62 lines
2.5 KiB
Python
62 lines
2.5 KiB
Python
""" Title: COVID Airborne Risk Assessment
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Author: <author(s) names>
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Date: <date>
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Code version: <code version>
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Availability: <where it's located> """
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from cara import model_scenarios_paper
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from cara.results_paper import *
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from cara.test_plots import *
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from cara.monte_carlo.data import symptomatic_vl_frequencies
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# Exhaled virions while talking, seated #
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print('\n<<<<<<<<<<< Vlout for Talking, seated >>>>>>>>>>>')
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#exposure_model_from_vl_talking()
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# Exhaled virions while breathing, seated #
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print('\n<<<<<<<<<<< Vlout for Breathing, seated >>>>>>>>>>>')
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#exposure_model_from_vl_breathing()
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# Exhaled virions while talking according to BLO model, seated #
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print('\n<<<<<<<<<<< Vlout for Talking, seated with chosen Cn,L >>>>>>>>>>>')
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#exposure_model_from_vl_talking_cn()
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# Exhaled virions while breathing according to BLO model, seated #
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print('\n<<<<<<<<<<< Vlout for Breathing, seated with chosen Cn,B >>>>>>>>>>>')
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#exposure_model_from_vl_breathing_cn()
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print('\n')
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############ Statistical Data ############
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############ Breathing model ############
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exposure_mc = model_scenarios_paper.breathing_exposure()
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exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
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breathing_er = [np.log10(er) for er in emission_rate]
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print('\n<<<<<<<<<<< Breathing model statistics >>>>>>>>>>>')
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print_er_info(emission_rate)
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############ Speaking model ############
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exposure_mc = model_scenarios_paper.speaking_exposure()
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exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
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speaking_er = [np.log10(er) for er in emission_rate]
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print('\n<<<<<<<<<<< Speaking model statistics >>>>>>>>>>>')
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print_er_info(emission_rate)
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############ Shouting model ############
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exposure_mc = model_scenarios_paper.shouting_exposure()
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exposure_model = exposure_mc.build_model(size=SAMPLE_SIZE)
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emission_rate = exposure_model.concentration_model.infected.emission_rate_when_present(cn_B=0.06, cn_L=0.2)
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shouting_er = [np.log10(er) for er in emission_rate]
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print('\n<<<<<<<<<<< Shouting model statistics >>>>>>>>>>>')
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print_er_info(emission_rate)
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############ Plots with Viral loads and emission rates
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viral_load_in_sputum = exposure_model.concentration_model.infected.virus.viral_load_in_sputum
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present_vl_er_histograms(viral_load_in_sputum, breathing_er, speaking_er, shouting_er)
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############ Used for testing ############
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#exposure_model_from_vl_talking_new_points()
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