Changed variable name
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1 changed files with 7 additions and 7 deletions
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@ -1159,10 +1159,10 @@ class ExposureModel:
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"""Probability that a randomly selected individual in a focal population is infected."""
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return cases*AB/population
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def probability_meet_infected_person(self, population, cases, event, i) -> _VectorisedFloat:
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"""Probability to meet x infected person in an event."""
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def probability_meet_infected_person(self, population, cases, event, x) -> _VectorisedFloat:
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"""Probability to meet x infected persons in an event."""
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AB = 5
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return sct.binom.pmf(i, event, self.probability_random_individual(cases, population, AB))
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return sct.binom.pmf(x, event, self.probability_random_individual(cases, population, AB))
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def infection_probability(self) -> _VectorisedFloat:
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exposure = self.exposure()
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@ -1194,14 +1194,14 @@ class ExposureModel:
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sum_probability = 0.0
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# Create an equivalent exposure model but with i infected cases
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total_people = self.concentration_model.infected.number + self.exposed.number
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I = (total_people if total_people < 10 else 10)
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for i in range(1, I):
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X = (total_people if total_people < 10 else 10)
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for x in range(1, X):
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exposure_model = nested_replace(
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self, {'concentration_model.infected.number': i}
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self, {'concentration_model.infected.number': x}
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)
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prob_exposed_occupant = exposure_model.infection_probability().mean() / 100
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# By means of a Binomial Distribution
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sum_probability += (prob_exposed_occupant)*self.probability_meet_infected_person(self.geographic_population, self.geographic_cases, self.exposed.number, i)
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sum_probability += (prob_exposed_occupant)*self.probability_meet_infected_person(self.geographic_population, self.geographic_cases, self.exposed.number, x)
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return sum_probability * 100
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else:
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return 0
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