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added shouting model and changed talking to speaking

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This commit is contained in:
Luis Aleixo 2021-09-06 11:04:03 +02:00
parent 57b6a668c0
commit f0c59b0c61
3 changed files with 52 additions and 12 deletions
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46
cara/model_scenarios_paper.py
View file

@ -1,5 +1,5 @@
from cara import models
from cara.monte_carlo.data import activity_distributions, virus_distributions
from cara.monte_carlo.data import activity_distributions, symptomatic_vl_frequencies
import cara.monte_carlo as mc
import numpy as np
@ -39,7 +39,10 @@ def breathing_exposure():
),
infected=mc.InfectedPopulation(
number=1,
virus=virus_distributions['SARS_CoV_2'],
virus=models.Virus(
viral_load_in_sputum=symptomatic_vl_frequencies,
infectious_dose=50.,
),
presence=mc.SpecificInterval(((0, 2),)),
mask=models.Mask.types["No mask"],
activity=activity_distributions['Seated'],
@ -55,8 +58,8 @@ def breathing_exposure():
)
return exposure_mc
######### Talking model ###########
def talking_exposure():
######### Speaking model ###########
def speaking_exposure():
exposure_mc = mc.ExposureModel(
concentration_model=mc.ConcentrationModel(
room=models.Room(volume=100, humidity=0.5),
@ -66,7 +69,10 @@ def talking_exposure():
),
infected=mc.InfectedPopulation(
number=1,
virus=virus_distributions['SARS_CoV_2'],
virus=models.Virus(
viral_load_in_sputum=symptomatic_vl_frequencies,
infectious_dose=50.,
),
presence=mc.SpecificInterval(((0, 2),)),
mask=models.Mask.types["No mask"],
activity=activity_distributions['Seated'],
@ -82,6 +88,36 @@ def talking_exposure():
)
return exposure_mc
######### Shouting model ###########
def shouting_exposure():
exposure_mc = mc.ExposureModel(
concentration_model=mc.ConcentrationModel(
room=models.Room(volume=100, humidity=0.5),
ventilation=models.AirChange(
active=models.SpecificInterval(((0, 24),)),
air_exch=0.25,
),
infected=mc.InfectedPopulation(
number=1,
virus=models.Virus(
viral_load_in_sputum=symptomatic_vl_frequencies,
infectious_dose=50.,
),
presence=mc.SpecificInterval(((0, 2),)),
mask=models.Mask.types["No mask"],
activity=activity_distributions['Seated'],
expiration=models.Expiration.types['Shouting'],
),
),
exposed=mc.Population(
number=14,
presence=mc.SpecificInterval(((0, 2),)),
activity=models.Activity.types['Seated'],
mask=models.Mask.types["No mask"],
),
)
return exposure_mc
######### Breathing model for specific viral load ###########
def breathing_exposure_vl(vl):
exposure_mc = mc.ExposureModel(

13
cara/plot_output.py
View file

@ -33,11 +33,18 @@ emission_rate = exposure_model.concentration_model.infected.emission_rate_when_p
print('\n<<<<<<<<<<< Breathing model statistics >>>>>>>>>>>')
print_er_info(emission_rate)
############ Talking model ############
exposure_mc = model_scenarios_paper.talking_exposure()
############ Speaking model ############
exposure_mc = model_scenarios_paper.speaking_exposure()
exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
print('\n<<<<<<<<<<< Talking model statistics >>>>>>>>>>>')
print('\n<<<<<<<<<<< Speaking model statistics >>>>>>>>>>>')
print_er_info(emission_rate)
############ Shouting model ############
exposure_mc = model_scenarios_paper.shouting_exposure()
exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
print('\n<<<<<<<<<<< Shouting model statistics >>>>>>>>>>>')
print_er_info(emission_rate)
############ Used for testing ############

5
cara/results_paper.py
View file

@ -117,7 +117,6 @@ def exposure_model_from_vl_breathing_cn():
emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(
cn_B=0.06, cn_L=0.2) / 2
er_means = np.append(er_means, np.mean(emission_rate))
print_er_info(er_means)
ax.plot(viral_loads, er_means, color=cmap.to_rgba(
cn, alpha=0.75), linewidth=1, ls='--')
plt.text(viral_loads[int(len(viral_loads)*0.9)], 10**4.2,
@ -230,8 +229,6 @@ def exposure_model_from_vl_talking_cn():
er_means = np.append(er_means, np.mean(emission_rate))
ax.plot(viral_loads, er_means, color=cmap.to_rgba(
cn, alpha=0.75), linewidth=1, ls='--')
'''Statistical Data'''
print_er_info(er_means)
plt.text(viral_loads[int(len(viral_loads)*0.93)], 10**5.5,
r"$\mathbf{c_{n,L}=0.2}$", color=cmap.to_rgba(cn), size='small')
@ -382,7 +379,7 @@ def print_er_info(er: np.array):
"""
print(f"MEAN of ER = {np.mean(er)}\n"
f"SD of ER = {np.std(er)}\n"
f"Median of qR = {np.quantile(er, 0.5)}\n")
f"Median of ER = {np.quantile(er, 0.5)}\n")
print(f"Percentiles of ER:")
for quantile in (0.01, 0.05, 0.25, 0.50, 0.55, 0.65, 0.75, 0.95, 0.99):