Added tests for most of adaboost

Code/MonoMultiViewClassifiers/MonoviewClassifiers/Adaboost.py

@@ -58,12 +58,14 @@ def randomizedSearch(X_train, y_train, randomState, outputFileName, KFolds=4, me
 
     param = {"classifier__n_estimators": randint(1, 150),
              "classifier__base_estimator": [DecisionTreeClassifier()]}
+
     metricModule = getattr(Metrics, metric[0])
     if metric[1] is not None:
         metricKWARGS = dict((index, metricConfig) for index, metricConfig in enumerate(metric[1]))
     else:
         metricKWARGS = {}
     scorer = metricModule.get_scorer(**metricKWARGS)
+
     grid = RandomizedSearchCV(pipeline, n_iter=nIter, param_distributions=param, refit=True, n_jobs=nbCores,
                               scoring=scorer, cv=KFolds, random_state=randomState)
     detector = grid.fit(X_train, y_train)

Code/Tests/Test_MonoviewClassifiers/test_Adaboost.py

 import unittest
 import numpy as np
+from sklearn.tree import DecisionTreeClassifier
 
 from ...MonoMultiViewClassifiers.MonoviewClassifiers import Adaboost
 
 
+class Test_canProbas(unittest.TestCase):
+
+    def test_simple(cls):
+        cls.assertTrue(Adaboost.canProbas())
+
+
+class Test_paramsToSet(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        cls.n_iter = 4
+        cls.random_state = np.random.RandomState(42)
+
+    def test_simple(cls):
+        res = Adaboost.paramsToSet(cls.n_iter, cls.random_state)
+        cls.assertEqual(len(res), cls.n_iter)
+        cls.assertEqual(type(res[0][0]), int)
+        cls.assertEqual(type(res[0][1]), type(DecisionTreeClassifier()))
+        cls.assertEqual([7,4,13,11], [resIter[0] for resIter in res])
+
+
+class Test_getKWARGS(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        cls.kwargs_list = [("CL_Adaboost_n_est", 10),
+                           ("CL_Adaboost_b_est", DecisionTreeClassifier())]
+
+    def test_simple(cls):
+        res = Adaboost.getKWARGS(cls.kwargs_list)
+        cls.assertIn("0", res)
+        cls.assertIn("1", res)
+        cls.assertEqual(type(res), dict)
+        cls.assertEqual(res["0"], 10)
+        # Can't test decision tree
+
+    def test_wrong(cls):
+        cls.kwargs_list[0] = ("chicken_is_heaven",42)
+        with cls.assertRaises(ValueError) as catcher:
+            Adaboost.getKWARGS(cls.kwargs_list)
+        exception = catcher.exception
+        # cls.assertEqual(exception, "Wrong arguments served to Adaboost")
+
+
+class Test_randomizedSearch(unittest.TestCase):
+
+    def test_simple(cls):
+        pass  # Test with simple params
+
+
 class Test_fit(unittest.TestCase):
 
     def setUp(self):