def update_tide_obs(curw_sim_pool, obs_connection, method, timestep, start_time, end_time, flo2d_model="flo2d"):
# [station_name,latitude,longitude,target]
extract_stations = read_csv('grids/tide_stations/extract_stations.csv')
extract_stations_dict = {} # keys: station_name , value: [latitude, longitude, target_model]
for obs_index in range(len(extract_stations)):
extract_stations_dict[extract_stations[obs_index][0]] = [extract_stations[obs_index][1],
extract_stations[obs_index][2],
extract_stations[obs_index][3]]
for station_name in extract_stations_dict.keys():
meta_data = {
'latitude': float('%.6f' % float(extract_stations_dict.get(station_name)[0])),
'longitude': float('%.6f' % float(extract_stations_dict.get(station_name)[1])),
'model': flo2d_model, 'method': method,
'grid_id': 'tide_{}'.format(station_name)
}
TS = Timeseries(pool=curw_sim_pool)
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_tide_ts = prepare_obs_tide_ts(connection=obs_connection, start_date=start_time, end_date=end_time,
extract_station=station_name)
for i in range(len(processed_tide_ts)):
if len(processed_tide_ts[i]) < 2:
processed_tide_ts.remove(processed_tide_ts[i])
final_tide_ts = fill_ts_missing_entries(start=start_time, end=end_time, timeseries=processed_tide_ts,
interpolation_method='linear', timestep=timestep)
if final_tide_ts is not None and len(final_tide_ts) > 0:
TS.insert_data(timeseries=final_tide_ts, tms_id=tms_id, upsert=True)
obs_end -
timedelta(days=1)).strftime('%Y-%m-%d %H:00:00')
processed_tide_ts = prepare_obs_tide_ts(
connection=connection,
start_date=start_date,
end_date=end_date,
extract_station=station_name)
for i in range(len(processed_tide_ts)):
if len(processed_tide_ts[i]) < 2:
processed_tide_ts.remove(processed_tide_ts[i])
final_tide_ts = fill_ts_missing_entries(
start=start_date,
end=end_date,
timeseries=processed_tide_ts,
interpolation_method='linear',
timestep=60)
if final_tide_ts is not None and len(final_tide_ts) > 0:
TS.insert_data(timeseries=final_tide_ts,
tms_id=tms_id,
upsert=True)
TS.update_latest_obs(id_=tms_id,
obs_end=final_tide_ts[-1][1])
except Exception as e:
traceback.print_exc()
logger.error("Exception occurred.")
finally:
connection.close()
def update_waterlevel_obs(obs_connection, curw_sim_pool, flo2d_model, method,
timestep, start_time, end_time):
try:
# [station_name,latitude,longitude,target]
extract_stations = read_csv(
'grids/waterlevel_stations/extract_stations.csv')
extract_stations_dict = {
} # keys: target_model , value: [latitude, longitude, station_name]
# older version ::: 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':
'waterlevel_{}'.format(station_name)
}
TS = Timeseries(pool=curw_sim_pool)
tms_id = TS.get_timeseries_id_if_exists(meta_data=meta_data)
ranwala_ts = []
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)
with obs_connection.cursor() as cursor1:
cursor1.callproc('getWL', (RANWALA_WL_ID, start_time, end_time))
results = cursor1.fetchall()
for result in results:
ranwala_ts.append([result.get('time'), result.get('value')])
interpolated_ranwala_ts = fill_ts_missing_entries(
start=start_time,
end=end_time,
timeseries=ranwala_ts,
interpolation_method='linear',
timestep=60)
estimated_wl_ts = []
if station_name == 'hanwella':
estimated_wl_ts = calculate_hanwella_wl_from_ranwala(
interpolated_ranwala_ts)
elif station_name == 'glencourse':
estimated_wl_ts = calculate_glencourse_wl_from_ranwala(
interpolated_ranwala_ts)
if estimated_wl_ts is not None and len(estimated_wl_ts) > 0:
TS.insert_data(timeseries=estimated_wl_ts,
tms_id=tms_id,
upsert=True)
except Exception as e:
traceback.print_exc()
obs_end = TS.get_obs_end(id_=tms_id)
start_date = (obs_end -
timedelta(days=1)).strftime("%Y-%m-%d %H:00:00")
with connection.cursor() as cursor1:
cursor1.callproc('getWL',
(RANWALA_WL_ID, start_date, end_date))
results = cursor1.fetchall()
for result in results:
ranwala_ts.append(
[result.get('time'),
result.get('value')])
interpolated_ranwala_ts = fill_ts_missing_entries(
start=start_date,
end=end_date,
timeseries=ranwala_ts,
interpolation_method='linear',
timestep=60)
estimated_wl_ts = []
if station_name == 'hanwella':
estimated_wl_ts = calculate_hanwella_wl_from_ranwala(
interpolated_ranwala_ts)
elif station_name == 'glencourse':
estimated_wl_ts = calculate_glencourse_wl_from_ranwala(
interpolated_ranwala_ts)
if estimated_wl_ts is not None and len(estimated_wl_ts) > 0:
TS.insert_data(timeseries=estimated_wl_ts,
tms_id=tms_id,