def get_datelist(begT, endT, dback=0, dnext=0):
days = [int(d.replace('-', '')) for d in meta_api.get_trading_date_range(int(begT), int(endT), 'SSE')]
dates = [int(d.replace('-', '')) for d in meta_api.get_trading_date_range(int(begT) - 40000, int(endT), 'SSE')]
days = dates[len(dates) - len(days) - dback:len(dates)+dnext]
actdays = np.array([int(d) for d in days])
return actdays
def Rankop_rank(xmatrix):
return pd.DataFrame(xmatrix).rank(pct=True, axis=0).values
''' Constants'''
delay = 1
start_date = str(20100101)
end_date = str(20181231)
histdays = 20 # need histdays >= delay
actdays = get_datelist(start_date, end_date, histdays, -1)
days = [
int(d.replace('-', '')) for d in meta_api.get_trading_date_range(
int(start_date), int(end_date), 'SSE')
]
daysdata = helpfunc_loadcache(actdays[0], actdays[-1], 'days')
symbols = helpfunc_loadcache(actdays[0], actdays[-1], 'stocks')
instruments = len(symbols)
startdi = daysdata.tolist().index(days[0])
enddi = startdi + len(days) - 1
'Data Part'
vwap = helpfunc_loadcache(actdays[0], actdays[-1], 'vwap', 'basedata')
high = helpfunc_loadcache(actdays[0], actdays[-1], 'high', 'basedata')
low = helpfunc_loadcache(actdays[0], actdays[-1], 'low', 'basedata')
groupdata = helpfunc_loadcache(actdays[0], actdays[-1], 'WIND01', 'basedata')
