# read SPY.csv
train = readTrain()

# Augment the features (year, month, date, day)
train_Aug = augFeatures(train)

# Normalization
train_norm = normalize(train_Aug)

# build Data, use last 30 days to predict next 5 days
X_train, Y_train = buildTrain(train_norm, 30, 5)

# shuffle the data, and random seed is 10
X_train, Y_train = shuffle(X_train, Y_train)

# split training data and validation data
X_train, Y_train, X_val, Y_val = splitData(X_train, Y_train, 0.1)
# X_trian: (5710, 30, 10)
# Y_train: (5710, 5, 1)
# X_val: (634, 30, 10)
# Y_val: (634, 5, 1)