def update_discharge_from_hechms(curw_sim_pool, curw_fcst_pool, flo2d_model,
method, start_time, end_time, sim_tag):
try:
TS = DTimeseries(pool=curw_sim_pool)
# [station_name,latitude,longitude,target,model,version,sim_tag,station]
extract_stations = read_csv(
os.path.join(ROOT_DIR,
'grids/discharge_stations/flo2d_stations.csv'))
for i in range(len(extract_stations)):
station_name = extract_stations[i][0]
latitude = extract_stations[i][1]
longitude = extract_stations[i][2]
target_model = extract_stations[i][3]
if target_model == flo2d_model:
if station_name in ("glencourse"):
meta_data = {
'latitude': float('%.6f' % float(latitude)),
'longitude': float('%.6f' % float(longitude)),
'model': target_model,
'method': method,
'grid_id': 'discharge_{}'.format(station_name)
}
tms_id = TS.get_timeseries_id_if_exists(
meta_data=meta_data)
if tms_id is None:
tms_id = TS.generate_timeseries_id(meta_data=meta_data)
meta_data['id'] = tms_id
TS.insert_run(meta_data=meta_data)
processed_discharge_ts = process_fcst_ts_from_hechms_outputs(
curw_fcst_pool=curw_fcst_pool,
extract_stations=extract_stations,
i=i,
start=start_time,
end=end_time,
sim_tag=sim_tag)
if processed_discharge_ts is not None and len(
processed_discharge_ts) > 0:
TS.insert_data(timeseries=processed_discharge_ts,
tms_id=tms_id,
upsert=True)
else:
continue # skip the current iteration
except Exception as e:
traceback.print_exc()
def update_discharge_obs(curw_sim_pool, flo2d_model, method, timestep,
start_time, end_time):
try:
discharge_TS = DTimeseries(pool=curw_sim_pool)
waterlevel_TS = WLTimeseries(pool=curw_sim_pool)
# [station_name,latitude,longitude,target]
extract_stations = read_csv(
'grids/discharge_stations/flo2d_stations.csv')
extract_stations_dict = {
} # keys: target_model , value: [latitude, longitude, station_name]
# keys: station_name , value: [latitude, longitude, target_model]
for obs_index in range(len(extract_stations)):
extract_stations_dict[extract_stations[obs_index][3]] = [
extract_stations[obs_index][1], extract_stations[obs_index][2],
extract_stations[obs_index][0]
]
station_name = extract_stations_dict.get(flo2d_model)[2]
meta_data = {
'latitude':
float('%.6f' % float(extract_stations_dict.get(flo2d_model)[0])),
'longitude':
float('%.6f' % float(extract_stations_dict.get(flo2d_model)[1])),
'model':
flo2d_model,
'method':
method,
'grid_id':
'discharge_{}'.format(station_name)
}
wl_meta_data = {
'latitude':
float('%.6f' % float(extract_stations_dict.get(flo2d_model)[0])),
'longitude':
float('%.6f' % float(extract_stations_dict.get(flo2d_model)[1])),
'model':
flo2d_model,
'method':
method,
'grid_id':
'waterlevel_{}'.format(station_name)
}
tms_id = discharge_TS.get_timeseries_id_if_exists(meta_data=meta_data)
wl_tms_id = waterlevel_TS.get_timeseries_id_if_exists(
meta_data=wl_meta_data)
if wl_tms_id is None:
print("Warning!!! {} waterlevel timeseries doesn't exist.".format(
station_name))
exit(1)
timeseries = []
if tms_id is None:
tms_id = discharge_TS.generate_timeseries_id(meta_data=meta_data)
meta_data['id'] = tms_id
discharge_TS.insert_run(meta_data=meta_data)
wl_timeseries = waterlevel_TS.get_timeseries(id_=wl_tms_id,
start_date=start_time,
end_date=end_time)
estimated_discharge_ts = []
if station_name == 'hanwella':
estimated_discharge_ts = calculate_hanwella_discharge(
wl_timeseries)
elif station_name == 'glencourse':
estimated_discharge_ts = calculate_glencourse_discharge(
wl_timeseries)
if estimated_discharge_ts is not None and len(
estimated_discharge_ts) > 0:
discharge_TS.insert_data(timeseries=estimated_discharge_ts,
tms_id=tms_id,
upsert=True)
except Exception as e:
traceback.print_exc()
target_model = extract_stations[i][3]
method = extract_stations[i][4]
meta_data = {
'latitude': float('%.6f' % float(latitude)),
'longitude': float('%.6f' % float(longitude)),
'model': target_model, 'method': method,
'grid_id': 'discharge_{}'.format(station_name)
}
tms_id = TS.get_timeseries_id_if_exists(meta_data=meta_data)
if tms_id is None:
tms_id = TS.generate_timeseries_id(meta_data=meta_data)
meta_data['id'] = tms_id
TS.insert_run(meta_data=meta_data)
existing_ts_end = TS.get_obs_end(id_=tms_id)
processed_discharge_ts = []
if existing_ts_end is None:
fcst_start = datetime.now() - timedelta(days=10)
else:
fcst_start = existing_ts_end + timedelta(hours=1)
if method in ('SF'): # process fcst ts from statistical forecasts
try:
timeseries = read_csv('{}/{}.csv'.format(INPUT_DIR, station_name))
processed_discharge_ts = process_fcsts_from_csv(timeseries=timeseries, fcst_start=fcst_start)
except FileNotFoundError as fe:
if wl_tms_id is None:
print("Warning!!! {} waterlevel timeseries doesn't exist.".
format(station_name))
continue
end_time = (datetime.now() + timedelta(
hours=5, minutes=30)).strftime(COMMON_DATE_TIME_FORMAT)
timeseries = []
if tms_id is None:
tms_id = discharge_TS.generate_timeseries_id(
meta_data=meta_data)
meta_data['id'] = tms_id
discharge_TS.insert_run(meta_data=meta_data)
start = (datetime.now() -
timedelta(days=10)).strftime(COMMON_DATE_TIME_FORMAT)
else:
obs_end = discharge_TS.get_obs_end(id_=tms_id)
if obs_end is None:
start = (
datetime.now() -
timedelta(days=10)).strftime(COMMON_DATE_TIME_FORMAT)
else:
start = (
obs_end -
timedelta(days=1)).strftime(COMMON_DATE_TIME_FORMAT)
wl_timeseries = waterlevel_TS.get_timeseries(id_=wl_tms_id,
start_date=start,