COSMIT pep8, removing unused imports

Author: amueller

sklearn/cluster/hierarchical.py

@@ -145,8 +145,8 @@ def ward_tree(X, connectivity=None, n_components=None, copy=True,
     moments_2 = np.zeros((n_nodes, n_features))
     moments_2[:n_samples] = X
     inertia = np.empty(len(coord_row), dtype=np.float)
-    _hierarchical.compute_ward_dist(moments_1, moments_2,
-                             coord_row, coord_col, inertia)
+    _hierarchical.compute_ward_dist(moments_1, moments_2, coord_row, coord_col,
+                                    inertia)
     inertia = list(six.moves.zip(inertia, coord_row, coord_col))
     heapify(inertia)
 

sklearn/covariance/graph_lasso_.py

@@ -511,7 +511,7 @@ def fit(self, X, y=None):
                                  n_alphas + 2)
             alphas = alphas[1:-1]
             if self.verbose and n_refinements > 1:
-                print('[GraphLassoCV] Done refinement % 2i out of %i: % 3is'\
+                print('[GraphLassoCV] Done refinement % 2i out of %i: % 3is'
                       % (i + 1, n_refinements, time.time() - t0))
 
         path = list(zip(*path))

sklearn/cross_validation.py

@@ -23,7 +23,6 @@
 from .utils.fixes import unique
 from .externals.joblib import Parallel, delayed
 from .metrics import SCORERS, Scorer
-import numbers
 
 __all__ = ['Bootstrap',
            'KFold',

sklearn/datasets/species_distributions.py

@@ -39,7 +39,6 @@
 from os import makedirs
 from os.path import join
 from os.path import exists
-import sys
 
 try:
     # Python 2

sklearn/feature_extraction/text.py

@@ -51,7 +51,7 @@ def strip_accents_unicode(s):
         ASCII equivalent.
     """
     return ''.join([c for c in unicodedata.normalize('NFKD', s)
-                     if not unicodedata.combining(c)])
+                    if not unicodedata.combining(c)])
 
 
 def strip_accents_ascii(s):

sklearn/feature_selection/selector_mixin.py

@@ -1,7 +1,6 @@
 # Authors: Gilles Louppe, Mathieu Blondel
 # License: BSD
 
-import sys
 import numpy as np
 
 from ..base import TransformerMixin

sklearn/linear_model/least_angle.py

@@ -243,7 +243,7 @@ def lars_path(X, y, Xy=None, Gram=None, max_iter=500,
 
             if verbose > 1:
                 print("%s\t\t%s\t\t%s\t\t%s\t\t%s" % (n_iter, active[-1], '',
-                                                            n_active, C))
+                                                      n_active, C))
 
         if method == 'lasso' and n_iter > 0 and prev_alpha[0] < alpha[0]:
             # alpha is increasing. This is because the updates of Cov are

sklearn/mixture/tests/test_gmm.py

@@ -1,4 +1,3 @@
-import itertools
 import unittest
 
 from nose.tools import assert_true