my_file=basedir + '/' + my_exp + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + filetype + '/update_comp_meandiff_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(nbv) + '_obs_inc_' + str(obs_increment[iv]) + '.grd'
print('Reading update comparisson for ',var_obs,' and ',var_upd)
#Read all the variables and levels at once
tmp_parameter[:,:,:,it] = np.squeeze( ctlr.read_data( my_file , ctl_dict , undef2nan = True ) )
#print( np.nanmin(tmp_parameter[:,:,:,it]) , np.nanmax( tmp_parameter[:,:,:,it] ) )
ctime = ctime + delta
it = it + 1
print ( "Finish time loop" )
rmse = np.sqrt( np.squeeze( np.nanmean( np.power( tmp_parameter , 2) , 3 ) ) )
bias = np.squeeze( np.nanmean( tmp_parameter , 3 ) )
print('RMSE ', np.nanmin(rmse) , np.nanmax(rmse) )
print('BIAS ', np.nanmin(bias) , np.nanmax(bias) )
my_file=outputdir + '/update_comp_meandiff_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(nbv) + '_obs_inc_' + str(obs_increment[iv]) + '_rmse' + '.grd'
comm.write_data(outfile=my_file,mydata=rmse,nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
my_file=outputdir + '/update_comp_meandiff_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(nbv) + '_obs_inc_' + str(obs_increment[iv]) + '_bias' + '.grd'
comm.write_data(outfile=my_file,mydata=bias,nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
#Read all the variables and levels at once
tmp_parameter[:, :, :, it] = np.squeeze(
ctlr.read_data(my_file, ctl_dict, undef2nan=True))
print(np.nanmin(tmp_parameter[:, :, :, it]),
np.nanmax(tmp_parameter[:, :, :, it]))
ctime = ctime + delta
it = it + 1
print("Finish time loop")
frequency = np.zeros(np.shape(tmp_parameter))
frequency[tmp_parameter > threshold] = 1.0
frequency[np.isnan(tmp_parameter)] = np.nan
frequency = np.squeeze(np.nanmean(frequency, 3))
print(np.nanmin(frequency), np.nanmax(frequency))
my_file = outputdir + '/' + file_name + '_freq' + '.grd'
comm.write_data(outfile=my_file,
mydata=frequency,
nx=nx,
ny=ny,
nz=nlev,
ie=endian,
acc=access)
my_file = basedir + my_exp + '/' + ctime.strftime(
"%Y%m%d%H%M%S"
) + '/' + my_file_type + '/' + '/' + file_name + '.grd'
#Read all the variables and levels at once
tmp_parameter[:, :, :, it] = np.squeeze(
ctlr.read_data(my_file, ctl_dict, undef2nan=True))
print(np.nanmin(tmp_parameter[:, :, :, it]),
np.nanmax(tmp_parameter[:, :, :, it]))
ctime = ctime + delta
it = it + 1
print("Finish time loop")
parameter = np.squeeze(np.nanmean(tmp_parameter, 3))
print(np.nanmin(parameter), np.nanmax(parameter))
my_file = outputdir + '/' + file_name + '_mean' + '.grd'
comm.write_data(outfile=my_file,
mydata=parameter,
nx=nx,
ny=ny,
nz=nlev,
ie=endian,
acc=access)
nx=nx,
ny=ny,
nz=nz,
nbv=nbv,
nmoments=nmoments,
undef=undef)
for imoment in range(0, nmoments):
momentstr = "%04d" % (imoment + 1)
my_file = basedir + '/' + my_exp_name + '/' + ctime.strftime(
"%Y%m%d%H%M%S"
) + '/' + my_file_type + '/moment' + momentstr + '.grd'
comm.write_data(outfile=my_file,
mydata=my_moments[:, :, :, imoment],
nx=nx,
ny=ny,
nz=nz,
ie=endian,
acc=access)
if get_kldistance:
print("Computing kl divergence" +
ctime.strftime("%Y%m%d%H%M%S"))
kldist = comm.compute_kld(my_ensemble=my_ensemble,
my_undefmask=my_undefmask,
nx=nx,
ny=ny,
nz=nz,
nbv=nbv,
undef=undef,
nbins=nbins)
#Compute tot cond
tot_cond_f = xf[:,:,:,:,iqr] + xf[:,:,:,:,iqs] + xf[:,:,:,:,iqg]
tot_cond_a = xa[:,:,:,:,iqr] + xa[:,:,:,:,iqs] + xa[:,:,:,:,iqg]
tot_cond_f[ tot_cond_f < np.min(tot_cond_f) ] = np.min(tot_cond_f)
tot_cond_a[ tot_cond_a < np.min(tot_cond_f) ] = np.min(tot_cond_f)
tot_cond_fcero_freq = np.sum( ( tot_cond_f == np.min(tot_cond_f) ).astype('int'),3)/nbv
tot_cond_acero_freq = np.sum( ( tot_cond_a == np.min(tot_cond_f) ).astype('int'),3)/nbv
#Write the analysis for the update variables
print('Writing data')
for ivar,my_var in enumerate(updated_variables) :
my_file=basedir + '/' + expname + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + file_type + '/update_dbz_' + my_var + '_obs_inc_' + str(obs_increment) + '_obserr_' + str(obs_error) + '.grd'
comm.write_data(outfile=my_file,mydata=xa_mean[:,:,:,ivar],nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
#Write the analysis reflectivity (reflectivity of the ensemble mean)
my_file=basedir + '/' + expname + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + file_type + '/update_dbz_dbz_obs_inc_' + str(obs_increment) + '_obserr_' + str(obs_error) + '.grd'
comm.write_data(outfile=my_file,mydata=xao_mean,nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
#Write the tot cond cero frec
my_file=basedir + '/' + expname + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + file_type + '/posterior_tot_cond_' + str(obs_increment) + '_obserr_' + str(obs_error) + '.grd'
comm.write_data(outfile=my_file,mydata=np.mean(tot_cond_a,3),nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
#Write the analysis tot cond cero frec
my_file=basedir + '/' + expname + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + file_type + '/posterior_tot_cond_cero_frec_' + str(obs_increment) + '_obserr_' + str(obs_error) + '.grd'
comm.write_data(outfile=my_file,mydata=tot_cond_acero_freq,nx=nx,ny=ny,nz=nlev,ie=endian,acc=access)
#Write the gues for the update variables
undefmask=my_undefmask[:, :, obs_record_list],
nens=nbv,
nx=nx,
ny=ny,
nz=local_nz,
obs_increment=obs_increment[iv],
obs_error=obs_error[iv])
my_file = basedir + '/' + my_exp_name + '/' + ctime.strftime(
"%Y%m%d%H%M%S"
) + '/' + my_file_type + '/update_comp_meandiff_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(
nbv) + '_obs_inc_' + str(obs_increment[iv]) + '.grd'
comm.write_data(outfile=my_file,
mydata=mean_diff,
nx=nx,
ny=ny,
nz=local_nz,
ie=endian,
acc=access)
my_file = basedir + '/' + my_exp_name + '/' + ctime.strftime(
"%Y%m%d%H%M%S"
) + '/' + my_file_type + '/update_comp_modediff_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(
nbv) + '_obs_inc_' + str(obs_increment[iv]) + '.grd'
comm.write_data(outfile=my_file,
mydata=mode_diff,
nx=nx,
ny=ny,
nz=local_nz,
ie=endian,
acc=access)
) + '/' + filetype + '/update_comp_kld_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(
nbv) + '_obs_inc_' + str(obs_increment[iv]) + '.grd'
print('Reading update comparisson for ', var_obs, ' and ', var_upd)
#Read all the variables and levels at once
tmp_parameter[:, :, :, it] = np.squeeze(
ctlr.read_data(my_file, ctl_dict, undef2nan=True))
#print( np.nanmin(tmp_parameter[:,:,:,it]) , np.nanmax( tmp_parameter[:,:,:,it] ) )
ctime = ctime + delta
it = it + 1
print("Finish time loop")
meankld = np.squeeze(np.nanmean(tmp_parameter, 3))
print('Mean KLD ', np.nanmin(meankld), np.nanmax(meankld))
my_file = outputdir + '/update_comp_vobs_' + var_obs + '_upd_obs_' + var_upd + '_ens_size_' + str(
nbv) + '_obs_inc_' + str(obs_increment[iv]) + '_kld' + '.grd'
comm.write_data(outfile=my_file,
mydata=meankld,
nx=nx,
ny=ny,
nz=nlev,
ie=endian,
acc=access)
for iobs , my_obs_var in enumerate( obs_variables ) :
print('Computing single obs update for variable ',my_var
[i_ind,e_ind]=get_var_start_end( ctl , my_var ) #Get start and end index.
hxf = my_ensemble[obs_location[0],obs_location[1],obs_location[2]+i_ind,:]
yo = np.mean( hxf ) + obs_increment[iobs]
#EnKF update
[umean,ustd,umode]compute_single_obs_update(hxf=hxf,ens=my_ensemble,mask=my_undefmask,nx=nx,ny=ny,nz=nz,nens=nbv,yo=yo,obs_error=obs_error[iobs]
,undef=undef,update_type=1]
prefix=basedir + '/' + my_exp_name + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + my_file_type + '/updateEnKF_' + my_obs_var + '_'
sufix = '_obsloc_x'+str(obs_location[0])+'_y'+str(obs_location[1])+'_z'+str(obs_location[2])+'.grd'
my_file= prefix + 'mean' + sufix
comm.write_data(outfile=my_file,mydata=umean,nx=nx,ny=ny,nz=nz,ie=endian,acc=access)
my_file= prefix + 'std' + sufix
comm.write_data(outfile=my_file,mydata=ustd,nx=nx,ny=ny,nz=nz,ie=endian,acc=access)
my_file= prefix + 'mode' + sufix
comm.write_data(outfile=my_file,mydata=umode,nx=nx,ny=ny,nz=nz,ie=endian,acc=access)
#ISPF update
[umean,ustd,umode]compute_single_obs_update(hxf=hxf,ens=my_ensemble,mask=my_undefmask,nx=nx,ny=ny,nz=nz,nens=nbv,yo=yo,obs_error=obs_error[iobs]
,undef=undef,update_type=2]
prefix=basedir + '/' + my_exp_name + '/' + ctime.strftime("%Y%m%d%H%M%S") + '/' + my_file_type + '/updateISPF_' + my_obs_var + '_'
sufix = '_obsloc_x'+str(obs_location[0])+'_y'+str(obs_location[1])+'_z'+str(obs_location[2])+'.grd'
my_file= prefix + 'mean' + sufix
comm.write_data(outfile=my_file,mydata=umean,nx=nx,ny=ny,nz=nz,ie=endian,acc=access)
my_file= prefix + 'std' + sufix
comm.write_data(outfile=my_file,mydata=ustd,nx=nx,ny=ny,nz=nz,ie=endian,acc=access)
my_file= prefix + 'mode' + sufix