def write_hospital_data_to_targets(country,
data_start_time=0,
data_end_time=365,
weekly_average=True):
region = country if country != "united-kingdom" else "united_kingdom"
target_path = os.path.join("../apps", "covid_19", "regions", region,
"targets.json")
times, values = read_hospital_data(country, data_start_time, data_end_time)
if weekly_average:
times, values = get_weekly_summed_targets(times, values)
if country in list(start_reporting.keys()):
min_time = start_reporting[country]
first_idx_to_keep = next(x[0] for x in enumerate(times)
if x[1] >= min_time)
times = times[first_idx_to_keep:]
values = values[first_idx_to_keep:]
with open(target_path, mode="r") as f:
targets = json.load(f)
targets[country_targets[country][1]]["times"] = times
targets[country_targets[country][1]]["values"] = values
with open(target_path, "w") as f:
json.dump(targets, f, indent=2)
def drop_who_data_to_targets(
country="australia", data_start_time=0, data_end_time=365, weekly_average=True
):
data = {}
output_name = {"confirmed": "notifications", "deaths": "infection_deaths"}
for variable in ["confirmed", "deaths"]:
times, values = read_who_data_from_csv(variable, country, data_start_time, data_end_time)
if weekly_average:
times, values = get_weekly_summed_targets(times, values)
data[variable] = {"times": times, "values": values}
region = country if country != "united-kingdom" else "united_kingdom"
target_path = os.path.join("../apps", "covid_19", "regions", region, "targets.json")
with open(target_path, mode="r") as f:
targets = json.load(f)
for variable in ["confirmed", "deaths"]:
targets[output_name[variable]]["times"] = data[variable]["times"]
targets[output_name[variable]]["values"] = data[variable]["values"]
with open(target_path, "w") as f:
json.dump(targets, f, indent=2)
country = Region.ITALY
PAR_PRIORS = get_prior_distributions_for_opti()
for i, par in enumerate(PAR_PRIORS):
if par["param_name"] == "contact_rate":
PAR_PRIORS[i]["distri_params"] = [0.025, 0.06]
TARGET_OUTPUTS = get_target_outputs_for_opti(country,
source='who',
data_start_time=61,
data_end_time=182)
# Use weekly counts
for target in TARGET_OUTPUTS:
target["years"], target["values"] = get_weekly_summed_targets(
target["years"], target["values"])
MULTIPLIERS = {}
PAR_PRIORS = add_dispersion_param_prior_for_gaussian(PAR_PRIORS,
TARGET_OUTPUTS,
MULTIPLIERS)
def run_calibration_chain(max_seconds: int, run_id: int, num_chains: int):
base.run_calibration_chain(
max_seconds,
run_id,
num_chains,
country,
PAR_PRIORS,