def test_functional_seniors_residence():
""" Run a simulation of 1 infection in a seniors residence, and perform some sanity checks """
with tempfile.TemporaryDirectory() as output_dir:
rng = np.random.RandomState(42)
# Config
start_time = datetime.datetime(2020, 2, 28, 0, 0)
simulation_days = 100
city_x_range = (0, 1000)
city_y_range = (0, 1000)
# Find the test_configs directory, and load the required config yaml
conf = get_test_conf("naive_local.yaml")
conf['simulation_days'] = simulation_days
conf['COVID_SPREAD_START_TIME'] = start_time
conf['INTERVENTION_START_TIME'] = start_time
conf['_MEAN_DAILY_UNKNOWN_CONTACTS'] = 0.5
env = Env(start_time)
city = EmptyCity(env, rng, city_x_range, city_y_range, conf)
sr = Household(
env=env,
rng=np.random.RandomState(rng.randint(2 ** 16)),
conf=conf,
name=f"SENIOR_RESIDENCE:0",
location_type="SENIOR_RESIDENCE",
lat=rng.randint(*city_x_range),
lon=rng.randint(*city_y_range),
area=1000,
capacity=None,
)
city.senior_residences.append(sr)
N = 10
# Create humans
ages = city.rng.randint(*(65, 100), size=N)
infection = [None] * N
# One initial infection
infection[0] = city.start_time
city.n_init_infected = 1
humans = [
Human(
env=city.env,
city=city,
name=i,
age=ages[i],
rng=rng,
conf=conf,
)
for i in range(N)
]
for human in humans:
human.assign_household(sr)
sr.residents.append(human)
human.mobility_planner.initialize()
# pick some humans and make sure they cannot recover (for later checks)
for i in range(N):
humans[i].never_recovers = True
# Infect one of the humans
humans[np.random.randint(N)]._get_infected(1)
city.humans = humans
city.hd = {h.name: h for h in humans}
city.initWorld()
outfile = os.path.join(output_dir, "test1")
env.process(city.run(SECONDS_PER_HOUR, outfile))
for human in city.humans:
env.process(human.run())
with unittest.mock.patch.object(
City, "run_app",
new=fake_run_app) as mock:
env.run(until=env.ts_initial+simulation_days*SECONDS_PER_DAY)
# Check dead humans are removed from the residence
assert sum([h.is_dead for h in city.humans]) == N - len(sr.residents)
# Check there are some dead
assert sum([h.is_dead for h in city.humans]) > 0
# Check there are no humans that are infectious
assert not any([h.is_infectious for h in city.humans])
def simulate(
n_people: int = 1000,
init_fraction_sick: float = 0.01,
start_time: datetime.datetime = datetime.datetime(2020, 2, 28, 0, 0),
simulation_days: int = 30,
outfile: typing.Optional[typing.AnyStr] = None,
out_chunk_size: typing.Optional[int] = None,
seed: int = 0,
conf: typing.Optional[typing.Dict] = None,
logfile: str = None,
):
"""
Runs a simulation.
Args:
n_people (int, optional): population size in simulation. Defaults to 1000.
init_fraction_sick (float, optional): population fraction initialized with Covid-19. Defaults to 0.01.
start_time (datetime, optional): Initial calendar date. Defaults to February 28, 2020.
simulation_days (int, optional): Number of days to run the simulation. Defaults to 10.
outfile (str, optional): Location to write logs. Defaults to None.
out_chunk_size (int, optional): size of chunks to write in logs. Defaults to None.
seed (int, optional): [description]. Defaults to 0.
conf (dict): yaml configuration of the experiment.
logfile (str): filepath where the console output and final tracked metrics will be logged. Prints to the console only if None.
Returns:
city (covid19sim.locations.city.City): The city object referencing people, locations, and the tracker post-simulation.
"""
if conf is None:
conf = {}
conf["n_people"] = n_people
conf["init_fraction_sick"] = init_fraction_sick
conf["start_time"] = start_time
conf["simulation_days"] = simulation_days
conf["outfile"] = outfile
conf["out_chunk_size"] = out_chunk_size
conf["seed"] = seed
conf['logfile'] = logfile
# set days and mixing constants
conf['_MEAN_DAILY_UNKNOWN_CONTACTS'] = conf['MEAN_DAILY_UNKNOWN_CONTACTS']
conf['_ENVIRONMENTAL_INFECTION_KNOB'] = conf['ENVIRONMENTAL_INFECTION_KNOB']
conf['_CURRENT_PREFERENTIAL_ATTACHMENT_FACTOR'] = conf['BEGIN_PREFERENTIAL_ATTACHMENT_FACTOR']
start_time_offset_days = conf['COVID_START_DAY']
intervention_start_days = conf['INTERVENTION_DAY']
# start of COVID spread
conf['COVID_SPREAD_START_TIME'] = start_time
# start of intervention
conf['INTERVENTION_START_TIME'] = None
if intervention_start_days >= 0:
conf['INTERVENTION_START_TIME'] = start_time + datetime.timedelta(days=intervention_start_days)
# start of simulation without COVID
start_time -= datetime.timedelta(days=start_time_offset_days)
conf['SIMULATION_START_TIME'] = str(start_time)
# adjust the simulation days
conf['simulation_days'] += conf['COVID_START_DAY']
simulation_days = conf['simulation_days']
console_logger = ConsoleLogger(frequency=SECONDS_PER_DAY, logfile=logfile, conf=conf)
logging.root.setLevel(getattr(logging, conf["LOGGING_LEVEL"].upper()))
rng = np.random.RandomState(seed)
env = Env(start_time)
city_x_range = (0, 1000)
city_y_range = (0, 1000)
city = City(
env, n_people, init_fraction_sick, rng, city_x_range, city_y_range, conf, logfile
)
# we might need to reset the state of the clusters held in shared memory (server or not)
if conf.get("RESET_INFERENCE_SERVER", False):
if conf.get("USE_INFERENCE_SERVER"):
inference_frontend_address = conf.get("INFERENCE_SERVER_ADDRESS", None)
print("requesting cluster reset from inference server...")
from covid19sim.inference.server_utils import InferenceClient
temporary_client = InferenceClient(
server_address=inference_frontend_address
)
temporary_client.request_reset()
else:
from covid19sim.inference.heavy_jobs import DummyMemManager
DummyMemManager.global_cluster_map = {}
# Initiate city process, which runs every hour
env.process(city.run(SECONDS_PER_HOUR, outfile))
# initiate humans
for human in city.humans:
env.process(human.run())
env.process(console_logger.run(env, city=city))
# Run simulation until termination
env.run(until=env.ts_initial + simulation_days * SECONDS_PER_DAY)
return city