From 418305d50aa32828ea31cd7a48c0904cbb61cd0e Mon Sep 17 00:00:00 2001 From: Andrejh Date: Fri, 19 Mar 2021 10:45:21 +0100 Subject: [PATCH] updates --- cara/mc-output-publication.py | 6 ++++++ cara/mc-output.py | 33 ++++++++++++++++----------------- 2 files changed, 22 insertions(+), 17 deletions(-) diff --git a/cara/mc-output-publication.py b/cara/mc-output-publication.py index a4805144..a12bc6aa 100644 --- a/cara/mc-output-publication.py +++ b/cara/mc-output-publication.py @@ -1,3 +1,9 @@ +""" Title: COVID Airborne Risk Assessment +Author: +Date: +Code version: +Availability: """ + from cara.montecarlo import * from cara.model_scenarios import * diff --git a/cara/mc-output.py b/cara/mc-output.py index 77a14046..2c186587 100644 --- a/cara/mc-output.py +++ b/cara/mc-output.py @@ -1,10 +1,3 @@ -""" Title: -Author: <author(s) names> -Date: <date> -Code version: <code version> -Availability: <where it's located> """ - - from cara.montecarlo import * from cara.model_scenarios import * @@ -14,7 +7,7 @@ from cara.model_scenarios import * #print(np.mean(classroom_model[0].infection_probability())) #print(np.mean(classroom_model[1].infection_probability())) #print(np.mean(chorale_model.infection_probability())+np.std(chorale_model.infection_probability())) -#print(np.quantile(chorale_model.infection_probability(),0.8)) +#print(np.quantile(chorale_model[0].infection_probability(),0.8)) #print(np.quantile(chorale_model.infection_probability(),0.90)) #print(np.quantile(chorale_model.infection_probability(),0.1)) @@ -27,20 +20,20 @@ from cara.model_scenarios import * # time_in_minutes=True, # normalize_y_axis=True) -compare_viruses_qr(violins=True) +#compare_viruses_qr(violins=True) -# print_qd_info(large_population_baselines[0]) +#print_qd_info(waiting_room_model_full_winter[1]) #print(np.mean(shared_office_model[1].infection_probability())) #composite_plot_pi_vs_viral_load([shared_office_worst_model[1], shared_office_model[1], shared_office_better_model[1]], # labels=['No mask &\nwindows closed', 'Baseline:Windows\nopen (10min/2h)', 'Windows open\n(10min/2h) +\nHEPA filter'], # colors=['tomato', '#1f77b4', 'limegreen'], -# title='Shared office scenario', +# title='', # vl_points=200) #composite_plot_pi_vs_viral_load([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1], classroom_model_full_open_multi_masks[1]], # labels=['Windows closed', 'Baseline:Windows\nopen (10min/2h)', 'Windows open\n(10min/2h) + HEPA', 'Multiple windows open', 'Multiple windows open\n+masks'], # colors=['tomato','#1f77b4', 'dodgerblue', 'seagreen', 'limegreen'], -# title='Classroom scenario', +# title='', # vl_points=200) #composite_plot_pi_vs_viral_load([ski_cabin_model_60[1], ski_cabin_model_30[1], ski_cabin_model_baseline_20[1], ski_cabin_model_10[1]], @@ -56,16 +49,16 @@ compare_viruses_qr(violins=True) # vl_points=200) #compare_concentration_curves([classroom_model_no_vent[1], classroom_model[1], classroom_model_with_hepa[1], classroom_model_full_open_multi[1]], -# labels=['Windows closed', 'Baseline:(windows 10min/2h)', 'Baseline:(windows 10min/2h) + HEPA', 'Multiple windows open'], +# labels=['Windows closed', 'Baseline: Windows open (10min/2h)', 'Windows open (10min/2h) + HEPA', 'Multiple windows open'], # colors=['tomato','#1f77b4', 'seagreen', 'limegreen'], -# title='Classroom scenario' +# title='' # ) - +# #compare_concentration_curves([waiting_room_model[1], waiting_room_model_full_summer[1], # waiting_room_model_full_winter[1], waiting_room_model_periodic_winter[1]], -# labels=['Baseline:(windows closed)', 'Windows open (summer)', 'Windows open (winter)', 'Windows open 5min/20min (winter)'], +# labels=['Baseline: Windows closed', 'Windows open (summer)', 'Windows open (winter)', 'Windows open 5min/20min (winter)'], # colors=['#1f77b4', 'darkorange', 'deepskyblue', 'lightskyblue'], -# title='Waiting room scenario' +# title='' # ) #plot_pi_vs_viral_load([shared_office_model[1]], labels=['Baseline'],title='') @@ -98,3 +91,9 @@ compare_viruses_qr(violins=True) # plt.title(f'Probability of infection in baseline case - {"English" if model.concentration_model.infected.qid == 60 else "Original"} variant') # plt.yticks([], []) # plt.show() + +#composite_plot_pi_vs_viral_load([shared_office_worst_model[1], shared_office_worst_model_infiltration[1]], +# labels=['No mask &\nwindows closed', 'Baseline:Windows\nopen (10min/2h)', 'Windows open\n(10min/2h) +\nHEPA filter'], +# colors=['tomato', '#1f77b4', 'limegreen'], +# title='Shared office scenario', +# vl_points=200)