def do_shedding_update(human_pop):
# This is not optimal. Only optimize if it really helps
global fertility
if fertility is None:
config = json.loads(open("nd.json").read())
fertility = config["Enable_Birth"] and config["Enable_Vital_Dynamics"]
stat_pop = 0
for human in human_pop:
hum_id = human["id"]
mcw = gi.get_mcw(hum_id)
#Can we make this conditional on
if fertility:
nd.update_node_stats(
(mcw, 0, gi.is_possible_mother(hum_id),
0)) # mcw, infectiousness, is_poss_mom, is_infected
"""
if gi.is_infected(hum_id):
if gi.has_latent_infection(hum_id):
print( "{0} has latent infection.".format( hum_id ) )
else:
print( "{0} has active infection (I guess).".format( hum_id ) )
else:
print( "{0} has no infection.".format( hum_id ) )
"""
stat_pop += mcw
if gi.is_infected(hum_id):
gi.update1(hum_id) # this should do shedding & vital-dynamics
return stat_pop
def expose_callback(individual_id):
"""
This function is the callback for exposure. It is registered with the intrahost module
and then called for each individual for each timestep. This is where you decide whether
an individual should get infected or not. In the limit, you could just return False here
and no-one would ever get infected. If you just returned True, everyone would be infected
always. The expectation is that you write some code that uses the contagion shed and does
some math. To be heterogeneous, you can use the individual id. The action and prob
parameters can be ignored.
"""
# The following code is just to demo the use of TBHIV-specific getters
if gi.is_infected(individual_id):
#print( "Individual {0} is apparently already infected.".format( individual_id ) )
return 0
if gi.get_immunity(individual_id) == 0:
return 0
global timestep
#print( "timestep = {0}, outbreak_timestep = {1}.".format( timestep, outbreak_timestep ) )
#if timestep in outbreak_timesteps:
# #if gi.get_immunity( individual_id ) == 1.0 and random.random() < 0.1: # let's infect some people at random (outbreaks)
# if random.random() < outbreak_coverage: # let's infect some people at random (outbreaks)
# print( "Let's force-infect (outbreak) uninfected, non-immune individual based on random draw." )
# return 1
if (timestep == 1) and (individual_id == 13):
return 1 # force-infect individual 13 at time 0
else:
if individual_id == 0:
pdb.set_trace()
global contagion_buckets
#global contagion_bucket_homog
#print( "Exposing individual {0} to contagion {1}.".format( individual_id, contagion_bucket ) )
#HINT-y code here
contagion = contagion_buckets[CHILD] + contagion_buckets[ADULT]
me = ADULT if gi.get_age(
individual_id) >= ADULT_CHILD_AGE_THRESHOLD else CHILD
my_factor_from_child = factors[me][CHILD]
my_factor_from_adult = factors[me][ADULT]
contagion = (contagion_buckets[CHILD] * my_factor_from_child) + (
contagion_buckets[ADULT] * my_factor_from_adult)
contagion /= len(human_pop)
#print( "HINT-y math: I am an {}, exposed to contagion {}.".format( "CHILD" if me == CHILD else "ADULT", contagion ) )
#contagion = contagion_bucket_homog
if gi.should_infect((individual_id, contagion)):
return 1
return 0
def update(self):
self.time += 1
for h in self.humans:
dgi.update(h)
# Pull people who've changed out of human and into werewolves
if dgi.is_infected(h) and not dgi.is_incubating(h):
self.humans.remove(h)
self.waiting_wolves.remove(
h
) # See above, they are in two places and need to be removed
self.werewolves.append(h)
if self.debug:
print(f"Individual {h} is a wolf!")
if self.time % HALLOWEEN_DAY == 0: # It is october 31
if len(self.werewolves) == 0: # and there are no werewolves
found_one = False
possible_humans = len(self.humans)
ages = []
min_age_exposure = self.min_age_werewolf_years * DAYS_YEAR
while not found_one and possible_humans > 0:
for h in self.humans:
possible_humans -= 1
age = dgi.get_age(h)
ages.append(age)
if age > min_age_exposure:
if age % DAYS_YEAR == HALLOWEEN_DAY:
self.humans.remove(h)
self.werewolves.append(h)
found_one = True
break
if found_one:
print("Found a new werewolf with a Halloween Birthday.")
else:
print("No cool birthdays, just taking someone.")
future_wolf = None
for h in self.humans:
age = dgi.get_age(h)
if not future_wolf and age > min_age_exposure:
self.humans.remove(h)
self.werewolves.append(h)
future_wolf = h
if future_wolf:
print("Found someone old enough.")
else:
print("No one old enough! No outbreak!")
print(ages)
sys.exit()
if self.enable_reporting:
self.report_step()
def expose_callback( action, prob, individual_id ):
"""
This function is the callback for exposure. It is registered with the intrahost module
and then called for each individual for each timestep. This is where you decide whether
an individual should get infected or not. In the limit, you could just return False here
and no-one would ever get infected. If you just returned True, everyone would be infected
always. The expectation is that you write some code that uses the contagion shed and does
some math. To be heterogeneous, you can use the individual id. The action and prob
parameters can be ignored.
"""
# The following code is just to demo the use of TBHIV-specific getters
if gi.is_infected( individual_id ):
#print( "Individual {0} is apparently already infected.".format( individual_id ) )
return 0
if gi.get_immunity( individual_id ) == 0:
return 0
global timestep
#print( "timestep = {0}, outbreak_timestep = {1}.".format( timestep, outbreak_timestep ) )
if timestep in outbreak_timesteps:
#if gi.get_immunity( individual_id ) == 1.0 and random.random() < 0.1: # let's infect some people at random (outbreaks)
if random.random() < outbreak_coverage: # let's infect some people at random (outbreaks)
print( "Let's force-infect (outbreak) uninfected, non-immune individual based on random draw." )
return 1
else:
if individual_id == 0:
pdb.set_trace()
global contagion_bucket
#print( "Exposing individual {0} to contagion {1}.".format( individual_id, contagion_bucket ) )
if gi.should_infect( ( individual_id, contagion_bucket ) ):
return 1
return 0
def is_incubating(person):
if gi.is_infected(person) and gi.get_infectiousness(person) == 0:
return True
else:
return False
def do_vitaldynamics_update(human_pop,
graveyard,
contagion,
census_cb=None,
death_cb=None):
num_infected = 0
num_incubating = 0
num_active = 0
num_suscept = 0
num_recover = 0
num_people = 0
num_deaths = 0
new_graveyard = []
for human in human_pop:
hum_id = human["id"]
if census_cb != None:
census_cb(hum_id)
gi.update2(
hum_id
) # this should do exposure; possible optimization would be to skip this entirely if zero contagion
mcw = gi.get_mcw(hum_id)
if gi.is_dead(hum_id):
# somebody died
print("{0} is dead.".format(hum_id))
new_graveyard.append(human)
num_deaths += mcw # can't use len(graveyard) coz mcw
if death_cb != None:
death_cb(hum_id)
num_people += mcw
global fertility
if fertility:
ipm = gi.is_possible_mother(hum_id)
ip = gi.is_pregnant(hum_id)
if hum_id == 0:
pdb.set_trace()
age = gi.get_age(hum_id)
#print( "Calling cfp with {0}, {1}, {2}, and {3}.".format( str(ipm), str(ip), str(age), str(hum_id) ) )
# TBD: Optimization? I happen to know that this is only necessary for females of a
# certain age. But technically that knowledge is for nd.
nd.consider_for_pregnancy((ipm, ip, hum_id, age, 1.0))
#print( str( json.loads(gi.serialize( hum_id ))["individual"]["susceptibility"] ) )
if gi.is_infected(hum_id):
if is_incubating(hum_id):
num_incubating += mcw
else:
num_infected += mcw # TBD: use_mcw
elif gi.get_immunity(hum_id) != 1.0:
num_recover += mcw # TBD: use mcw
else:
num_suscept += mcw # TBD: use mcw
#if gi.has_active_infection( hum_id ):
# num_active += 1
# serialize seems to be broken when you had an intervention (or at least a SimpleVaccine)
#serial_man = gi.serialize( hum_id )
#if hum_id == 1:
#print( json.dumps( json.loads( serial_man ), indent=4 ) )
#print( "infectiousness: " + str( json.loads( serial_man )["individual"]["infectiousness"] ) )
#print( "Updating fertility for this timestep." )
for corpse in new_graveyard:
if corpse in human_pop:
human_pop.pop(human_pop.index(corpse))
else:
print("Exception trying to remove individual from python list: " +
str(ex))
graveyard.extend(new_graveyard)
nd.update_fertility()
exposeds.append(num_incubating)
prevalence.append(num_infected)
active_prevalence.append(num_active)
susceptible.append(num_suscept)
recovered.append(num_recover)
disdeaths.append(num_deaths)
def do_vitaldynamics_update(human_pop,
graveyard,
census_cb=None,
death_cb=None):
num_infected = 0
num_incubating = 0
num_active = 0
num_suscept = 0
num_recover = 0
new_graveyard = []
for human in human_pop:
hum_id = human["id"]
if census_cb != None:
census_cb(hum_id)
gi.update2(hum_id) # this should do exposure
if gi.is_dead(hum_id):
# somebody died
print("{0} is dead.".format(hum_id))
new_graveyard.append(human)
if death_cb != None:
death_cb(hum_id)
# TESTING THIS
ipm = gi.is_possible_mother(hum_id)
ip = gi.is_pregnant(hum_id)
if hum_id == 0:
pdb.set_trace()
age = gi.get_age(hum_id)
#print( "Calling cfp with {0}, {1}, {2}, and {3}.".format( str(ipm), str(ip), str(age), str(hum_id) ) )
nd.consider_for_pregnancy((ipm, ip, hum_id, age, 1.0))
#print( str( json.loads(gi.serialize( hum_id ))["individual"]["susceptibility"] ) )
if gi.is_infected(hum_id):
if is_incubating(hum_id):
num_incubating += 1
else:
num_infected += 1 # TBD: use_mcw
elif gi.get_immunity(hum_id) != 1.0:
num_recover += 1 # TBD: use mcw
else:
num_suscept += 1 # TBD: use mcw
#if gi.has_active_infection( hum_id ):
# num_active += 1
# serialize seems to be broken when you had an intervention (or at least a SimpleVaccine)
#serial_man = gi.serialize( hum_id )
#if hum_id == 1:
#print( json.dumps( json.loads( serial_man ), indent=4 ) )
#print( "infectiousness: " + str( json.loads( serial_man )["individual"]["infectiousness"] ) )
#print( "Updating fertility for this timestep." )
for corpse in new_graveyard:
if corpse in human_pop:
human_pop.pop(human_pop.index(corpse))
else:
print("Exception trying to remove individual from python list: " +
str(ex))
graveyard.extend(new_graveyard)
nd.update_fertility()
exposeds.append(num_incubating)
prevalence.append(num_infected)
active_prevalence.append(num_active)
susceptible.append(num_suscept)
recovered.append(num_recover)
disdeaths.append(len(graveyard))
print("Forced infections.")
for x in range(25):
for person in people:
dgi.update(person)
pass
pass
incubating = 0
infected = 0
for person in people:
if dgi.is_incubating(person):
incubating += 1
pass
if dgi.is_infected(person):
infected += 1
pass
pass
print(f"25 days later... incubating: {incubating}\tinfected: {infected}")
for x in range(5):
for person in people:
dgi.update(person)
pass
pass
incubating = 0
infected = 0
for person in people:
if dgi.is_incubating(person):
