DEATH_CLIMATOLOGY_TYPE = 'death'
PASSAGE_CLIMATOLOGY_TYPE = 'passage'
if __name__ == '__main__':
spc_date_strings = time_conversion.get_spc_dates_in_range(
first_spc_date_string=FIRST_SPC_DATE_STRING,
last_spc_date_string=LAST_SPC_DATE_STRING)
num_spc_dates = len(spc_date_strings)
storm_object_table_by_spc_date = [None] * num_spc_dates
num_storm_objects_by_hour = numpy.full(NUM_HOURS_PER_DAY, 0, dtype=int)
speeds = []
for working_date_index in range(num_spc_dates):
date_in_memory_indices = utils._get_dates_needed(
working_date_index=working_date_index,
num_dates=num_spc_dates,
climatology_type=PASSAGE_CLIMATOLOGY_TYPE)
for i in range(num_spc_dates):
if i in date_in_memory_indices:
if storm_object_table_by_spc_date[i] is None:
# Find tracking files for [i]th date.
these_tracking_file_names = (
tracking_io.find_processed_files_one_spc_date(
spc_date_string=spc_date_strings[i],
data_source='segmotion',
top_processed_dir_name=TOP_PROCESSED_DIR_NAME,
tracking_scale_metres2=TRACKING_SCALE_METRES2))
# Read tracking files for [i]th date.
date_needed_indices.append(working_date_index)
return numpy.array(date_needed_indices, dtype=int)
if __name__ == '__main__':
spc_date_strings = time_conversion.get_spc_dates_in_range(
first_spc_date_string=FIRST_SPC_DATE_STRING,
last_spc_date_string=LAST_SPC_DATE_STRING)
num_spc_dates = len(spc_date_strings)
storm_object_table_by_spc_date = [None] * num_spc_dates
storm_ages = []
for working_date_index in range(num_spc_dates):
date_in_memory_indices = utils._get_dates_needed(
working_date_index=working_date_index, num_dates=num_spc_dates)
for i in range(num_spc_dates):
if i in date_in_memory_indices:
if storm_object_table_by_spc_date[i] is None:
these_tracking_file_names = (
tracking_io.find_processed_files_one_spc_date(
spc_date_string=spc_date_strings[i],
data_source='segmotion',
top_processed_dir_name=TOP_PROCESSED_DIR_NAME,
tracking_scale_metres2=TRACKING_SCALE_METRES2))
storm_object_table_by_spc_date[i] = (
tracking_io.read_many_processed_files(
these_tracking_file_names))