)
add_argparse_arguments(argparser)
args = argparser.parse_args()
import numpyro
numpyro.set_host_device_count(args.num_chains)
if __name__ == "__main__":
print(f"Running Sensitivity Analysis {__file__} with config:")
config = load_model_config(args.model_config)
pprint_mb_dict(config)
print("Loading Data")
data = preprocess_data(get_data_path())
data.featurize(**config["featurize_kwargs"])
data.mask_new_variant(new_variant_fraction_fname=get_new_variant_path(), )
data.mask_from_date("2021-01-09")
print("Loading EpiParam")
ep = EpidemiologicalParameters()
# shift delays
ep.generation_interval["mean"] = (ep.generation_interval["mean"] +
args.gen_int_mean_shift)
ep.onset_to_death_delay["mean"] = (ep.onset_to_death_delay["mean"] +
args.death_delay_mean_shift)
ep.onset_to_case_delay["mean"] = (ep.onset_to_case_delay["mean"] +
args = argparser.parse_args()
import numpyro
numpyro.set_host_device_count(args.num_chains)
if __name__ == "__main__":
print(f"Running Sensitivity Analysis {__file__} with config:")
config = load_model_config(args.model_config)
pprint_mb_dict(config)
start_date = args.window_of_analysis[0]
end_date = args.window_of_analysis[1]
print("Loading Data")
data = preprocess_data(get_data_path(), start_date=start_date)
data.featurize(**config["featurize_kwargs"])
data.mask_new_variant(new_variant_fraction_fname=get_new_variant_path(), )
try:
data.mask_from_date(end_date)
except ValueError:
pass
print("Loading EpiParam")
ep = EpidemiologicalParameters()
model_func = get_model_func_from_str(args.model_type)
ta = get_target_accept_from_model_str(args.model_type)
td = get_tree_depth_from_model_str(args.model_type)
