329 lines
14 KiB
Python
329 lines
14 KiB
Python
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
|
|
from stock.util.Stock2Vector import Stock2Vector
|
|
|
|
class LabelChecker (HTS):
|
|
buySellChecker = None
|
|
stock2Vector = None
|
|
|
|
def __init__(self, RESOURCE_PATH):
|
|
super().__init__(RESOURCE_PATH)
|
|
self.buySellChecker = BuySellChecker()
|
|
self.stock2Vector = Stock2Vector(RESOURCE_PATH)
|
|
return
|
|
|
|
def checkTransaction(self, data, duration=60):
|
|
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)]
|
|
|
|
# 매수 처리
|
|
p_min_price = 999999999
|
|
# - 10을 한 것은 3시 11분까지 매수를 하기 위함임
|
|
for i in range(size-duration-10):
|
|
min_price, min_price_c, = 9999999, -1
|
|
for c in range(i, i+duration):
|
|
if min(data["close"][c], data["close"][c]) < min_price:
|
|
min_price = min(data["close"][c], data["close"][c])
|
|
min_price_c = c
|
|
|
|
# 매수 처리
|
|
if min_price_c > 0:
|
|
isValid = True
|
|
for c in range(2, 10):
|
|
if bsLine['buy'][min_price_c - c] > 0:
|
|
isValid = False
|
|
break
|
|
if isValid:
|
|
if min_price < p_min_price:
|
|
bsLine['buy'][min_price_c] = min_price
|
|
bsLine['buy_weight'][min_price_c] = 1
|
|
p_min_price = min_price
|
|
|
|
# 매도 처리
|
|
buy_i = [c for c in range(size) if bsLine['buy'][c] > 0]
|
|
for i in range(len(buy_i)):
|
|
if i < len(buy_i)-1:
|
|
boundry = data["high"][buy_i[i]+1: buy_i[i+1]]
|
|
if len(boundry) > 1:
|
|
max_price = max(boundry)
|
|
for c in range(buy_i[i], buy_i[i+1]):
|
|
if data["high"][c] == max_price:
|
|
isValid = False
|
|
for d in range(c - 1, 0, -1):
|
|
if bsLine['sell'][d] > 0 and bsLine['buy'][d] < 0:
|
|
break
|
|
if bsLine['sell'][d] < 0 and bsLine['buy'][d] > 0:
|
|
isValid = True
|
|
break
|
|
if isValid:
|
|
bsLine['sell'][c] = max_price
|
|
bsLine['sell_weight'][c] = 1
|
|
else:
|
|
# - 5를 한 것은 3시 16분까지 매도를 하기 위함임
|
|
boundry = data["high"][buy_i[i] + 1: len(data["high"])-5]
|
|
if len(boundry) > 1:
|
|
max_price = max(boundry)
|
|
for c in range(buy_i[i], len(data["high"])):
|
|
if data["high"][c] == max_price:
|
|
isValid = False
|
|
for d in range(c-1, 0, -1):
|
|
if bsLine['sell'][d] > 0 and bsLine['buy'][d] < 0 :
|
|
break
|
|
if bsLine['sell'][d] < 0 and bsLine['buy'][d] > 0 :
|
|
isValid = True
|
|
break
|
|
if isValid:
|
|
bsLine['sell'][c] = max_price
|
|
bsLine['sell_weight'][c] = 1
|
|
|
|
return bsLine, data
|
|
|
|
def draw_simple(self, stock_code, given_day, data, bsLine):
|
|
data = data.loc[pd.DatetimeIndex(data.index).day == int(given_day[6:])]
|
|
buy_line = bsLine['buy'][381:]
|
|
sell_line = bsLine['sell'][381:]
|
|
|
|
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))
|
|
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')
|
|
candle_data = [candle_stick, buy_check, sell_check]
|
|
|
|
df = pd.DataFrame(bsLine)
|
|
df = df.fillna(-1)
|
|
buy_count = len(df.loc[df["buy"] > 0])
|
|
sell_count = len(df.loc[df["sell"] > 0])
|
|
|
|
self.fig = go.FigureWidget(data=candle_data)
|
|
self.buy_data = self.fig.data[1]
|
|
self.fig.update_layout(height=1000, title=stock_code + "_" + given_day + "_" + str(buy_count) + "," + str(sell_count))
|
|
self.fig.show()
|
|
|
|
return
|
|
|
|
def draw_detail(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',
|
|
'avg6': 'float',
|
|
'avg9': 'float',
|
|
'avg12': 'float',
|
|
'avg27': 'float',
|
|
'avg54': 'float',
|
|
'fast_k': 'float',
|
|
'slow_k': 'float',
|
|
'slow_d': 'float',
|
|
'rsi': 'float',
|
|
'rsis': 'float'
|
|
})
|
|
|
|
buy_size = []
|
|
buy_colors = []
|
|
for i in range(len(buy_line)):
|
|
if buy_line[i] < 0:
|
|
buy_colors.append("#ffffff")
|
|
buy_line[i] = nan
|
|
buy_size.append(0)
|
|
else:
|
|
buy_colors.append("#D87D0F")
|
|
buy_size.append(10 + (5 * 1))
|
|
|
|
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=buy_size, 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='#8F8203')
|
|
avg6 = go.Scatter(x=data['date'], y=data["avg6"], name="avg6", line_color='#089B5B')
|
|
avg9 = go.Scatter(x=data['date'], y=data["avg9"], name="avg9", line_color='#ff00ff')
|
|
avg12 = go.Scatter(x=data['date'], y=data["avg12"], name="avg12", line_color='#1469F4')
|
|
avg27 = go.Scatter(x=data['date'], y=data["avg27"], name="avg27", line_color='#000000')
|
|
avg54 = go.Scatter(x=data['date'], y=data["avg54"], name="avg54", line_color='#008000')
|
|
|
|
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, avg6, avg9, avg12, avg27, avg54, 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]
|
|
|
|
# 그래프를 그린다.
|
|
"""
|
|
fig = go.Figure(data=candle_data)
|
|
fig.update_layout(title=stock_code + "_" + given_day)
|
|
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=5000, title=stock_code + "_" + given_day + "_" + str(buy_count) + "," + str(sell_count))
|
|
fig.show()
|
|
|
|
return
|
|
|
|
def writeLabelFile(self, stock_code, bsLine, data, ymd):
|
|
if not os.path.isdir(os.path.join(self.RESOURCE_PATH, "tmp")):
|
|
os.mkdir(os.path.join(self.RESOURCE_PATH, "tmp"))
|
|
|
|
outFileName = os.path.join(self.RESOURCE_PATH, "tmp", stock_code+"."+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", stock_code+"."+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, view=False):
|
|
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)
|
|
|
|
if view:
|
|
self.draw_simple(stock_code, ymd, data, bsLine)
|
|
#self.draw_detail(stock_code, ymd, data, bsLine)
|
|
|
|
return bsLine, data
|
|
def showLabels(self, stock_code, ymd, outFp=None):
|
|
LAST_DATA = self.stock2Vector.getLastData(stock_code, ymd)
|
|
result = self.stock2Vector.getRealTime(stock_code, ymd, LAST_DATA)
|
|
|
|
# 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
|
|
data = self.buySellChecker.analyze(result)
|
|
|
|
# 4일치 중에서 앞에 3일은 제거한다.
|
|
date = data['date'].dt.date.unique().tolist()
|
|
data = data[data['date'].dt.date != date[0]]
|
|
data = data[data['date'].dt.date != date[1]]
|
|
data = data[data['date'].dt.date != date[2]]
|
|
|
|
bsLine = {}
|
|
lows = data["low"].tolist()
|
|
closes = data["close"].tolist()
|
|
labels = data["label"].tolist()
|
|
size = len(lows)
|
|
|
|
# Type=False, 시뮬레이션 적용
|
|
bsLine['buy'] = [-1 for i in range(size)]
|
|
bsLine['sell'] = [-1 for i in range(size)]
|
|
for i in range(size):
|
|
if outFp is not None:
|
|
self.buySellChecker.write(outFp, data, i)
|
|
outFp.flush()
|
|
if labels[i] == 1:
|
|
bsLine['sell'][i] = closes[i]
|
|
if labels[i] == 2:
|
|
bsLine['buy'][i] = lows[i]
|
|
|
|
if outFp is None:
|
|
#self.draw_simple(stock_code, ymd, data, bsLine)
|
|
self.draw_detail(stock_code, ymd, data, bsLine)
|
|
return
|
|
|
|
def getDate(self, stock_code):
|
|
ymds = self.getYMD(stock_code)
|
|
return ymds
|
|
|
|
if __name__ == "__main__":
|
|
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")
|
|
db_filename = os.path.join(RESOURCE_PATH, "hts.db")
|
|
|
|
labelChecker = LabelChecker(RESOURCE_PATH)
|
|
|
|
stock_codes = {
|
|
"252670": ['20220701', '20220704', '20220705', '20220706', '20220707',
|
|
'20220708', '20220711', '20220712', '20220713', '20220714',
|
|
'20220715', '20220718', '20220719', '20220720', '20220721',
|
|
'20220722', '20220725', '20220726', '20220727', '20220728',
|
|
'20220729', '20220801', '20220802', '20220803', '20220804',
|
|
'20220805', '20220808', '20220809', '20220810', '20220811',
|
|
'20220812', '20220816'],
|
|
#"122630": ['20220801', '20220802', '20220803', '20220804', '20220805', '20220808', '20220809', '20220810', '20220811', '20220812'],
|
|
}
|
|
|
|
for stock_code in stock_codes:
|
|
for ymd in stock_codes[stock_code]:
|
|
labelChecker.showLabels(stock_code, ymd)
|