diff --git a/Simulation.py b/Simulation.py index c7241a9..9b6d3bb 100644 --- a/Simulation.py +++ b/Simulation.py @@ -135,25 +135,25 @@ class Simulation (HTS): if method == "answer": bsLine, data = self.labelMaker.makeCandidate(stock_code, today, view=True) - - elif method == "ml": - LAST_DATA = self.stock2Vector.getLastData(stock_code, today, n=10) - result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) - - df, minmax_df = self.stock2Vector.preprocessData(result) - bsLine, data = self.stockPredictor.predict(df, minmax_df, isRealTime=False) else: - LAST_DATA = self.stock2Vector.getLastData(stock_code, today) - result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) + if method == "ml": + LAST_DATA = self.stock2Vector.getLastData(stock_code, today, n=10) + result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) - # 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다. - data = self.buySellChecker.analyze(result) - # 사야 할 시점과 팔아야 할 시점을 체크한다. - bsLine, data = self.buySellChecker.checkTransaction(data, stock_code, isRealTime=False) + df, minmax_df = self.stock2Vector.preprocessData(result) + bsLine, data = self.stockPredictor.predict(df, minmax_df, isRealTime=False) + else: + LAST_DATA = self.stock2Vector.getLastData(stock_code, today) + result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) - if data is not None: - # 그래프를 그린다. - self.draw(stock_code, today, data, bsLine) + # 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다. + data = self.buySellChecker.analyze(result) + # 사야 할 시점과 팔아야 할 시점을 체크한다. + bsLine, data = self.buySellChecker.checkTransaction(data, stock_code, isRealTime=False) + + if data is not None: + # 그래프를 그린다. + self.draw(stock_code, today, data, bsLine) return @@ -166,13 +166,14 @@ if __name__ == "__main__": stock_codes = { # 252670 # 122630 - "122630": ['20220803'], + "252670": ['20220804'], } + method = "answer" # "ml", "answer" for stock_code in stock_codes: simulation = Simulation(RESOURCE_PATH) for given_day in stock_codes[stock_code]: - simulation.simulate(stock_code, given_day, method='ml') + simulation.simulate(stock_code, given_day, method=method) print ("done...")