PEP8 in cross_validation module + tests

Author: ogrisel

sklearn/cross_validation.py

@@ -1053,10 +1053,11 @@ def cross_val_predict(estimator, X, y=None, cv=None, n_jobs=1,
     # Check for sparse predictions
     if sp.issparse(preds[0]):
         preds = sp.vstack(preds, format=preds[0].format)
-    else :
+    else:
         preds = np.concatenate(preds)
     return preds[inv_locs]
 
+
 def _fit_and_predict(estimator, X, y, train, test, verbose, fit_params):
     """Fit estimator and predict values for a given dataset split.
 

sklearn/tests/test_cross_validation.py

@@ -1097,6 +1097,7 @@ def test_check_is_partition():
     p[0] = 23
     assert_false(cval._check_is_partition(p, 100))
 
+
 def test_cross_val_predict_sparse_prediction():
     # check that cross_val_predict gives same result for sparse and dense input
     X, y = make_multilabel_classification(n_classes=2, n_labels=1,
@@ -1107,7 +1108,6 @@ def test_cross_val_predict_sparse_prediction():
     y_sparse = csr_matrix(y)
     classif = OneVsRestClassifier(SVC(kernel='linear'))
     preds = cval.cross_val_predict(classif, X, y, cv=10)
-    preds_sparse = cval.cross_val_predict(classif, X_sparse,y_sparse, cv=10)
+    preds_sparse = cval.cross_val_predict(classif, X_sparse, y_sparse, cv=10)
     preds_sparse = preds_sparse.toarray()
     assert_array_almost_equal(preds_sparse, preds)
-