channel
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output_alpha=255ifA.dtype==np.uint8else1.0
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else:
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output_alpha=_resample(# resample alpha channel
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self,A[...,3],out_shape,t)
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output=_resample(# resample rgb channels
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self,_rgb_to_rgba(A[..., :3]),out_shape,t)
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elifnp.ndim(alpha)>0:# Array alpha
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# user-specified array alpha overrides the existing alpha channel
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output_alpha=_resample(self,alpha,out_shape,t)
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output=_resample(
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self,_rgb_to_rgba(A[..., :3]),out_shape,t)
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else:# Scalar alpha
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ifA.shape[2]==3:# broadcast scalar alpha
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output_alpha= (255*alpha)ifA.dtype==np.uint8elsealpha
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else:# or apply scalar alpha to existing alpha channel
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output_alpha=_resample(self,A[...,3],out_shape,t)*alpha
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output=_resample(
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self,_rgb_to_rgba(A[..., :3]),out_shape,t)
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output[...,3]=output_alpha# recombine rgb and alpha
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# output is now either a 2D array of normed (int or float) data

‎lib/matplotlib/tests/test_image.py

Lines changed: 46 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1711,3 +1711,49 @@ def test_resample_dtypes(dtype, ndim):
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axes_image=ax.imshow(data)
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# Before fix the following raises ValueError for some dtypes.
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axes_image.make_image(None)[0]
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@pytest.mark.parametrize('intp_stage', ('data','rgba'))
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@check_figures_equal()
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deftest_interpolation_stage_rgba_respects_alpha_param(fig_test,fig_ref,intp_stage):
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axs_tst=fig_test.subplots(2,3)
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axs_ref=fig_ref.subplots(2,3)
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ny,nx=3,3
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scalar_alpha=0.5
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array_alpha=np.random.rand(ny,nx)
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# When the image does not have an alpha channel, alpha should be specified
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# by the user or default to 1.0
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im_rgb=np.random.rand(ny,nx,3)
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im_concat_default_a=np.ones((ny,nx,1))# alpha defaults to 1.0
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im_rgba=np.concatenate(# combine rgb channels with array alpha
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(im_rgb,array_alpha.reshape((ny,nx,1))),axis=-1
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)
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axs_tst[0][0].imshow(im_rgb)
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axs_ref[0][0].imshow(np.concatenate((im_rgb,im_concat_default_a),axis=-1))
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axs_tst[0][1].imshow(im_rgb,interpolation_stage=intp_stage,alpha=scalar_alpha)
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axs_ref[0][1].imshow(
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np.concatenate(# combine rgb channels with broadcasted scalar alpha
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(im_rgb,scalar_alpha*im_concat_default_a),axis=-1
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),interpolation_stage=intp_stage
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)
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axs_tst[0][2].imshow(im_rgb,interpolation_stage=intp_stage,alpha=array_alpha)
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axs_ref[0][2].imshow(im_rgba,interpolation_stage=intp_stage)
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# When the image already has an alpha channel, multiply it by the
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# scalar alpha param, or replace it by the array alpha param
1745+
axs_tst[1][0].imshow(im_rgba)
1746+
axs_ref[1][0].imshow(im_rgb,alpha=array_alpha)
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axs_tst[1][1].imshow(im_rgba,interpolation_stage=intp_stage,alpha=scalar_alpha)
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axs_ref[1][1].imshow(
1749+
np.concatenate(# combine rgb channels with scaled array alpha
1750+
(im_rgb,scalar_alpha*array_alpha.reshape((ny,nx,1))),axis=-1
1751+
),interpolation_stage=intp_stage
1752+
)
1753+
new_array_alpha=np.random.rand(ny,nx)
1754+
axs_tst[1][2].imshow(im_rgba,interpolation_stage=intp_stage,alpha=new_array_alpha)
1755+
axs_ref[1][2].imshow(
1756+
np.concatenate(# combine rgb channels with new array alpha
1757+
(im_rgb,new_array_alpha.reshape((ny,nx,1))),axis=-1
1758+
),interpolation_stage=intp_stage
1759+
)

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