def let_train_invests(self, corps, start_no=1):
"""입력한 회사들에 대해서 학습시키고 모의투자를 실행한다."""
if self.params.is_all_corps_model == True and self.params.remove_session_file == True:
learning = Learning(self.params)
learning.delete_learning_image()
comp_rmses = []
no = 1
for index, corp_data in corps.iterrows():
if no < start_no:
no += 1
continue
corp_code = corp_data['종목코드']
corp_name = corp_data['회사명']
try:
result = self.let_train_invest(corp_code, corp_name, no)
except Exception as inst:
print(inst)
no += 1
continue
comp_rmses.append(result)
if no % 10 == 0:
df_comp_rmses = pd.DataFrame(comp_rmses,
columns=self.result_columns)
DataUtils.save_excel(df_comp_rmses,
self.get_result_file_path())
no += 1
def let_train_invest(self, corp_code, corp_name, no):
"""입력한 회사에 대해서 학습시키고 모의투자를 실행한다."""
stocks = Stocks(self.params)
stock_data = stocks.get_stock_data(corp_code)
invest_count = self.params.invest_count
if invest_count == 0:
rmse_val, train_cnt, data_params, dataX_last, scaler_close = self.let_train_only(
corp_code, stock_data)
last_money = self.params.invest_money
all_invest_money = last_money
else:
if self.params.is_all_corps_model == False and self.params.remove_session_file == True:
learning = Learning(self.params)
learning.delete_learning_image(corp_code)
invest = MockInvestment(self.params)
rmse_val, train_cnt, data_params, dataX_last, scaler_close = self.let_train_only(
corp_code, stock_data)
last_money, last_predict, invest_predicts, all_invest_money = invest.let_invest(
corp_code, dataX_last, data_params)
if self.params.result_type == 'forcast':
invest = MockInvestment(self.params)
last_money, last_predict, invest_predicts, all_invest_money = \
invest.let_invest(corp_code, dataX_last, data_params)
last_date = stock_data.tail(1)['date'].to_string(index=False)
last_close_money, last_pred_money = invest.get_real_money(
data_params, scaler_close, last_predict)
last_pred_ratio = (last_pred_money -
last_close_money) / last_close_money * 100
last_pred_ratio = "{:.2f}".format(last_pred_ratio) + "%"
print(no, last_date, corp_code, corp_name, rmse_val, train_cnt,
last_close_money, last_pred_money, last_pred_ratio)
return [
no, last_date, corp_code, corp_name, rmse_val, train_cnt,
last_close_money, last_pred_money, last_pred_ratio
]
else:
print(no, corp_code, corp_name, rmse_val, last_money,
all_invest_money, train_cnt)
return [
no, corp_code, corp_name, rmse_val, last_money,
all_invest_money, train_cnt
]