'_height-' + heightstr + '_nens-' + str(args.nens) + '_tstart-' +
str(args.tstart) + '_tend-' + str(args.tend) + '_tinc-' +
str(args.tinc) + '_minmem-' + str(args.minmem) + '_dr-' +
str(args.dr) + '.nc')
if args.det == 'True':
savestr += '_det'
print savestr
# Convert times to timedelta objects
tstart = timedelta(
hours=args.tstart) # Cannot be 0 because of tau_c calculation!
tend = timedelta(hours=args.tend)
tinc = timedelta(minutes=args.tinc) # temporal resolution for analysis
# Setup - Create or define lists
timelist = make_timelist(tstart, tend, tinc)
print len(timelist)
itlist = range(len(timelist))
nlist = [256, 128, 64, 32, 16, 8, 4]
histbinedges = [0, 0.1, 0.2, 0.5, 1, 2, 5, 10, 1000]
# Setup - Directories for input data
ensdir = '/home/scratch/users/stephan.rasp/' + args.date + '/deout_ceu_pspens/'
radarpref = '/project/meteo/w2w/A6/radolan/netcdf_cosmo_de/raa01-rw_10000-'
radarsufx = '-dwd---bin.nc'
# Analysis-specific setup
dx = 2800. # Grid Spacing ATTENTION: Hard coded and wrong as of now
# Get analysis level
help='Recompute pre-processed files.')
parser.set_defaults(recompute=False)
args = parser.parse_args()
assert args.n_kernel % 2 == 1, 'n_kernel must be odd'
kernel = (np.ones((args.n_kernel, args.n_kernel)) / float(
(args.n_kernel * args.n_kernel)))
# Loop over time
tstart = yyyymmddhhmmss_strtotime(args.date_ana_start)
tend = yyyymmddhhmmss_strtotime(args.date_ana_stop)
tint = timedelta(hours=1)
if tstart == tend:
timelist = [tstart]
else:
timelist = make_timelist(tstart, tend, tint)
# Set up figure
fig, axarr = plt.subplots(1, 2, figsize=(10, 6))
# Loop over experiments
expid_str = ''
exp_list = []
for ie, expid in enumerate(args.expid):
print 'expid = ', expid
expid_str += expid + '_'
DATA_DIR = datadir + expid
# Check if saved data is available
savedir = savedir_base + expid + '/verif_ana_prec/'
if not os.path.exists(savedir): os.makedirs(savedir)
def plot_prec_stamps(inargs):
"""
Plots precipitation stamps of obs, det and ensemble every hour for each
date and time specified
Parameters
----------
inargs : argparse object
Argparse object with all input arguments
"""
# Loop over dates
for idate, date in enumerate(make_datelist(inargs)):
print('Date ' + date)
# Loop over times
for t in make_timelist(timedelta(hours=inargs.time_start),
timedelta(hours=inargs.time_end),
timedelta(hours=1)):
print('Time ' + str(t))
# Load all CU objects
fobjlist = []
titlelist = []
# 1st: Radar
radarpref = (get_config(inargs, 'paths', 'radar_data') +
get_config(inargs, 'paths', 'radar_prefx'))
radarsufx = get_config(inargs, 'paths', 'radar_sufix')
dtradar = timedelta(minutes=10)
radartime = yymmddhhmm(yyyymmddhh_strtotime(date) + t - dtradar)
radarfn = radarpref + radartime + radarsufx
radar_fobj = getfobj_ncdf(radarfn, fieldn='pr', dwdradar=True)
# Crop data
l11, l12, l21, l22, l11_rad, l12_rad, l21_rad, l22_rad = \
get_domain_limits(inargs)
l11_diff = l11_rad - l11
l12_diff = l12_rad - l12
l21_diff = l21_rad - l21
l22_diff = l22_rad - l22
radar_fobj.data = radar_fobj.data[l11_diff:l12_diff,
l21_diff:l22_diff]
radar_fobj.lats = radar_fobj.lats[l11_diff:l12_diff,
l21_diff:l22_diff]
radar_fobj.lons = radar_fobj.lons[l11_diff:l12_diff,
l21_diff:l22_diff]
fobjlist.append(radar_fobj)
titlelist.append('Radar')
# 2nd: det
ncdffn_pref = (get_config(inargs, 'paths', 'raw_data') + date +
'/deout_ceu_pspens/' + 'det' + '/OUTPUT/lfff')
fobjlist.append(
getfobj_ncdf(ncdffn_pref + ddhhmmss(t) + '.nc_30m_surf',
'PREC_ACCUM'))
titlelist.append('Det')
# 3rd: ens
ncdffn = 'lfff' + ddhhmmss(t) + '.nc_30m_surf'
date_dir = (get_config(inargs, 'paths', 'raw_data') + date +
'/deout_ceu_pspens/')
fobjlist.extend(
getfobj_ncdf_ens(date_dir,
'sub',
inargs.nens,
ncdffn,
dir_suffix='/OUTPUT/',
fieldn='PREC_ACCUM',
nfill=1))
titlelist.extend(
['Member ' + str(i + 1) for i in range(inargs.nens)])
# Now plot
n_panels = len(fobjlist)
n_cols = 4
n_rows = int(np.ceil(float(n_panels) / n_cols))
pw = get_config(inargs, 'plotting', 'page_width')
fig, axmat = plt.subplots(n_rows,
n_cols,
figsize=(pw, 3.0 * n_rows))
axflat = np.ravel(axmat)
for i in range(len(fobjlist)):
plt.sca(axflat[i])
cf = plot_stamp(inargs, fobjlist[i], cmPrec, levelsPrec,
axflat[i], 'PREC_ACCUM')
axflat[i].set_title(titlelist[i])
cb = fig.colorbar(cf,
cax=fig.add_axes([0.4, 0.15, 0.2, 0.02]),
orientation='horizontal')
cb.set_label('Accumulation [mm/h]')
titlestr = ((yyyymmddhh_strtotime(date) +
t).strftime('%d %b - %H UTC'))
fig.suptitle(titlestr)
plt.subplots_adjust(wspace=0.02, left=0.02, right=0.98)
# Save figure and log
save_fig_and_log(fig,
None,
inargs,
'prec_stamps',
datestr=((yyyymmddhh_strtotime(date) +
t).strftime('%Y%m%d_%H')))
def plot_prec_stamps(inargs):
"""
Plots precipitation stamps of obs, det and ensemble every hour for each
date and time specified
Parameters
----------
inargs : argparse object
Argparse object with all input arguments
"""
# TODO: Update colors
cmPrec = ((1, 1, 1), (0, 0.627, 1), (0.137, 0.235, 0.98),
(0.392, 0, 0.627), (0.784, 0, 0.627))
# (0.1 , 0.1 , 0.784),
levelsPrec = [0, 1, 3, 10, 30, 100.]
# Loop over dates
for idate, date in enumerate(make_datelist(inargs)):
# Loop over times
for t in make_timelist(timedelta(hours=inargs.time_start),
timedelta(hours=inargs.time_end),
timedelta(hours=1)):
# Load all CU objects
fobjlist = []
titlelist = []
# 1st: Radar
fobjlist.append(get_and_crop_radar_fobj(inargs, date, t))
titlelist.append('Radar')
# 2nd: det
ncdffn_pref = (get_config(inargs, 'paths', 'raw_data') + date +
'/deout_ceu_pspens/' + 'det' + '/OUTPUT/lfff')
fobjlist.append(
getfobj_ncdf(ncdffn_pref + ddhhmmss(t) + '.nc_30m_surf',
'PREC_ACCUM'))
titlelist.append('Det')
# 3rd: ens
ncdffn = 'lfff' + ddhhmmss(t) + '.nc_30m_surf'
date_dir = (get_config(inargs, 'paths', 'raw_data') + date +
'/deout_ceu_pspens/')
fobjlist.extend(
getfobj_ncdf_ens(date_dir,
'sub',
inargs.nens,
ncdffn,
dir_suffix='/OUTPUT/',
fieldn='PREC_ACCUM',
nfill=1))
titlelist.extend(['Mem ' + str(i + 1) for i in range(inargs.nens)])
# Now plot
n_panels = len(fobjlist)
n_cols = 4
n_rows = int(np.ceil(float(n_panels) / n_cols))
fig, axmat = plt.subplots(n_rows,
n_cols,
figsize=(10, 3.5 * n_rows))
axflat = np.ravel(axmat)
for i in range(len(fobjlist)):
plt.sca(axflat[i])
cf, tmp = ax_contourf(axflat[i],
fobjlist[i],
colors=cmPrec,
pllevels=levelsPrec,
ji0=(50 + inargs.zoom_lat1,
50 + inargs.zoom_lon1),
ji1=(357 - 51 + inargs.zoom_lat2,
357 - 51 + inargs.zoom_lon2),
sp_title=titlelist[i],
Basemap_drawrivers=False,
npars=0,
nmers=0)
cb = fig.colorbar(cf,
cax=fig.add_axes([0.4, 0.1, 0.2, 0.02]),
orientation='horizontal')
cb.set_label('Accumulation [mm/h]')
titlestr = (yyyymmddhh_strtotime(date).strftime(
get_config(inargs, 'plotting', 'date_fmt')) + ' ' +
str(t.seconds / 3600).zfill(2) + 'UTC')
fig.suptitle(titlestr)
plt.tight_layout(rect=[0, 0.1, 1, 0.93])
# Save figure and log
save_fig_and_log(fig,
None,
inargs,
'prec_stamps',
date=date,
time=str(t.seconds / 3600).zfill(2))