def save_worker(target_id, description, input_dir):
print("saving {}...".format(description))
years = list(range(1980, int(utils.get_gbd_parameter("max_year")) + 1))
save_results_cod(input_dir=input_dir,
input_file_pattern='death_{location_id}.csv',
cause_id=target_id,
description=description,
sex_id=[1, 2],
metric_id=1,
year_id=years,
mark_best=True)
print("model saved.")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-c",
"--cause_id",
type=int,
help="The cause ID of that these draws will save")
parser.add_argument("-p",
"--run_id",
type=str,
help="The run id of the draws/prioritization")
cmd_args = parser.parse_args()
cause_id = cmd_args.cause_id
run_id = cmd_args.run_id
print("**UPLOADING {} TO COD DB**".format(cause_id))
input_dir = "FILEPATH"
save_results_cod(input_dir=input_dir.format(cause_id),
input_file_pattern="{location_id}.csv",
year_id=list(range(1980, 2020)),
cause_id=cause_id,
description="final shock models",
metric_id=1,
model_version_type_id=5,
mark_best=True,
decomp_step='step4',
gbd_round_id=6)
print("**COD DB UPLOAD WAS APPARENTLY SUCCESSFUL**")
logging.info("{} Generate square data".format(pretty_now()))
# Maybe not for opioids
square_data = make_square_data(cause_id, age_groups, gbd_round_id)
logging.info("{} Combine imported cases and square data".format(
pretty_now()))
data = pd.concat([data, square_data]).reset_index(drop=True)
data = data.groupby([
'location_id', 'year_id', 'sex_id', 'age_group_id', 'cause_id'
]).sum().reset_index()
logging.info("{} Saving Data".format(pretty_now()))
data.to_csv(os.path.join(outdir, 'to_upload.csv'), index=False)
save_results_cod(outdir,
'to_upload.csv',
cause_id,
"New imported cases",
decomp_step=decomp_step,
gbd_round_id=gbd_round_id,
model_version_type_id=7,
mark_best=True,
db_env='prod')
logging.info("{} All Done".format(pretty_now()))
except Exception:
logging.exception(
"{} Uncaught exception in generate_imported_cases".format(
pretty_now()))
sys.exit(1)
pool.join()
data = pd.concat(distributions)
logging.info("{} Generate square data".format(pretty_now()))
square_data = make_square_data(cause_id, age_groups, gbd_round_id)
logging.info("{} Combine imported cases and square data".format(
pretty_now()))
data = pd.concat([data, square_data]).reset_index(drop=True)
data = data.groupby([
'location_id', 'year_id', 'sex_id', 'age_group_id', 'cause_id'
]).sum().reset_index()
logging.info("{} Saving Data".format(pretty_now()))
data.to_csv(os.path.join(outdir, 'to_upload.csv'), index=False)
save_results_cod(outdir,
'to_upload.csv',
cause_id,
"New imported cases",
model_version_type_id=7,
mark_best=True,
db_env='prod')
logging.info("{} All Done".format(pretty_now()))
except Exception:
logging.exception(
"{} Uncaught exception in generate_imported_cases".format(
pretty_now()))
sys.exit(1)
model_id = int(model_id)
start_year = int(start_year)
end_year = int(end_year)
logger.info("Saving results for maternal {type}".format(type=model_type))
########################################################################
# Save results
########################################################################
if model_type == "cod":
print("Saving results for COD")
save_results_cod(input_dir=directory,
input_file_pattern=file_pattern,
cause_id=model_id,
description=description,
sex_id=2,
year_id=range(start_year, end_year + 1),
mark_best=True)
elif model_type == "epi":
print("Saving results for EPI")
save_results_epi(input_dir=directory,
input_file_pattern=file_pattern,
modelable_entity_id=model_id,
description=description,
sex_id=2,
year_id=range(start_year, end_year + 1),
measure_id=18,
mark_best=True)
elif model_type == "sdg":
print("Saving results for SDG")
end_year = int(end_year)
decomp_step_id = int(decomp_step_id)
logger.info("Saving results for maternal {type}".format(type=model_type))
########################################################################
# Save results
########################################################################
if model_type == "cod":
print("Saving results for COD")
save_results_cod(
input_dir=directory,
input_file_pattern=file_pattern,
cause_id=model_id,
description=description,
sex_id=2,
year_id=list(range(start_year, end_year + 1)),
mark_best=True,
gbd_round_id=maternal_fns.GBD_ROUND_ID,
decomp_step=decomp.decomp_step_from_decomp_step_id(decomp_step_id))
elif model_type == "epi":
print("Saving results for EPI")
save_results_epi(
input_dir=directory,
input_file_pattern=file_pattern,
modelable_entity_id=model_id,
description=description,
sex_id=2,
year_id=list(range(start_year, end_year + 1)),
measure_id=18,
mark_best=True,