def test(test_gen, model_path):
test_result = Test.run_test(test_gen, model_path, 10)
Drawer.draw_test_result(test_result)
def test(data_path, model_path, target_size):
model = Model.load_model(model_path)
Test.run_test(model, data_path, target_size)
save=True,
NAME='AAPL')
train.run()
train.run_test()
else:
testing = Test(
data_file=df,
model_file='Outputs/AAPL_1min_10shift_979585.pth',
H1=128,
H2=256,
fx_pair='AAPL',
round_to=4,
)
testing.run_test(sym_0='', sym_1='', shift_pred=None, mov_ave=10)
# TODO what if I made a MovingAverage of the Predictions to keep it above and below the real
sys.exit(-123)
df = pd.read_csv(
file) # , index_col=0) # TODO: Add `, index_col=0` when using the AAPL
# df = df[:-50]
data_np = np.array(df).astype(dtype='float64')
random.shuffle(
data_np) # TODO: You'll want to comment this out for market data
data = separate_train_val_test(data_np)
print(
