Merge

multiview_platform/mono_multi_view_classifiers/multiview_classifiers/pseudo_cq_fusion/pseudo_cq_fusion.py

@@ -35,11 +35,7 @@ class PseudoCQFusionClass(diversity_utils.DiversityFusionClass):
         diversity_utils.DiversityFusionClass.__init__(self, randomState, NB_CORES=1, **kwargs)
 
     def getSpecificAnalysis(self, classificationKWARGS):
-<<<<<<< HEAD
-        stringAnalysis = "Classifiers used for each view : "+ ', '.join(self.classifiers_names)+\
-                         ', with a pseudo CQ of '+str(self.div_measure)
-=======
+
         stringAnalysis = "Classifiers used for each view : " + ', '.join(self.classifiers_names) +\
                          ', with a pseudo CQ of ' + str(self.div_measure)
->>>>>>> 7b3e918b4fb2938657cae3093d95b1bd6fc461d4
         return stringAnalysis
\ No newline at end of file

multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py

@@ -79,6 +79,7 @@ class Test_initTrainTest(unittest.TestCase):
     def test_simple(cls):
         X_train, y_train, X_test, y_test, X_test_multiclass = exec_classif_mono_view.init_train_test(
             cls.X, cls.Y, cls.classification_indices)
+
         np.testing.assert_array_equal(X_train, np.array(
             [np.array([102, 435, 348, 270, 106]),
              np.array([466, 214, 330, 458, 87]),

multiview_platform/tests/test_utils/test_execution.py

@@ -26,9 +26,9 @@ class Test_initStatsIterRandomStates(unittest.TestCase):
         cls.statsIter = 1
 
     def test_one_statiter(cls):
-
         cls.state = cls.random_state.get_state()[1]
         statsIterRandomStates = execution.init_stats_iter_random_states(
+
             cls.statsIter, cls.random_state)
         np.testing.assert_array_equal(statsIterRandomStates[0].get_state()[1],
                                       cls.state)
@@ -36,6 +36,7 @@ class Test_initStatsIterRandomStates(unittest.TestCase):
     def test_multiple_iter(cls):
         cls.statsIter = 3
         statsIterRandomStates = execution.init_stats_iter_random_states(
+
             cls.statsIter, cls.random_state)
         cls.assertAlmostEqual(len(statsIterRandomStates), 3)
         cls.assertNotEqual(statsIterRandomStates[0].randint(5000),
@@ -99,6 +100,7 @@ class Test_initRandomState(unittest.TestCase):
             tmp_path+"random_state.pickle",
             tmp_path)
         os.remove(tmp_path+"random_state.pickle")
+
         np.testing.assert_array_equal(randomState_to_pickle.beta(1, 100, 100),
                                       pickled_randomState.beta(1, 100, 100))
 

requirements.txt

@@ -14,4 +14,3 @@ pandas==0.23.3
 m2r==0.2.1
 docutils==0.12
 pyyaml==3.12
-tkinter==8.6