cash_y = []
cash_x = []
for prices in market.iterate(tick_names=False):
y_pred = [
m.predict(get_ith_col_x(np.array(prices).reshape((-1, p, 30)), i))
for i, m in enumerate(models)
]
y_pred = np.array(y_pred).flatten()
y_preds.append(y_pred)
returns = np.divide(
np.subtract(np.array(y_pred), np.array(prices[-1])),
np.array(prices[-1]))
returns = returns.flatten()
max_return = max(returns)
max_index = list(returns).index(max_return)
cash = market.liquidate_stocks(market.ticks)
cash_y.append(cash)
# print(f'cash: {cash}, sec: {market.get_tick_from_index(max_index)}')
cash_x.append(
datetime.fromisoformat(str(market.date) + ' ' + str(market.time)))
market.buy([(max_index, cash)], with_index=True)
trades.append(max_index)
cash = market.liquidate_stocks(market.ticks)
print(cash)
x_test, y_test = tools.build_ar_x_y(x_test, p=p, rest=2)
x_purge, y_purge = tools.build_ar_x_y(x_purge, p=p, rest=2)
# for i in range(0, 30):
# yt = np.array(get_ith_col_y(np.array(y).reshape(-1, 30), i))
# ypurge = [None]*len(yt) + list(np.array(get_ith_col_y(np.array(y_purge).reshape((-1, 30)), i))) + [None]*len(y_preds)
