Commit 2faabd95 authored by brunner's avatar brunner
Browse files

no bias correction, not needed

parent f96c45ff
...@@ -337,7 +337,7 @@ class Optimizer(object): ...@@ -337,7 +337,7 @@ class Optimizer(object):
if np.abs(res) > threshold: if np.abs(res) > threshold:
# if np.abs(res) > threshold + abs(bias): # if np.abs(res) > threshold + abs(bias):
# if np.abs(res_rej) > threshold: # if np.abs(res_rej) > threshold:
logging.debug('Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)' % (self.sitecode[n], self.obs_ids[n], res, threshold + abs(bias))) logging.debug('Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)' % (self.sitecode[n], self.obs_ids[n], res, threshold))
# logging.debug('Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)' % (self.sitecode[n], self.obs_ids[n], res_rej, threshold)) # logging.debug('Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)' % (self.sitecode[n], self.obs_ids[n], res_rej, threshold))
self.flags[n] = 2 self.flags[n] = 2
......
...@@ -128,26 +128,26 @@ class ObservationOperator(object): ...@@ -128,26 +128,26 @@ class ObservationOperator(object):
logging.info('Starting COSMO') logging.info('Starting COSMO')
# os.system('python run_chain.py '+self.dacycle['run.name']+' '+abs_start_time_ch+' '+str(starth+lag*168)+' '+str(endh+lag*168)+' -j meteo icbc int2lm post_int2lm oae octe online_vprm cosmo -f') os.system('python run_chain.py '+self.dacycle['run.name']+' '+abs_start_time_ch+' '+str(starth+lag*168)+' '+str(endh+lag*168)+' -j meteo icbc int2lm post_int2lm oae octe online_vprm cosmo -f')
logging.info('COSMO done!') logging.info('COSMO done!')
# Here the extraction of COSMO output starts # Here the extraction of COSMO output starts
dicts = self.read_csv(dacycle) dicts = self.read_csv(dacycle)
# rlat, rlon, dicts, path_in = self.get_hhl_data(dacycle, lag, 'lffd'+abs_start_time+'c.nc', dicts, starth, endh) rlat, rlon, dicts, path_in = self.get_hhl_data(dacycle, lag, 'lffd'+abs_start_time+'c.nc', dicts, starth, endh)
logging.info('Starting parallel extraction \m/') logging.info('Starting parallel extraction \m/')
# args = [ args = [
# (dacycle, dacycle['time.sample.start']+timedelta(hours = 24*n), dicts, rlat, rlon, path_in) (dacycle, dacycle['time.sample.start']+timedelta(hours = 24*n), dicts, rlat, rlon, path_in)
# for n in range(self.days) for n in range(self.days)
# ] ]
# with Pool(self.days) as pool: with Pool(self.days) as pool:
# pool.starmap(self.get_cosmo_data, args) pool.starmap(self.get_cosmo_data, args)
logging.info('Finished parallel extraction \m/') logging.info('Finished parallel extraction \m/')
# self.cat_cosmo_data(advance, dacycle) self.cat_cosmo_data(advance, dacycle)
for i in range(self.forecast_nmembers): for i in range(self.forecast_nmembers):
idx = str(i+1).zfill(3) idx = str(i+1).zfill(3)
......
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