Rename equalize_hist to equalize and minor cleanup

doc/examples/plot_equalize_hist.py

@@ -5,7 +5,7 @@ Histogram Equalization
 
 This examples takes an image with low contrast and enhances its contrast using
 histogram equalization. Histogram equalization enhances contrast by "spreading
-out the most frequent intensity values" in an image [1]. The equalized image
+out the most frequent intensity values" in an image [1]_. The equalized image
 has a roughly linear cumulative distribution function, as shown in this example.
 
 .. [1] http://en.wikipedia.org/wiki/Histogram_equalization
@@ -18,25 +18,24 @@ from skimage.util.dtype import dtype_range
 from skimage import exposure
 
 
-def plot_hist(img, bins=256, ax=None):
+def plot_hist(img, bins=256):
     """Plot histogram and cumulative histogram for image"""
-    ax = ax if ax is not None else plt.gca()
     img_cdf, bins = exposure.cumulative_distribution(img, bins)
-    ax.hist(img.ravel(), bins=bins)
-    ax_right = ax.twinx()
-    ax_right.plot(bins, img_cdf, 'r')
+    plt.hist(img.ravel(), bins=bins)
+    ax_cdf = plt.twinx()
+    ax_cdf.plot(bins, img_cdf, 'r')
     xmin, xmax = dtype_range[img.dtype.type]
-    ax.set_xlim(xmin, xmax)
+    plt.xlim(xmin, xmax)
 
-    ax.set_ylabel('# pixels')
-    ax.set_xlabel('pixel intensiy')
-    ax_right.set_ylabel('fraction of total intensity')
+    plt.ylabel('# pixels')
+    plt.xlabel('pixel intensiy')
+    ax_cdf.set_ylabel('fraction of total intensity')
 
 
 img_orig = data.camera()
 # squeeze image intensities to lower image contrast
 img = img_orig / 5 + 100
-img_eq = exposure.equalize_hist(img)
+img_eq = exposure.equalize(img)
 
 plt.subplot(2, 2, 1)
 plt.imshow(img, cmap=plt.cm.gray, vmin=0, vmax=255)

skimage/exposure/__init__.py

@@ -1 +1 @@
-from exposure import histogram, equalize_hist, cumulative_distribution
+from exposure import histogram, equalize, cumulative_distribution

skimage/exposure/exposure.py

@@ -3,14 +3,15 @@ import numpy as np
 import skimage
 
 
-__all__ = ['histogram', 'cumulative_distribution', 'equalize_hist']
+__all__ = ['histogram', 'cumulative_distribution', 'equalize']
 
 
 def histogram(image, nbins, density=True):
     """Return histogram of image.
 
     Unlike `numpy.histogram`, this function returns the centers of bins and
-    does not rebin integer arrays.
+    does not rebin integer arrays. For integer arrays, each integer value has
+    its own bin, which improves speed and intensity-resolution.
 
     Parameters
     ----------
@@ -80,7 +81,7 @@ def cumulative_distribution(image, nbins=256):
     return img_cdf, bin_centers
 
 
-def equalize_hist(image, nbins=256):
+def equalize(image, nbins=256):
     """Return image after histogram equalization.
 
     Parameters
@@ -97,7 +98,7 @@ def equalize_hist(image, nbins=256):
 
     Notes
     -----
-    This function is adapted from [1] with the author's permission.
+    This function is adapted from [1]_ with the author's permission.
 
     References
     ----------

skimage/exposure/tests/test_exposure.py

@@ -9,16 +9,16 @@ from skimage import exposure
 test_img = data.camera() / 5 + 100
 
 
-def test_equalize_hist_ubyte():
-    img_eq = exposure.equalize_hist(test_img)
+def test_equalize_ubyte():
+    img_eq = exposure.equalize(test_img)
 
     cdf, bin_edges = exposure.cumulative_distribution(img_eq)
     check_cdf_slope(cdf)
 
 
-def test_equalize_hist_float():
+def test_equalize_float():
     img = skimage.img_as_float(test_img)
-    img_eq = exposure.equalize_hist(img)
+    img_eq = exposure.equalize(img)
 
     cdf, bin_edges = exposure.cumulative_distribution(img_eq)
     check_cdf_slope(cdf)