def fun(stocks):
# print(os.getpid(), stocks)
kline = 'usa_kline_day'
pixel = 64
length = pixel * 2
interval = KlineInfo.get_interval(kline=kline)
off = KlineInfo.get_off(kline=kline)
table_name = 'MACD_and_MA_' + kline
print(table_name)
for sc in stocks:
print(os.getpid(), sc)
end_time = dt.datetime(2018, 6, 20)
start_time = dt.datetime(2015, 1, 1)
data = KlineData.read_data(code=sc,
start_date=Calendar.calc(start_time,
-off)['date'],
end_date=end_time,
kline=kline,
timemerge=True)
if len(data) <= (off - 20):
continue
data = calculate.calculate_data(data, interval)
# data = data.sort_values(by=['date'], ascending=True)
data = data.dropna()
# data = data[0:len(data) - interval]
while end_time > dt.datetime(2016, 1, 5):
# print(sc,dt.datetime.now())
data0 = data.tail(length)
data0 = data0.reset_index(drop=True)
profit = data0['profit']
date = data0['date']
data0 = calculate.data_normalization(data=data0,
pixel=pixel,
length=length)
# print(sc, dt.datetime.now())
data0['date'] = date
data0['profit'] = profit
if len(data0) < length:
break
data0 = data0.reset_index(drop=True)
profit = data0.profit.iloc[length - 1]
date = data0.date.iloc[length - 1]
if 'min' in kline:
if 'A' in table_name:
if date.hour != 15:
data = data[data.date < dt.datetime(
date.year, date.month, date.day)]
break
if abs(profit) > 0.11:
data = data[data.date < dt.datetime(
date.year, date.month, date.day)]
continue
else:
if abs(profit) > 0.1 * interval:
data = data[data.date < dt.datetime(
date.year, date.month, date.day)]
continue
# print(sc, dt.datetime.now())
try:
visualization.draw_macd_and_ma(data=data0,
profits=profit,
date=date,
code=sc,
table_name=table_name,
pixel=pixel,
length=length)
pass
except Exception as e:
print(e)
pass
data = data[
data.date < dt.datetime(date.year, date.month, date.day)]
end_time = date
return 1
def fun(data):
stocks=data['stocks']
kline=data['kline']
# print(os.getpid(), stocks)
table_name='MA_A_'+kline
interval = KlineInfo.get_interval(kline)
detal=KlineInfo.get_detal(kline)
off=KlineInfo.get_off(kline=kline)
day_interval=KlineInfo.get_day_interval(kline)
pixel=64
for sc in stocks:
end_time = Calendar.today()
start_time = Calendar.calc(end_time,-day_interval)['date']
# end_time = dt.datetime(2018,8,1)
# start_time=dt.datetime(2018,6,20)
data = KlineData.read_data(code=sc, start_date=Calendar.calc(start_time, -off)['date'], end_date=end_time,
kline=kline, timemerge=True)
if len(data) <= 200:
continue
data = CalMa.cal_ma(data, interval,detal)
data = data.dropna()
print(sc)
while end_time > start_time:
data0 = data.tail(pixel)
data0 = data0.reset_index(drop=True)
profit = data0['profit']
profitself = data0['profit_self']
date = data0['date']
data0 = CalMa.data_normalization(data0,pixel)
data0['date'] = date
data0['profit'] = profit
data0['profitself'] = profitself
if len(data0) < pixel:
break
data0 = data0.reset_index(drop=True)
profit = data0.profit.iloc[len(data0)-1]
profitself = data0.profitself.iloc[len(data0)-1]
date = data0.date.iloc[len(data0)-1]
if 'min' in kline:
if 'A' in table_name:
if date.hour != 15:
data = data[data.date < dt.datetime(date.year, date.month, date.day)]
break
if abs(profit) > 0.11 or abs(profitself) > 0.097:
data = data[data.date < dt.datetime(date.year, date.month, date.day)]
continue
else:
if abs(profit) > 0.1 * interval:
data = data[data.date < dt.datetime(date.year, date.month, date.day)]
continue
if 'A' in table_name:
if abs(profitself) > 0.097:
data = data[data.date < dt.datetime(date.year, date.month, date.day)]
continue
try:
visualization.draw_ma_line(data=data0, profits=profit,
date=date, code=sc,
table_name=table_name,pixel=pixel)
except Exception as e:
print(e)
pass
data = data[data.date < dt.datetime(date.year, date.month, date.day)]
end_time = date
return 1
