def data_collect(start_step, nst, geos_datapath, obs_datapath, viewmode_list, \
err_scale=1.0, do_debug=False, do_dump=True, dumpflnm=None):
""" doys in date to be read in read in
"""
fen = open(geos_datapath + '/' + 'ens_pos.dat', 'r')
line = fen.readline()
line = fen.readline()
terms = line.split()
step = int(terms[1])
nstep = int(terms[3])
line = fen.readline()
lines = fen.readlines()
fen.close()
em_st = list()
em_end = list()
yyyy_st = list()
yyyy_end = list()
doy_st = list()
doy_end = list()
co2flnm = list()
sel_x_idx = range(1, 4)
for line in lines:
line = line.strip()
if (len(line) < 1):
break
terms = line.split()
print terms
em_st.append(int(terms[0]))
em_end.append(int(terms[1]))
yyyy_st.append(int(terms[2]))
yyyy_end.append(int(terms[3]))
doy_st.append(int(terms[4]))
doy_end.append(int(terms[5]))
co2flnm.append(terms[6])
yyyy = yyyy_st[start_step]
doy0 = doy_st[start_step]
doy1 = doy0 + nst * step - 1 # 096 0406
# set up the start days
st_days = list()
for iday in range(doy0, doy1 + 1, step):
sday = r'%4.4dD%3.3d' % (yyyy, iday)
st_days.append(sday)
print st_days
do_debug = False
iplot = 0
state_v = stv_c.state_vector(st_days,
do_debug=False,
datapath=geos_datapath)
nx, ne = state_v.nx, state_v.ne
print 'nx, ne', nx, ne
nreg = (nx) / size(st_days)
x = array(state_v.stv)
data_count = list()
istep = 0
doys = arange(doy0, doy1)
iday = 0
nusd_obs = 0
fclim = open('clim_co2.dat', 'r')
lines = fclim.readlines()
fclim.close()
aprior = list()
apr_pres = list()
for iline in lines:
terms = iline.split()
aprior.append(float(terms[1]))
apr_pres.append(float(terms[0]))
aprior = array(aprior)
apr_pres = array(apr_pres)
apr_pres = log10(apr_pres)
# starting to collect the observations and y
istep = 0
# figure(1)
# show()
# figure(1)
sel_doys = [-1, -8, -15]
day_cnt = 0
for doy in doys:
yyyy, mm, dd = tm.doy_to_time_array(doy, yyyy)
print 'year mm dd', yyyy, mm, dd
y = list()
iend = 0
full_doy = r'%4.4dD%3.3d' % (yyyy, doy)
# check whether it is necessary to include surface flux (stv) during cerntain days
for st_dd in st_days[:]:
if (full_doy < st_dd):
print full_doy, st_dd
break
else:
iend = iend + 1
real_nx = iend * nreg
real_ne = real_nx + 1
# generate x
# the ensemble members need to be included
sel_eid = list()
iend = 0
print em_st
while True:
print em_st[iend], real_ne
if (real_ne < em_st[iend]):
break
else:
sel_eid.append(iend)
if (real_ne <= em_end[iend]):
break
else:
iend = iend + 1
# generate model obs
sdate = r'%4.4dD%3.3d' % (yyyy, doy)
ncflnm = obs_datapath + "oco" + "." + sdate + ".nc"
if (doy == doys[0]):
sdate0 = sdate
dumpext = r"%2.2d" % nst
dumpext = "." + sdate0 + "_N" + dumpext
viewmode = viewmode_list[doy - 1]
ncflnm = obs_datapath + "/oco_" + viewmode + "." + sdate + ".nc"
print ncflnm
std_od, std_cflag = ofb.ncf_read(ncflnm, ['od', 'cloud'])
iy = 0
print 'sel_eid', sel_eid
for eid in sel_eid:
est = em_st[eid]
eend = em_end[eid]
print 'sttt days', st_days[eid]
# if (day_cnt==0):
# the new code needs the right starting time for ctm file
ctm_date = st_days[eid]
ctm_yyyy, ctm_doy = int(ctm_date[0:4]), int(ctm_date[5:8])
ctm_yyyy, ctm_mm, ctm_dd = tm.doy_to_time_array(ctm_doy, ctm_yyyy)
ctm_date0 = r'%4.4d%2.2d%2.2d' % (ctm_yyyy, ctm_mm, ctm_dd)
# r'%4.4d%2.2d%2.2d' % (yyyy, mm, dd)
print '=' * 20 + 'read in data and calculate xco2' + '=' * 20
obs=obo.obs_operator(yyyy, mm, dd, est, eend, \
aprior=aprior, apr_pres=apr_pres, \
viewmode=viewmode,\
datapath=geos_datapath,
ctm_date0=ctm_date0)
ytop = min([eend, real_ne])
for em in range(est, ytop + 1):
if (em == est):
if (istep > 300):
print 'em', em, est
obs.get_obs_prof(em, std_od=std_od, std_cf=std_cflag)
else:
obs.get_obs_prof(em, idx=used_idx, do_update=False)
if (iy == 0):
# em_id is different from em. em_id is the 'real id' in the whole ensemble set
em_id = obs.em_id[em - 1]
print 'em_id', em_id, em - 1
xgp0 = obs.obs_xgp[em_id]
xgp = obs.obs_xgp[em_id]
print size(xgp), size(std_od), size(std_cflag)
obs_err = obs.obs_err
obs_err = array(obs_err)
obs_err = obs_err
# print 'shape obs+err', shape(obs_err)
rnd_obs_err = array(obs_err)
for iobs in range(size(obs_err)):
err_val = obs_err[iobs]
rnd_err = rnd.normal(scale=err_val)
rnd_obs_err[iobs] = rnd_err
# err_scale=1.0
if (do_debug):
subplot(2, 1, 1)
plot(obs_err)
plot(rnd_obs_err)
subplot(2, 1, 2)
hist(rnd_obs_err)
hist(obs_err)
show()
rnd_obs_err = err_scale * rnd_obs_err
cflag = obs.obs_cflag
otime = obs.obs_time
olat = obs.obs_lat
olon = obs.obs_lon
od = obs.obs_od
lwi = obs.obs_lwi
lwi = lwi.astype(int)
# used_idx=where(logical_and(cflag==0, od<=0.3, lwi<>1))
osza = obs.obs_sza
sel1 = logical_and(cflag == 0, od <= 0.3)
sel2 = logical_and(lwi <> 1, lwi <> 2)
# used_idx=where(sel1)
# used_idx=where(logical_and(sel1, sel2))
# used_idx=where(cflag==0)
used_idx = where(logical_and(obs_err < 4.0, sel1))
used_idx = squeeze(used_idx)
print 'used_idx', len(used_idx)
xgp = xgp[used_idx]
xgp0 = xgp0[used_idx]
obs_err = 1.0e-6 * obs_err[used_idx]
rnd_obs_err = 1.0e-6 * rnd_obs_err[used_idx]
imax = argmax(rnd_obs_err)
print 'max(obs err), max(rnd_obs_err)', 1.0e6 * obs_err[
imax], 1.0e6 * rnd_obs_err[imax]
olat = olat[used_idx]
olon = olon[used_idx]
lwi = lwi[used_idx]
otime = otime[used_idx]
od = od[used_idx]
# r=array(varData)
# r=r*r
else: # just others for ensemble
em_id = obs.em_id[em - 1]
# print 'em_id', em_id, em-1
xgp = obs.obs_xgp[em_id]
if (em == est):
print em, est
print len(used_idx)
xgp = xgp[used_idx]
if (istep > 300):
print 'type xgp', type(xgp)
print 'len-xgp', len(xgp)
if (em == 2):
print 'xgp', xgp[0:6]
y.append(array(xgp))
if (do_debug):
print ii, ne, shape(xgp)
if (do_debug and ii == 4):
# figure(1)
# plot(xgp[0:300],'r')
# plot(xgp0[0:300], 'b')
z = xgp - xgp0
print 'max dev', max(z)
iy = iy + 1
for same_y in range(real_ne, ne):
y.append(array(xgp0)) # filled with the same value
# show()
y = array(y)
y = transpose(y)
if (istep > 300):
print type(y)
print len(y)
ix = y[0]
print type(ix)
# read in the data
obs_f = NetCDFFile(ncflnm)
yobs = obs_f.variables['xco2']
yobs_err = obs_f.variables['err']
yobs = array(yobs)
# yobs_err=array(yobs_err)
yobs_err = array(yobs_err)
# print 'shape yobs', shape(yobs)
yobs = squeeze(yobs)
yobs_err = squeeze(yobs_err)
obs_f.close()
yobs = yobs[used_idx]
yobs_err = yobs_err[used_idx]
print 'shape y & yobs', shape(y), shape(yobs)
if (istep == 0):
all_y = array(y)
all_yobs = array(yobs)
all_yobs_err = array(yobs_err)
all_rnd_err = array(rnd_obs_err)
all_lat = array(olat)
all_lon = array(olon)
all_lwi = array(lwi)
all_time = array(otime)
all_od = array(od)
else:
all_y = concatenate((all_y, y))
all_yobs = concatenate((all_yobs, yobs))
all_yobs_err = concatenate((all_yobs_err, yobs_err))
all_rnd_err = concatenate((all_rnd_err, rnd_obs_err))
all_lat = concatenate((all_lat, olat))
all_lon = concatenate((all_lon, olon))
all_lwi = concatenate((all_lwi, lwi))
all_time = concatenate((all_time, otime))
all_od = concatenate((all_od, od))
print 'istep & shape ', istep, shape(all_y), shape(all_yobs), shape(
all_yobs_err), shape(all_rnd_err)
istep = istep + 1
data_count.append(size(yobs))
day_cnt = day_cnt + 1
if (day_cnt == gcdf.temporal_resolution):
day_cnt = 0
data_count = array(data_count)
factor = 1.0e6
all_y = factor * all_y
all_yobs = factor * all_yobs
all_rnd_err = factor * all_rnd_err
all_yobs_err = factor * all_yobs_err
if (do_dump):
if (dumpflnm == None):
ncdump = geos_datapath + '/' + 'obs' + dumpext + ".nc"
else:
ncdump = geos_datapath + '/' + dumpflnm + "_" + dumpext + ".nc"
xnx = arange(nx)
xne = arange(ne)
xny = arange(size(all_y[:, 0]))
dimTypes = ['i', 'i', 'i', 'i']
dimVars = [xnx, xne, xny, doys]
dimNames = ['nx', 'ne', 'ny', 'doys']
x_info = ofb.geos_varinfo('x', 'f', ['nx', 'ne'], x)
y_info = ofb.geos_varinfo('y', 'f', ['ny', 'ne'], all_y)
yobs_info = ofb.geos_varinfo('obs', 'f', ['ny'], all_yobs)
yobs_err_info = ofb.geos_varinfo('err', 'f', ['ny'], all_yobs_err)
rnd_err_info = ofb.geos_varinfo('rnd_err', 'f', ['ny'], all_rnd_err)
count_info = ofb.geos_varinfo('daily_count', 'i', ['doys'], data_count)
lat_info = ofb.geos_varinfo('lat', 'f', ['ny'], all_lat)
lon_info = ofb.geos_varinfo('lon', 'f', ['ny'], all_lon)
time_info = ofb.geos_varinfo('time', 'f', ['ny'], all_time)
od_info = ofb.geos_varinfo('od', 'f', ['ny'], all_od)
lwi_info = ofb.geos_varinfo('lwi', 'i', ['ny'], all_lwi)
ofb.ncf_write_by_varinfo(ncdump, dimNames, dimTypes, dimVars, \
[x_info, y_info, yobs_info, yobs_err_info, rnd_err_info, lat_info, lon_info, time_info, od_info, lwi_info, count_info])
return x, all_y, all_yobs, all_yobs_err, all_rnd_err, data_count, doys, \
all_lat, all_lon, all_time, all_lwi, all_od
print('select-runs',select_runs)
print('step range:',list(range(gcdf.nstep_start, nstep)))
#gcdf.restart_file
pre_year = 1985
pre_restart_name = ' '
#>>/ps/loop0/over each step
for istep in range(gcdf.nstep_start, nstep): # run through the emission time period
npbf = em_npb[istep]
pbflnm = em_ch4flnm[istep]
yyyy_st = em_yyyy_st[istep]
doy_st = em_doy_st[istep]
yyyy, mm, dd = tm.doy_to_time_array(doy_st, yyyy_st)
##c/tau_st in seconds since 1985.1.1.0.0
tau_st = tm.get_tau(yyyy,mm, dd)
# print('-'*10+'starting year, month, day:', yyyy, mm, dd)
istep_end = min(istep+lag_window, len(em_doy_st)-1)
# print('-'*10+'istep_start, istep_end:' istep, istep_end)
if (sub_sous):
nsub_sous = gcdf.n_sous_loop
# sub emission sources loop
else:
nsub_sous = 1
def get_daily_avg(yyyy, doy_list, lvl_st, lvl_end, doy_end=328, **keywords):
# end of the assimilation period
yyyy, mm, dd = tmdl.doy_to_time_array(doy_end, yyyy)
sdate = r'%4.4d%2.2d%2.2d' % (yyyy, 11, 28)
resflnm = 'co_flux.' + sdate
tmp = ['x', 'bm']
xx, bend = ofb.ncf_read(resflnm + ".nc", tmp)
xx0 = ones(size(xx), float)
old_mm = 0
nreg = 11
inc_nx = 12
daily_obs = list()
daily_prof = list()
daily_prof0 = list()
daily_prof_sel = list()
daily_cnt = list()
# get hidx, the location of tagged tracers in the reduced jacobian
# 0== not used; 1-11 == FF+BF+BB at 11 regions; 12 == chemistry
chm_idx = list()
for doy in doy_list:
yyyy, mm, dd = tmdl.doy_to_time_array(doy, yyyy)
if (mm > old_mm):
for imm in range(old_mm + 1, mm + 1):
if (imm == 1):
hidx = [0] + range(1, nreg + 1) + range(
1, nreg + 1) + [nreg + 1] * 5
nx = 12
chm_idx.append(nx - 1)
new_hidx = [0] + range(nx + 1, nx + inc_nx) + range(
nx + 1, nx + inc_nx) + [nx + inc_nx] * 5
nx = nx + inc_nx
hidx = hidx + new_hidx
chm_idx.append(nx - 1)
else:
new_hidx = [0] + range(nx + 1, nx + inc_nx) + range(
nx + 1, nx + inc_nx) + [nx + inc_nx] * 5
nx = nx + inc_nx
hidx = hidx + new_hidx
chm_idx.append(nx - 1)
old_mm = mm
# print nx
# print hidx
print doy, yyyy, mm, dd, nx
xx_sel = array(xx0)
# required the model value
xx_list = list()
key_words = list()
do_it = 0
# prior vs posterior
if ('prior' in keywords):
do_it = keywords['prior']
if (do_it == 1):
xx_list.append(xx0) # a-priori
key_words.append('prior')
do_it = 0
if ('posterior' in keywords):
do_it = keywords['posterior']
if (do_it == 1):
xx_list.append(xx) # a-priori
key_words.append('posterior')
do_it = 0
# backgrounds
if ('prior_bg' in keywords):
do_it = keywords['prior_bg']
if (do_it == 1):
xx_add = zeros(nx, float)
xx_add[0:nreg] = xx0[0:nreg]
key_words.append('prior_bg')
xx_list.append(xx_add)
if ('new_bg' in keywords):
do_it = keywords['new_bg']
if (do_it == 1):
xx_add = zeros(nx, float)
xx_add[0:nreg] = xx[0:nreg]
key_words.append('new_bg')
xx_list.append(xx_add)
# chemistry production
if ('prior_chm' in keywords):
do_it = keywords['prior_chm']
if (do_it == 1):
xx_add = zeros(nx, float)
xx_add[chm_idx] = xx0[chm_idx]
xx_list.append(xx_add)
key_words.append('prior_chm')
do_it = 0
if ('new_chm' in keywords):
do_it = keywords['new_chm']
if (do_it == 1):
xx_add = zeros(nx, float)
xx_add[chm_idx] = xx[chm_idx]
xx_list.append(xx_add)
key_words.append('new_chm')
do_it = 0
if ('prior_sel' in keywords):
do_it = keywords['prior_sel']
if (do_it > 0):
xx_add = zeros(nx, float)
xx_add[do_it - 1] = xx0[do_it - 1]
xx_list.append(xx_add)
key_words.append('prior_sel')
do_it = 0
if ('new_sel' in keywords):
do_it = keywords['new_sel']
if (do_it > 0):
xx_add = zeros(nx, float)
xx_add[do_it - 1] = xx[do_it - 1]
xx_list.append(xx_add)
key_words.append('new_sel')
cnt_avg, obs_avg, prof_avg, pres=\
get_daily_reg_avg(yyyy, mm, dd, xx_list,\
hidx, nx, nreg, lvl_st, lvl_end)
daily_obs.append(obs_avg)
daily_prof.append(prof_avg)
daily_cnt.append(cnt_avg)
daily_obs = array(daily_obs)
daily_prof = array(daily_prof)
daily_cnt = array(daily_cnt)
return daily_cnt, daily_obs, daily_prof, key_words, squeeze(pres)
def __init__(self, cur_yyyy, doy_st, doy_end, rerun_st=1, rerun_end=2):
self.rerun_est = rerun_st
self.rerun_eend = rerun_end
self.rerun_datapath = gcdf.data_path
self.cur_yyyy = cur_yyyy
viewmode_nadir = ['nadir'] * 16
viewmode_glint = ['glint'] * 16
if (gcdf.view_mode == 'nadir'):
viewmode_list = viewmode_nadir + viewmode_nadir
elif (gcdf.view_mode == 'glint'):
viewmode_list = viewmode_glint + viewmode_glint
else:
viewmode_list = viewmode_nadir + viewmode_glint
viewmode_list = viewmode_list * 12
viewmode_code = list()
for idoy in range(doy_st, doy_end + 1):
yyyy, mm, dd = tm.doy_to_time_array(idoy, self.cur_yyyy)
sdate = r'%4.4dD%3.3d' % (yyyy, idoy)
viewmode = viewmode_list[idoy - 1]
ncflnm = "./" + gcdf.view_type + "_" + viewmode + "." + sdate + ".nc"
org_ncflnm = gcdf.obs_path + "/" + gcdf.view_type + "_" + viewmode + "." + sdate + ".nc"
print ncflnm
varnames=['time', 'obs_lvl', 'lon', 'lat', 'cloud', 'nclear', 'xco2', 'xco2_ap', \
'err', 'rnd_err', \
'od', 'lwi', 'sza', 'obs_pres', 'obs_ak', 'obs_apr']
time, obs_lvl, lon, lat, cloud, nclear, xco2, xco2_ap, \
err, rnd_err, \
od, lwi, sza, obs_pres, obs_ak, obs_apr=\
ofb.ncf_read(org_ncflnm, varnames)
nobs = size(lat)
self.olat = array(lat)
self.olon = array(lon)
self.otime = array(time)
self.obs_ak = array(obs_ak)
self.obs_apr = array(obs_apr)
self.obs_xgp0 = array(xco2_ap)
self.obs_pres = array(obs_pres)
hm0 = self.read_new_mean_y(yyyy, mm, dd)
hm0 = squeeze(hm0)
if (max(hm0) > 1.0):
hm0 = 1.0e-6 * hm0
dimnames = ['time', 'obs_lvl']
dimtypes = ['f', 'i']
dimvars = [time, obs_lvl]
lon_info = ofb.geos_varinfo('lon', 'f', ['time'], lon)
lat_info = ofb.geos_varinfo('lat', 'f', ['time'], lat)
cloud_info = ofb.geos_varinfo('cloud', 'f', ['time'], cloud)
nclear_info = ofb.geos_varinfo('nclear', 'f', ['time'], nclear)
xco2_info = ofb.geos_varinfo('xco2', 'f', ['time'], hm0)
xco2_ap_info = ofb.geos_varinfo('xco2_ap', 'f', ['time'], xco2_ap)
err_info = ofb.geos_varinfo('err', 'f', ['time'], err)
rnd_err_info = ofb.geos_varinfo('rnd_err', 'f', ['time'], rnd_err)
od_info = ofb.geos_varinfo('od', 'f', ['time'], od)
lwi_info = ofb.geos_varinfo('lwi', 'f', ['time'], lwi)
sza_info = ofb.geos_varinfo('sza', 'f', ['time'], sza)
obs_pres_info = ofb.geos_varinfo('obs_pres', 'f',
['time', 'obs_lvl'], obs_pres)
obs_ak_info = ofb.geos_varinfo('obs_ak', 'f', ['time', 'obs_lvl'],
obs_ak)
obs_apr_info = ofb.geos_varinfo('obs_apr', 'f',
['time', 'obs_lvl'], obs_apr)
ofb.ncf_write_by_varinfo(ncflnm, dimnames, dimtypes, dimvars, [lon_info, lat_info, cloud_info, \
nclear_info, xco2_info, xco2_ap_info, \
err_info, rnd_err_info, \
od_info, lwi_info, sza_info, obs_pres_info, obs_ak_info, obs_apr_info])
usd_doy = list()
fobs_list = open('./mop_obs_2006.list', 'r')
raw_date_list = fobs_list.readlines()
fobs_list.close()
obs_date_list = list()
for sobs_date in raw_date_list:
sobs_date = sobs_date.replace('\n', '')
sobs_date = sobs_date.strip()
obs_date_list.append(sobs_date)
doy_list = list()
for doy in range(doy_st, doy_end):
yyyy, mm, dd = tmdl.doy_to_time_array(doy, yyyy)
sobs_date = r'%4.4d.%2.2d.%2.2d' % (yyyy, mm, dd)
if (sobs_date in obs_date_list):
# print sobs_date
doy_list.append(doy)
# get the daily regional observation/model average for doys in doy_list
#
daily_cnt, daily_obs, daily_prof, key_words, pres=\
get_daily_avg(yyyy, doy_list, lvl_st, lvl_end, \
prior=1,\
posterior=1,\
prior_bg=1,\
new_bg=1,\
def data_collect(yyyy, doy, \
nst,\
step,\
em_st,\
em_end,\
geos_datapath, \
obs_datapath,\
viewmode_list, \
not_first_period=False,\
err_scale=1.0, \
do_debug=False,\
do_dump=True, \
dumpflnm=None):
""" doys in date to be read in read in
"""
doy0=doy
doy1=doy0 +nst*step # 096 0406
# set up the start days
doys=arange(doy0, doy1)
iday=0
nusd_obs=0
fclim=open('clim_co2.dat', 'r')
lines=fclim.readlines()
fclim.close()
aprior=list()
apr_pres=list()
for iline in lines:
terms=iline.split()
aprior.append(float(terms[1]))
apr_pres.append(float(terms[0]))
aprior=array(aprior)
apr_pres=array(apr_pres)
apr_pres=log10(apr_pres)
# starting to collect the observations and y
#
# figure(1)
# show()
# figure(1)
sel_doys=[-1, -8, -15]
int_step=0
all_days=size(em_st)
all_data_list=arange(all_data)
int_step=0
out_step=step
data_count=list()
print doy0, doy1, doys
# tt=raw_input()
for doy in doys:
yyyy, mm,dd=tm.doy_to_time_array(doy, yyyy)
print 'year mm dd', yyyy, mm, dd
y=list()
iend=0
full_doy=r'%4.4dD%3.3d' % (yyyy, doy)
sdate=r'%4.4dD%3.3d' % (yyyy, doy)
# check whether it is necessary to include surface flux (stv) during cerntain days
iy=0
if (int_step==0):
dumpext=r"%2.2d" % nst
dumpext="."+sdate+"_N"+dumpext
viewmode=viewmode_list[doy-1]
ncflnm_obs=obs_datapath+"/oco_"+viewmode+"."+sdate+".nc"
print ncflnm_obs
std_od, std_cflag=ofb.ncf_read(ncflnm_obs, ['od', 'cloud'])
for eid in all_data_list:
est=em_st[eid]
eend=em_end[eid]
sdate=r'%4.4dD%3.3d' % (yyyy, doy)
ncflnm=obs_datapath+"oco"+"."+sdate+".nc"
# print 'sel_eid', sel_eid
obs=obo.obs_operator(yyyy, mm, dd, est, eend, \
aprior=aprior, apr_pres=apr_pres, \
viewmode=viewmode,\
datapath=geos_datapath)
ytop=eend
for em in range(est,ytop+1):
if (em==est):
obs.get_obs_prof(em, std_od=std_od, std_cf=std_cflag)
else:
# print 'iy', iy, em, est
obs.get_obs_prof(em, idx=used_idx, do_update=False)
if (iy==0):
# em_id is different from em. em_id is the 'real id' in the whole ensemble set
em_id=obs.em_id[em-1]
print 'em_id', em_id, em-1
xgp0=obs.obs_xgp[em_id]
xgp=obs.obs_xgp[em_id]
print size(xgp), size(std_od), size(std_cflag)
obs_err=obs.obs_err
obs_err=array(obs_err)
obs_err=obs_err
# print 'shape obs+err', shape(obs_err)
rnd_obs_err=array(obs_err)
rnd_err=rnd.normal(scale=obs_err)
rnd_obs_err[iobs]=rnd_err
# err_scale=1.0
if (do_debug):
subplot(2,1,1)
plot(obs_err)
plot(rnd_obs_err)
subplot(2,1,2)
hist(rnd_obs_err)
hist(obs_err)
show()
rnd_obs_err=err_scale*rnd_obs_err
cflag=obs.obs_cflag
otime=obs.obs_time
olat=obs.obs_lat
olon=obs.obs_lon
od=obs.obs_od
lwi=obs.obs_lwi
lwi=lwi.astype(int)
# used_idx=where(logical_and(cflag==0, od<=0.3, lwi<>1))
osza=obs.obs_sza
sel1=logical_and(cflag==0, od<=0.3)
sel2=logical_and(lwi<>1, lwi<>2)
# used_idx=where(sel1)
# used_idx=where(logical_and(sel1, sel2))
# used_idx=where(cflag==0)
used_idx=where(logical_and(obs_err<4.0, sel1))
used_idx=squeeze(used_idx)
print 'used_idx', len(used_idx)
xgp=xgp[used_idx]
xgp0=xgp0[used_idx]
obs_err=1.0e-6*obs_err[used_idx]
rnd_obs_err=1.0e-6*rnd_obs_err[used_idx]
imax=argmax(rnd_obs_err)
print 'max(obs err), max(rnd_obs_err)', 1.0e6*obs_err[imax], 1.0e6*rnd_obs_err[imax]
olat=olat[used_idx]
olon=olon[used_idx]
lwi=lwi[used_idx]
otime=otime[used_idx]
od=od[used_idx]
# r=array(varData)
# r=r*r
else: # just others for ensemble
em_id=obs.em_id[em-1]
# print 'em_id', em_id, em-1
xgp=obs.obs_xgp[em_id]
if (em==est):
print em, est
print len(used_idx)
xgp=xgp[used_idx]
if (istep>300):
print 'type xgp',type(xgp)
print 'len-xgp', len(xgp)
if (em==2):
print 'xgp', xgp[0:6]
y.append(array(xgp))
if (do_debug):
print ii, ne, shape(xgp)
if (do_debug and ii==4):
# figure(1)
# plot(xgp[0:300],'r')
# plot(xgp0[0:300], 'b')
z=xgp-xgp0
print 'max dev', max(z)
iy=iy+1
# show()
y=array(y)
y=transpose(y)
print 'y-shape', shape(y), shape(xgp)
if (istep>300):
print type(y)
print len(y)
ix=y[0]
print type(ix)
# read in the data
print ncflnm_obs
obs_f=NetCDFFile(ncflnm_obs)
yobs=obs_f.variables['xco2']
yobs_err=obs_f.variables['err']
yobs=array(yobs)
# yobs_err=array(yobs_err)
yobs_err=array(yobs_err)
# print 'shape yobs', shape(yobs)
yobs=squeeze(yobs)
yobs_err=squeeze(yobs_err)
obs_f.close()
yobs=yobs[used_idx]
yobs_err=yobs_err[used_idx]
if (int_step==0):
all_y=array(y)
all_yobs=array(yobs)
all_yobs_err=array(yobs_err)
all_rnd_err=array(rnd_obs_err)
all_lat=array(olat)
all_lon=array(olon)
all_lwi=array(lwi)
all_time=array(otime)
all_od=array(od)
state_v=stv_c.state_vector(sdate, do_debug=False, datapath=geos_datapath)
nx, ne=state_v.nx, state_v.ne
print 'nx, ne', nx,ne
nreg=(nx)/size(st_days)
x=array(state_v.stv)
else:
all_y=concatenate((all_y, y))
all_yobs=concatenate((all_yobs, yobs))
all_yobs_err=concatenate((all_yobs_err, yobs_err))
all_rnd_err=concatenate((all_rnd_err, rnd_obs_err))
all_lat=concatenate((all_lat, olat))
all_lon=concatenate((all_lon, olon))
all_lwi=concatenate((all_lwi, lwi))
all_time=concatenate((all_time, otime))
all_od=concatenate((all_od, od))
print 'shape y & yobs', shape(y), shape(yobs)
print 'istep & shape ',istep, shape(all_y), shape(all_yobs), shape(all_yobs_err), shape(all_rnd_err)
data_count.append(size(yobs))
int_step=int_step+1
print '*'*40+'int_step'+'*'*80
print int_step
if ((int_step==out_step) and do_dump):
if (dumpflnm==None):
ncdump=geos_datapath+'/'+'obs'+dumpext+"_"+sdate0+".nc"
else:
ncdump=geos_datapath+'/'+dumpflnm+"_"+dumpext+".nc"
tmp_data_count=array(data_count)
factor=1.0e6
all_y=factor*all_y
all_yobs=factor*all_yobs
all_rnd_err=factor*all_rnd_err
all_yobs_err=factor*all_yobs_err
xnx=arange(nx)
xne=arange(ne)
xny=arange(size(all_y[:,0]))
xney=arange(size(all_y[0,:]))
dimTypes=['i', 'i','i','i', 'i']
dimVars=[xnx, xne, xny, xney, doys]
dimNames=['nx', 'ne', 'ny', 'ney', 'doys']
x_info=ofb.geos_varinfo('x', 'f', ['nx', 'ne'], x)
y_info=ofb.geos_varinfo('y', 'f', ['ny', 'ney'], all_y)
yobs_info=ofb.geos_varinfo('obs', 'f', ['ny'], all_yobs)
yobs_err_info=ofb.geos_varinfo('err', 'f', ['ny'], all_yobs_err)
rnd_err_info=ofb.geos_varinfo('rnd_err', 'f', ['ny'], all_rnd_err)
count_info=ofb.geos_varinfo('daily_count', 'i', ['doys'], tmp_data_count)
lat_info=ofb.geos_varinfo('lat', 'f', ['ny'], all_lat)
lon_info=ofb.geos_varinfo('lon', 'f', ['ny'], all_lon)
time_info=ofb.geos_varinfo('time', 'f', ['ny'], all_time)
od_info=ofb.geos_varinfo('od', 'f', ['ny'], all_od)
lwi_info=ofb.geos_varinfo('lwi', 'i', ['ny'], all_lwi)
ofb.ncf_write_by_varinfo(ncdump, dimNames, dimTypes, dimVars, \
[x_info, y_info, yobs_info, yobs_err_info, \
rnd_err_info, lat_info, lon_info, time_info, od_info, lwi_info, count_info])
int_step=0
data_count=array(data_count)
print 'shape, all_y', shape(all_y)
return x, all_y, all_yobs, all_yobs_err, all_rnd_err, data_count, doys, \
all_lat, all_lon, all_time, all_lwi, all_od
def gen_transcom_coef(flux_name,\
yyyy,\
coef_a,\
inv_step,\
inv_path=gcdf.inv_path,\
modelname='GEOS5', \
category='CO2-SRCE', ntracer=1, \
do_debug=True, \
test_month=0):
# print flnm
ext1 = bpy.get_name_ext_2d()
ext1 = ext1.strip()
model_res = bpy.get_res_ext()
model_res = model_res.strip()
# model information
gc_lon = cmgrd.get_model_lon(model_res=model_res)
ix = size(gc_lon)
gc_lat = cmgrd.get_model_lat(model_res=model_res)
iy = size(gc_lat)
reg_m = rco2_f.read_region_map('2006D001')
reg_m = squeeze(reg_m)
nreg = max(reg_m.flat) + 1
coef_m = zeros(shape(reg_m), float)
# nx=nreg # -1
# nst=(yyyy-2003)*12*nx
nst = 0
idoy = 1
nstep = inv_step
print 'nstep, nreg', nstep, nreg
inc_doy = 8
for istep in range(0, nstep):
# read biomass_burning in regular grid box
# covert to ktC /y
coef_cut = coef_a[nst:nst + nreg]
coef_m[:, :] = 0
sdoy = r'%4.4dD%3.3d' % (yyyy, idoy)
reg_flux = rco2_f.read_reg_flux_map(sdoy)
print shape(reg_flux)
for ireg in range(nreg):
coef_m[:, :] = coef_m[:, :] + coef_cut[ireg] * reg_flux[:, :, ireg]
yyyy, mm, dd = tm.doy_to_time_array(idoy, yyyy)
tau0 = tm.get_tau(yyyy, mm, dd)
tau0 = tau0 / 3600.0
idoy = idoy + inc_doy
yyyy, mm, dd = tm.doy_to_time_array(idoy, yyyy)
tau1 = tm.get_tau(yyyy, mm, dd)
tau1 = tau1 / 3600.0
full_flnm = flux_name + sdoy
funit = wfbp.open_flux_bpch2_file(full_flnm, title='flux')
unit = 'kg/s'
print '--------sum--------'
print 'step:', istep
print 'max, min adjustment (GtC/a):', ocu.kg_s_to_GtC_Y * max(
coef_m.flat), ocu.kg_s_to_GtC_Y * min(coef_m.flat)
print 'total adjustment (GtC/a):', ocu.kg_s_to_GtC_Y * sum(coef_m)
print 'max, min adjustment (kg/s):', max(coef_m.flat), min(coef_m.flat)
print 'total adjustment (kg/s):', sum(coef_m)
print '--------end--------'
wfbp.write_flux_record(funit, coef_m, \
gc_lon, gc_lat,\
tau0, tau1,\
ntracer, \
modelname,\
category,\
unit, \
do_debug=False)
wfbp.close_flux_bpch2_file(funit)
nst = nst + nreg
doy_end = doy_end - 1
else:
doy_end = tm.day_of_year(yyyy, mm, 31)
doy_end = doy_end
sdate = r'%4.4d%2.2d' % (yyyy, mm)
ndays = doy_end - doy_st + 1
em_st, em_end = 1, 2
datapath = "/home/lfeng/local_disk_2/tag_co2/run4_nep_cp/run_" + str(
yyyy) + "_new/"
for idoy in range(doy_st, doy_end + 1):
yyyy, mm, dd = tm.doy_to_time_array(idoy, yyyy)
lon, lat, z, cur_t, cur_sp, data_list= read_daily_field(yyyy, mm, dd, \
em_st, em_end, \
gpcategory=["IJ-AVG-$"],\
gpnames=None,\
gptracers=None ,\
datapath=datapath)
val1 = 1.0e6 * data_list[0]
val2 = 1.0e6 * data_list[1]
if (idoy == doy_st):
sp = array(cur_sp)
t = array(cur_t)
def create_new_input_file(run_step,\
YYYY,\
DOY,\
pbuse,\
pb_start=1,\
member_start=1, \
member_end=12, \
co2flnm='CO2_EMISSION_EN',\
tmpfile="input.geos.temp", \
newfile="input.geos.new" , \
em_step=None, \
em_doy=None,\
em_yyyy=None,\
em_pbuse=None,\
do_bk_run=4,\
data_path=gcdf.data_path,\
run_path=gcdf.run_path,\
**keywords \
):
""" create the new input to drive the ensemble run
YYYY: years of the time serier
DOY: doys of the time serier
em_doy: the date need emission
"""
ntime = size(YYYY)
if ('time_start' in keywords):
ts = keywords['time_start']
syyyy = ts[0:4]
yst = int(syyyy)
dst = ts[4:7]
dst = int(dst)
# mmst=int(smm)
# sdd=ts[6:8]
# ddst=int(sdd)
# dst=tm.day_of_year(yst, mmst, ddst)
else:
yst = YYYY[0]
dst = DOY[0]
tst = tm.doy_to_utc(dst, sec=0, yyyy=yst)
tst = tst.replace('-', '')
tst = tst.replace(':', '')
print(tst)
if (em_step == None):
iday0 = DOY[0]
for iday in DOY[1:]:
if (iday > iday0):
em_step = iday - iday0
break
else:
iday0 = iday
if ('time_end' in keywords):
te = keywords['time_end']
syyyy = te[0:4]
yed = int(syyyy)
smm = te[4:6]
mmst = int(smm)
sdd = te[6:8]
ddst = int(sdd)
ded = tm.day_of_year(yst, mmst, ddst)
else:
yed = YYYY[1] #-1
ded = DOY[1] #-1
# the endtime should be + timestep
# yed, ded=tm.next_doy(yed, ded, em_step)
tend = tm.doy_to_utc(ded, sec=0, yyyy=yed)
tend = tend.replace('-', '')
tend = tend.replace(':', '')
print(tend)
fin = open(tmpfile, "r") # open a temporary input.geos
lines = fin.readlines()
print(len(lines))
fin.close()
fout = open(newfile, "w") # write to new input.geos file
section_start = 0
colwidth = 25
line_count = 0
ntracer = member_end - member_start + 1
# enafix=r'EN%4.4d-EN%4.4d' % (member_start, member_end)
enafix = r'ST%3.3d.EN%4.4d-EN%4.4d' % (run_step, member_start, member_end)
for line in lines:
if ("SIMULATION MENU" in line):
section_start = 1
line_count = 0
fout.write(line)
elif ("TRACER MENU" in line):
section_start = 2
line_count = 0
fout.write(line)
elif ("ND51 MENU" in line):
section_start = 3
line_count = 0
fout.write(line)
elif ("OUTPUT MENU" in line):
section_start = 10
line_count = 0
fout.write(line)
elif ("ENSEMBLE MENU" in line):
section_start = 4
line_count = 0
fout.write(line)
elif ("DIAGNOSTIC MENU" in line):
section_start = 5
line_count = 0
fout.write(line)
elif ("GAMAP MENU" in line):
section_start = 6
line_count = 0
fout.write(line)
elif ("PROD & LOSS MENU" in line):
section_start = 7
line_count = 0
fout.write(line)
elif ("ND50 MENU" in line):
section_start = 8
line_count = 0
fout.write(line)
elif (section_start > 0):
line_count = line_count + 1
line_head = line[0:colwidth]
line_left = line[colwidth:]
if (section_start == 1):
if (line_count == 1):
new_line = line_head + " " + tst + " "
fout.write(new_line + "\n")
elif (line_count == 2):
line_head = line[0:colwidth]
new_line = line_head + " " + tend + " "
fout.write(new_line + "\n")
elif (line_count == 3):
print(line_left)
line_left = line_left.replace('$RUNPATH', run_path)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 4):
print(line_left)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 6):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 13):
line_left = line_left.replace('$RUNPATH', run_path)
new_line = line_head + line_left
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
elif (section_start == 2): # tracer menu
if (line_count == 1):
fout.write(line)
elif (line_count == 2):
line_head = line[0:colwidth]
snum = r'%4d' % (ntracer)
new_line = line_head + " " + snum + " " + "\n"
fout.write(new_line)
elif (line_count == 3):
fout.write(line)
elif (line_count == 4):
line_head = line[0:colwidth]
tracer_no = line[colwidth:colwidth + 5]
line_left = line[colwidth + 5:]
tracer_id = 1
tracers = list()
for itracer in range(member_end - member_start + 1):
st1 = r'Tracer #%3.3d ENSEM' % (itracer + member_start)
lst1 = len(st1)
new_head = st1[:] + ' ' * (colwidth - 1 - lst1) + ":"
st1 = r'%5d' % (tracer_id)
lst1 = len(st1)
new_tracer_no = (5 - lst1) * ' ' + st1
new_line = new_head + new_tracer_no + line_left
fout.write(new_line)
tracers.append(tracer_id)
tracer_id = tracer_id + 1
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
pass
elif (section_start == 3): # ND51 menu
if (line_count == 1):
fout.write(line)
elif (line_count == 2):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 4):
line_left = ""
for itracer in [1, member_end - member_start + 1]:
stracer = r' %d' % (itracer)
line_left = line_left + stracer
line_left = line_left + ' ' + '199' # 196 198 199 200 201 output other information
new_line = line_head + line_left + ' \n'
print(new_line)
# tx=raw_input()
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
elif (section_start == 4): #ensemble menu
if (line_count == 1):
st1 = r' %d ' % member_start
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 2):
st1 = r' %d ' % member_end
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 3):
st1 = r' %d ' % do_bk_run
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 4):
st1 = r' %d ' % ntime
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 5):
st1 = ""
if (em_doy == None):
em_doy = DOY
for doy in em_doy:
sdoy = r'%d' % doy
st1 = st1 + ' ' + sdoy
st1 = st1 + ' '
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 6):
st1 = ""
if (em_yyyy == None):
for yyyy in YYYY:
syyyy = r'%d' % yyyy
st1 = st1 + ' ' + syyyy
else:
for yyyy in em_yyyy:
syyyy = r'%d' % yyyy
st1 = st1 + ' ' + syyyy
st1 = st1 + ' '
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 7):
st1 = r' %d ' % pb_start
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 8):
st1 = ""
if (em_pbuse == None):
for pbuse in pbuse:
spbuse = r'%d' % pbuse
st1 = st1 + ' ' + spbuse
else:
for pbuse in em_pbuse:
spbuse = r'%d' % pbuse
st1 = st1 + ' ' + spbuse
st1 = st1 + ' '
new_line = line_head + st1 + ' \n'
fout.write(new_line)
elif (line_count == 9): # 'flnm'
new_line = line_head + ' ' + co2flnm.strip() + '\n'
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
elif (section_start == 47): #P/L menu
line_head = line[0:colwidth]
tracer_no = line[colwidth:colwidth + 5]
line_left = line[colwidth + 5:]
tracer_id = 1
tracers = list()
if (line_count <= 3):
# print line_count, line
fout.write(line)
elif (line_count == 4):
st1 = r'%d' % (member_end - member_start + 1 + 5)
new_line = line_head + ' ' + st1 + ' \n'
fout.write(new_line)
elif (line_count == 5):
fout.write(line)
for itracer in range(1, member_end - member_start + 1 + 5):
st1 = r'Prod/Loss Family #%d' % (itracer +
member_start)
lst1 = len(st1)
new_head = st1[:] + ' ' * (colwidth - 1 - lst1) + ":"
st1 = r'%5d' % (tracer_id)
lst1 = len(st1)
new_tracer_no = (5 - lst1) * ' ' + st1
line_left = 'PCO: CO%3.3d' % (itracer)
new_line = new_head + ' ' + line_left + '\n'
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
pass
elif (section_start == 5): #diagnostic menu
if (line_count == 1):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
elif (section_start == 6): #gamap menu
if (line_count == 1):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 2):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
elif (section_start == 8): # ND50 menu
if (line_count == 1):
fout.write(line)
elif (line_count == 2):
line_left = line_left.replace('$DATAPATH', data_path)
line_left = line_left.replace('STYYY.ENXXXX-ENXXXX',
enafix)
new_line = line_head + line_left
fout.write(new_line)
elif (line_count == 4):
line_left = ""
for itracer in [1, member_end - member_start + 1]:
stracer = r' %d' % (itracer)
line_left = line_left + stracer
line_left = line_left + ' ' + '399' # output other information
new_line = line_head + line_left + ' \n'
fout.write(new_line)
elif (line[0:2] == '--'):
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
elif (section_start == 10): #output menu
if (line_count == 1):
id_cnt = 0
yyyy_list = list()
mm_list = list()
dd_list = list()
for idoy in DOY:
cyyyy, cmm, cdd = tm.doy_to_time_array(
idoy, YYYY[id_cnt])
yyyy_list.append(cyyyy)
mm_list.append(cmm)
dd_list.append(cdd)
id_cnt = id_cnt + 1
yyyy_list = array(yyyy_list)
mm_list = array(mm_list)
dd_list = array(dd_list)
if ((line_count >= 1) and (line_count < 13)):
line_left = line_left.replace('3', '0')
sel_mm = where(mm_list == line_count)
# print size(sel_mm), sel_mm
if (size(sel_mm) > 0):
if (size(sel_mm) == 1):
sel_mm = [squeeze(sel_mm)]
else:
sel_mm = squeeze(sel_mm)
for isel in sel_mm:
sel_dd = dd_list[isel]
ispace = 0
# skip the line
for ichar in line_left:
if (ichar != ' '):
break
else:
ispace = ispace + 1
sel_dd = sel_dd + ispace
print(line_left)
if (sel_dd >= len(line_left)):
sel_dd = len(line_left) - 1
if (sel_dd == 1):
tline_1 = '3'
else:
tline_1 = line_left[0:sel_dd - 1]
tline_1 = tline_1 + '3'
tline_1 = tline_1 + line_left[sel_dd:]
line_left = tline_1
new_line = line_head + line_left
fout.write(new_line)
elif (line[0:2] == '--'): # the section end line
line_count = 0
section_start = 0
fout.write(line)
else:
fout.write(line)
else:
fout.write(line)
fout.close()
print('reach the end')
