def __init__(self, an_time, filename, label=""):
qc_obs = surfex.dataset_from_file(an_time, filename)
observations = []
for i in range(0, len(qc_obs)):
observations.append(
Observation(qc_obs.obstimes[i], qc_obs.dataset.lons[i],
qc_obs.dataset.lats[i], qc_obs.dataset.elevs[i],
qc_obs.dataset.value[i]))
ObservationSet.__init__(self, observations, label=label)
def write_obsmon_sqlite_file(**kwargs):
modes = ["total", "land", "sea"]
stat_cols = ["nobs", "fg_bias", "fg_abs_bias", "fg_rms", "fg_dep", "fg_uncorr", "bc", "an_bias", "an_abs_bias",
"an_rms", "an_dep"]
an_time = kwargs["dtg"]
if isinstance(an_time, str):
an_time = datetime.strptime(an_time, "%Y%m%d%H")
dtg = an_time.strftime("%Y%m%d%H")
varname = kwargs["varname"]
dbname = kwargs["output"]
operator = "bilinear"
if "operator" in kwargs:
operator = kwargs["operator"]
qc = kwargs["qc"]
obs_titan = surfex.dataset_from_file(an_time, qc, skip_flags=[150])
conn = open_db(dbname)
create_db(conn, modes, stat_cols)
fg_file = kwargs["fg_file"]
fg_var = kwargs["file_var"]
an_file = kwargs["an_file"]
an_var = kwargs["file_var"]
# Only first guess file implemented at the moment
geo_in, validtime, an_field, glafs, gelevs = surfex.read_first_guess_netcdf_file(an_file, an_var)
geo_in, validtime, fg_field, glafs, gelevs = surfex.read_first_guess_netcdf_file(fg_file, fg_var)
fg_dep = surfex.Departure(operator, geo_in, obs_titan, fg_field, "first_guess").get_departure()
an_dep = surfex.Departure(operator, geo_in, obs_titan, an_field, "analysis").get_departure()
obs_titan = surfex.dataset_from_file(an_time, qc, skip_flags=[150, 199], fg_dep=fg_dep, an_dep=an_dep)
populate_usage_db(conn, dtg, varname, obs_titan)
populate_obsmon_db(conn, dtg, calculate_statistics(obs_titan, modes, stat_cols),
modes, stat_cols, varname)
close_db(conn)
def write_obsmon_sqlite_file(args):
modes = ["total", "land", "sea"]
stat_cols = [
"nobs", "fg_bias", "fg_abs_bias", "fg_rms", "fg_dep", "fg_uncorr",
"bc", "an_bias", "an_abs_bias", "an_rms", "an_dep"
]
dtg = args.DTG
an_time = datetime.strptime(dtg, "%Y%m%d%H")
varname = args.varname
dbname = args.output
obs_titan = surfex.dataset_from_file(an_time, args.qc, skip_flags=[150])
conn = open_db(dbname)
create_db(conn, modes, stat_cols)
cache = surfex.Cache(False, 3600)
fg_file = args.fg_file
fg_var = args.file_var
an_file = args.an_file
an_var = args.file_var
# Only first guess file implemented at the moment
geo_in, validtime, an_field, glafs, gelevs = surfex.read_first_guess_netcdf_file(
an_file, an_var)
geo_in, validtime, fg_field, glafs, gelevs = surfex.read_first_guess_netcdf_file(
fg_file, fg_var)
dx = []
dy = []
for i in range(0, len(obs_titan.flags)):
dx.append(0.5)
dy.append(0.5)
settings = {
"nam_lonlatval": {
"xx": obs_titan.lons[:],
"xy": obs_titan.lats[:],
"xdx": dx,
"xdy": dy
}
}
geo_out = surfex.LonLatVal(settings)
an_interpolated_field = surfex.NearestNeighbour(geo_in, geo_out, distance_check=False, cache=cache). \
interpolate(an_field)
fg_interpolated_field = surfex.NearestNeighbour(geo_in, geo_out, distance_check=False, cache=cache). \
interpolate(fg_field)
fg_dep = []
an_dep = []
for o in range(0, len(obs_titan.flags)):
fg_dep.append(obs_titan.values[o] - fg_interpolated_field[o])
an_dep.append(obs_titan.values[o] - an_interpolated_field[o])
obs_titan = surfex.dataset_from_file(an_time,
args.qc,
skip_flags=[150, 199],
fg_dep=fg_dep,
an_dep=an_dep)
populate_usage_db(conn, dtg, varname, obs_titan)
populate_obsmon_db(conn, dtg,
calculate_statistics(obs_titan, modes, stat_cols),
modes, stat_cols, varname)
close_db(conn)
def execute(self, **kwargs):
if self.var_name in self.translation:
var = self.translation[self.var_name]
else:
raise Exception
hlength = 30000
vlength = 100000
wlength = 0.5
land_only = True
max_locations = 20
elev_gradient = 0
epsilon = 0.25
hlength = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#HLENGTH",
default=hlength)
vlength = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#VLENGTH",
default=vlength)
wlength = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#WLENGTH",
default=wlength)
elev_gradient = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#GRADIENT",
default=elev_gradient)
land_only = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#LAND_ONLY",
default=land_only)
max_locations = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#MAX_LOCATIONS",
default=max_locations)
epsilon = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#EPISLON",
default=epsilon)
minvalue = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#MINVALUE",
default=None,
abort=False)
maxvalue = self.config.get_setting("OBSERVATIONS#OI#" + var +
"#MAXVALUE",
default=None,
abort=False)
input_file = self.archive + "/raw_" + var + ".nc"
output_file = self.archive + "/an_" + var + ".nc"
# Get input fields
geo, validtime, background, glafs, gelevs = surfex.read_first_guess_netcdf_file(
input_file, var)
an_time = validtime
# Read OK observations
obs_file = self.system_file_paths.get_system_file("obs_dir",
"qc_" + var +
".json",
basedtg=self.dtg)
observations = surfex.dataset_from_file(an_time, obs_file, qc_flag=0)
field = surfex.horizontal_oi(geo,
background,
observations,
gelevs=gelevs,
glafs=glafs,
hlength=hlength,
vlength=vlength,
wlength=wlength,
land_only=land_only,
max_locations=max_locations,
elev_gradient=elev_gradient,
epsilon=epsilon,
minvalue=minvalue,
maxvalue=maxvalue)
if os.path.exists(output_file):
os.unlink(output_file)
surfex.write_analysis_netcdf_file(output_file,
field,
var,
validtime,
gelevs,
glafs,
new_file=True,
geo=geo)