def plot_one_date(self, plot_date, **kwargs):
datestr = plot_date.strftime('%Y%m%dT000000Z')
basename = 'field_%s' % datestr
prev_date = plot_date - dt.timedelta(1)
rf1 = os.path.join(
self.root_forecast_dir, prev_date.strftime('%Y%m%d'), 'restart',
basename) # restart after 1 day of previous forecast
rf2 = os.path.join(self.root_forecast_dir,
plot_date.strftime('%Y%m%d'), 'inputs',
basename) # restart after assimilation
nb1 = NextsimBin(rf1,
add_gmsh=True,
logfile=os.path.join(self.root_forecast_dir,
prev_date.strftime('%Y%m%d'),
'nextsim.log'),
**kwargs)
nb2 = NextsimBin(rf2)
plot_vars = [
'M_conc',
'M_thick',
'M_snow_thick',
'M_ridge_ratio',
'M_tice_0',
'M_tice_1',
'M_tice_2',
'M_sst',
'M_sss',
'M_tsurf_thin',
'M_h_thin',
'M_hs_thin',
'M_conc_thin',
]
innovs = dict()
vtypes = dict()
for v in plot_vars:
v1 = nb1.get_var(v)
v2 = nb2.get_var(v)
k = 'innov-' + v
innovs[k] = v2 - v1
vtypes[k] = 'f'
nb1.add_vars(innovs, vtypes)
gridded_vars = nb1.interp_vars(list(innovs))
outdir = os.path.join(self.root_forecast_dir,
plot_date.strftime('%Y%m%d'), 'innovation_plots')
nsl.make_dir(outdir)
for v, arr in gridded_vars.items():
fig = nb1.get_gridded_figure(arr.T,
land_color=[1, 1, 1],
clim=[-.5, .5],
cmap='balance')
figname = '%s/%s-%s.png' % (outdir, v, datestr)
print('Saving %s' % figname)
fig.savefig(figname)
plt.close(fig)
return nb1.mesh_info.gmsh_mesh
def run(args):
'''
make the file
Parameters:
-----------
args : argparse.Namespace
'''
nsl.make_dir(args.outdir)
outfile = os.path.join(args.outdir, args.date.strftime(NEW_FILEMASK))
# open arome file and ecmwf file for each day of forecast
ec_dsets = open_ecmwf(args)
dst_data = {v: [] for v in DST_VARS}
dst_vecs = []
for i, ec_ds in ec_dsets.items():
'''
loop over each day of forecast:
- eg 1st day of forecast is in legacy*.1.nc,
2nd day of forecast is in legacy*.2.nc
'''
print('Day %i: Using file %s' % (i, ec_ds.filepath()))
in_ec2_time_range = test_ec2_time_range(ec_ds,
args.date + dt.timedelta(i))
dst_vecs.append(set_destination_coordinates(ec_ds, in_ec2_time_range))
# fetch, interpolate and blend all variables from ECMWF and AROME
for dst_var_name in DST_VARS:
# Interpolate data from ECMWF
ec_var_name = DST_VARS[dst_var_name]
print('Read', ec_var_name)
dst_data[dst_var_name].append(
get_ec2_var(ec_ds, ec_var_name, in_ec2_time_range))
# set DST_DATA (combine days 1,2,... before exporting)
dst_vec = merge_days(dst_data, dst_vecs)
# save the output
export(outfile, ec_ds, dst_vec)
def run(args):
'''
process one day's AROME file
Parameters:
-----------
args : argparse.Namespace
parsed command line arguments
'''
ar_ds, ar_ds2, ar_proj, ar_pts = open_arome(args.date)
dst_vec, dst_shape = set_destination_coordinates(ar_proj, ar_ds, ar_ds2)
# save the output
outfile = args.date.strftime(AR_FILEMASK_NEW)
outdir = os.path.split(outfile)[0]
nsl.make_dir(outdir)
print('Exporting %s' % outfile)
with Dataset(outfile, 'w') as dst_ds:
create_dimensions(ar_ds, dst_ds, dst_vec)
create_variables(ar_ds, ar_ds2, dst_ds, dst_vec, dst_shape)
for ds in [ar_ds, ar_ds2]:
ds.close()
def run(args):
'''
make the file
Parameters:
-----------
args : argparse.Namespace
'''
os.makedirs(os.path.dirname(NEW_FILEMASK), exist_ok=True)
outfile = args.date.strftime(NEW_FILEMASK)
if os.path.exists(outfile):
print(f'{outfile} exists - skipping')
return
# open arome file and ecmwf file
ar_ds, ar_proj, ar_pts = open_arome(args.date)
ec_ds, ec_pts = open_ecmwf(args.date)
in_ec2_time_range = test_ec2_time_range(ec_ds, args.date)
if args.plot:
# plot the grid if desired
figname = outfile.replace('.nc', '.png')
plot_destination_grid(figname, ar_proj, ar_pts)
# set target coords
(dst_vec, dst_ecp, dst_arp,
dst_shape) = set_destination_coordinates(ar_proj, ar_ds)
# distance to AROME border
ar_shp = [len(v) for v in ar_pts]
ar_dist = create_distance(ar_shp)
dst_ardist_grd = interpolate(ar_dist, ar_pts, dst_arp, dst_shape)
#if args.save_grid:
# # save the grid
# print('Exporting %s' %GRID_FILE)
# with Dataset(GRID_FILE, 'w') as dst_ds:
# add_grid_to_file(dst_ds, ar_ds, dst_ecp, dst_vec, dst_shape)
sz = list(dst_ardist_grd.shape)
num_ens_mems = len(dst_vec['ensemble_member'])
sz.insert(1, num_ens_mems)
for dst_var_name in DST_VARS:
DST_DATA[dst_var_name] = np.zeros(sz)
# fetch, interpolate and blend all variables from ECMWF and AROME
load_transformed_ECMWF(ec_ds, dst_vec, in_ec2_time_range, ec_pts, dst_ecp,
dst_shape)
for i_ens in range(num_ens_mems):
ar_data = load_transformed_AROME(ar_ds, i_ens, dst_vec, ar_proj,
ar_shp, ar_pts, dst_arp, dst_shape)
# Compute destination product from ECMWF data
if 0:
# test plots
kw = dict(vmin=0, vmax=3e6)
for n in range(8):
nsl.make_dir('figs0')
figname = 'figs0/ec_%s_%i.png' % (dst_var_name, n)
print('Saving %s' % figname)
plt.imshow(dst_ecd_grd[n, :, :], origin='upper', **kw)
plt.colorbar()
plt.title(dst_var_name)
plt.savefig(figname)
plt.close()
figname = 'figs0/ar_%s_%i.png' % (dst_var_name, n)
print('Saving %s' % figname)
plt.imshow(ar_data[dst_var_name][n, :, :],
origin='upper',
**kw)
plt.colorbar()
plt.title(dst_var_name)
plt.savefig(figname)
plt.close()
# blend and add to destination data
print('- Blending AROME and ECMWF')
for dst_var_name in DST_VARS:
DST_DATA[dst_var_name][:, i_ens, :, :] = blend(
ar_data[dst_var_name], EC_DATA[dst_var_name], dst_ardist_grd)
assert (np.all(np.isfinite(DST_DATA[dst_var_name][:,
i_ens, :, :])))
#export the files
export4d(outfile, ar_ds, dst_ecp, dst_vec, dst_shape)
'2T' : lambda x : x,
'2D' : lambda x : x,
'MSL' : lambda x : x,
'SSRD' : accumulate_ecmwf,
'STRD' : accumulate_ecmwf,
#'STRD' : lambda x : x, #to test
'TP' : accumulate_ecmwf,
}
#dst_var = 'air_temperature_2m'
#DST_VARS = {dst_var: DST_VARS[dst_var]}
if __name__ == '__main__':
args = parse_args(sys.argv[1:])
outdir = os.path.split(NEW_FILEMASK)[0]
nsl.make_dir(outdir)
outfile = os.path.join(outdir, NEW_FILEMASK % args.date)
# open arome file and ecmwf file
ar_ds, ar_proj, ar_pts = open_arome(args.date)
ec_ds, ec_pts = open_ecmwf(args.date)
if args.plot:
# plot the grid if desired
figname = outfile.replace('.nc', '.png')
plot_destination_grid(figname, ar_proj, ar_pts)
# set target coords
(dst_vec, dst_ecp, dst_arp,
dst_shape) = set_destination_coordinates(ar_proj, ar_ds)