def fun(stocks):
# print(os.getpid(), stocks)
kline = 'index_min5'
pixel=54
n=5
count=2
interval = KlineInfo.get_interval(kline=kline)
detal=KlineInfo.get_detal(kline=kline)
table_name='A_Volume_'+kline+'_version5'
print(table_name)
for sc in stocks:
end_time = dt.datetime(2018, 8, 15)
start_time = dt.datetime(2016, 1, 1)
data = KlineData.read_data(code=sc, start_date=Calendar.calc(start_time, -203)['date'], end_date=end_time,
kline=kline, timemerge=True)
if len(data) <= 200 :
continue
data=CalMa.cal_profit(data,interval,detal)
data=data.dropna()
d = data.date.iloc[-1]
data=data[data.date<=dt.datetime(d.year,d.month,d.day,9,55)]
print(sc)
while end_time > start_time:
data0 = data.tail(pixel*4)
amax=data0.volume.max()
data0 = data0.tail(pixel)
data0 = data0.reset_index(drop=True)
profit = data0.profit.iloc[ - 1]
profitself = data0.profit_self.iloc[- 1]
date = data0['date']
if len(data0) < pixel:
break
date2 = date.iloc[ - 6]
date1 = date.iloc[ - 1]
data0=CalMa.data_normalization_volume2(data0,pixel=pixel+n*count,amax=amax)
if 'min' in kline:
if 'A' in table_name:
if date1.hour != 9 and date1.minute!=55:
data = data[data.date <= dt.datetime(date2.year, date2.month, date2.day, 9, 55)]
break
if abs(profit) > 0.11 or abs(profitself)>0.097:
data = data[data.date <= dt.datetime(date2.year, date2.month, date2.day, 9, 55)]
continue
else:
if abs(profit) > 0.1 * interval:
data = data[data.date <= dt.datetime(date2.year, date2.month, date2.day, 9, 55)]
continue
if 'A' in table_name:
if abs(profitself) > 0.097:
data = data[data.date <= dt.datetime(date2.year, date2.month, date2.day, 9, 55)]
print(sc, str(profitself) + '_' + str(date))
continue
try:
visualization.draw_volume(data=data0, profits=profit,
date=date1, code=sc,
table_name=table_name, pixel=pixel, n=n,
count=count)
pass
except Exception as e:
print(e)
pass
data = data[data.date <= dt.datetime(date2.year, date2.month, date2.day,9,55)]
end_time = date2
return 1
def fun(stocks):
# print(os.getpid(), stocks)
kline = 'index_min5'
pixel = 64
length = 12
count = 5
interval = 48
hour = 9
minute = 55
detal = KlineInfo.get_detal(kline=kline)
# wave=0.02
# amount_data=50000000
table_name = 'A_MA_Stub_' + kline + '_version5'
print(table_name)
for sc in stocks:
print(sc)
end_time = dt.datetime(2018, 8, 15)
start_time = dt.datetime(2016, 1, 1)
data = KlineData.read_data(code=sc,
start_date=Calendar.calc(start_time,
-8)['date'],
end_date=end_time,
kline=kline,
timemerge=True)
if len(data) <= 200:
continue
# data = CalMacd.cal_macd(data=data, interval=interval, detal=detal)
# data=CalMa.cal_ma_stub(data=data,interval=interval,detal=detal)
data = CalMa.cal_profit(data=data, interval=interval, detal=detal)
data = data.dropna()
d = data.date.iloc[-1]
data = data[
data.date <= dt.datetime(d.year, d.month, d.day, hour, minute)]
while end_time > start_time:
# print(sc,dt.datetime.now())
data0 = data.tail(length)
data0 = data0.reset_index(drop=True)
profit = data0['profit']
profit_self = data0['profit_self']
date = data0['date']
# amin, amax = data0.low.min(), data0.high.max()
if len(data0) < length:
break
date1 = date.iloc[length - 1]
date2 = date.iloc[length - 10]
# data0 = CalMacd.data_normalization(data0,pixel=pixel)
data0 = CalMa.data_stub_normalization(data0, pixel=pixel)
profit = profit.iloc[length - 1]
profitself = profit_self.iloc[length - 1]
profit_relative = 0
if 'min' in kline:
if 'A' in table_name:
if date1.hour != hour and date1.minute != minute:
# data = data[data.date < dt.datetime(date2.year, date2.month, date2.day)]
break
if abs(profit) > 0.11 or abs(profitself) > 0.097:
data = data[data.date <= dt.datetime(
date2.year, date2.month, date2.day, hour, minute)]
continue
else:
if abs(profit) > 0.1 * interval:
data = data[data.date <= dt.datetime(
date2.year, date2.month, date2.day, hour, minute)]
continue
if 'A' in table_name:
if abs(profitself) > 0.097:
data = data[data.date <= dt.datetime(
date2.year, date2.month, date2.day, hour, minute)]
print(sc, str(profitself) + '_' + str(date1))
continue
try:
visualization.draw_ma_stub_line2(
data=data0,
profits=profit,
date=date1,
code=sc,
table_name=table_name,
pixel=pixel,
length=length,
profit_relative=profit_relative,
count=count)
pass
except Exception as e:
print(e)
pass
data = data[data.date <= dt.datetime(date2.year, date2.month,
date2.day, hour, minute)]
end_time = date2
return 1