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updated dynamic total_prob_rule method

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This commit is contained in:
Luis Aleixo 2023-05-17 14:55:43 +02:00
parent df77bdd1b5
commit 2a3c598488
1 changed files with 3 additions and 1 deletions
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4
caimira/models.py
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@ -1696,6 +1696,7 @@ class ExposureModel:
state_change_times = self.population_state_change_times()
for interval in zip(state_change_times[:-1], state_change_times[1:]):
sum_probability = 0.0
exposed_present = self.exposed.people_present(interval[1])
infected_present = self.concentration_model.infected.people_present(interval[1])
@ -1731,10 +1732,11 @@ class ExposureModel:
n = total_people - num_infected
# By means of the total probability rule
prob_at_least_one_infected = 1 - (1 - prob_ind)**n
total_probability_rule.append(prob_at_least_one_infected *
sum_probability += (prob_at_least_one_infected *
self.geographical_data.probability_meet_infected_person(
self.concentration_model.infected.virus,
num_infected, total_people))
total_probability_rule.append(sum_probability)
if (isinstance(self.exposed.number, IntPiecewiseConstant) or
isinstance(self.concentration_model.infected.number, IntPiecewiseConstant)):