Fixed loader problems

MANIFEST.in

@@ -4,5 +4,4 @@ include scikits/__init__.py
 recursive-include doc *
 recursive-include examples *
 recursive-include scikits *.c *.h *.pyx
-recursive-include scikits/learn/datasets *.csv *.csv.gz *.TXT *.rst 
-recursive-include scikits/learn/datasets/images *.jpg *.txt
+recursive-include scikits/learn/datasets *.csv *.csv.gz *.TXT *.rst *.jpg *.txt

examples/cluster/vq_china.py

@@ -8,25 +8,22 @@
 number of colors required to show the image.
 """
 print __doc__
-
+import os
 import numpy as np
 import pylab as pl
 from scikits.learn.cluster import KMeans
 from scikits.learn.datasets import load_sample_images
-# Try to import Image and imresize from PIL. We do this here to prevent
-# this module from depending on PIL.
-try:
-    try:
-        from scipy.misc import Image
-    except ImportError:
-        from scipy.misc.pilutil import Image
-except ImportError:
-    raise ImportError("The Python Imaging Library (PIL)"
-                      "is required to load data from jpeg files")
 
 # Get all sample images and obtain just china.jpg
+sample_image_name = "china.jpg"
 sample_images = load_sample_images()
-index = sample_images.filenames.index("china.jpg")
+index = None
+for i, filename in enumerate(sample_images.filenames):
+    if filename.endswith(sample_image_name):
+        index = i
+        break
+if index is None:
+    raise AttributeError("Cannot find sample image: %s" % sample_image_name)
 image_data = sample_images.images[index]
 
 # Load Image and transform to a 2D numpy array.
@@ -36,13 +33,13 @@
 # Take a sample of the data.
 sample_indices = range(len(image_array))
 np.random.shuffle(sample_indices)
-sample_indices = sample_indices[:int(len(image_array) * 0.5)]
+sample_indices = sample_indices[:int(len(image_array) * 0.2)]
 sample_data = image_array[sample_indices]
 
 # Perform Vector Quantisation with 256 clusters.
 k = 256
 kmeans = KMeans(k=k)
-kmeans.fit(image_array)
+kmeans.fit(sample_data)
 # Get labels for all points
 labels = kmeans.predict(image_array)
 # Save the reduced dataset. Only the centroids and labels need to be saved.
@@ -56,8 +53,9 @@ def recreate_image(centroids, labels, w, h):
     for i in range(w):
         for j in range(h):
             image[i][j] = centroids[labels[label_num]]
-            print labels[label_num], label_num
             label_num += 1
+    print np.histogram(labels)
+    print set(labels)
     return image
 
 # Display all results, alongside original image
@@ -67,5 +65,5 @@ def recreate_image(centroids, labels, w, h):
 centroids, labels = reduced_image
 im = pl.imshow(recreate_image(centroids, labels, w, h))
 
-show()
+pl.show()
 

scikits/learn/datasets/base.py

@@ -7,6 +7,7 @@
 #               2010 Olivier Grisel <olivier.grisel@ensta.org>
 # License: Simplified BSD
 
+import os
 import csv
 import shutil
 import textwrap
@@ -372,9 +373,20 @@ def load_sample_images():
     >>> # pl.matshow(images.images[0]) # Visualize the first image
     >>> # pl.show()
     """
+    # Try to import Image and imresize from PIL. We do this here to prevent
+    # this module from depending on PIL.
+    try:
+        try:
+            from scipy.misc import Image
+        except ImportError:
+            from scipy.misc.pilutil import Image
+    except ImportError:
+        raise ImportError("The Python Imaging Library (PIL)"
+                          "is required to load data from jpeg files")
     module_path = join(dirname(__file__), "images")
     descr = open(join(module_path, 'README.txt')).read()
-    filenames = [filename for filename in os.listdir(module_path)
+    filenames = [join(module_path, filename)
+                 for filename in os.listdir(module_path)
                  if filename.endswith(".jpg")]
     # Load image data for each image in the source folder.
     images = [np.asarray(Image.open(filename))

scikits/learn/datasets/setup.py

@@ -7,6 +7,7 @@ def configuration(parent_package='', top_path=None):
     config = Configuration('datasets', parent_package, top_path)
     config.add_data_dir('data')
     config.add_data_dir('descr')
+    config.add_data_dir('images')
 
 
     config.add_extension('_svmlight_format',