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')