From 6e223050fbcd4ddd57ebe9137c66ab72970650b1 Mon Sep 17 00:00:00 2001 From: Andre Henriques Date: Fri, 4 Jun 2021 13:08:03 +0000 Subject: [PATCH 1/3] update C(t) plot labels --- cara/apps/calculator/report_generator.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/cara/apps/calculator/report_generator.py b/cara/apps/calculator/report_generator.py index 6cead28c..8ae90534 100644 --- a/cara/apps/calculator/report_generator.py +++ b/cara/apps/calculator/report_generator.py @@ -128,13 +128,13 @@ def plot(times, concentrations, model: models.ExposureModel): fig = plt.figure() ax = fig.add_subplot(1, 1, 1) datetimes = [datetime(1970, 1, 1) + timedelta(hours=time) for time in times] - ax.plot(datetimes, concentrations, lw=2, color='#1f77b4', label='Concentration') + ax.plot(datetimes, concentrations, lw=2, color='#1f77b4', label='Mean concentration') ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) ax.set_xlabel('Time of day') - ax.set_ylabel('Concentration ($q/m^3$)') - ax.set_title('Concentration of infectious quanta') + ax.set_ylabel('Mean concentration ($q/m^3$)') + ax.set_title('Mean concentration of infectious quanta') ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter("%H:%M")) # Plot presence of exposed person From 8dc8e8f42ab64d6bf3e62e8abe35682b4e3c1653 Mon Sep 17 00:00:00 2001 From: Andre Henriques Date: Fri, 4 Jun 2021 13:17:45 +0000 Subject: [PATCH 2/3] delete 'Exposure Graph' title --- .../calculator/templates/base/calculator.report.html.j2 | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/cara/apps/calculator/templates/base/calculator.report.html.j2 b/cara/apps/calculator/templates/base/calculator.report.html.j2 index 4896ebf0..174a85eb 100644 --- a/cara/apps/calculator/templates/base/calculator.report.html.j2 +++ b/cara/apps/calculator/templates/base/calculator.report.html.j2 @@ -210,11 +210,11 @@

{% block report_summary %} Taking into account the uncertainties tied to the model variables, in this scenario, the probability of one exposed occupant getting infected P(i) is {{ prob_inf | non_zero_percentage }}[*] and the expected number of new cases is {{ expected_new_cases | float_format }}. -

[*] The results are based on the parameters and assumptions published in the CERN Open Report CERN-OPEN-2021-004

+

[*] The results are based on the parameters and assumptions published in the CERN Open Report CERN-OPEN-2021-004

{% endblock report_summary %}

-

Exposure graph:

- + +

Alternative scenarios:

From 30923e490fc4ecf0d0942a1dd8d0f3e1431b1137 Mon Sep 17 00:00:00 2001 From: Andre Henriques Date: Fri, 4 Jun 2021 13:25:52 +0000 Subject: [PATCH 3/3] text edit in alternative scenario notes --- cara/apps/calculator/templates/base/calculator.report.html.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/cara/apps/calculator/templates/base/calculator.report.html.j2 b/cara/apps/calculator/templates/base/calculator.report.html.j2 index 174a85eb..58a4096e 100644 --- a/cara/apps/calculator/templates/base/calculator.report.html.j2 +++ b/cara/apps/calculator/templates/base/calculator.report.html.j2 @@ -246,7 +246,7 @@

Notes for alternative scenarios:

  1. This graph shows the concentration of infectious quanta in the air. The filtration of Type I and FFP2 masks, if worn, applies not only to the emission rate but also to the individual exposure (i.e. inhalation). - For this reason, scenarios with different types of mask will show the same concentration on the graph but have different Pi values.
    2. + For this reason, scenarios with different types of mask will show the same concentration on the graph but have different absorbed doses and infection probabilities.
  2. If you have selected more sophisticated options, such as HEPA filtration or FFP2 masks, this will be indicated in the plot as the "base scenario", representing the inputs inserted in the form.
    The other alternative scenarios shown for comparison will not include either HEPA filtration or FFP2 masks.