# assume data_frame is in GMT time
# remove Fri after 22:00 GMT
# remove Sat
# remove Sun before 19:00 GMT
# Monday = 0, ..., Sunday = 6
data_frame = data_frame.ix[~((data_frame.index.dayofweek == 4) & (data_frame.index.hour > 22))]
data_frame = data_frame.ix[~((data_frame.index.dayofweek == 5))]
data_frame = data_frame.ix[~((data_frame.index.dayofweek == 6)& (data_frame.index.hour < 19))]
return data_frame
# functions to test class
if __name__ == '__main__':
logger = LoggerManager.getLogger(__name__)
tsf = TimeSeriesFilter()
if False:
start = pandas.to_datetime('2000-01-01')
end = pandas.to_datetime('2020-01-01')
logger.info('Get FX holidays')
hols = tsf.get_holidays(start, end, cal='FX')
print(hols)
logger.info('Get business days, excluding holidays')
bus_days = tsf.create_calendar_bus_days(start, end, cal='FX')
print(bus_days)
elif freq == 'intraday':
self.logger.info('Total calculated returns for intraday not implemented yet')
return None
if data_frame_agg is None:
data_frame_agg = cross_vals
else:
data_frame_agg = data_frame_agg.join(cross_vals, how='outer')
# strip the nan elements
data_frame_agg = data_frame_agg.dropna()
return data_frame_agg
if __name__ == '__main__':
logger = LoggerManager.getLogger(__name__)
fxcf = FXCrossFactory()
path = "d:/"
import datetime
# DEMO: download intraday download
if True:
#
start = '01 Jan 2014'
end = '06 Nov 2014'
cross = 'EURGBP'
intraday_vals = fxcf.get_fx_cross(start, end, cross, cut = "NYC", source = "bloomberg", freq = "intraday", cache_algo = 'cache_algo_return')
