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Speed up RGBA-stage image resampling #32275

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Merged
iccir merged 2 commits into from
Sep 3, 2026
Merged

Speed up RGBA-stage image resampling #32275

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53fbb32
Speed up RGBA-stage image resampling
zekebarger Aug 31, 2026
cd98107
Address review: demultiply naming, parametrize the test
zekebarger Sep 2, 2026
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23 changes: 15 additions & 8 deletions lib/matplotlib/image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -461,8 +461,6 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
if not (A.ndim == 2 or A.ndim == 3 and A.shape[-1] in (3, 4)):
raise ValueError(f"Invalid shape {A.shape} for image data")

float_rgba_in = A.ndim == 3 and A.shape[-1] == 4 and A.dtype.kind == 'f'

# if antialiased, this needs to change as window sizes
# change:
interpolation_stage = self._interpolation_stage
Expand Down Expand Up @@ -566,13 +564,22 @@ def get_scaled_dtype(A):
# Resample in premultiplied alpha space. (TODO: Consider
# implementing premultiplied-space resampling in
# span_image_resample_rgba_affine::generate?)
if float_rgba_in and np.ndim(alpha) == 0 and np.any(A[..., 3] < 1):
# Do not modify original RGBA input
A = A.copy()
A[..., :3] *= A[..., 3:]
# Multiplying the whole array and then restoring the alpha channel
# is faster than an in-place multiply of the strided A[..., :3]
# view. If alpha is uniformly 1, premultiplication can be skipped.
alpha_in = A[..., 3]
if (alpha_in != 1).any():
A = A * alpha_in[..., None]
A[..., 3] = alpha_in
res = _resample(self, A, out_shape, t)
np.divide(res[..., :3], res[..., 3:], out=res[..., :3],
where=res[..., 3:] != 0)
# Demultiply. Zeroes in the divisor are replaced by ones,
# which leaves the corresponding (premultiplied) RGB values
# untouched. Dividing the whole contiguous array is several
# times faster than np.divide(..., where=...) into the strided
# res[..., :3] view.
alpha_out = res[..., 3].copy()
res /= np.where(alpha_out != 0, alpha_out, 1)[..., None]
res[..., 3] = alpha_out
if post_apply_alpha:
res[..., 3] *= alpha

Expand Down
20 changes: 20 additions & 0 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -1860,6 +1860,26 @@ def test_resample_dtypes(dtype, ndim):
axes_image.make_image(None)[0]


@pytest.mark.parametrize('alpha', [0, 0.25, 0.5, 0.75, 1])
def test_rgba_stage_demultiplies_resampled_alpha(alpha):
# Issue 32240: resampling in the 'rgba' stage happens in premultiplied alpha
# space, so the RGB channels are demultiplied afterwards. The original
# colors must come back independently of the alpha channel, and a zero
# resampled alpha must not be divided by.
rgb = [0.2, 0.4, 0.6]
data = np.empty((4, 4, 4))
data[..., :3] = rgb
data[..., 3] = alpha
fig, ax = plt.subplots()
axes_image = ax.imshow(data, interpolation='nearest', interpolation_stage='rgba')
image = axes_image.make_image(None)[0]
# A fully transparent image premultiplies to zero and is never divided back.
expected_rgb = np.multiply(rgb, 255) if alpha else [0, 0, 0]
# The rendered image is a single flat colour, so compare against it directly.
assert_array_equal(np.unique(image.reshape(-1, 4), axis=0),
[[*expected_rgb, int(alpha * 255)]])


@pytest.mark.parametrize('intp_stage', ('data', 'rgba'))
@check_figures_equal(extensions=['png', 'pdf', 'svg'])
def test_interpolation_stage_rgba_respects_alpha_param(fig_test, fig_ref, intp_stage):
Expand Down
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