import os import sys # save accuracy score results = open(os.path.basename(__file__) + '.csv', 'w') # get_data_block_start from get_data import GetData getData = GetData() fields = ['Open', 'High', 'Low', 'Close', 'Adj_Close'] accuracy = {} features = getData.getAllFeatures() symbols = getData.getAllSymbols() # get_data_block_end for symbol in symbols: accuracy[symbol] = [] for field in range(1, 5): labels = getData.getSymbolCLFLabels(symbol, field) ######################## # now the real MA work # ######################## # create train and test data set X_test, X_train, y_test, y_train = train_test_split(features, labels,
def test_getAllFeatures3(self): getData = GetData(5) features = getData.getAllFeatures('open', 'close') self.assertIsNotNone(features) self.assertEqual(len(features[0][0]), 2)
def test_getAllFeatures1(self): getData = GetData() features = getData.getAllFeatures() self.assertIsNotNone(features)
def test_getAllFeatures2(self): getData = GetData(101) features = getData.getAllFeatures() self.assertIsNotNone(features) self.assertEqual(len(features), 100)