183 lines
7.3 KiB
Python
183 lines
7.3 KiB
Python
import os
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from datetime import datetime, timedelta
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import pandas as pd
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import plotly.graph_objects as go
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from plotly import subplots
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from BuySellChecker import BuySellChecker
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class Simulation:
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buySellChecker = None
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def __init__(self):
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self.buySellChecker = BuySellChecker()
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#self.connect()
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return
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def getCSV(self, fileName, given_day, result):
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data = pd.read_csv(fileName)
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days = data.날짜
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time = data.시간
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open = data.시가
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close = data.종가
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high = data.고가
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low = data.저가
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vol = data.거래량
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start_time = datetime.strptime(given_day + " 090000", '%Y%m%d %H%M%S')
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for i in range(len(data)):
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temp = datetime.strptime(str(days[i]) + " " + str(time[i]).zfill(4)+"00", '%Y%m%d %H%M%S')
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if temp < start_time:
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continue
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if temp not in result["check"]:
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result["check"].add(temp)
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result["time"].append(temp)
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result["open"].append(open[i])
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result["close"].append(close[i])
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result["high"].append(high[i])
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result["low"].append(low[i])
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result["vol"].append(vol[i])
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return
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def checkTransaction(self, data):
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size = len(data["Close"])
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bsLine = {}
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bsLine['buy'] = [-1 for i in range(size)]
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bsLine['weight'] = [-1 for i in range(size)]
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bsLine['sell'] = [-1 for i in range(size)]
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for i in range(6, size-5):
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buy, weight, sell = self.buySellChecker.getPriceAndWeight1(data, i)
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bsLine['buy'][i] = buy
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bsLine['weight'][i] = weight
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bsLine['sell'][i] = sell
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return bsLine
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def draw(self, stock_code, given_day, data, bsLine):
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buy_line = bsLine['buy']
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sell_line = bsLine['sell']
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# 그래프 설정을 위한 변수를 생성한다.
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data['Open'] = pd.to_numeric(data['Open'])
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data['High'] = pd.to_numeric(data['High'])
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data['Low'] = pd.to_numeric(data['Low'])
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data['Close'] = pd.to_numeric(data['Close'])
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data['Volume'] = pd.to_numeric(data['Volume'])
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data['avg5'] = pd.to_numeric(data['avg5'])
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data["fast_k"] = pd.to_numeric(data['fast_k'])
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data["slow_k"] = pd.to_numeric(data['slow_k'])
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data["slow_d"] = pd.to_numeric(data['slow_d'])
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data["rsi"] = pd.to_numeric(data['rsi'])
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data["rsis"] = pd.to_numeric(data['rsis'])
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buy_colors = []
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for i in range(len(buy_line)):
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if buy_line[i] < 0:
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buy_colors.append("#ffffff")
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buy_line[i] = data["lower"][0]
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else:
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buy_colors.append("#ff00ff")
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sell_colors = []
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for i in range(len(sell_line)):
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if sell_line[i] < 0:
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sell_colors.append("#ffffff")
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sell_line[i] = data["lower"][0]
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else:
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sell_colors.append("#00ced1")
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# 그래프를 설정한다.
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buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
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sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
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bolinger_upper = go.Scatter(x=data['Date'], y=data["upper"], name="upper", line_color='#8B4513')
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bolinger_lower = go.Scatter(x=data['Date'], y=data["lower"], name="lower", line_color='#8B4513')
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avg5 = go.Scatter(x=data['Date'], y=data["avg5"], name="avg5", line_color='#000000')
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candle_stick = go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], increasing_line_color='red', decreasing_line_color='blue')
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volume_line = go.Scatter(x=data['Date'], y=data["Volume"], mode='lines', name='Volume')
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fast_k_line = go.Scatter(x=data['Date'], y=data["fast_k"], mode='lines', name='fast_k')
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slow_k_line = go.Scatter(x=data['Date'], y=data["slow_k"], mode='lines', name='slow_k')
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slow_d_line = go.Scatter(x=data['Date'], y=data["slow_d"], mode='lines', name='slow_d')
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rsi_line = go.Scatter(x=data['Date'], y=data["rsi"], mode='lines', name='rsi')
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rsis_line = go.Scatter(x=data['Date'], y=data["rsis"], mode='lines', name='rsis')
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#candle_data = [candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60]
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candle_data = [candle_stick, bolinger_upper, bolinger_lower, avg5, buy_check, sell_check]
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volume_data = [volume_line]
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stochastic_data = [slow_k_line, slow_d_line]
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rsi_data = [rsi_line, rsis_line]
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# 그래프를 그린다.
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"""
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fig = go.Figure(data=candle_data)
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fig.update_layout(title=stock_code + "_" + given_day)
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fig.show()
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"""
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fig = subplots.make_subplots(rows=4, cols=1, subplot_titles=('캔들', "거래량", "스토캐스틱", "RSI"))
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for trace in candle_data:
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fig.append_trace(trace, 1, 1)
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for trace in volume_data:
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fig.append_trace(trace, 2, 1)
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for trace in stochastic_data:
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fig.append_trace(trace, 3, 1)
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for trace in rsi_data:
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fig.append_trace(trace, 4, 1)
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#fig.update_xaxes(nticks=5)
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#fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False)
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df = pd.DataFrame(bsLine)
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df = df.fillna(-1)
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buy_count = len(df.loc[df["buy"] > 0])
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sell_count = len(df.loc[df["sell"] > 0])
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fig.update_layout(height=1800, title=stock_code + "_" + given_day + "_" + str(buy_count)+","+str(sell_count))
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fig.show()
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return
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def simulate(self, stock_code, GIVEN_DAY):
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result = {"check": set(),
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"time": [],
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"open": [],
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"close": [],
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"high": [],
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"low": [],
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"vol": []}
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# 데이터를 가지고 온다.
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self.getCSV("./data/"+stock_code+"_"+GIVEN_DAY+".csv", GIVEN_DAY, result)
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# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
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data = self.buySellChecker.analyze(result)
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# 사야 할 시점과 팔아야 할 시점을 체크한다.
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bsLine = self.checkTransaction(data)
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# 그래프를 그린다.
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self.draw(stock_code, GIVEN_DAY, data, bsLine)
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return
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if __name__ == "__main__":
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today = datetime.today()
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PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__))))
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RESOURCE_DIR = PROJECT_HOME + "/resources/analysis/"+today.strftime("%Y%m%d")
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stock_codes = ["252670", "122630"]
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given_days = ['20210901','20210902','20210903','20210906','20210907','20210908','20210909','20210910','20210913',
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'20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929',
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'20210930','20211001', '20211005','20211006', '20211007','20211008', '20211012','20211013', '20211014', '20211018']
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simulation = Simulation()
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given_days = sorted(given_days, reverse=True)
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for given_day in given_days:
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simulation.simulate(stock_codes[0], given_day)
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print ("done...")
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