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')
