parser = argparse.ArgumentParser(description='Run Bayesian compartmental models.') parser.add_argument('place', help='place to use (e.g., US state)') parser.add_argument('--start', help='start date', default='2020-03-04') parser.add_argument('--end', help='end date', default=None) parser.add_argument('--prefix', help='path prefix for saving results', default='results') parser.add_argument('--config', help='model configuration name', default='SEIRD') args = parser.parse_args() if args.config not in dir(configs): print(f'Invalid config: {args.config}. Options are {dir(configs)}') exit() config = getattr(configs, args.config) data = util.load_data() util.run_place(data, args.place, start=args.start, end=args.end, prefix=args.prefix, model_type=config['model'], **config['args']) util.gen_forecasts(data, args.place, start=args.start, prefix=args.prefix, show=False)
dest='run', action='store_false') parser.add_argument('--config', help='model configuration name', default='SEIRD') parser.set_defaults(run=True) args = parser.parse_args() if args.config not in dir(configs): print(f'Invalid config: {args.config}. Options are {dir(configs)}') exit() config = getattr(configs, args.config) data = config.get('data') or util.load_data() # My best reconstruction of MO backlogs reports ~Sep 5-6. Information # here (https://twitter.com/HealthyLivingMo) but exact numbers don't # match JHU data, so I redistributed as best I could util.redistribute(data['MO']['data'], '2020-09-04', 16, 60) util.redistribute(data['MO']['data'], '2020-09-05', 56, 60) util.redistribute(data['MO']['data'], '2020-09-06', 15, 60) # MA changed definition of confirmed case util.redistribute(data['MA']['data'], '2020-09-03', -7936, 90, col='confirmed')