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Used the new function names in example and test.

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This commit is contained in:
Steven Silvester
2012-12-08 15:03:11 -06:00
parent e91129de53
commit 71f505f71c
2 changed files with 8 additions and 11 deletions
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doc/examples/plot_equalize.py
+2 -3
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@@ -23,7 +23,6 @@ from skimage.util.dtype import dtype_range
from skimage import exposure
import matplotlib.pyplot as plt
import numpy as np
@@ -62,11 +61,11 @@ p98 = np.percentile(img, 98)
img_rescale = exposure.rescale_intensity(img, in_range=(p2, p98))
# Equalization
img_eq = exposure.equalize(img)
img_eq = exposure.equalize_hist(img)
img_eq = img_as_ubyte(img_eq)
# Adaptive Equalization
img_adapteq = exposure.adapthist(img, clip_limit=0.03)
img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)
img_adapteq = img_as_ubyte(img_adapteq)
# Display results
skimage/exposure/tests/test_exposure.py
+6 -8
View File
@@ -1,13 +1,11 @@
import numpy as np
from numpy.testing import assert_array_almost_equal as assert_close
import skimage
from skimage import io
from skimage import data
from skimage import exposure
from skimage.color import rgb2gray
from skimage.util.dtype import dtype_range
io.use_plugin('qt')
# Test histogram equalization
# ===========================
@@ -18,7 +16,7 @@ test_img = exposure.rescale_intensity(data.camera() / 5. + 100)
def test_equalize_ubyte():
img = skimage.img_as_ubyte(test_img)
img_eq = exposure.equalize(img)
img_eq = exposure.equalize_hist(img)
cdf, bin_edges = exposure.cumulative_distribution(img_eq)
check_cdf_slope(cdf)
@@ -26,7 +24,7 @@ def test_equalize_ubyte():
def test_equalize_float():
img = skimage.img_as_float(test_img)
img_eq = exposure.equalize(img)
img_eq = exposure.equalize_hist(img)
cdf, bin_edges = exposure.cumulative_distribution(img_eq)
check_cdf_slope(cdf)
@@ -81,8 +79,8 @@ def test_adapthist_scalar():
'''Test a scalar uint8 image
'''
img = skimage.img_as_ubyte(data.moon())
adapted = exposure.adapthist(img, clip_limit=0.02)
assert adapted.min() == 0=
adapted = exposure.equalize_adapthist(img, clip_limit=0.02)
assert adapted.min() == 0
assert adapted.max() == (1 << 16) - 1
assert img.shape == adapted.shape
full_scale = skimage.exposure.rescale_intensity(skimage.img_as_uint(img))
@@ -99,7 +97,7 @@ def test_adapthist_grayscale():
img = skimage.img_as_float(data.lena())
img = rgb2gray(img)
img = np.dstack((img, img, img))
adapted = exposure.adapthist(img, 10, 9, clip_limit=0.01,
adapted = exposure.equalize_adapthist(img, 10, 9, clip_limit=0.01,
nbins=128)
assert_almost_equal = np.testing.assert_almost_equal
assert img.shape == adapted.shape
@@ -112,7 +110,7 @@ def test_adapthist_color():
'''Test a color uint16 image
'''
img = skimage.img_as_uint(data.lena())
adapted = exposure.adapthist(img, clip_limit=0.01)
adapted = exposure.equalize_adapthist(img, clip_limit=0.01)
assert_almost_equal = np.testing.assert_almost_equal
assert adapted.min() == 0
assert adapted.max() == 1.0