added room_capacity as optional (and therefore results in l/s/p)

caimira/apps/calculator/co2_model_generator.py

@@ -22,7 +22,7 @@ class CO2FormData(FormData):
     CO2_data: dict
     fitting_ventilation_states: list
     fitting_ventilation_type: str
-    room_capacity: int
+    room_capacity: typing.Optional[int]
 
     #: The default values for undefined fields. Note that the defaults here
     #: and the defaults in the html form must not be contradictory.
@@ -46,7 +46,7 @@ class CO2FormData(FormData):
         'infected_lunch_start': '12:30',
         'infected_people': 1,
         'infected_start': '08:30',
-        'room_capacity': 10,
+        'room_capacity': None,
         'room_volume': NO_DEFAULT,
         'specific_breaks': '{}',
         'total_people': NO_DEFAULT,
@@ -65,10 +65,11 @@ def validate(self):
         self.validate_population_parameters()
 
         # Validate room capacity
-        if type(self.room_capacity) is not int:
-            raise TypeError(f'The room capacity should be a valid integer (> 0). Got {type(self.room_capacity)}.')
-        if self.room_capacity <= 0:
-            raise TypeError(f'The room capacity should be a valid integer (> 0). Got {self.room_capacity}.')
+        if self.room_capacity:
+            if type(self.room_capacity) is not int:
+                raise TypeError(f'The room capacity should be a valid integer (> 0). Got {type(self.room_capacity)}.')
+            if self.room_capacity <= 0:
+                raise TypeError(f'The room capacity should be a valid integer (> 0). Got {self.room_capacity}.')
 
         # Validate specific inputs - breaks (exposed and infected)
         if self.specific_breaks != {}:

caimira/apps/calculator/form_data.py

@@ -410,6 +410,12 @@ def _safe_int_cast(value) -> int:
         return int(value)
     else:
         raise TypeError(f"Unable to safely cast {value} ({type(value)} type) to int")
+
+
+def _safe_optional_int_cast(value) -> typing.Optional[int]:
+    if value is None or value == '':
+        return None
+    return _safe_int_cast(value)
 
 
 #: Mapping of field name to a callable which can convert values from form
@@ -427,6 +433,8 @@ def cast_class_fields(cls):
             _CAST_RULES_NATIVE_TO_FORM_ARG[_field.name] = time_minutes_to_string
         elif _field.type is int:
             _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = _safe_int_cast
+        elif _field.type is typing.Optional[int]:
+            _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = _safe_optional_int_cast
         elif _field.type is float:
             _CAST_RULES_FORM_ARG_TO_NATIVE[_field.name] = float
         elif _field.type is bool:

caimira/models.py

@@ -218,7 +218,7 @@ class Room:
     humidity: _VectorisedFloat = 0.5
 
     #: The maximum occupation of the room - design limit
-    capacity: float = 10
+    capacity: typing.Optional[int] = None
 
 
 @dataclass(frozen=True)
@@ -1596,11 +1596,10 @@ def fun(x):
         the_predictive_CO2 = self.CO2_concentrations_from_params(the_CO2_concentration_model)
 
         # Ventilation in L/s
-        flow_rates_l_s = [vent / 3600 * self.room.volume * 1000 
-                                    for vent in ventilation_values] # 1m^3 = 1000L
+        flow_rates_l_s = [vent / 3600 * self.room.volume * 1000 for vent in ventilation_values] # 1m^3 = 1000L
 
         # Ventilation in L/s/person
-        flow_rates_l_s_p = [flow_rate / self.room.capacity for flow_rate in flow_rates_l_s]
+        flow_rates_l_s_p = [flow_rate / self.room.capacity for flow_rate in flow_rates_l_s] if self.room.capacity else None
 
         return {
             "exhalation_rate": exhalation_rate,