From ca786d7e7fb2bcad8ab681ca354b959167128eaf Mon Sep 17 00:00:00 2001
From: Luis Aleixo <luis.aleixo@cern.ch>
Date: Tue, 30 May 2023 11:04:38 +0200
Subject: [PATCH] added results with different viral load values

---
 caimira/apps/calculator/report_generator.py   | 43 +++++++++++++++++++
 .../templates/base/calculator.report.html.j2  | 19 ++++++++
 2 files changed, 62 insertions(+)

diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py
index 7beb5fee..873d0c0c 100644
--- a/caimira/apps/calculator/report_generator.py
+++ b/caimira/apps/calculator/report_generator.py
@@ -139,6 +139,7 @@ def calculate_report_data(form: FormData, model: models.ExposureModel) -> typing
     expected_new_cases = np.array(model.expected_new_cases()).mean()
     uncertainties_plot_src = img2base64(_figure2bytes(uncertainties_plot(model))) if form.conditional_probability_plot else None
     exposed_presence_intervals = [list(interval) for interval in model.exposed.presence_interval().boundaries()]
+    manufacture_viral_load_scenarios(model)
 
     return {
         "model_repr": repr(model),
@@ -302,6 +303,18 @@ def non_zero_percentage(percentage: int) -> str:
         return "99.9%"
     else:
         return "{:0.1f}%".format(percentage)
+    
+
+def manufacture_viral_load_scenarios(model: mc.ExposureModel) -> typing.Dict[str, mc.ExposureModel]:
+    viral_load = model.concentration_model.infected.virus.viral_load_in_sputum
+    viral_load_values = [np.quantile(viral_load, percentil) for percentil in (0.05, 0.5, 0.95)]
+    scenarios = {}
+    for vl in viral_load_values:
+        specific_vl_scenario = dataclass_utils.nested_replace(model, 
+            {'concentration_model.infected.virus.viral_load_in_sputum': vl}
+        )
+        scenarios[str(round(np.log10(vl), 1))] = specific_vl_scenario
+    return scenarios
 
 
 def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.ExposureModel]:
@@ -374,6 +387,32 @@ def scenario_statistics(mc_model: mc.ExposureModel, sample_times: typing.List[fl
     }
 
 
+def comparison_report_viral_load(
+        report_data: typing.Dict[str, typing.Any],
+        scenarios: typing.Dict[str, mc.ExposureModel],
+):  
+    statistics = {
+        # 'Current scenario' : {
+        #     'probability_of_infection': report_data['prob_inf'],
+        #     'expected_new_cases': report_data['expected_new_cases'],
+        # }
+    }
+
+    results = []
+    for mc_model in scenarios.values():
+        results.append({
+            'probability_of_infection': np.mean(mc_model.infection_probability()),
+            'expected_new_cases': np.mean(mc_model.expected_new_cases()),
+        })
+
+    for (name, model), model_stats in zip(scenarios.items(), results):
+        statistics[name] = model_stats
+
+    return {
+        'stats': statistics,
+    }
+
+
 def comparison_report(
         form: FormData,
         report_data: typing.Dict[str, typing.Any],
@@ -449,7 +488,11 @@ class ReportGenerator:
         scenario_sample_times = interesting_times(model)
         report_data = calculate_report_data(form, model)
         context.update(report_data)
+        alternative_viral_loads = manufacture_viral_load_scenarios(model)
         alternative_scenarios = manufacture_alternative_scenarios(form)
+        context['alternative_viral_load'] = comparison_report_viral_load(
+            report_data, alternative_viral_loads
+        )
         context['alternative_scenarios'] = comparison_report(
             form, report_data, alternative_scenarios, scenario_sample_times, executor_factory=executor_factory,
         )
diff --git a/caimira/apps/templates/base/calculator.report.html.j2 b/caimira/apps/templates/base/calculator.report.html.j2
index 020d40b5..ffc7644f 100644
--- a/caimira/apps/templates/base/calculator.report.html.j2
+++ b/caimira/apps/templates/base/calculator.report.html.j2
@@ -161,6 +161,25 @@
 									{% block report_summary_footnote %}
 									{% endblock report_summary_footnote %}
 								</div>
+								<br>
+								<table class="table w-auto">
+									<thead class="thead-light">
+										<tr>
+											<th>Scenario</th>
+											<th>P(I)</th>
+											<th>Expected new cases</th>
+										</tr>
+									</thead>
+									<tbody>
+									{% for scenario_name, scenario_stats in alternative_viral_load.stats.items() %}
+										<tr>
+											<td> Viral load: 10<sup>{{ scenario_name }}</sup></td>
+											<td> {{ scenario_stats.probability_of_infection | non_zero_percentage }}</td>
+											<td style="text-align:right">{{ scenario_stats.expected_new_cases | float_format }}</td>
+										</tr>
+									{% endfor %}
+									</tbody>
+								</table>
 								<br><p id="section1">* The results are based on the parameters and assumptions published in the CARA publication: <a href="https://doi.org/10.1098/rsfs.2021.0076"> doi.org/10.1098/rsfs.2021.0076</a>.</p><br>
 								{% if form.short_range_option == "short_range_yes" %}
 									{% if 'Speaking' in form.short_range_interactions|string or 'Shouting' in form.short_range_interactions|string %}