Reverting to a refinement factor of 4 in the time-dependence of Geneva temperature; optimizing the caching; decreasing the timeout value in tests

cara/data.py

@@ -38,7 +38,7 @@ GenevaTemperatures_hourly = {
 }
 # same temperatures on a finer temperature mesh
 GenevaTemperatures = {
-    month: GenevaTemperatures_hourly[month].refine(refine_factor=10)
+    month: GenevaTemperatures_hourly[month].refine(refine_factor=4)
     for month,temperatures in Geneva_hourly_temperatures_celsius_per_hour.items()
 }
 

cara/models.py

@@ -711,7 +711,6 @@ class InfectedPopulation(Population):
 
         return self.emission_rate_when_present()
 
-    @cached()
     def emission_rate(self, time) -> _VectorisedFloat:
         """
         The emission rate of the entire population.
@@ -741,7 +740,6 @@ class ConcentrationModel:
         return k + self.virus.decay_constant(self.room.humidity
                     ) + self.ventilation.air_exchange(self.room, time)
 
-    @cached()
     def _concentration_limit(self, time: float) -> _VectorisedFloat:
         """
         Provides a constant that represents the theoretical asymptotic 
@@ -753,7 +751,6 @@ class ConcentrationModel:
 
         return (self.infected.emission_rate(time)) / (IVRR * V)
 
-    @cached()
     def state_change_times(self):
         """
         All time dependent entities on this model must provide information about
@@ -798,6 +795,9 @@ class ConcentrationModel:
         return (self.last_state_change(stop) <= start)
 
     @cached()
+    def _concentration_at_state_change(self, time: float) -> _VectorisedFloat:
+        return self.concentration(time)
+
     def concentration(self, time: float) -> _VectorisedFloat:
         """
         Virus quanta concentration, as a function of time.
@@ -816,7 +816,7 @@ class ConcentrationModel:
         concentration_limit = self._concentration_limit(next_state_change_time)
 
         t_last_state_change = self.last_state_change(time)
-        concentration_at_last_state_change = self.concentration(t_last_state_change)
+        concentration_at_last_state_change = self._concentration_at_state_change(t_last_state_change)
 
         delta_time = time - t_last_state_change
         fac = np.exp(-IVRR * delta_time)

cara/tests/apps/calculator/test_report_generator.py

@@ -11,7 +11,7 @@ def test_generate_report(baseline_form):
     # generate a report for it. Because this is what happens in the cara
     # calculator, we confirm that the generation happens within a reasonable
     # time threshold.
-    time_limit: float = 30.0  # seconds
+    time_limit: float = 20.0  # seconds
 
     start = time.perf_counter()
 

cara/tests/apps/calculator/test_webapp.py

@@ -6,7 +6,7 @@ import tornado.testing
 import cara.apps.calculator
 from cara.apps.calculator.report_generator import generate_qr_code
 
-_TIMEOUT = 30.
+_TIMEOUT = 20.
 
 @pytest.fixture
 def app():

cara/tests/test_known_quantities.py

@@ -394,4 +394,4 @@ def test_quanta_hourly_dep_refined(month,expected_quanta):
         )
     )
     quanta = m.quanta_exposure()
-    npt.assert_allclose(quanta, expected_quanta, rtol=0.01)
+    npt.assert_allclose(quanta, expected_quanta, rtol=0.02)