Adding _VectorisedFloat types in ExposureModel outputs and for eta_inhale of Mask

cara/models.py

@@ -460,7 +460,7 @@ class Mask:
     η_leaks: _VectorisedFloat
 
     #: Filtration efficiency of masks when inhaling.
-    η_inhale: float
+    η_inhale: _VectorisedFloat
 
     #: Particle sizes in cm.
     particle_sizes: typing.Tuple[float, float, float, float] = (
@@ -695,7 +695,7 @@ class ExposureModel:
     #: The number of times the exposure event is repeated (default 1).
     repeats: int = 1
 
-    def quanta_exposure(self) -> float:
+    def quanta_exposure(self) -> _VectorisedFloat:
         """The number of virus quanta per meter^3."""
         exposure = 0.0
 
@@ -707,7 +707,7 @@ class ExposureModel:
             exposure += integrate(self.concentration_model.concentration, start, stop)
         return exposure * self.repeats
 
-    def infection_probability(self):
+    def infection_probability(self) -> _VectorisedFloat:
         exposure = self.quanta_exposure()
 
         inf_aero = (
@@ -719,12 +719,12 @@ class ExposureModel:
         # Probability of infection.
         return (1 - np.exp(-inf_aero)) * 100
 
-    def expected_new_cases(self):
+    def expected_new_cases(self) -> _VectorisedFloat:
         prob = self.infection_probability()
         exposed_occupants = self.exposed.number
         return prob * exposed_occupants / 100
 
-    def reproduction_number(self):
+    def reproduction_number(self) -> _VectorisedFloat:
         """
         The reproduction number can be thought of as the expected number of
         cases directly generated by one infected case in a population.