def test_loadAllDatasets(self):
chalearnWrapper = ChalearnWrapper(files_loc='../data/chalearn_autoML_challenge')
available_datasets = chalearnWrapper.getAvailableDatasets()
available_datasets = ['dorothea', 'christine', 'jasmine', 'madeline', 'philippine', 'sylvine', 'albert', 'dilbert', 'fabert', 'robert', 'volkert']
for dataset_name in available_datasets:
print("loading dataset {0}".format(dataset_name))
chalearnWrapper.get_train_test_dataset(dataset_name)
class TestChalearnWrapper(TestCase):
def setUp(self):
self.dataset_loc = '../data/chalearn_autoML_challenge'
self.adult_dataset_loc = path.join(self.dataset_loc, 'round0/adult')
self.chalearnWrapper = ChalearnWrapper(self.dataset_loc)
def test_getDatasetFiles(self):
datasetFiles = self.chalearnWrapper.getDatasetFiles(self.adult_dataset_loc, 'adult')
def test_getAvailableDatasets(self):
available_datasets = self.chalearnWrapper.getAvailableDatasets()
self.assertTrue('adult' in available_datasets)
def test_getDataset(self):
mlProblem = self.chalearnWrapper.getMLproblem('adult')
self.assertTrue(mlProblem.has_key('train_data'))
def test_loadDatasetPropertiesDict(self):
self.chalearnWrapper.loadDatasetPropertiesDict(path.join(self.dataset_loc, 'round0/adult/adult_public.info'))
def test_loadNoHeaderDataframe(self):
df = self.chalearnWrapper.loadNoHeaderDataframe(path.join(self.dataset_loc, 'round0/adult/adult_train.data'))
self.assertEqual(df.values.shape[0], 34190)
self.assertEqual(df.values.shape[1], 24)
def test_loadDataset(self):
chalearnWrapper = ChalearnWrapper(files_loc='../data/chalearn_autoML_challenge')
mlProblem = chalearnWrapper.getMLproblem('adult')
dataLoader = TrainTestDataLoader(train=mlProblem.train_df, test=mlProblem.test_df, train_labels=mlProblem.train_labels, try_date_parse=False)
dataLoader.cleanData(max_onehot_limit=200)
X, X_sub, y = dataLoader.getTrainTestData()
def test_loadAllDatasets(self):
chalearnWrapper = ChalearnWrapper(files_loc='../data/chalearn_autoML_challenge')
available_datasets = chalearnWrapper.getAvailableDatasets()
available_datasets = ['dorothea', 'christine', 'jasmine', 'madeline', 'philippine', 'sylvine', 'albert', 'dilbert', 'fabert', 'robert', 'volkert']
for dataset_name in available_datasets:
print("loading dataset {0}".format(dataset_name))
chalearnWrapper.get_train_test_dataset(dataset_name)
