def save_forecast_timeseries(my_adapter, timeseries, my_model_date,
my_model_time, my_opts):
print('CSVTODAT:: save_forecast_timeseries:: len', len(timeseries),
my_model_date, my_model_time)
forecast_timeseries = extractForecastTimeseries(timeseries,
my_model_date,
my_model_time,
by_day=True)
# print(forecastTimeseries[:10])
extracted_timeseries = extractForecastTimeseriesInDays(forecast_timeseries)
print('Extracted forecast types # :', len(extracted_timeseries))
# for ll in extractedTimeseries :
# print(ll)
force_insert = my_opts.get('forceInsert', False)
my_model_date_time = datetime.datetime.strptime(
'%s %s' % (my_model_date, my_model_time), '%Y-%m-%d %H:%M:%S')
# TODO: Check whether station exist in Database
run_name = my_opts.get('runName', 'Cloud-1')
less_char_index = run_name.find('<')
greater_char_index = run_name.find('>')
# if less_char_index > -1 and greater_char_index > -1 and less_char_index < greater_char_index :
if -1 < less_char_index < greater_char_index > -1:
start_str = run_name[:less_char_index]
date_format_str = run_name[less_char_index + 1:greater_char_index]
end_str = run_name[greater_char_index + 1:]
try:
date_str = my_model_date_time.strftime(date_format_str)
run_name = start_str + date_str + end_str
except ValueError:
raise ValueError("Incorrect data format " + date_format_str)
types = [
'Forecast-0-d', 'Forecast-1-d-after', 'Forecast-2-d-after',
'Forecast-3-d-after', 'Forecast-4-d-after', 'Forecast-5-d-after',
'Forecast-6-d-after', 'Forecast-7-d-after', 'Forecast-8-d-after',
'Forecast-9-d-after'
]
meta_data = {
'station': 'Hanwella',
'variable': 'Discharge',
'unit': 'm3/s',
'type': types[0],
'source': 'HEC-HMS',
'name': run_name,
}
for index in range(0, min(len(types), len(extracted_timeseries))):
meta_data_copy = copy.deepcopy(meta_data)
meta_data_copy['type'] = types[index]
event_id = my_adapter.get_event_id(meta_data_copy)
if event_id is None:
event_id = my_adapter.create_event_id(meta_data_copy)
print('HASH SHA256 created: ', event_id)
else:
print('HASH SHA256 exists: ', event_id)
if not force_insert:
print(
'Timeseries already exists. User --force to update the existing.\n'
)
continue
# for l in timeseries[:3] + timeseries[-2:] :
# print(l)
row_count = my_adapter.insert_timeseries(event_id,
extracted_timeseries[index],
force_insert)
print('%s rows inserted.\n' % row_count)
def save_forecast_timeseries(my_adapter, my_timeseries, my_model_date, my_model_time, my_opts):
print('EXTRACTFLO2DWATERLEVEL:: save_forecast_timeseries >>', my_opts)
# Convert date time with offset
date_time = datetime.strptime('%s %s' % (my_model_date, my_model_time), Constants.COMMON_DATE_TIME_FORMAT)
if 'utcOffset' in my_opts:
date_time = date_time + my_opts['utcOffset']
my_model_date = date_time.strftime('%Y-%m-%d')
my_model_time = date_time.strftime('%H:%M:%S')
# If there is an offset, shift by offset before proceed
forecast_timeseries = []
if 'utcOffset' in my_opts:
print('Shit by utcOffset:', my_opts['utcOffset'].resolution)
for item in my_timeseries:
forecast_timeseries.append(
[datetime.strptime(item[0], Constants.COMMON_DATE_TIME_FORMAT) + my_opts['utcOffset'], item[1]])
forecast_timeseries = extractForecastTimeseries(forecast_timeseries, my_model_date, my_model_time, by_day=True)
else:
forecast_timeseries = extractForecastTimeseries(my_timeseries, my_model_date, my_model_time, by_day=True)
# print(forecast_timeseries[:10])
extracted_timeseries = extractForecastTimeseriesInDays(forecast_timeseries)
# for ll in extractedTimeseries :
# print(ll)
# Check whether existing station
force_insert = my_opts.get('forceInsert', False)
station = my_opts.get('station', '')
is_station_exists = adapter.get_station({'name': station})
if is_station_exists is None:
print('WARNING: Station %s does not exists. Continue with others.' % station)
return
# TODO: Create if station does not exists.
run_name = my_opts.get('run_name', 'Cloud-1')
less_char_index = run_name.find('<')
greater_char_index = run_name.find('>')
if -1 < less_char_index > -1 < greater_char_index:
start_str = run_name[:less_char_index]
date_format_str = run_name[less_char_index + 1:greater_char_index]
end_str = run_name[greater_char_index + 1:]
try:
date_str = date_time.strftime(date_format_str)
run_name = start_str + date_str + end_str
except ValueError:
raise ValueError("Incorrect data format " + date_format_str)
types = [
'Forecast-0-d',
'Forecast-1-d-after',
'Forecast-2-d-after',
'Forecast-3-d-after',
'Forecast-4-d-after',
'Forecast-5-d-after',
'Forecast-6-d-after',
'Forecast-7-d-after',
'Forecast-8-d-after',
'Forecast-9-d-after',
'Forecast-10-d-after',
'Forecast-11-d-after',
'Forecast-12-d-after',
'Forecast-13-d-after',
'Forecast-14-d-after'
]
meta_data = {
'station': station,
'variable': 'WaterLevel',
'unit': 'm',
'type': types[0],
'source': 'FLO2D',
'name': run_name
}
for i in range(0, min(len(types), len(extracted_timeseries))):
meta_data_copy = copy.deepcopy(meta_data)
meta_data_copy['type'] = types[i]
event_id = my_adapter.get_event_id(meta_data_copy)
if event_id is None:
event_id = my_adapter.create_event_id(meta_data_copy)
print('HASH SHA256 created: ', event_id)
else:
print('HASH SHA256 exists: ', event_id)
if not force_insert:
print('Timeseries already exists. User --force to update the existing.\n')
continue
# for l in timeseries[:3] + timeseries[-2:] :
# print(l)
row_count = my_adapter.insert_timeseries(event_id, extracted_timeseries[i], force_insert)
print('%s rows inserted.\n' % row_count)