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)