def test__infection_is_isolated(selector):
geography = Geography.from_file({"area": ["E00002559"]})
world = generate_world_from_geography(geography, include_households=True)
interaction = Interaction.from_file()
infection_seed = InfectionSeed(world.super_areas, selector)
n_cases = 5
infection_seed.unleash_virus(
n_cases) # play around with the initial number of cases
policies = Policies([])
simulator = Simulator.from_file(
world=world,
interaction=interaction,
infection_selector=selector,
config_filename=pathlib.Path(__file__).parent.absolute() /
"interaction_test_config.yaml",
leisure=None,
policies=policies,
save_path=None,
)
infected_people = [person for person in world.people if person.infected]
assert len(infected_people) == 5
infected_households = []
for household in world.households:
infected = False
for person in household.people:
if person.infected:
infected = True
break
if infected:
infected_households.append(household)
assert len(infected_households) <= 5
simulator.run()
for person in world.people:
if not (person.residence.group in infected_households):
assert not person.infected and person.susceptible
def test__school_contact_matrices():
interaction_instance = Interaction.from_file()
xi = 0.3
age_min = 3
age_max = 7
school_years = tuple(range(age_min, age_max + 1))
contact_matrix = interaction_instance.contact_matrices["school"]
n_contacts_same_year = interaction._get_contacts_in_school(
contact_matrix, school_years, 4, 4)
assert n_contacts_same_year == 2.875 * 3
n_contacts_year_above = interaction._get_contacts_in_school(
contact_matrix, school_years, 4, 5)
assert n_contacts_year_above == xi * 2.875 * 3
n_contacts_teacher_teacher = interaction._get_contacts_in_school(
contact_matrix, school_years, 0, 0)
assert n_contacts_teacher_teacher == 5.25 * 3
n_contacts_teacher_student = interaction._get_contacts_in_school(
contact_matrix, school_years, 0, 4)
np.isclose(n_contacts_teacher_student, (16.2 * 3 / len(school_years)),
rtol=1e-6)
n_contacts_student_teacher = interaction._get_contacts_in_school(
contact_matrix, school_years, 4, 0)
assert n_contacts_student_teacher == 0.81 * 3
def test__full_run(dummy_world, selector):
world = dummy_world
# restore health status of people
for person in world.people:
person.health_information = None
person.susceptibility = 1.0
person.dead = False
leisure_instance = leisure.generate_leisure_for_world(
world=world,
list_of_leisure_groups=[
"pubs",
"cinemas",
"groceries",
"household_visits",
"care_home_visits",
],
)
leisure_instance.distribute_social_venues_to_households(world.households)
interaction = Interaction.from_file()
policies = Policies.from_file()
sim = Simulator.from_file(
world=world,
interaction=interaction,
infection_selector=selector,
config_filename=test_config,
leisure=leisure_instance,
policies=policies,
save_path=None,
)
seed = InfectionSeed(sim.world.super_areas, selector)
seed.unleash_virus(1)
sim.run()
def test__contact_matrices_from_default():
interaction = Interaction.from_file(config_filename=test_config)
np.testing.assert_allclose(
interaction.contact_matrices["pub"],
np.array([[3 * (1 + 0.12) * 24 / 3]]),
rtol=0.05,
)
xi = 0.3
contacts_school = interaction.contact_matrices["school"]
for i in range(len(contacts_school)):
for j in range(len(contacts_school)):
if i == j:
if i == 0:
assert contacts_school[i][j] == 5.25 * 3 # 24 / 8
else:
assert contacts_school[i][j] == 2.875 * 3
else:
if i == 0:
assert np.isclose(contacts_school[i][j],
16.2 * 3,
rtol=1e-6)
elif j == 0:
assert np.isclose(contacts_school[i][j],
0.81 * 3,
atol=0,
rtol=1e-6)
else:
assert np.isclose(
contacts_school[i][j],
xi**abs(i - j) * 2.875 * 3,
atol=0,
rtol=1e-6,
)
def apply(self, date: datetime, interaction: Interaction):
active_policies = self.get_active(date)
beta_reductions = defaultdict(lambda: 1.0)
for policy in active_policies:
beta_reductions_dict = policy.apply()
for group in beta_reductions_dict:
beta_reductions[group] *= beta_reductions_dict[group]
interaction.beta_reductions = beta_reductions
def create_interaction():
interaction = Interaction.from_file()
interaction.beta['school'] = 0.8
interaction.beta['cinema'] = 0.0
interaction.beta['pub'] = 0.0
interaction.beta['household'] = 10.0
interaction.alpha_physical = 2.7
return interaction
def apply(self, date: datetime, interaction: Interaction):
"""
Implement social distancing policy
-----------
Parameters:
betas: e.g. (dict) from DefaultInteraction, e.g. DefaultInteraction.from_file(selector=selector).beta
Assumptions:
- Currently we assume that social distancing is implemented first and this affects all
interactions and intensities globally
- Currently we assume that the changes are not group dependent
TODO:
- Implement structure for people to adhere to social distancing with a certain compliance
- Check per group in config file
"""
if self.end_time == date: # deactivate policy, restore betas.
for key, value in self.original_betas.items():
interaction.beta[key] = value
if self.start_time == date: # activate policy, save current betas.
for key, value in self.beta_factors.items():
self.original_betas[key] = interaction.beta[key]
interaction.beta[key] = interaction.beta[key] * value
def test__checkpoints_are_saved(selector):
june.simulator.logger.disabled = True
sim = run_simulator(selector)
fresh_world = generate_world_from_hdf5("./checkpoint_world.hdf5")
interaction = Interaction.from_file()
policies = Policies([])
sim_recovered = Simulator.from_checkpoint(
world=fresh_world,
checkpoint_path="tests/checkpoint_2020-03-25.pkl",
interaction=interaction,
infection_selector=selector,
config_filename=test_config,
leisure=None,
policies=policies,
save_path="tests",
)
# check timer is correct
assert sim_recovered.timer.initial_date == sim.timer.initial_date
assert sim_recovered.timer.final_date == sim.timer.final_date
assert sim_recovered.timer.now == sim.timer.now
assert sim_recovered.timer.date.date() == datetime.datetime(2020, 3, 26).date()
assert sim_recovered.timer.shift == sim.timer.shift
assert sim_recovered.timer.delta_time == sim.timer.delta_time
for person1, person2 in zip(sim.world.people, sim_recovered.world.people):
assert person1.id == person2.id
if person1.health_information is not None:
assert person2.health_information is not None
h1 = person1.health_information
h2 = person2.health_information
for slot in h1.__slots__:
if slot == "infection":
inf1 = h1.infection
inf2 = h2.infection
assert inf1.start_time == inf1.start_time
assert inf1.last_time_updated == inf1.last_time_updated
assert inf1.infection_probability == inf2.infection_probability
assert inf1.transmission.probability == inf2.transmission.probability
assert inf1.symptoms.tag == inf2.symptoms.tag
assert inf1.symptoms.max_severity == inf2.symptoms.max_severity
continue
p1_attr = getattr(person1.health_information, slot)
p2_attr = getattr(person2.health_information, slot)
assert p1_attr == p2_attr
assert person1.susceptible == person2.susceptible
assert person1.infected == person2.infected
assert person1.recovered == person2.recovered
assert person1.susceptibility == person2.susceptibility
assert person1.dead == person2.dead
def setup_sim(dummy_world, selector):
world = dummy_world
leisure_instance = leisure.generate_leisure_for_world(
world=world, list_of_leisure_groups=["pubs", "cinemas", "groceries"])
leisure_instance.distribute_social_venues_to_households(world.households)
interaction = Interaction.from_file()
policies = Policies.from_file()
sim = Simulator.from_file(
world=world,
infection_selector=selector,
interaction=interaction,
config_filename=test_config,
leisure=leisure_instance,
policies=policies,
)
sim.activity_manager.leisure.generate_leisure_probabilities_for_timestep(
3, False)
return sim
def test__average_time_to_infect(n_teachers, mode):
selector_config = paths.configs_path / "defaults/transmission/TransmissionConstant.yaml"
transmission_probability = 0.1
selector = InfectionSelector.from_file(
transmission_config_path=selector_config)
n_students = 1
contact_matrices = {
"contacts": [[n_teachers - 1, 1], [1, 0]],
"proportion_physical": [[
0,
0,
], [0, 0]],
"xi": 1.0,
"characteristic_time": 24,
}
interaction = Interaction(
beta={
"school": 1,
},
alpha_physical=1,
contact_matrices={"school": contact_matrices},
)
n_days = []
for _ in range(200):
people, school = create_school(n_students, n_teachers)
for student in people[:n_students]:
selector.infect_person_at_time(student, time=0)
for teacher in people[n_students:n_students + n_teachers - 1]:
selector.infect_person_at_time(teacher, time=0)
school.clear()
teacher = people[-1]
n_days.append(
days_to_infection(interaction, teacher, school, people,
n_students))
teacher_teacher = transmission_probability * (n_teachers - 1)
student_teacher = transmission_probability / n_students
np.testing.assert_allclose(
np.mean(n_days),
1.0 / (teacher_teacher + student_teacher),
rtol=0.1,
)
def run_simulator(selector):
world = create_world()
world.to_hdf5("./checkpoint_world.hdf5")
# restore health status of people
for person in world.people:
person.health_information = None
person.susceptibility = 1.0
person.dead = False
interaction = Interaction.from_file()
policies = Policies([])
sim = Simulator.from_file(
world=world,
interaction=interaction,
infection_selector=selector,
config_filename=test_config,
leisure=None,
policies=policies,
save_path="tests",
)
seed = InfectionSeed(sim.world.super_areas, selector)
seed.unleash_virus(20)
sim.run()
return sim
def make_interaction(self):
interaction = Interaction.from_file(
config_filename=self.baseline_interaction_path, population=self.population
)
if self.alpha_physical is not None:
interaction.alpha_physical = self.alpha_physical
if self.betas is not None:
allowed_betas = interaction.beta
for key, value in self.betas.items():
if key not in allowed_betas:
raise ValueError(
f"Trying to change a beta for a non-existing group."
)
else:
interaction.beta[key] = value
# susceptibility
if self.susceptibilities_by_age is not None:
interaction.susceptibilities_by_age = self.susceptibilities_by_age
interaction.set_population_susceptibilities(
population=self.population,
susceptibilities_by_age=self.susceptibilities_by_age,
)
return interaction
# =================================== policies ===============================#
policies = Policies.from_file(
camp_configs_path / "defaults/policy/home_care_policy.yaml",
base_policy_modules=("june.policy", "camps.policy"),
)
# ============================================================================#
# =================================== infection ===============================#
selector = InfectionSelector.from_file(health_index_generator=health_index_generator)
interaction = Interaction.from_file(
config_filename=camp_configs_path
/ "defaults/interaction/ContactInteraction_med_low_low_low.yaml",
)
cases_detected = {
"CXB-202": 3,
"CXB-204": 6,
"CXB-208": 8,
"CXB-203": 1,
"CXB-207": 2,
"CXB-213": 2,
} # By the 24th May
print("Detected cases = ", sum(cases_detected.values()))
msoa_region_filename = camp_data_path / "input/geography/area_super_area_region.csv"
def create_interaction():
interaction = Interaction.from_file()
interaction.selector = infect.InfectionSelector.from_file(
transmission_config_path=constant_config)
return interaction
def generate_simulator():
record = Record(record_path=save_path,
record_static_data=True,
mpi_rank=mpi_rank)
if mpi_rank == 0:
with h5py.File(world_file, "r") as f:
super_area_names = f["geography"]["super_area_name"][:]
super_area_ids = f["geography"]["super_area_id"][:]
super_area_names = [name.decode() for name in super_area_names]
super_area_name_to_id = {
key: value
for key, value in zip(super_area_names, super_area_ids)
}
# make dictionary super_area_id -> domain
domain_splitter = DomainSplitter(number_of_domains=mpi_size,
world_path=world_file)
super_areas_per_domain = domain_splitter.generate_domain_split(
niter=20)
super_area_names_to_domain_dict = {}
super_area_ids_to_domain_dict = {}
for domain, super_areas in super_areas_per_domain.items():
for super_area in super_areas:
super_area_names_to_domain_dict[super_area] = domain
super_area_ids_to_domain_dict[int(
super_area_name_to_id[super_area])] = domain
with open("super_area_ids_to_domain.json", "w") as f:
json.dump(super_area_ids_to_domain_dict, f)
with open("super_area_names_to_domain.json", "w") as f:
json.dump(super_area_names_to_domain_dict, f)
mpi_comm.Barrier()
if mpi_rank > 0:
with open("super_area_ids_to_domain.json", "r") as f:
super_area_ids_to_domain_dict = json.load(f,
object_hook=keys_to_int)
domain = Domain.from_hdf5(
domain_id=mpi_rank,
super_areas_to_domain_dict=super_area_ids_to_domain_dict,
hdf5_file_path=world_file,
)
record.static_data(world=domain)
# regenerate lesiure
leisure = generate_leisure_for_config(domain, config_path)
#
# health index and infection selecctor
health_index_generator = HealthIndexGenerator.from_file()
infection_selector = InfectionSelector(
health_index_generator=health_index_generator)
oc = Observed2Cases.from_file(
health_index_generator=health_index_generator, smoothing=True)
daily_cases_per_region = oc.get_regional_latent_cases()
daily_cases_per_super_area = oc.convert_regional_cases_to_super_area(
daily_cases_per_region, dates=["2020-02-28", "2020-03-02"])
infection_seed = InfectionSeed(
world=domain,
infection_selector=infection_selector,
daily_super_area_cases=daily_cases_per_super_area,
seed_strength=100,
)
# interaction
interaction = Interaction.from_file(
config_filename="./config_interaction.yaml", population=domain.people)
# policies
policies = Policies.from_file()
# events
events = Events.from_file()
# create simulator
travel = Travel()
simulator = Simulator.from_file(
world=domain,
policies=policies,
events=events,
interaction=interaction,
leisure=leisure,
travel=travel,
infection_selector=infection_selector,
infection_seed=infection_seed,
config_filename=config_path,
record=record,
)
print("simulator ready to go")
return simulator
include_commute=True)
print("World length", len(world.people))
world.to_hdf5("world.hdf5")
world = generate_world_from_hdf5("world.hdf5")
# leisure
geography = load_geography_from_hdf5("world.hdf5")
world.cinemas = Cinemas.for_geography(geography)
world.pubs = Pubs.for_geography(geography)
world.groceries = Groceries.for_super_areas(world.super_areas,
venues_per_capita=1 / 500)
world.cemeteries = Cemeteries()
selector = InfectionSelector.from_file()
interaction = Interaction.from_file()
print(interaction.beta)
# modify interactions (example x 2)
interaction.beta['household'] *= 2
print(interaction.beta)
interaction.alpha_physical
interaction.alpha_physical /= 2
interaction.alpha_physical
# # Seed the disease
# There are two options implemented in the seed at the moment, either you specify the number of cases and these are then homogeneously distributed by population to the different areas, or you use UK data on cases per region. For now use the first case.
seed = InfectionSeed(
world.super_areas,
selector,
)
def create_interaction():
interaction = Interaction.from_file()
return interaction
camp_configs_path / "defaults/policy/home_care_policy.yaml",
base_policy_modules=("june.policy", "camps.policy"),
)
# ============================================================================#
# =================================== infection ===============================#
selector = InfectionSelector(
health_index_generator=health_index_generator,
transmission_config_path=transmission_config_path,
)
interaction = Interaction.from_file(
config_filename=camp_configs_path / "defaults/interaction/" /
args.parameters,
population=world.people,
)
if args.child_susceptibility:
interaction = Interaction.from_file(
config_filename=camp_configs_path /
"defaults/interaction/ContactInteraction_med_low_low_low_child.yaml",
population=world.people,
)
else:
interaction = Interaction.from_file(
config_filename=camp_configs_path / "defaults/interaction/" /
args.parameters,
population=world.people,
)
