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Removed unused code

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This commit is contained in:
Luis Aleixo 2022-02-08 09:55:51 +00:00
parent 4704a6e022
commit d2164383e5
10 changed files with 2 additions and 87 deletions
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9
cara/apps/calculator/model_generator.py
View file

@ -418,13 +418,6 @@ class FormData:
infected_occupants = self.infected_people
if self.short_range_option == "short_range_no":
sr_presence=[]
sr_activities=[]
else:
sr_presence=self.short_range_intervals()
sr_activities=self.short_range_activities()
infected = mc.InfectedPopulation(
number=infected_occupants,
virus=virus,
@ -433,8 +426,6 @@ class FormData:
activity=activity,
expiration=expiration,
host_immunity=0.,
short_range_presence=sr_presence,
short_range_activities=sr_activities,
)
return infected

32
cara/apps/calculator/report_generator.py
View file

@ -12,9 +12,8 @@ import jinja2
import numpy as np
from cara import models
from cara.monte_carlo.data import initial_concentrations_mouth, dilution_factor
from ... import monte_carlo as mc
from .model_generator import FormData, _DEFAULT_MC_SAMPLE_SIZE, build_expiration
from .model_generator import FormData, _DEFAULT_MC_SAMPLE_SIZE
from ... import dataclass_utils
@ -97,41 +96,13 @@ def interesting_times(model: models.ExposureModel, approx_n_pts=100) -> typing.L
return nice_times
def short_range_interesting_times(model: models.ExposureModel, times: typing.List[float]) -> typing.List[float]:
short_range_times : typing.List[float] = []
for period in model.concentration_model.infected.short_range_presence:
start, finish = tuple(period.boundaries())
short_range_times = short_range_times + [time for time in times if time > start and time < finish]
return short_range_times
def jet_origin_concentrations(model: models.ExposureModel) -> typing.List[float]:
return [initial_concentrations_mouth[activity] for activity in model.concentration_model.infected.short_range_activities]
def short_range_initial_concentrations(model: models.ExposureModel, time: float):
dilution = dilution_factor(distance=np.linspace(0.1, 2., 1000))
jet_origin_initial_concentrations = jet_origin_concentrations(model)
for index, interaction in enumerate(model.concentration_model.infected.short_range_presence):
start, finish = tuple(interaction.boundaries())
if start <= time <= finish:
concentration = model.concentration_model.concentration(float(time))
jet_origin_concentration = jet_origin_initial_concentrations[index] * model.concentration_model.infected.virus.viral_load_in_sputum
return concentration + ((1/dilution)*(jet_origin_concentration - concentration))
def calculate_report_data(model: models.ExposureModel):
times = interesting_times(model)
times_short_range = short_range_interesting_times(model, times)
concentrations = [
np.array(model.concentration_model.concentration(float(time))).mean()
for time in times
]
short_range_concentrations = [
np.array(short_range_initial_concentrations(model, float(time))).mean()
for time in times_short_range
]
highest_const = max(concentrations)
prob = np.array(model.infection_probability()).mean()
er = np.array(model.concentration_model.infected.emission_rate_when_present()).mean()
@ -147,7 +118,6 @@ def calculate_report_data(model: models.ExposureModel):
"exposed_presence_intervals": [list(interval) for interval in model.exposed.presence.boundaries()],
"cumulative_doses": list(cumulative_doses),
"concentrations": concentrations,
"short_range_concentrations": short_range_concentrations,
"highest_const": highest_const,
"prob_inf": prob,
"emission_rate": er,

8
cara/models.py
View file

@ -32,7 +32,7 @@ or length N arrays, where N is the number of parameterisations to run; N must be
the same for all parameters of a single model.
"""
from dataclasses import dataclass, field
from dataclasses import dataclass
import typing
import numpy as np
@ -762,12 +762,6 @@ class _PopulationWithVirus(Population):
#: The virus with which the population is infected.
virus: Virus
#: Short range interactions
short_range_presence: typing.List[SpecificInterval]
#: The type of expiractory activities in the short range interactions
short_range_activities: typing.List[str]
@method_cache
def fraction_of_infectious_virus(self) -> _VectorisedFloat:
"""

2
cara/tests/conftest.py
View file

@ -23,8 +23,6 @@ def baseline_model():
host_immunity=0.,
# superspreading event, where ejection factor is fixed based
# on Miller et al. (2020) - 50 represents the infectious dose.
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)

4
cara/tests/models/test_concentration_model.py
View file

@ -47,8 +47,6 @@ def test_concentration_model_vectorisation(override_params):
),
expiration=models._ExpirationBase.types['Breathing'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -71,8 +69,6 @@ def simple_conc_model():
virus=models.Virus.types['SARS_CoV_2'],
expiration=models.Expiration.types['Breathing'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)

6
cara/tests/models/test_exposure_model.py
View file

@ -66,8 +66,6 @@ def known_concentrations(func):
virus=models.Virus.types['SARS_CoV_2_ALPHA'],
expiration=models.Expiration.types['Speaking'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
)
normed_func = lambda x: func(x) / dummy_infected_population.emission_rate_when_present()
return KnownNormedconcentration(dummy_room, dummy_ventilation,
@ -166,8 +164,6 @@ def conc_model():
# superspreading event, where ejection factor is fixed based
# on Miller et al. (2020) - 50 represents the infectious dose.
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -211,8 +207,6 @@ def test_infectious_dose_vectorisation():
),
expiration=models.Expiration.types['Speaking'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
)
cm = known_concentrations(lambda t: 1.2)
cm = replace(cm, infected=infected_population)

2
cara/tests/test_infected_population.py
View file

@ -37,8 +37,6 @@ def test_infected_population_vectorisation(override_params):
),
expiration=cara.models._ExpirationBase.types['Breathing'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
)
emission_rate = infected.emission_rate(10)
assert isinstance(emission_rate, np.ndarray)

8
cara/tests/test_known_quantities.py
View file

@ -76,8 +76,6 @@ def build_model(interval_duration):
host_immunity=0.,
# superspreading event, where ejection factor is fixed based
# on Miller et al. (2020) - 50 represents the infectious dose.
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -240,8 +238,6 @@ def build_hourly_dependent_model(
activity=models.Activity.types['Light activity'],
known_individual_emission_rate=970 * 50,
host_immunity=0,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -265,8 +261,6 @@ def build_constant_temp_model(outside_temp, intervals_open=((7.5, 8.5),)):
activity=models.Activity.types['Light activity'],
known_individual_emission_rate=970 * 50,
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -297,8 +291,6 @@ def build_hourly_dependent_model_multipleventilation(month, intervals_open=((7.5
activity=models.Activity.types['Light activity'],
known_individual_emission_rate=970 * 50,
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)

2
cara/tests/test_monte_carlo.py
View file

@ -55,8 +55,6 @@ def baseline_mc_model() -> cara.monte_carlo.ConcentrationModel:
activity=cara.models.Activity.types['Light activity'],
expiration=cara.models.Expiration.types['Breathing'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)

16
cara/tests/test_monte_carlo_full_models.py
View file

@ -67,8 +67,6 @@ def shared_office_mc():
activity=activity_distributions['Seated'],
expiration=build_expiration({'Speaking': 0.33, 'Breathing': 0.67}),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -111,8 +109,6 @@ def classroom_mc():
activity=activity_distributions['Light activity'],
expiration=build_expiration('Speaking'),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -146,8 +142,6 @@ def ski_cabin_mc():
activity=activity_distributions['Moderate activity'],
expiration=build_expiration('Speaking'),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -187,8 +181,6 @@ def skagit_chorale_mc():
activity=activity_distributions['Moderate activity'],
expiration=build_expiration('Shouting'),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -228,8 +220,6 @@ def bus_ride_mc():
activity=activity_distributions['Seated'],
expiration=build_expiration('Speaking'),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -264,8 +254,6 @@ def gym_mc():
activity=activity_distributions['Heavy exercise'],
expiration=expiration_distributions['Breathing'],
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -300,8 +288,6 @@ def waiting_room_mc():
activity=activity_distributions['Seated'],
expiration=build_expiration({'Speaking': 0.3, 'Breathing': 0.7}),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)
@ -379,8 +365,6 @@ def test_small_shared_office_Geneva(mask_type, month, expected_pi,
activity=activity_distributions['Seated'],
expiration=build_expiration({'Speaking': 0.33, 'Breathing': 0.67}),
host_immunity=0.,
short_range_presence=[],
short_range_activities=[],
),
evaporation_factor=0.3,
)