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)
