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Remove useless multichannel=True kwarg from tests

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This commit is contained in:
Himanshu Mishra
2016-02-05 14:38:13 +05:30
parent b40d028550
commit 7014d04327
3 changed files with 24 additions and 20 deletions
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doc/examples/filters/plot_denoise.py
+2 -4
View File
@@ -49,16 +49,14 @@ ax[0, 0].set_title('noisy')
ax[0, 1].imshow(denoise_tv_chambolle(noisy, weight=0.1, multichannel=True))
ax[0, 1].axis('off')
ax[0, 1].set_title('TV')
ax[0, 2].imshow(denoise_bilateral(noisy, sigma_range=0.05, sigma_spatial=15,
multichannel=True))
ax[0, 2].imshow(denoise_bilateral(noisy, sigma_range=0.05, sigma_spatial=15))
ax[0, 2].axis('off')
ax[0, 2].set_title('Bilateral')
ax[1, 0].imshow(denoise_tv_chambolle(noisy, weight=0.2, multichannel=True))
ax[1, 0].axis('off')
ax[1, 0].set_title('(more) TV')
ax[1, 1].imshow(denoise_bilateral(noisy, sigma_range=0.1, sigma_spatial=15,
multichannel=True))
ax[1, 1].imshow(denoise_bilateral(noisy, sigma_range=0.1, sigma_spatial=15))
ax[1, 1].axis('off')
ax[1, 1].set_title('(more) Bilateral')
ax[1, 2].imshow(astro)
skimage/restoration/_denoise.py
+17 -10
View File
@@ -66,14 +66,21 @@ def denoise_bilateral(image, win_size=5, sigma_range=None, sigma_spatial=1,
>>> astro = astro[220:300, 220:320]
>>> noisy = astro + 0.6 * astro.std() * np.random.random(astro.shape)
>>> noisy = np.clip(noisy, 0, 1)
>>> denoised = denoise_bilateral(noisy, sigma_range=0.05,
... sigma_spatial=15, multichannel=True)
>>> denoised = denoise_bilateral(noisy, sigma_range=0.05, sigma_spatial=15)
"""
if multichannel:
if image.ndim != 3:
raise ValueError("Use ``multichannel=False`` for 2D grayscale images. "
"The last axis of the input image must be multiple "
"color channels not another spatial dimension.")
if image.ndim == 2:
raise ValueError("Use ``multichannel=False`` for 2D grayscale "
"images. The last axis of the input image "
"must be multiple color channels not another "
"spatial dimension.")
else:
raise ValueError("Bilateral filter is only implemented for "
"2D grayscale images (image.ndim == 2) and "
"2D multichannel (image.ndim == 3) images, "
"but the input image has {0} dimensions. "
"".format(image.ndim))
elif image.shape[2] not in (3, 4):
if image.shape[2] > 4:
warnings.warn("The last axis of the input image is interpreted "
@@ -86,11 +93,11 @@ def denoise_bilateral(image, win_size=5, sigma_range=None, sigma_spatial=1,
warnings.warn(msg.format(image.shape))
else:
if image.ndim > 2:
raise TypeError("Bilateral filter is not implemented for "
"grayscale images of 3 or more dimensions, "
"but input image has {0} dimension. Use "
"``multichannel=True`` for 2-D RGB "
"images.".format(image.shape))
raise ValueError("Bilateral filter is not implemented for "
"grayscale images of 3 or more dimensions, "
"but input image has {0} dimension. Use "
"``multichannel=True`` for 2-D RGB "
"images.".format(image.shape))
mode = _mode_deprecations(mode)
skimage/restoration/tests/test_denoise.py
+5 -6
View File
@@ -175,10 +175,8 @@ def test_denoise_bilateral_color():
img += 0.5 * img.std() * np.random.rand(*img.shape)
img = np.clip(img, 0, 1)
out1 = restoration.denoise_bilateral(img, sigma_range=0.1,
sigma_spatial=20, multichannel=True)
out2 = restoration.denoise_bilateral(img, sigma_range=0.2,
sigma_spatial=30, multichannel=True)
out1 = restoration.denoise_bilateral(img, sigma_range=0.1, sigma_spatial=20)
out2 = restoration.denoise_bilateral(img, sigma_range=0.2, sigma_spatial=30)
# make sure noise is reduced in the checkerboard cells
assert img[30:45, 5:15].std() > out1[30:45, 5:15].std()
@@ -187,14 +185,14 @@ def test_denoise_bilateral_color():
def test_denoise_bilateral_3d_grayscale():
img = np.ones((50, 50, 3))
assert_raises(TypeError, restoration.denoise_bilateral, img, \
assert_raises(ValueError, restoration.denoise_bilateral, img,
multichannel=False)
def test_denoise_bilateral_3d_multichannel():
img = np.ones((50, 50, 50))
with expected_warnings(["grayscale"]):
result = restoration.denoise_bilateral(img, multichannel=True)
result = restoration.denoise_bilateral(img)
expected = np.empty_like(img)
expected.fill(np.nan)
@@ -204,6 +202,7 @@ def test_denoise_bilateral_3d_multichannel():
def test_denoise_bilateral_multidimensional():
img = np.ones((10, 10, 10, 10))
assert_raises(ValueError, restoration.denoise_bilateral, img)
assert_raises(ValueError, restoration.denoise_bilateral, img,
multichannel=True)