ntimes=int( 1 + np.around((etime-itime).seconds / delta.seconds) ) #Total number of times.
ctl_file = basedir + '/' + my_exp + '/ctl/update_mean_diff.ctl'
outputdir=basedir + '/' + my_exp + '/time_mean/' + filetype + '/'
if not os.path.exists( outputdir) :
os.makedirs( outputdir )
#=========================================================
# READ CTL FILE
#=========================================================
ctl_dict = ctlr.read_ctl( ctl_file )
nx=ctl_dict['nx']
ny=ctl_dict['nx']
nlev=len( ctl_dict['full_lev_list'] )
nt=int(1) #Force the number of times to be one.
ctl_dict['nt']=int(1) #Force the number of times to be one.
undef=np.float32( ctl_dict['undef'] )
if ctl_dict['big_endian'] :
dtypein = '>f4'
endian='big_endian'
else :
dtypein = 'f4'
endian='little_endian'
delta = dt.timedelta(seconds=deltat[iexp])
#Compute the total number of times
ntimes = int(1 + np.around(
(etime - itime).seconds / delta.seconds)) #Total number of times.
#=========================================================
# READ CTL FILE
#=========================================================
if iexp == 0:
ctl_file = basedir + '/' + my_exp + '/ctl/update_mean_diff.ctl'
ctl_dict = ctlr.read_ctl(ctl_file)
nx = ctl_dict['nx']
ny = ctl_dict['nx']
nlev = ctl_dict['nz']
nt = int(1) #Force the number of times to be one.
ctl_dict['nt'] = int(1) #Force the number of times to be one.
undef = np.float32(ctl_dict['undef'])
ctl_file_2 = basedir + '/' + my_exp + '/ctl/guesgp.ctl'
ctl_dict_2 = ctlr.read_ctl(ctl_file_2)
#=========================================================
# READ LAT LON
basedir = '/home/ra001011/a03471/data/output_data/'
exps = ['LE_D1_1km_5min']
lat_radar = 34.823
lon_radar = 135.523
radar_range = 60.0e3 #Radar range in meters (to define the radar mask)
#=========================================================
# READ LAT LON
#=========================================================
latlon_file = basedir + '/LE_D1_1km_5min/latlon/latlon.grd'
latlon_ctl = basedir + '/LE_D1_1km_5min/latlon/latlon.ctl'
ctl_dict = ctlr.read_ctl(latlon_ctl)
my_data = ctlr.read_data_grads(latlon_file, ctl=ctl_dict)
lon = np.squeeze(my_data['glon'])
lat = np.squeeze(my_data['glat'])
topo = np.squeeze(my_data['topo'])
#Exclude areas outside the radar domain.
radar_mask = cmf.distance_range_mask(lon_radar, lat_radar, radar_range, lon,
lat)
#=========================================================================================
#Plot the mean topography and PAWR radar range
#=========================================================================================
obs_increment = [5.0, 5.0, 5.0, 5.0, 2.0, 2.0, 2.0, 2.0]
obs_error = [5.0, 5.0, 5.0, 5.0, 2.0, 2.0, 2.0, 2.0]
nbv = 1000
sigma_smooth = 2.0
#=========================================================
# LOOP OVER FILE TYPES
#=========================================================
profile_mean_rmsd = dict()
profile_mean_rmsu = dict()
profile_kld = dict()
ctl_dict = ctlr.read_ctl(basedir + '/LE_D1_1km_5min/ctl/moment0001_for.ctl')
for iexp, my_exp in enumerate(exps):
profile_mean_rmsd[my_exp] = []
profile_mean_rmsu[my_exp] = []
profile_kld[my_exp] = []
#=========================================================
# READ THE DATA
#=========================================================
for iv, my_obs_inc in enumerate(obs_increment):
var_obs = variable_combination[0][iv]
var_upd = variable_combination[1][iv]
#=========================================================
# PLOT MODEL DOMAIN
#=========================================================
lat_radar = 34.823
lon_radar = 135.523
radar_range = 60.0e3 #Radar range in meters (to define the radar mask)
#=========================================================
# READ LAT LON AND TOPO
#=========================================================
latlon_file = basedir + '/LE_D1_1km_5min/latlon/latlon.grd'
latlon_ctl = basedir + '/LE_D1_1km_5min/latlon/latlon.ctl'
ctl_dict = ctlr.read_ctl(latlon_ctl)
my_data = ctlr.read_data_grads(latlon_file, ctl=ctl_dict)
lon = np.squeeze(my_data['glon'])
lat = np.squeeze(my_data['glat'])
topo = np.squeeze(my_data['topo'])
#Exclude areas outside the radar domain.
radar_mask = cmf.distance_range_mask(lon_radar, lat_radar, radar_range, lon,
lat)
#=========================================================================================
#Plot the mean topography and PAWR radar range
#=========================================================================================
