TST Clean up the cross_validation and grid_search tests.

raghavrv · raghavrv · commit 50b5e268d91e · 2015-06-28T06:45:03.000+05:30
diff --git a/sklearn/tests/test_cross_validation.py b/sklearn/tests/test_cross_validation.py
@@ -7,7 +7,6 @@
 from scipy import stats
 
 from sklearn.utils.testing import assert_true
-from sklearn.utils.testing import assert_false
 from sklearn.utils.testing import assert_equal
 from sklearn.utils.testing import assert_almost_equal
 from sklearn.utils.testing import assert_raises
@@ -896,26 +895,6 @@ def test_shufflesplit_reproducible():
     assert_array_equal(list(a for a, b in ss), list(a for a, b in ss))
 
 
-def test_safe_split_with_precomputed_kernel():
-    clf = SVC()
-    clfp = SVC(kernel="precomputed")
-
-    iris = load_iris()
-    X, y = iris.data, iris.target
-    K = np.dot(X, X.T)
-
-    cv = cval.ShuffleSplit(X.shape[0], test_size=0.25, random_state=0)
-    tr, te = list(cv)[0]
-
-    X_tr, y_tr = cval._safe_split(clf, X, y, tr)
-    K_tr, y_tr2 = cval._safe_split(clfp, K, y, tr)
-    assert_array_almost_equal(K_tr, np.dot(X_tr, X_tr.T))
-
-    X_te, y_te = cval._safe_split(clf, X, y, te, tr)
-    K_te, y_te2 = cval._safe_split(clfp, K, y, te, tr)
-    assert_array_almost_equal(K_te, np.dot(X_te, X_tr.T))
-
-
 def test_cross_val_score_allow_nans():
     # Check that cross_val_score allows input data with NaNs
     X = np.arange(200, dtype=np.float64).reshape(10, -1)
@@ -1092,12 +1071,3 @@ def test_sparse_fit_params():
     fit_params = {'sparse_sample_weight': coo_matrix(np.eye(X.shape[0]))}
     a = cval.cross_val_score(clf, X, y, fit_params=fit_params)
     assert_array_equal(a, np.ones(3))
-
-
-def test_check_is_partition():
-    p = np.arange(100)
-    assert_true(cval._check_is_partition(p, 100))
-    assert_false(cval._check_is_partition(np.delete(p, 23), 100))
-
-    p[0] = 23
-    assert_false(cval._check_is_partition(p, 100))
diff --git a/sklearn/tests/test_grid_search.py b/sklearn/tests/test_grid_search.py
@@ -34,8 +34,7 @@
 from sklearn.datasets import make_blobs
 from sklearn.datasets import make_multilabel_classification
 from sklearn.grid_search import (GridSearchCV, RandomizedSearchCV,
-                                 ParameterGrid, ParameterSampler,
-                                 ChangedBehaviorWarning)
+                                 ParameterGrid, ParameterSampler)
 from sklearn.svm import LinearSVC, SVC
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.tree import DecisionTreeClassifier
@@ -44,9 +43,17 @@
 from sklearn.metrics import f1_score
 from sklearn.metrics import make_scorer
 from sklearn.metrics import roc_auc_score
-from sklearn.cross_validation import KFold, StratifiedKFold, FitFailedWarning
+from sklearn.cross_validation import KFold, StratifiedKFold
 from sklearn.preprocessing import Imputer
 from sklearn.pipeline import Pipeline
+try:
+    # We should be able to import these Warnings from the old files too.
+    from sklearn.grid_search import ChangedBehaviorWarning
+    from sklearn.cross_validation import FitFailedWarning
+except ImportError:
+    raise AssertionError("The import of ChangedBehaviorWarning and/or "
+                         "FitFailedWarning from the old files, was not "
+                         "successful.")
 
 
 # Neither of the following two estimators inherit from BaseEstimator,
