From 8d1c4ae041d2a3e93dd2e7c095e238a072db697d Mon Sep 17 00:00:00 2001 From: dsyoon Date: Tue, 2 Aug 2022 13:10:37 +0900 Subject: [PATCH 1/2] init --- Simulation.py | 25 +++++++++++++++++-------- stock/util/LabelMaker.py | 8 ++++++++ 2 files changed, 25 insertions(+), 8 deletions(-) create mode 100644 stock/util/LabelMaker.py diff --git a/Simulation.py b/Simulation.py index 5c6eeec..37c3b03 100644 --- a/Simulation.py +++ b/Simulation.py @@ -3,6 +3,7 @@ import pandas as pd import plotly.graph_objects as go from plotly import subplots import os +import sqlite3 from hts.HTS import HTS from stock.util.Stock2Vector import Stock2Vector @@ -126,19 +127,27 @@ class Simulation (HTS): return - def simulate(self, stock_code, today): + def getData(self): + return + + def simulate(self, stock_code, today, type="rule"): LAST_DATA = self.stock2Vector.getLastData(stock_code, today) result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) - # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. - data = self.buySellChecker.analyzeByRule(result) + if type == "rule": + # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. + data = self.buySellChecker.analyzeByRule(result) + # 사야 할 시점과 팔아야 할 시점을 체크한다. + bsLine, data = self.buySellChecker.checkTransaction(data, stock_code, False) + elif type == "labeltest": + data = self.getData(result) + else: + data = None - # 사야 할 시점과 팔아야 할 시점을 체크한다. - bsLine, data = self.buySellChecker.checkTransaction(data, stock_code, False) - - # 그래프를 그린다. - self.draw(stock_code, today, data, bsLine) + if data is not None: + # 그래프를 그린다. + self.draw(stock_code, today, data, bsLine) return diff --git a/stock/util/LabelMaker.py b/stock/util/LabelMaker.py new file mode 100644 index 0000000..50a5e09 --- /dev/null +++ b/stock/util/LabelMaker.py @@ -0,0 +1,8 @@ +import sqlite3 + +class LabelMaker: + def __init__(self): + return + +if __name__ == "__main__": + labelMaker = LabelMaker() \ No newline at end of file From a191fba93ac5221201671ef7adff967bb39b4af4 Mon Sep 17 00:00:00 2001 From: "dosang.yoon" Date: Tue, 2 Aug 2022 15:48:28 +0900 Subject: [PATCH 2/2] init --- HTS_122630.py | 20 +--- HTS_252670.py | 12 +- Simulation.py | 19 ++-- hts/BuySellChecker.py | 37 +++---- resources/tmp/20220727.buy.csv | 13 +++ resources/tmp/20220727.sell.csv | 8 ++ resources/tmp/20220728.buy.csv | 14 +++ resources/tmp/20220728.sell.csv | 9 ++ resources/tmp/20220729.buy.csv | 8 ++ resources/tmp/20220729.sell.csv | 5 + stock/util/LabelMaker.py | 187 +++++++++++++++++++++++++++++++- 11 files changed, 279 insertions(+), 53 deletions(-) create mode 100644 resources/tmp/20220727.buy.csv create mode 100644 resources/tmp/20220727.sell.csv create mode 100644 resources/tmp/20220728.buy.csv create mode 100644 resources/tmp/20220728.sell.csv create mode 100644 resources/tmp/20220729.buy.csv create mode 100644 resources/tmp/20220729.sell.csv diff --git a/HTS_122630.py b/HTS_122630.py index 52306c4..07d2bc9 100644 --- a/HTS_122630.py +++ b/HTS_122630.py @@ -28,14 +28,6 @@ class HTS_122630 (HTS): self.buySellChecker = BuySellChecker() return - def checkTransaction(self, data): - size = len(data["close"]) - - last_index = size - 1 - sell, weight = self.buySellChecker.getSellPriceAndWeight_15000(data, last_index) - buy, weight = self.buySellChecker.getBuyPriceAndWeight_15000(data, last_index) - return buy, weight, sell - def getSellingPrice(self, final_price): # 만약 잔고가 있으면 장부가보다 5원 높게 매도한다. jangoDic = self.requstJango() @@ -92,20 +84,20 @@ class HTS_122630 (HTS): result = self.getRealTime(self.stock_code, today, LAST_DATA) # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. - data = self.buySellChecker.analyzeByRule(result) + data = self.buySellChecker.analyze(result) # 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다. - bsLine, data = self.buySellChecker.checkTransaction(data, self.stock_code, True) - bs_buy_price = bsLine['buy'] - bs_weight = bsLine['buy_weight'] - bs_sell_price = bsLine['sell'] + bsLine, data = self.buySellChecker.checkTransaction(data, self.stock_code, isRealTime=True) + bs_buy_price = bsLine['buy'][0] + bs_buy_weight = bsLine['buy_weight'][0] + bs_sell_price = bsLine['sell'][0] data_size = len(data["close"]) final_price = data["close"][data_size-1] if bs_buy_price > 0: # 기본 100 주에 가중치를 추가해서 매수한다. - BUY_COUNT = int(self.buy_count * bs_weight) + BUY_COUNT = int(self.buy_count * bs_buy_weight) # 매수를 주문한다. orderNum = self.requestOrder(OrderType.buy, self.stock_code, BUY_COUNT, bs_buy_price) diff --git a/HTS_252670.py b/HTS_252670.py index 237601a..97bb909 100644 --- a/HTS_252670.py +++ b/HTS_252670.py @@ -85,20 +85,20 @@ class HTS_252670 (HTS): result = self.getRealTime(self.stock_code, today, LAST_DATA) # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. - data = self.buySellChecker.analyzeByRule(result) + data = self.buySellChecker.analyze(result) # 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다. - bsLine, data = self.buySellChecker.checkTransaction(data, self.stock_code, True) - bs_buy_price = bsLine['buy'] - bs_weight = bsLine['buy_weight'] - bs_sell_price = bsLine['sell'] + bsLine, data = self.buySellChecker.checkTransaction(data, self.stock_code, isRealTime=True) + bs_buy_price = bsLine['buy'][0] + bs_buy_weight = bsLine['buy_weight'][0] + bs_sell_price = bsLine['sell'][0] data_size = len(data["close"]) final_price = data["close"][data_size-1] if bs_buy_price > 0: # 기본 100 주에 가중치를 추가해서 매수한다. - BUY_COUNT = int(self.buy_count * bs_weight) + BUY_COUNT = int(self.buy_count * bs_buy_weight) # 매수를 주문한다. orderNum = self.requestOrder(OrderType.buy, self.stock_code, BUY_COUNT , bs_buy_price) diff --git a/Simulation.py b/Simulation.py index 37c3b03..36c3314 100644 --- a/Simulation.py +++ b/Simulation.py @@ -3,7 +3,6 @@ import pandas as pd import plotly.graph_objects as go from plotly import subplots import os -import sqlite3 from hts.HTS import HTS from stock.util.Stock2Vector import Stock2Vector @@ -98,7 +97,7 @@ class Simulation (HTS): # 그래프를 그린다. """ - fig = go.Figure(hts=candle_data) + fig = go.Figure(data=candle_data) fig.update_layout(title=stock_code + "_" + given_day) fig.show() """ @@ -127,8 +126,8 @@ class Simulation (HTS): return - def getData(self): - return + def analyzeAutoMode(self, data): + return data, None def simulate(self, stock_code, today, type="rule"): LAST_DATA = self.stock2Vector.getLastData(stock_code, today) @@ -136,14 +135,14 @@ class Simulation (HTS): result = self.stock2Vector.getRealTime(stock_code, today, LAST_DATA) if type == "rule": - # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. - data = self.buySellChecker.analyzeByRule(result) + # 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, False) - elif type == "labeltest": - data = self.getData(result) + bsLine, data = self.buySellChecker.checkTransaction(data, stock_code, isRealTime=False) + elif type == "auto": + data, bsLine = self.analyzeAutoMode(result) else: - data = None + data, bsLine = None, None if data is not None: # 그래프를 그린다. diff --git a/hts/BuySellChecker.py b/hts/BuySellChecker.py index 75971db..65e3afa 100644 --- a/hts/BuySellChecker.py +++ b/hts/BuySellChecker.py @@ -746,14 +746,7 @@ class BuySellChecker: return sell, weight - - - - - - - - def analyzeByRule(self, result): + def analyze(self, result): open = result["open"] close = result["close"] high = result["high"] @@ -1161,7 +1154,7 @@ class BuySellChecker: data = data.fillna(close[0]) return data - def checkTransaction(self, data, stock_code, type=True): + def checkTransaction(self, data, stock_code, isRealTime=True): # 4일치 중에서 앞에 2일은 제거한다. date = data['date'].dt.date.unique().tolist() data = data[data['date'].dt.date != date[0]] @@ -1170,7 +1163,8 @@ class BuySellChecker: # 어제 오늘 데이터로 분석 bsLine = {} size = len(data["close"]) - if type: + if isRealTime: + # isRealTime=True, 실시간 적용 last_index = size - 1 if stock_code == "252670": @@ -1180,25 +1174,28 @@ class BuySellChecker: sell, weight = self.getSellPriceAndWeight_15000(data, last_index) buy, weight = self.getBuyPriceAndWeight_15000(data, last_index) - bsLine['buy'] = buy - bsLine['buy_weight'] = weight - bsLine['sell'] = sell - bsLine['sell_weight'] = weight + bsLine['buy'] = [buy] + bsLine['buy_weight'] = [weight] + bsLine['sell'] = [sell] + bsLine['sell_weight'] = [weight] else: + # Type=False, 시뮬레이션 적용 bsLine['buy'] = [-1 for i in range(size)] - bsLine['weight'] = [-1 for i in range(size)] + bsLine['buy_weight'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)] + bsLine['sell_weight'] = [-1 for i in range(size)] for i in range(size): if stock_code == "252670": - sell, weight = self.getSellPriceAndWeight_3000(data, i) - buy, weight = self.getBuyPriceAndWeight_3000(data, i) + sell, sell_weight = self.getSellPriceAndWeight_3000(data, i) + buy, buy_weight = self.getBuyPriceAndWeight_3000(data, i) else: - sell, weight = self.getSellPriceAndWeight_15000(data, i) - buy, weight = self.getBuyPriceAndWeight_15000(data, i) + sell, sell_weight = self.getSellPriceAndWeight_15000(data, i) + buy, buy_weight = self.getBuyPriceAndWeight_15000(data, i) bsLine['buy'][i] = buy - bsLine['weight'][i] = weight + bsLine['buy_weight'][i] = buy_weight bsLine['sell'][i] = sell + bsLine['sell_weight'][i] = sell_weight return bsLine, data diff --git a/resources/tmp/20220727.buy.csv b/resources/tmp/20220727.buy.csv new file mode 100644 index 0000000..482877c --- /dev/null +++ b/resources/tmp/20220727.buy.csv @@ -0,0 +1,13 @@ +2022-07-27 09:19:00,3060 +2022-07-27 09:20:00,3070 +2022-07-27 09:21:00,3070 +2022-07-27 09:53:00,3075 +2022-07-27 09:57:00,3075 +2022-07-27 09:58:00,3075 +2022-07-27 12:26:00,3090 +2022-07-27 12:27:00,3090 +2022-07-27 12:31:00,3090 +2022-07-27 12:32:00,3090 +2022-07-27 12:33:00,3090 +2022-07-27 12:36:00,3090 +2022-07-27 12:38:00,3090 diff --git a/resources/tmp/20220727.sell.csv b/resources/tmp/20220727.sell.csv new file mode 100644 index 0000000..80be832 --- /dev/null +++ b/resources/tmp/20220727.sell.csv @@ -0,0 +1,8 @@ +2022-07-27 09:05:00,3085 +2022-07-27 09:06:00,3085 +2022-07-27 09:08:00,3085 +2022-07-27 09:34:00,3085 +2022-07-27 10:29:00,3105 +2022-07-27 10:30:00,3105 +2022-07-27 13:07:00,3105 +2022-07-27 13:24:00,3105 \ No newline at end of file diff --git a/resources/tmp/20220728.buy.csv b/resources/tmp/20220728.buy.csv new file mode 100644 index 0000000..f5ed134 --- /dev/null +++ b/resources/tmp/20220728.buy.csv @@ -0,0 +1,14 @@ +2022-07-28 09:07:00,2975 +2022-07-28 09:08:00,2985 +2022-07-28 09:09:00,2995 +2022-07-28 09:10:00,2995 +2022-07-28 09:51:00,2995 +2022-07-28 09:52:00,3000 +2022-07-28 09:53:00,3000 +2022-07-28 09:55:00,3000 +2022-07-28 09:57:00,3000 +2022-07-28 09:58:00,3005 +2022-07-28 09:59:00,3005 +2022-07-28 11:59:00,3005 +2022-07-28 12:00:00,3010 +2022-07-28 12:01:00,3010 diff --git a/resources/tmp/20220728.sell.csv b/resources/tmp/20220728.sell.csv new file mode 100644 index 0000000..84d13a4 --- /dev/null +++ b/resources/tmp/20220728.sell.csv @@ -0,0 +1,9 @@ +2022-07-28 09:32:00,3025 +2022-07-28 10:23:00,3035 +2022-07-28 10:37:00,3035 +2022-07-28 10:38:00,3035 +2022-07-28 10:41:00,3035 +2022-07-28 10:44:00,3035 +2022-07-28 10:46:00,3035 +2022-07-28 12:24:00,3030 +2022-07-28 14:27:00,3040 diff --git a/resources/tmp/20220729.buy.csv b/resources/tmp/20220729.buy.csv new file mode 100644 index 0000000..33454d5 --- /dev/null +++ b/resources/tmp/20220729.buy.csv @@ -0,0 +1,8 @@ +2022-07-29 09:34:00,2945 +2022-07-29 09:35:00,2945 +2022-07-29 09:36:00,2945 +2022-07-29 09:37:00,2945 +2022-07-29 09:38:00,2950 +2022-07-29 09:39:00,2950 +2022-07-29 09:40:00,2950 +2022-07-29 12:31:00,2990 diff --git a/resources/tmp/20220729.sell.csv b/resources/tmp/20220729.sell.csv new file mode 100644 index 0000000..cbf2399 --- /dev/null +++ b/resources/tmp/20220729.sell.csv @@ -0,0 +1,5 @@ +2022-07-29 10:07:00,2985 +2022-07-29 10:49:00,2990 +2022-07-29 12:53:00,3010 +2022-07-29 14:15:00,3015 +2022-07-29 14:16:00,3015 diff --git a/stock/util/LabelMaker.py b/stock/util/LabelMaker.py index 50a5e09..7a4c864 100644 --- a/stock/util/LabelMaker.py +++ b/stock/util/LabelMaker.py @@ -1,8 +1,189 @@ -import sqlite3 +import os +import csv +from math import nan +import pandas as pd +import plotly.graph_objects as go +from plotly import subplots + +from hts.HTS import HTS +from hts.BuySellChecker import BuySellChecker + +class LabelMaker (HTS): + buySellChecker = None -class LabelMaker: def __init__(self): + super().__init__(RESOURCE_PATH) + self.buySellChecker = BuySellChecker() + return + + def checkTransaction(self, data): + bsLine = {} + size = len(data["close"]) + + # Type=False, 시뮬레이션 적용 + bsLine['buy'] = [-1 for i in range(size)] + bsLine['buy_weight'] = [-1 for i in range(size)] + bsLine['sell'] = [-1 for i in range(size)] + bsLine['sell_weight'] = [-1 for i in range(size)] + + for i in range(size-60): + min_price, min_price_c, max_price, max_price_c = 9999999, -1, 0, -1 + for c in range(i, i+60): + if data["close"][c] > max_price: + max_price = data["close"][c] + max_price_c = c + if data["close"][c] < min_price: + min_price = data["close"][c] + min_price_c = c + + if min_price_c > 0: + bsLine['buy'][min_price_c] = min_price + bsLine['buy_weight'][min_price_c] = 1 + if max_price_c > 0: + bsLine['sell'][max_price_c] = max_price + bsLine['sell_weight'][min_price_c] = 1 + + return bsLine, data + + def draw(self, stock_code, given_day, data, bsLine): + buy_line = bsLine['buy'] + sell_line = bsLine['sell'] + + # 그래프 설정을 위한 변수를 생성한다. + data = data.astype({'open': 'int', + 'high': 'int', + 'low': 'int', + 'close': 'int', + 'volume': 'int', + 'avg3': 'float', + 'avg5': 'float', + 'avg10': 'float', + 'avg20': 'float', + 'avg30': 'float', + 'avg60': 'float', + 'fast_k': 'float', + 'slow_k': 'float', + 'slow_d': 'float', + 'rsi': 'float', + 'rsis': 'float' + }) + + buy_colors = [] + for i in range(len(buy_line)): + if buy_line[i] < 0: + buy_colors.append("#ffffff") + buy_line[i] = nan + else: + buy_colors.append("#ff00ff") + sell_colors = [] + for i in range(len(sell_line)): + if sell_line[i] < 0: + sell_colors.append("#ffffff") + sell_line[i] = nan + else: + sell_colors.append("#00ced1") + + # 그래프를 설정한다. + buy_check = go.Scatter(x=data['date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0)) + sell_check = go.Scatter(x=data['date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0)) + upper = go.Scatter(x=data['date'], y=data["upper"], name="upper", line_color='#000000') + lower = go.Scatter(x=data['date'], y=data["lower"], name="lower", line_color='#000000') + avg3 = go.Scatter(x=data['date'], y=data["avg3"], name="avg3", line_color='#1469F4') + avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#089B5B') + avg10 = go.Scatter(x=data['date'], y=data["avg10"], name="avg10", line_color='#ff00ff') + avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#8F8203') + avg30 = go.Scatter(x=data['date'], y=data["avg30"], name="avg30", line_color='#000000') + + 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') + volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume') + #fast_k_line = go.Scatter(x=hts['date'], y=hts["fast_k"], mode='lines', name='fast_k') + + macd_line = go.Scatter(x=data['date'], y=data["macd"], mode='lines', name='macd') + macd_s_line = go.Scatter(x=data['date'], y=data["macds"], mode='lines', name='macds') + macd_o_line = go.Scatter(x=data['date'], y=data["macdo"], mode='lines', name='macdo') + + slow_k_line = go.Scatter(x=data['date'], y=data["slow_k"], mode='lines', name='slow_k') + slow_d_line = go.Scatter(x=data['date'], y=data["slow_d"], mode='lines', name='slow_d') + + rsi_line = go.Scatter(x=data['date'], y=data["rsi"], mode='lines', name='rsi') + rsis_line = go.Scatter(x=data['date'], y=data["rsis"], mode='lines', name='rsis') + + candle_data = [candle_stick, upper, lower, avg3, avg5, avg10, avg20, avg30, buy_check, sell_check] + volume_data = [volume_line] + macd_data = [macd_line, macd_s_line, macd_o_line] + stochastic_data = [slow_k_line, slow_d_line] + rsi_data = [rsi_line, rsis_line] + + """ + fig = go.Figure(data=candle_data) + df = pd.DataFrame(bsLine) + df = df.fillna(-1) + buy_count = len(df.loc[df["buy"] > 0]) + sell_count = len(df.loc[df["sell"] > 0]) + + fig.update_layout(height=1000, title=stock_code + "_" + given_day + "_" + str(buy_count)+","+str(sell_count)) + fig.show() + """ + + fig = subplots.make_subplots(rows=5, cols=1, subplot_titles=('캔들', "거래량", "MACD", "스토캐스틱", "RSI")) + for trace in candle_data: + fig.append_trace(trace, 1, 1) + for trace in volume_data: + fig.append_trace(trace, 2, 1) + for trace in macd_data: + fig.append_trace(trace, 3, 1) + for trace in stochastic_data: + fig.append_trace(trace, 4, 1) + for trace in rsi_data: + fig.append_trace(trace, 5, 1) + #fig.update_xaxes(nticks=5) + #fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False) + + df = pd.DataFrame(bsLine) + df = df.fillna(-1) + buy_count = len(df.loc[df["buy"] > 0]) + sell_count = len(df.loc[df["sell"] > 0]) + + fig.update_layout(height=3000, title=stock_code + "_" + given_day + "_" + str(buy_count)+","+str(sell_count)) + fig.show() + + + return + + def writeLabelFile(self, bsLine, data, ymd): + outFileName = os.path.join(self.RESOURCE_PATH, "tmp", ymd+".sell.csv") + with open(outFileName, "w", encoding="utf-8") as outFp: + writer = csv.writer(outFp) + for i, price in enumerate(bsLine["sell"]): + if price != -1: + writer.writerow([data['date'][i], bsLine["sell"][i]]) + + outFileName = os.path.join(self.RESOURCE_PATH, "tmp", ymd + ".buy.csv") + with open(outFileName, "w", encoding="utf-8") as outFp: + writer = csv.writer(outFp) + for i, price in enumerate(bsLine["buy"]): + if price != -1: + writer.writerow([data['date'][i], bsLine["buy"][i]]) + return + + def makeCandidate(self, stock_code, ymd="20220727"): + result = {"check": set(), "time": [], "open": [], "close": [], "high": [], "low": [], "vol": [], "label": []} + self.getDBData(stock_code, ymd, result) + + data = self.buySellChecker.analyze(result) + bsLine, data = self.checkTransaction(data) + + self.writeLabelFile(bsLine, data, ymd) + self.draw(stock_code, ymd, data, bsLine) return if __name__ == "__main__": - labelMaker = LabelMaker() \ No newline at end of file + PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__)))))) + RESOURCE_PATH = os.path.join(PROJECT_HOME, "resources") + + labelMaker = LabelMaker() + + stock_code = "252670" + #stock_code = "122630" + + labelMaker.makeCandidate(stock_code, "20220727") \ No newline at end of file