TST: Test the positivity constraint for dictionary learning.

scikit-learn · Feb 18, 2016 · fc931aa · fc931aa
1 parent 9ab1866
commit fc931aa
Showing 1 changed file with 6 additions and 2 deletions.
diff --git a/sklearn/decomposition/tests/test_dict_learning.py b/sklearn/decomposition/tests/test_dict_learning.py
@@ -38,8 +38,9 @@ def test_dict_learning_positivity():
     n_components = 5
     dico = DictionaryLearning(
         n_components, transform_algorithm='lasso_lars', random_state=0,
-        transform_positive=True).fit(X)
+        transform_positive=True, fit_positive=True).fit(X)
     code = dico.transform(X)
+    assert_true((dico.components_ >= 0).all())
     assert_true((code >= 0).all())
 
 
@@ -126,13 +127,16 @@ def test_dict_learning_online_positivity():
 
     dico = MiniBatchDictionaryLearning(
         n_components, transform_algorithm='lasso_lars', random_state=0,
-        transform_positive=True).fit(X)
+        transform_positive=True, fit_positive=True).fit(X)
     code = dico.transform(X)
+    assert_true((dico.components_ >= 0).all())
     assert_true((code >= 0).all())
 
     code, dictionary = dict_learning_online(X, n_components=n_components,
                                             alpha=1, random_state=rng,
+                                            dict_positive=True,
                                             code_positive=True)
+    assert_true((dictionary >= 0).all())
     assert_true((code >= 0).all())