Consideration on the time the first person (either infected or exposed)...

Consideration on the time the first person (either infected or exposed) arrives at the enclosed space

cara/apps/calculator/model_generator.py

@@ -301,11 +301,11 @@ class FormData:
         return outside_temp
 
     def ventilation(self) -> models._VentilationBase:
-        always_on = models.PeriodicInterval(period=120, duration=120)
+        always_on = models.PeriodicInterval(period=120, duration=120, start=0)
         # Initializes a ventilation instance as a window if 'natural_ventilation' is selected, or as a HEPA-filter otherwise
         if self.ventilation_type == 'natural_ventilation':
             if self.window_opening_regime == 'windows_open_periodically':
-                window_interval = models.PeriodicInterval(self.windows_frequency, self.windows_duration)
+                window_interval = models.PeriodicInterval(self.windows_frequency, self.windows_duration, min(self.infected_start, self.exposed_start))
             else:
                 window_interval = always_on
 

cara/apps/expert.py

@@ -487,7 +487,7 @@ baseline_model = models.ExposureModel(
     concentration_model=models.ConcentrationModel(
         room=models.Room(volume=75),
         ventilation=models.SlidingWindow(
-            active=models.PeriodicInterval(period=120, duration=15),
+            active=models.PeriodicInterval(period=120, duration=15, start=8),
             inside_temp=models.PiecewiseConstant((0., 24.), (293.15,)),
             outside_temp=models.PiecewiseConstant((0., 24.), (283.15,)),
             window_height=1.6, opening_length=0.6,
@@ -540,7 +540,7 @@ class CARAStateBuilder(state.StateBuilder):
         )
         # Initialise the HVAC state
         s._states['Mechanical'].dcs_update_from(
-            models.HVACMechanical(models.PeriodicInterval(period=24*60, duration=24*60), 500.)
+            models.HVACMechanical(models.PeriodicInterval(period=24*60, duration=24*60, start=0), 500.)
         )
         return s
 

cara/models.py

@@ -124,12 +124,15 @@ class PeriodicInterval(Interval):
     #: A value greater than :data:`period` signifies the event is permanently
     #: occurring, a value of 0 signifies that the event never happens.
     duration: float
-
+    
+    #: Time at which the first person (infected or exposed) arrives at the enclosed space.
+    start: float
+    
     def boundaries(self) -> BoundarySequence_t:
         if self.period == 0 or self.duration == 0:
             return tuple()
         result = []
-        for i in np.arange(0, 24, self.period / 60):
+        for i in np.arange(self.start, 24, self.period / 60):
             # NOTE: It is important that the time type is float, not np.float, in
             # order to allow hashability (for caching).
             result.append((float(i), float(i+self.duration/60)))

cara/tests/apps/calculator/test_model_generator.py

@@ -59,14 +59,14 @@ def test_ventilation_slidingwindow(baseline_form: model_generator.FormData):
     assert isinstance(baseline_window, models.SlidingWindow)
 
     window = models.SlidingWindow(
-        active=models.PeriodicInterval(period=120, duration=10),
+        active=models.PeriodicInterval(period=120, duration=10, start=minutes_since_midnight(9 * 60)),
         inside_temp=models.PiecewiseConstant((0, 24), (293,)),
         outside_temp=baseline_window.outside_temp,
         window_height=1.6, opening_length=0.6,
     )
 
     ach = models.AirChange(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         air_exch=0.25,
     )
     ventilation = models.MultipleVentilation((window, ach))
@@ -91,13 +91,13 @@ def test_ventilation_hingedwindow(baseline_form: model_generator.FormData):
     assert isinstance(baseline_window, models.HingedWindow)
 
     window = models.HingedWindow(
-        active=models.PeriodicInterval(period=120, duration=10),
+        active=models.PeriodicInterval(period=120, duration=10, start=minutes_since_midnight(9 * 60)),
         inside_temp=models.PiecewiseConstant((0, 24), (293,)),
         outside_temp=baseline_window.outside_temp,
         window_height=1.6, window_width=1., opening_length=0.6,
     )
     ach = models.AirChange(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         air_exch=0.25,
     )
     ventilation = models.MultipleVentilation((window, ach))
@@ -108,7 +108,7 @@ def test_ventilation_hingedwindow(baseline_form: model_generator.FormData):
 def test_ventilation_mechanical(baseline_form: model_generator.FormData):
     room = models.Room(75)
     mech = models.HVACMechanical(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         q_air_mech=500.,
     )
     baseline_form.ventilation_type = 'mechanical_ventilation'
@@ -123,7 +123,7 @@ def test_ventilation_mechanical(baseline_form: model_generator.FormData):
 def test_ventilation_airchanges(baseline_form: model_generator.FormData):
     room = models.Room(75)
     airchange = models.AirChange(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         air_exch=3.,
     )
     baseline_form.ventilation_type = 'mechanical_ventilation'
@@ -152,17 +152,17 @@ def test_ventilation_window_hepa(baseline_form: model_generator.FormData):
 
     # Now build the equivalent ventilation instance directly, and compare.
     window = models.SlidingWindow(
-        active=models.PeriodicInterval(period=120, duration=10),
+        active=models.PeriodicInterval(period=120, duration=10, start=minutes_since_midnight(9 * 60)),
         inside_temp=models.PiecewiseConstant((0, 24), (293,)),
         outside_temp=baseline_window.outside_temp,
         window_height=1.6, opening_length=0.6,
     )
     hepa = models.HEPAFilter(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         q_air_mech=250.,
     )
     ach = models.AirChange(
-        active=models.PeriodicInterval(period=120, duration=120),
+        active=models.PeriodicInterval(period=120, duration=120, start=0),
         air_exch=0.25,
     )
     ventilation = models.MultipleVentilation((window, hepa, ach))

cara/tests/conftest.py

@@ -48,7 +48,7 @@ def exposure_model_w_outside_temp_changes(baseline_exposure_model: models.Exposu
     exp_model = cara.dataclass_utils.nested_replace(
         baseline_exposure_model, {
             'concentration_model.ventilation': models.SlidingWindow(
-                active=models.PeriodicInterval(2.2 * 60, 1.8 * 60),
+                active=models.PeriodicInterval(2.2 * 60, 1.8 * 60, 0),
                 inside_temp=models.PiecewiseConstant((0., 24.), (293,)),
                 outside_temp=cara.data.GenevaTemperatures['Jan'],
                 window_height=1.6,

cara/tests/models/test_concentration_model.py

@@ -24,7 +24,7 @@ def test_concentration_model_vectorisation(override_params):
     }
     defaults.update(override_params)
 
-    always = models.PeriodicInterval(240, 240)  # TODO: This should be a thing on an interval.
+    always = models.PeriodicInterval(240, 240, 0)  # TODO: This should be a thing on an interval.
     c_model = models.ConcentrationModel(
         models.Room(defaults['volume'], defaults['humidity']),
         models.AirChange(always, defaults['air_change']),

cara/tests/models/test_exposure_model.py

@@ -36,7 +36,7 @@ class KnownNormedconcentration(models.ConcentrationModel):
         return self.normed_concentration_function(time)
 
 
-halftime = models.PeriodicInterval(120, 60)
+halftime = models.PeriodicInterval(120, 60, 0)
 populations = [
     # A simple scalar population.
     models.Population(

cara/tests/test_known_quantities.py

@@ -18,7 +18,7 @@ def test_no_mask_superspeading_emission_rate(baseline_model):
 @pytest.fixture
 def baseline_periodic_window():
     return models.SlidingWindow(
-        active=models.PeriodicInterval(period=120, duration=15),
+        active=models.PeriodicInterval(period=120, duration=15, start=0),
         inside_temp=models.PiecewiseConstant((0., 24.), (293,)),
         outside_temp=models.PiecewiseConstant((0., 24.), (283,)),
         window_height=1.6, opening_length=0.6,
@@ -33,7 +33,7 @@ def baseline_room():
 @pytest.fixture
 def baseline_periodic_hepa():
     return models.HEPAFilter(
-        active=models.PeriodicInterval(period=120, duration=15),
+        active=models.PeriodicInterval(period=120, duration=15, start=0),
         q_air_mech=514.74,
     )
 
@@ -63,7 +63,7 @@ def build_model(interval_duration):
     model = models.ConcentrationModel(
         room=models.Room(volume=75),
         ventilation=models.HEPAFilter(
-            active=models.PeriodicInterval(period=120, duration=interval_duration),
+            active=models.PeriodicInterval(period=120, duration=interval_duration, start=0),
             q_air_mech=500.,
         ),
         infected=models.EmittingPopulation(

cara/tests/test_monte_carlo.py

@@ -42,7 +42,7 @@ def baseline_mc_model() -> cara.monte_carlo.ConcentrationModel:
     mc_model = cara.monte_carlo.ConcentrationModel(
         room=cara.monte_carlo.Room(volume=cara.monte_carlo.sampleable.Normal(75, 20)),
         ventilation=cara.monte_carlo.SlidingWindow(
-            active=cara.models.PeriodicInterval(period=120, duration=120),
+            active=cara.models.PeriodicInterval(period=120, duration=120, start=0),
             inside_temp=cara.models.PiecewiseConstant((0., 24.), (293,)),
             outside_temp=cara.models.PiecewiseConstant((0., 24.), (283,)),
             window_height=1.6, opening_length=0.6,

cara/tests/test_monte_carlo_full_models.py

@@ -25,13 +25,13 @@ def shared_office_mc():
         ventilation = models.MultipleVentilation(
             ventilations=(
                 models.SlidingWindow(
-                    active=models.PeriodicInterval(period=120, duration=120),
+                    active=models.PeriodicInterval(period=120, duration=120, start=0),
                     inside_temp=models.PiecewiseConstant((0., 24.), (298,)),
                     outside_temp=data.GenevaTemperatures['Jun'],
                     window_height=1.6,
                     opening_length=0.2,
                 ),
-                models.AirChange(active=models.PeriodicInterval(period=120, duration=120), air_exch=0.25),
+                models.AirChange(active=models.PeriodicInterval(period=120, duration=120, start=0), air_exch=0.25),
             )
         ),
         infected=mc.InfectedPopulation(
@@ -67,13 +67,13 @@ def classroom_mc():
         ventilation = models.MultipleVentilation(
             ventilations=(
                 models.SlidingWindow(
-                    active=models.PeriodicInterval(period=120, duration=120),
+                    active=models.PeriodicInterval(period=120, duration=120, start=0),
                     inside_temp=models.PiecewiseConstant((0., 24.), (293,)),
                     outside_temp=data.TorontoTemperatures['Dec'],
                     window_height=1.6,
                     opening_length=0.2,
                 ),
-                models.AirChange(active=models.PeriodicInterval(period=120, duration=120), air_exch=0.25),
+                models.AirChange(active=models.PeriodicInterval(period=120, duration=120, start=0), air_exch=0.25),
             )
         ),
         infected=mc.InfectedPopulation(
@@ -107,8 +107,8 @@ def ski_cabin_mc():
     concentration_mc = mc.ConcentrationModel(
         room=models.Room(volume=10, humidity=0.3),
         ventilation=models.MultipleVentilation(
-            (models.AirChange(active=models.PeriodicInterval(period=120, duration=120), air_exch=0.0),
-            models.AirChange(active=models.PeriodicInterval(period=120, duration=120), air_exch=0.25))),
+            (models.AirChange(active=models.PeriodicInterval(period=120, duration=120, start=0), air_exch=0.0),
+            models.AirChange(active=models.PeriodicInterval(period=120, duration=120, start=0), air_exch=0.25))),
         infected=mc.InfectedPopulation(
             number=1,
             presence=models.SpecificInterval(((0, 20/60),)),
@@ -141,7 +141,7 @@ def skagit_chorale_mc():
     concentration_mc = mc.ConcentrationModel(
         room=models.Room(volume=810, humidity=0.5),
             ventilation=models.AirChange(
-                active=models.PeriodicInterval(period=120, duration=120),
+                active=models.PeriodicInterval(period=120, duration=120, start=0),
                 air_exch=0.7),
             infected=mc.InfectedPopulation(
                 number=1,
@@ -180,7 +180,7 @@ def bus_ride_mc():
     concentration_mc = mc.ConcentrationModel(
         room=models.Room(volume=45, humidity=0.5),
             ventilation=models.AirChange(
-                active=models.PeriodicInterval(period=120, duration=120),
+                active=models.PeriodicInterval(period=120, duration=120, start=0),
                 air_exch=1.25),
             infected=mc.InfectedPopulation(
                 number=1,

cara/tests/test_ventilation.py

@@ -79,7 +79,7 @@ def test_hinged_window_vectorisation(override_params):
     defaults.update(override_params)
     room = models.Room(volume=75)
     t = 0.5
-    window = models.HingedWindow(models.PeriodicInterval(60, 30), **defaults)
+    window = models.HingedWindow(models.PeriodicInterval(60, 30, 0), **defaults)
     if {'window_height', 'opening_length', 'window_width'}.intersection(override_params):
         assert isinstance(window.discharge_coefficient, np.ndarray)
     else: