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simplified logic for building a CO2 model

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This commit is contained in:
Luis Aleixo 2023-11-01 16:03:47 +01:00
parent 446cc88345
commit 9245166c4a
1 changed files with 21 additions and 8 deletions
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25
caimira/apps/calculator/co2_model_generator.py
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@ -97,9 +97,9 @@ class CO2FormData(model_generator.FormData):
instance.validate_population_parameters()
return instance
def population_present_changes(self) -> typing.List[float]:
state_change_times = set(self.infected_present_interval().transition_times())
state_change_times.update(self.exposed_present_interval().transition_times())
def population_present_changes(self, infected_presence: models.Interval, exposed_presence: models.Interval) -> typing.List[float]:
state_change_times = set(infected_presence.transition_times())
state_change_times.update(exposed_presence.transition_times())
return sorted(state_change_times)
def ventilation_transition_times(self) -> typing.Tuple[float, ...]:
@ -112,12 +112,25 @@ class CO2FormData(model_generator.FormData):
return tuple((self.CO2_data['times'][0], self.CO2_data['times'][-1]))
def build_model(self, size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2DataModel: # type: ignore
infected_population: models.Population = self.infected_population().build_model(size)
exposed_population: models.Population = self.exposed_population().build_model(size)
all_state_changes=self.population_present_changes()
# Build a simple infected and exposed population for the case when presence
# intervals and number of people are dynamic. Activity type is not needed.
infected_presence = self.infected_present_interval()
infected_population = models.SimplePopulation(
number=self.infected_people,
presence=infected_presence,
activity=None, # type: ignore
)
exposed_presence = self.exposed_present_interval()
exposed_population=models.SimplePopulation(
number=self.total_people - self.infected_people,
presence=exposed_presence,
activity=None, # type: ignore
)
all_state_changes=self.population_present_changes(infected_presence, exposed_presence)
total_people = [infected_population.people_present(stop) + exposed_population.people_present(stop)
for _, stop in zip(all_state_changes[:-1], all_state_changes[1:])]
return models.CO2DataModel(
room_volume=self.room_volume,
number=models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people)),