added methods to generate CO2 model

caimira/apps/calculator/model_generator.py

@@ -304,9 +304,8 @@ class FormData:
                     
             if total_percentage != 100:
                 raise ValueError(f'The sum of all respiratory activities should be 100. Got {total_percentage}.')
-        
-
-    def build_mc_model(self) -> mc.ExposureModel:
+    
+    def initialize_room(self) -> models.Room:
         # Initializes room with volume either given directly or as product of area and height
         if self.volume_type == 'room_volume_explicit':
             volume = self.room_volume
@@ -323,7 +322,10 @@ class FormData:
             humidity = float(self.humidity)
             inside_temp = self.inside_temp
 
-        room = models.Room(volume=volume, inside_temp=models.PiecewiseConstant((0, 24), (inside_temp,)), humidity=humidity)
+        return models.Room(volume=volume, inside_temp=models.PiecewiseConstant((0, 24), (inside_temp,)), humidity=humidity)
+
+    def build_mc_model(self) -> mc.ExposureModel:
+        room = self.initialize_room()        
 
         infected_population = self.infected_population()
         
@@ -357,6 +359,21 @@ class FormData:
     def build_model(self, sample_size=DEFAULT_MC_SAMPLE_SIZE) -> models.ExposureModel:
         return self.build_mc_model().build_model(size=sample_size)
 
+    def build_CO2_model(self, sample_size=DEFAULT_MC_SAMPLE_SIZE) -> models.CO2ConcentrationModel:
+        population = mc.Population(
+            number=self.total_people,
+            presence=self.infected_present_interval(),
+            mask=models.Mask.types[self.mask_type],
+            activity=activity_distributions[ACTIVITIES[ACTIVITY_TYPES.index(self.activity_type)]['activity']],
+            host_immunity=0.,
+        )
+        # Builds a CO2 concentration model based on model inputs
+        return mc.CO2ConcentrationModel(
+            room=self.initialize_room(),
+            ventilation=self.ventilation(),
+            CO2_emitters=population,
+        ).build_model(size=sample_size)
+
     def tz_name_and_utc_offset(self) -> typing.Tuple[str, float]:
         """
         Return the timezone name (e.g. CET), and offset, in hours, that need to

caimira/apps/calculator/report_generator.py

@@ -133,7 +133,13 @@ def calculate_report_data(form: FormData, model: models.ExposureModel) -> typing
         for time1, time2 in zip(times[:-1], times[1:])
     ])
 
-    prob = np.array(model.infection_probability())
+    CO2_model: models.CO2ConcentrationModel = form.build_CO2_model()
+    CO2_concentrations = [
+        np.array(CO2_model.concentration(float(time))).mean()
+        for time in times
+    ]
+    
+    prob = np.array(model.infection_probability()).mean()
     prob_dist_count, prob_dist_bins = np.histogram(prob/100, bins=100, density=True)
     prob_probabilistic_exposure = np.array(model.total_probability_rule()).mean()
     expected_new_cases = np.array(model.expected_new_cases()).mean()
@@ -158,6 +164,7 @@ def calculate_report_data(form: FormData, model: models.ExposureModel) -> typing
         "prob_probabilistic_exposure": prob_probabilistic_exposure,
         "expected_new_cases": expected_new_cases,
         "uncertainties_plot_src": uncertainties_plot_src,
+        "CO2_concentrations": CO2_concentrations,
     }