added test for dynamic occupancy from input form

caimira/apps/calculator/co2_model_generator.py

@@ -59,8 +59,10 @@ def __init__(self, **kwargs):
         self.data_registry = DataRegistry()
 
     def validate(self):
-        # Validate population parameters
-        self.validate_population_parameters()
+        # Validate population parameters when static occupancy is defined.
+        # Dynamic population is validated in the generate_dynamic_occupancy method.
+        if self.occupancy_format == 'static':
+            self.validate_population_parameters()
 
         # Validate specific inputs - breaks (exposed and infected)
         if self.specific_breaks != {}:

caimira/apps/calculator/defaults.py

@@ -38,7 +38,7 @@
     'infected_lunch_option': True,
     'infected_lunch_start': '12:30',
     'infected_people': 1,
-    'dynamic_infected_occupancy': '[]',
+    'dynamic_infected_occupancy': NO_DEFAULT,
     'infected_start': '08:30',
     'inside_temp': NO_DEFAULT,
     'location_latitude': NO_DEFAULT,

caimira/apps/calculator/model_generator.py

@@ -77,8 +77,10 @@ class VirusFormData(FormData):
     _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = DEFAULTS
 
     def validate(self):
-        # Validate population parameters
-        self.validate_population_parameters()
+        # Validate population parameters when static occupancy is defined.
+        # Dynamic population is validated in the generate_dynamic_occupancy method.
+        if self.occupancy_format == 'static':
+            self.validate_population_parameters()
 
         validation_tuples = [('activity_type', self.data_registry.population_scenario_activity.keys()),
                              ('mechanical_ventilation_type', MECHANICAL_VENTILATION_TYPES),

caimira/apps/calculator/report_generator.py

@@ -171,7 +171,7 @@ def calculate_report_data(form: VirusFormData, model: models.ExposureModel, exec
     # Probabilistic exposure
     if form.exposure_option == "p_probabilistic_exposure" and form.occupancy_format == "static":
         prob_probabilistic_exposure = np.array(model.total_probability_rule()).mean()
-    else: prob_probabilistic_exposure = 0
+    else: prob_probabilistic_exposure = -1
     # Expected new cases
     if (form.occupancy_format == "static"):
         expected_new_cases = np.array(model.expected_new_cases()).mean()
@@ -479,7 +479,7 @@ def scenario_statistics(
         # It means we have data to calculate the total_probability_rule
         prob_probabilistic_exposure = model.total_probability_rule()
     else:
-        prob_probabilistic_exposure = 0.
+        prob_probabilistic_exposure = -1
 
     if (compute_expected_new_cases):
         expected_new_cases = np.mean(model.expected_new_cases())

caimira/tests/apps/calculator/test_report_generator.py

@@ -2,6 +2,7 @@
 from functools import partial
 import os
 import time
+import json
 
 import numpy as np
 import pytest
@@ -115,3 +116,62 @@ def test_expected_new_cases(baseline_form_with_sr: VirusFormData):
 
     lr_expected_new_cases = alternative_statistics['stats']['Base scenario without short-range interactions']['expected_new_cases']
     np.testing.assert_almost_equal(sr_lr_expected_new_cases, lr_expected_new_cases + sr_lr_prob_inf * baseline_form_with_sr.short_range_occupants, 2)
+
+
+def test_static_vs_dynamic_occupancy_from_form(baseline_form_data, data_registry):
+    """ 
+    Assert that the results between a static and dynamic occupancy model (from form inputs) are similar. 
+    """
+    executor_factory = partial(
+        concurrent.futures.ThreadPoolExecutor, 1,
+    )
+
+    # By default the baseline form accepts static occupancy
+    static_occupancy_baseline_form: VirusFormData = VirusFormData.from_dict(baseline_form_data, data_registry)
+    static_occupancy_model = static_occupancy_baseline_form.build_model()
+    static_occupancy_report_data = calculate_report_data(static_occupancy_baseline_form, static_occupancy_model, executor_factory)
+
+    # Update the initial form data to include dynamic occupancy (please note the 4 coffee and 1 lunch breaks)
+    baseline_form_data['occupancy_format'] = 'dynamic'
+    baseline_form_data['dynamic_infected_occupancy'] = json.dumps([
+        {'total_people': 1, 'start_time': '09:00', 'finish_time': '10:03'},
+        {'total_people': 0, 'start_time': '10:03', 'finish_time': '10:13'},
+        {'total_people': 1, 'start_time': '10:13', 'finish_time': '11:16'},
+        {'total_people': 0, 'start_time': '11:16', 'finish_time': '11:26'},
+        {'total_people': 1, 'start_time': '11:26', 'finish_time': '12:30'},
+        {'total_people': 0, 'start_time': '12:30', 'finish_time': '13:30'},
+        {'total_people': 1, 'start_time': '13:30', 'finish_time': '14:53'},
+        {'total_people': 0, 'start_time': '14:53', 'finish_time': '15:03'},
+        {'total_people': 1, 'start_time': '15:03', 'finish_time': '16:26'},
+        {'total_people': 0, 'start_time': '16:26', 'finish_time': '16:36'},
+        {'total_people': 1, 'start_time': '16:36', 'finish_time': '18:00'},
+    ])
+    baseline_form_data['dynamic_exposed_occupancy'] = json.dumps([
+        {'total_people': 9, 'start_time': '09:00', 'finish_time': '10:03'},
+        {'total_people': 0, 'start_time': '10:03', 'finish_time': '10:13'},
+        {'total_people': 9, 'start_time': '10:13', 'finish_time': '11:16'},
+        {'total_people': 0, 'start_time': '11:16', 'finish_time': '11:26'},
+        {'total_people': 9, 'start_time': '11:26', 'finish_time': '12:30'},
+        {'total_people': 0, 'start_time': '12:30', 'finish_time': '13:30'},
+        {'total_people': 9, 'start_time': '13:30', 'finish_time': '14:53'},
+        {'total_people': 0, 'start_time': '14:53', 'finish_time': '15:03'},
+        {'total_people': 9, 'start_time': '15:03', 'finish_time': '16:26'},
+        {'total_people': 0, 'start_time': '16:26', 'finish_time': '16:36'},
+        {'total_people': 9, 'start_time': '16:36', 'finish_time': '18:00'},
+    ])
+    baseline_form_data['total_people'] = 0
+    baseline_form_data['infected_people'] = 0
+
+    dynamic_occupancy_baseline_form: VirusFormData = VirusFormData.from_dict(baseline_form_data, data_registry)
+    dynamic_occupancy_model = dynamic_occupancy_baseline_form.build_model()
+    dynamic_occupancy_report_data = calculate_report_data(dynamic_occupancy_baseline_form, dynamic_occupancy_model, executor_factory)
+
+    assert (list(sorted(static_occupancy_model.concentration_model.infected.presence.transition_times())) == 
+            list(dynamic_occupancy_model.concentration_model.infected.number.transition_times))
+    assert (list(sorted(static_occupancy_model.exposed.presence.transition_times())) == 
+            list(dynamic_occupancy_model.exposed.number.transition_times))
+
+    np.testing.assert_almost_equal(static_occupancy_report_data['prob_inf'], dynamic_occupancy_report_data['prob_inf'], 1)
+    assert dynamic_occupancy_report_data['expected_new_cases'] == -1
+    assert dynamic_occupancy_report_data['prob_probabilistic_exposure'] == -1
+