) 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)