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Update tests to also use reasonable weights for TV denoising

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Gregory R. Lee
2015-12-23 12:30:12 -05:00
parent f143f4b39e
commit 3f5aa73eb4
1 changed files with 6 additions and 6 deletions
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skimage/restoration/tests/test_denoise.py
+6 -6
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@@ -21,7 +21,7 @@ def test_denoise_tv_chambolle_2d():
# clip noise so that it does not exceed allowed range for float images.
img = np.clip(img, 0, 1)
# denoise
denoised_astro = restoration.denoise_tv_chambolle(img, weight=60.0)
denoised_astro = restoration.denoise_tv_chambolle(img, weight=0.25)
# which dtype?
assert denoised_astro.dtype in [np.float, np.float32, np.float64]
from scipy import ndimage as ndi
@@ -30,12 +30,12 @@ def test_denoise_tv_chambolle_2d():
# test if the total variation has decreased
assert grad_denoised.dtype == np.float
assert (np.sqrt((grad_denoised**2).sum())
< np.sqrt((grad**2).sum()) / 2)
< np.sqrt((grad**2).sum()))
def test_denoise_tv_chambolle_multichannel():
denoised0 = restoration.denoise_tv_chambolle(astro[..., 0], weight=60.0)
denoised = restoration.denoise_tv_chambolle(astro, weight=60.0,
denoised0 = restoration.denoise_tv_chambolle(astro[..., 0], weight=0.25)
denoised = restoration.denoise_tv_chambolle(astro, weight=0.25,
multichannel=True)
assert_equal(denoised[..., 0], denoised0)
@@ -46,7 +46,7 @@ def test_denoise_tv_chambolle_float_result_range():
int_astro = np.multiply(img, 255).astype(np.uint8)
assert np.max(int_astro) > 1
denoised_int_astro = restoration.denoise_tv_chambolle(int_astro,
weight=60.0)
weight=0.25)
# test if the value range of output float data is within [0.0:1.0]
assert denoised_int_astro.dtype == np.float
assert np.max(denoised_int_astro) <= 1.0
@@ -62,7 +62,7 @@ def test_denoise_tv_chambolle_3d():
mask += 20 * np.random.rand(*mask.shape)
mask[mask < 0] = 0
mask[mask > 255] = 255
res = restoration.denoise_tv_chambolle(mask.astype(np.uint8), weight=100)
res = restoration.denoise_tv_chambolle(mask.astype(np.uint8), weight=0.4)
assert res.dtype == np.float
assert res.std() * 255 < mask.std()