diff --git a/caimira/apps/calculator/co2_model_generator.py b/caimira/apps/calculator/co2_model_generator.py
index 3544fe54..51a950b2 100644
--- a/caimira/apps/calculator/co2_model_generator.py
+++ b/caimira/apps/calculator/co2_model_generator.py
@@ -22,6 +22,7 @@ class CO2FormData(FormData):
CO2_data: dict
fitting_ventilation_states: list
fitting_ventilation_type: str
+ room_capacity: int
#: The default values for undefined fields. Note that the defaults here
#: and the defaults in the html form must not be contradictory.
@@ -45,6 +46,7 @@ class CO2FormData(FormData):
'infected_lunch_start': '12:30',
'infected_people': 1,
'infected_start': '08:30',
+ 'room_capacity': 10,
'room_volume': NO_DEFAULT,
'specific_breaks': '{}',
'total_people': NO_DEFAULT,
@@ -62,6 +64,14 @@ class CO2FormData(FormData):
# Validate population parameters
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 < self.total_people:
+ raise TypeError(f'The room capacity should be higher than the total people in the room. Got {self.room_capacity}.')
+
# Validate specific inputs - breaks (exposed and infected)
if self.specific_breaks != {}:
if type(self.specific_breaks) is not dict:
@@ -181,6 +191,7 @@ class CO2FormData(FormData):
return models.CO2DataModel(
data_registry=self.data_registry,
+ room_capacity=self.room_capacity,
room_volume=self.room_volume,
occupancy=models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people)),
ventilation_transition_times=self.ventilation_transition_times(),
diff --git a/caimira/apps/calculator/static/js/co2_form.js b/caimira/apps/calculator/static/js/co2_form.js
index fb45044b..5b8d4a2c 100644
--- a/caimira/apps/calculator/static/js/co2_form.js
+++ b/caimira/apps/calculator/static/js/co2_form.js
@@ -19,6 +19,7 @@ const CO2_data_form = [
"infected_lunch_start",
"infected_people",
"infected_start",
+ "room_capacity",
"room_volume",
"specific_breaks",
"total_people",
@@ -137,6 +138,7 @@ function generateJSONStructure(endpoint, jsonData) {
$("#generate_fitting_data").prop("disabled", false);
$("#fitting_ventilation_states").prop("disabled", false);
$("[name=fitting_ventilation_type]").prop("disabled", false);
+ $("#room_capacity").prop("disabled", false);
plotCO2Data(endpoint);
}
}
@@ -152,7 +154,9 @@ function validateFormInputs(obj) {
const $referenceNode = $("#DIVCO2_data_dialog");
for (let i = 0; i < CO2_data_form.length; i++) {
const $requiredElement = $(`[name=${CO2_data_form[i]}]`).first();
- if ($requiredElement.attr('name') !== "fitting_ventilation_states" && $requiredElement.val() === "") {
+ if ($requiredElement.attr('name') !== "fitting_ventilation_states" &&
+ $requiredElement.attr('name') !== "room_capacity" &&
+ $requiredElement.val() === "") {
insertErrorFor(
$referenceNode,
`'${$requiredElement.attr('name')}' must be defined. `
@@ -236,6 +240,36 @@ function validateCO2Form() {
);
submit = false;
}
+ // Validate room capacity
+ const roomCapacity = $fittingToSubmit.find("input[name=room_capacity]");
+ const roomCapacityVal = roomCapacity.val();
+ if (roomCapacityVal !== "") {
+ const roomCapacityNumber = Number(roomCapacityVal);
+ const totalPeopleNumber = Number($("#total_people").val());
+ if (!Number.isInteger(roomCapacityNumber) || roomCapacityNumber <= 0) {
+ insertErrorFor(
+ $referenceNode,
+ `'${roomCapacity.attr('name')}' must be a valid integer (> 0).`
+ );
+ submit = false;
+ }
+ else if (roomCapacityNumber < totalPeopleNumber){
+ insertErrorFor(
+ $referenceNode,
+ `'${roomCapacity.attr('name')}' must be higher than the total people.`
+ );
+ submit = false;
+ }
+ console.log(roomCapacityNumber)
+ console.log(totalPeopleNumber)
+ }
+ else {
+ insertErrorFor(
+ $referenceNode,
+ `'${roomCapacity.attr('name')}' must be defined.`
+ );
+ submit = false;
+ }
}
return submit;
@@ -341,6 +375,11 @@ function submitFittingAlgorithm(url) {
"disabled",
true
);
+ // Disable room capacity input
+ $("#room_capacity").prop(
+ "disabled",
+ true
+ );
// Prepare data for submission
const CO2_mapping = formatCO2DataForm(CO2_data_form);
diff --git a/caimira/apps/templates/base/calculator.form.html.j2 b/caimira/apps/templates/base/calculator.form.html.j2
index 497bf33e..377f0433 100644
--- a/caimira/apps/templates/base/calculator.form.html.j2
+++ b/caimira/apps/templates/base/calculator.form.html.j2
@@ -363,6 +363,11 @@
+ Room data:
+
+
+
+
diff --git a/caimira/models.py b/caimira/models.py
index 6127125a..4bcb0f22 100644
--- a/caimira/models.py
+++ b/caimira/models.py
@@ -1526,11 +1526,13 @@ class ShortRangeModel:
@dataclass(frozen=True)
class CO2DataModel:
'''
- The CO2DataModel class models CO2 data based on room volume, ventilation transition times, and people presence.
- It uses optimization techniques to fit the model's parameters and estimate the exhalation rate and ventilation
- values that best match the measured CO2 concentrations.
+ The CO2DataModel class models CO2 data based on room volume and capacity,
+ ventilation transition times, and people presence.
+ It uses optimization techniques to fit the model's parameters and estimate the
+ exhalation rate and ventilation values that best match the measured CO2 concentrations.
'''
data_registry: DataRegistry
+ room_capacity: int
room_volume: float
occupancy: IntPiecewiseConstant
ventilation_transition_times: typing.Tuple[float, ...]
@@ -1592,30 +1594,8 @@ class CO2DataModel:
the_predictive_CO2 = self.CO2_concentrations_from_params(the_CO2_concentration_model)
# Ventilation in L/s/person
- def max_occupancy_in_interval(start: float, stop: float) -> int:
- """
- Given a certain ventilation interval, get the maximum number of
- people in that period of time.
- """
- max_people: int = 0
- for i, (people_start, people_stop) in enumerate(zip(self.occupancy.transition_times[:-1],
- self.occupancy.transition_times[1:])):
- if people_stop <= start or people_start >= stop:
- continue
- if self.occupancy.values[i] > max_people: max_people = self.occupancy.values[i]
- return max_people
-
- vent_volume_liter_person = []
- for i, (vent_start, vent_stop) in enumerate(zip(self.ventilation_transition_times[:-1],
- self.ventilation_transition_times[1:])):
- max_people = max_occupancy_in_interval(vent_start, vent_stop)
- if max_people == 0:
- # If in a certain interval there are no occupancy, the flow rate per second/person is 0
- vent_volume_liter_person.append(0)
- else:
- vent_volume_liter_person.append(
- ventilation_values[i] / 3600 * self.room_volume / max_people * 1000
- ) # 1m^3 = 1000L
+ vent_volume_liter_person = [vent / 3600 * self.room_volume / self.room_capacity * 1000
+ for vent in ventilation_values] # 1m^3 = 1000L
return {
"exhalation_rate": exhalation_rate,