Solving white space + improving code +PEP8

Solving white space + Correcting code

Solving white spaces

Solving white spaces

Solving white spaces

Answering comments

Correcting silly mistakes

Solving white spaces

Trying again... now with Travis enabled

doc/examples/features_detection/plot_blob.py

@@ -34,19 +34,20 @@ independent of the size of blobs as internally the implementation uses
 box filters instead of convolutions. Bright on dark as well as dark on
 bright blobs are detected. The downside is that small blobs (<3px) are not
 detected accurately. See :py:meth:`skimage.feature.blob_doh` for usage.
-
 """
 
-from matplotlib import pyplot as plt
 from skimage import data
 from skimage.feature import blob_dog, blob_log, blob_doh
 from math import sqrt
 from skimage.color import rgb2gray
 
+import matplotlib.pyplot as plt
+
 image = data.hubble_deep_field()[0:500, 0:500]
 image_gray = rgb2gray(image)
 
 blobs_log = blob_log(image_gray, max_sigma=30, num_sigma=10, threshold=.1)
+
 # Compute radii in the 3rd column.
 blobs_log[:, 2] = blobs_log[:, 2] * sqrt(2)
 
@@ -61,14 +62,17 @@ titles = ['Laplacian of Gaussian', 'Difference of Gaussian',
           'Determinant of Hessian']
 sequence = zip(blobs_list, colors, titles)
 
+fig, axes = plt.subplots(1, 3, figsize=(14, 4), sharex=True, sharey=True,
+                         subplot_kw={'adjustable': 'box-forced'})
+plt.tight_layout()
 
-fig,axes = plt.subplots(1, 3, sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
 axes = axes.ravel()
 for blobs, color, title in sequence:
     ax = axes[0]
     axes = axes[1:]
     ax.set_title(title)
     ax.imshow(image, interpolation='nearest')
+    ax.set_axis_off()
     for blob in blobs:
         y, x, r = blob
         c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)