updates following reviewing process:

- replaced 'dynamic_exposed_occupancy', 'dynamic_infected_occupancy' and 'dynamic_occupancy' by 'occupancy' that encompasses both
- developed respective functionality, including CAiMIRA UI and REST API
- simplified logic with entry overlaps and respective validation
- simplified CO2 logic with dynamic groups
- simplified logic with alternative scenarios
- changed default identifier of unique group
- handled naming conventions
- updated existing tests and added new tests for the most recent structure
- generate docscrings update

caimira/src/caimira/api/controller/virus_report_controller.py

@@ -29,7 +29,7 @@ def submit_virus_form(form_data: typing.Dict, report_generation_parallelism: typ
 
     form_obj: VirusFormData = generate_form_obj(form_data=form_data, data_registry=data_registry)
     report_data: typing.Dict = generate_report(form_obj=form_obj, report_generation_parallelism=report_generation_parallelism)
-    
+
     # Handle model representation
     if report_data['model']:
         report_data['model'] = repr(report_data['model'])

caimira/src/caimira/calculator/models/models.py

@@ -1643,7 +1643,7 @@ class ExposureModel:
     exposed_to_short_range: int = 0
 
     #: Unique group identifier
-    identifier: str = 'static'
+    identifier: str = 'group_1'
 
     #: The number of times the exposure event is repeated (default 1).
     @property
@@ -1930,8 +1930,10 @@ class ExposureModelGroup:
         """
         first_concentration_model = self.exposure_models[0].concentration_model
         for model in self.exposure_models[1:]:
-            if model.concentration_model != first_concentration_model:
-                raise ValueError("All ExposureModels must have the same ConcentrationModel.")
+            # Check that the number of infected people and their presence is the same
+            if (model.concentration_model.infected.number != first_concentration_model.infected.number or
+                model.concentration_model.infected.presence != first_concentration_model.infected.presence):
+                raise ValueError("All ExposureModels must have the same infected number and presence in the ConcentrationModel.")
 
     @method_cache
     def _deposited_exposure_list(self) -> typing.List[_VectorisedFloat]:

caimira/src/caimira/calculator/models/monte_carlo/models.py

@@ -74,7 +74,6 @@ def _build_mc_model(model: dataclass_instance) -> typing.Type[MCModelBase[_Model
             elif new_field.type == typing.Tuple[models.SpecificInterval, ...]:
                 SI = getattr(sys.modules[__name__], "SpecificInterval")
                 field_type = typing.Tuple[typing.Union[models.SpecificInterval, SI], ...]
-
             elif new_field.type == typing.Union[int, models.IntPiecewiseConstant]:
                 IPC = getattr(sys.modules[__name__], "IntPiecewiseConstant")
                 field_type = typing.Union[int, models.IntPiecewiseConstant, IPC]

caimira/src/caimira/calculator/report/virus_report_data.py

@@ -246,13 +246,13 @@ def group_results(form: VirusFormData, model_group: models.ExposureModelGroup) -
 
 
 @profiler.profile
-def calculate_report_data(form: VirusFormData, executor_factory: typing.Callable[[], concurrent.futures.Executor]) -> typing.Dict[str, typing.Any]:
+def calculate_report_data(form: VirusFormData, 
+                          executor_factory: typing.Callable[[], concurrent.futures.Executor]) -> typing.Dict[str, typing.Any]:
     """
-    Simulation output data.
+    Generates the simulation output data.
     """
     model_group: models.ExposureModelGroup = form.build_model()
     results_per_group: typing.Dict[str, typing.Any] = group_results(form, model_group)
-
     times = interesting_times(model_group)
     
     # CO2 concentration 
@@ -458,8 +458,13 @@ def calculate_vl_scenarios_percentiles(model: mc.ExposureModel) -> typing.Dict[s
     }
 
 
-def manufacture_alternative_scenarios(form: VirusFormData) -> typing.Dict[str, typing.Union[mc.ExposureModel, mc.ExposureModelGroup]]:
-    scenarios = {}
+def manufacture_alternative_scenarios(form: VirusFormData) -> typing.Dict[str, mc.ExposureModel]:
+    """
+    Generates the data structure containing all the alternative scenarios.
+    It is only compatible with single group occupancy models, therefore
+    it returns an ExposureModel object and not an ExposureModelGroup.
+    """
+    scenarios: typing.Dict[str, models.ExposureModelGroup] = {}
     if (form.short_range_option == "short_range_no"):
         # Two special option cases - HEPA and/or FFP2 masks.
         FFP2_being_worn = bool(form.mask_wearing_option ==
@@ -512,31 +517,33 @@ def manufacture_alternative_scenarios(form: VirusFormData) -> typing.Dict[str, t
             scenarios['Neither ventilation nor masks'] = without_mask_or_vent.build_mc_model()
     else:
         # Adjust the number of exposed people with long-range exposure based on short-range interactions
-        if form.occupancy_format == 'static':
+        if not form.occupancy:
             no_short_range_alternative = dataclass_utils.replace(form, short_range_interactions={}, total_people=form.total_people - form.short_range_occupants)
-        elif form.occupancy_format == 'dynamic':
-            for group_name, occupancy_list in form.dynamic_exposed_occupancy.items():
+        else:
+            for group_id, group in form.occupancy.items():
                 # Check if the group exists in short-range interactions
-                if group_name in form.short_range_interactions:
+                if group_id in form.short_range_interactions:
                     short_range_count = form.short_range_occupants
-                    total_people = occupancy_list['total_people']
+                    total_people = group['total_people']
                     if total_people > short_range_count > 0:
                         # Update the total_people with the adjusted value
-                       occupancy_list['total_people'] = max(0, total_people - short_range_count)
-            no_short_range_alternative = dataclass_utils.replace(form, short_range_interactions={}, dynamic_exposed_occupancy=form.dynamic_exposed_occupancy)        
+                       group['total_people'] = max(0, total_people - short_range_count)
+            no_short_range_alternative = dataclass_utils.replace(form, short_range_interactions={}, occupancy=form.occupancy)        
         scenarios['Base scenario without short-range interactions'] = no_short_range_alternative.build_mc_model()
 
+    for sceario_name, scenario in scenarios.items():
+        scenarios[sceario_name] = scenario.exposure_models[0] # type: ignore
     return scenarios
 
 
 def scenario_statistics(
-    mc_model_group: mc.ExposureModelGroup,
+    mc_model: mc.ExposureModel,
     sample_times: typing.List[float],
     compute_prob_exposure: bool,
 ):
-    model_group: models.ExposureModelGroup = mc_model_group.build_model(
-        size=mc_model_group.data_registry.monte_carlo['sample_size'])
-    model = model_group.exposure_models[0]
+    model = mc_model.build_model(
+        size=mc_model.data_registry.monte_carlo['sample_size']
+    )
     
     return {
         'probability_of_infection': np.mean(model.infection_probability()),
@@ -552,21 +559,21 @@ def scenario_statistics(
 def comparison_report(
         form: VirusFormData,
         report_data: typing.Dict[str, typing.Any],
-        scenarios: typing.Dict[str, mc.ExposureModelGroup],
+        scenarios: typing.Dict[str, mc.ExposureModel],
         executor_factory: typing.Callable[[], concurrent.futures.Executor],
 ):  
     if (form.short_range_option == "short_range_no"):
         statistics = {
             'Current scenario': {
-                'probability_of_infection': report_data['groups']['static']['prob_inf'],
-                'expected_new_cases': report_data['groups']['static']['expected_new_cases'],
-                'concentrations': report_data['groups']['static']['concentrations'],
+                'probability_of_infection': report_data['groups']['group_1']['prob_inf'],
+                'expected_new_cases': report_data['groups']['group_1']['expected_new_cases'],
+                'concentrations': report_data['groups']['group_1']['concentrations'],
             }
         }
     else:
         statistics = {}
 
-    compute_prob_exposure = form.short_range_option == "short_range_yes" and form.exposure_option == "p_probabilistic_exposure" and form.occupancy_format == "static"
+    compute_prob_exposure = form.short_range_option == "short_range_yes" and form.exposure_option == "p_probabilistic_exposure" and not form.occupancy
         
     with executor_factory() as executor:
         results = executor.map(
@@ -585,7 +592,9 @@ def comparison_report(
     }
 
 
-def alternative_scenarios_data(form: VirusFormData, report_data: typing.Dict[str, typing.Any], executor_factory: typing.Callable[[], concurrent.futures.Executor]) -> typing.Dict[str, typing.Any]:
+def alternative_scenarios_data(form: VirusFormData, 
+                               report_data: typing.Dict[str, typing.Any], 
+                               executor_factory: typing.Callable[[], concurrent.futures.Executor]) -> typing.Dict[str, typing.Any]:
     alternative_scenarios: typing.Dict[str, typing.Any] = manufacture_alternative_scenarios(form=form)
     return {
         'alternative_scenarios': comparison_report(form=form, report_data=report_data, scenarios=alternative_scenarios, executor_factory=executor_factory)

caimira/src/caimira/calculator/validators/co2/co2_validator.py

@@ -28,8 +28,6 @@ class CO2FormData(FormData):
     # and the defaults in any html form must not be contradictory.
     _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = {
         'CO2_data': '{}',
-        'dynamic_exposed_occupancy': '{}',
-        'dynamic_infected_occupancy': '[]',
         'exposed_coffee_break_option': 'coffee_break_0',
         'exposed_coffee_duration': 5,
         'exposed_finish': '17:30',
@@ -47,7 +45,7 @@ class CO2FormData(FormData):
         'infected_lunch_start': '12:30',
         'infected_people': 1,
         'infected_start': '08:30',
-        'occupancy_format': 'static',
+        'occupancy': '{}',
         'room_capacity': None,
         'room_volume': NO_DEFAULT,
         'specific_breaks': '{}',
@@ -74,7 +72,7 @@ class CO2FormData(FormData):
                 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 != {} and self.occupancy_format == 'static':
+        if self.specific_breaks != {} and not self.occupancy:
             if type(self.specific_breaks) is not dict:
                 raise TypeError('The specific breaks should be in a dictionary.')
 

caimira/src/caimira/calculator/validators/defaults.py

@@ -16,8 +16,6 @@ DEFAULTS = {
     'calculator_version': NO_DEFAULT,
     'ceiling_height': 0.,
     'conditional_probability_viral_loads': False,
-    'dynamic_exposed_occupancy': '{}',
-    'dynamic_infected_occupancy': '[]',
     'event_month': 'January',
     'exposed_coffee_break_option': 'coffee_break_0',
     'exposed_coffee_duration': 5,
@@ -49,7 +47,7 @@ DEFAULTS = {
     'mask_type': 'Type I',
     'mask_wearing_option': 'mask_off',
     'mechanical_ventilation_type': 'not-applicable',
-    'occupancy_format': 'static',
+    'occupancy': '{}',
     'opening_distance': 0.,
     'precise_activity': '{}',
     'room_heating_option': False,

caimira/src/caimira/calculator/validators/form_validator.py

@@ -36,15 +36,11 @@ class FormData:
     infected_lunch_start: minutes_since_midnight    #Used if infected_dont_have_breaks_with_exposed
     infected_start: minutes_since_midnight
     infected_people: int
-    occupancy_format: str
+    occupancy: dict
     room_volume: float
     specific_breaks: dict
     total_people: int
 
-    # Dynamic occupancy inputs
-    dynamic_exposed_occupancy: dict
-    dynamic_infected_occupancy: list
-
     data_registry: DataRegistry
 
     _DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = DEFAULTS
@@ -96,147 +92,169 @@ class FormData:
                 if default is not NO_DEFAULT and value in [default, 'not-applicable']:
                     form_dict.pop(attr)
         return form_dict
-    
-    def validate_dynamic_input(self, dynamic_input_value, input_name, dynamic_input_key = None):
-        # Check if the input is a valid non-empty list
-        specific_group_msg = f' in "{dynamic_input_key}" ("presence")' if dynamic_input_key else ''
 
-        if not isinstance(dynamic_input_value, list) :
-            raise TypeError(f'The input "{input_name}"{specific_group_msg} should be a valid, non-empty list. Got "{type(dynamic_input_value)}".')
-        # Check if input is populated
-        if len(dynamic_input_value) == 0:
-            raise ValueError(f'The input "{input_name}" should be a valid, non-empty list. Got "{dynamic_input_value}".')
+    def validate_group_presence_input(self, group_id: str, group_presence: typing.Dict):
+        """
+        When occupancy is defined, this method validates the
+        presence times within an occupancy group.
+        """
+        # Checks if the presence input is a valid list
+        if not isinstance(group_presence, list):
+            raise TypeError(f'The presence parameter in occupancy group "{group_id}" should be a valid list. Got {type(group_presence)}.')
+        # Checks if the presence input is populated
+        if len(group_presence) == 0:
+            raise TypeError(f'The presence parameter in occupancy group "{group_id}" should be a valid, non-empty list. Got {group_presence}.')
         
-        # To store already processed interactions for overlap checking
-        existing_dynamic_infected_interval = []
-        existing_dynamic_exposed_interval = []
-        short_range_existing_interaction = []
+        # Already processed presence intervals for overlap checking
+        existing_occupancy_presence_interval = []
         
-        for entry in dynamic_input_value:
-            # Check if each entry is a dictionary
-            if not isinstance(entry, typing.Dict):
-                raise TypeError(f'Each entry in "{input_name}" should be a dictionary. Got "{type(entry)}".')
+        for presence_interval in group_presence:
+            # Checks if each presence entry is a valid dict
+            if not isinstance(presence_interval, typing.Dict):
+                raise TypeError(f'Each presence interval should be a valid dictionary. Got {type(presence_interval)} in occupancy group "{group_id}".')
 
-            # Check for required keys in each entry
-            dict_keys = entry.keys()
+            # Parameters in each presence entry
+            presence_params = presence_interval.keys()
 
-            # Check for the "start_time" and "finish_time" keys for "dynamic_exposed_occupancy" and "dynamic_infected_occupancy"
-            if input_name in ["dynamic_exposed_occupancy", "dynamic_infected_occupancy"]:
-                # Check for time format in "start_time" and "finish_time"
-                for time_key in ["start_time", "finish_time"]:
-                    if time_key not in dict_keys:
-                        raise TypeError(f'Missing "{time_key}" key in "{input_name}"{specific_group_msg}. Got keys: "{list(dict_keys)}".')
-                    time_value = entry[time_key]
-                    if not re.compile("^(2[0-3]|[01]?[0-9]):([0-5]?[0-9])$").match(time_value):
-                        raise ValueError(f'Invalid time format for "{time_key}" in "{input_name}"{specific_group_msg}. Expected "HH:MM". Got "{time_value}".')
-                if entry["finish_time"] <= entry["start_time"]:
-                    raise ValueError(f'Occupancy presence in "{input_name}"{specific_group_msg} entry has a finish time after the start time. Got start time: "{entry["start_time"]}" and finish time: "{entry["finish_time"]}".')
-                                        
-            # Check for the "dynamic_infected_occupancy" uniqueness of intervals, 
-            # as well as the "total_people" keyword and its constraints
-            if input_name == "dynamic_infected_occupancy":
-                self.check_overlap(entry, existing_dynamic_infected_interval)
-                existing_dynamic_infected_interval.append(entry)
-                if "total_people" not in dict_keys:
-                    raise TypeError(f'Missing "total_people" key in "dynamic_infected_occupancy". Got keys: "{list(dict_keys)}".')
-                else:
-                    value = entry["total_people"]
-                    if not isinstance(value, int) or value < 0:
-                        raise ValueError(f'The "total_people" in "{input_name}" should be a non-negative integer. Got "{value}".')
+            # Checks for the "start_time" and "finish_time" params
+            for time_param in ["start_time", "finish_time"]:
+                if time_param not in presence_params:
+                    raise TypeError(f'Missing {time_param} key in presence parameter of occupancy group "{group_id}".' 
+                                    f' Got keys: {", ".join(presence_params)}.')
+                
+                time_value = presence_interval[time_param]
+                if not re.compile("^(2[0-3]|[01]?[0-9]):([0-5]?[0-9])$").match(time_value):
+                    raise ValueError(f'Invalid time format found in presence parameter of occupancy group "{group_id}". '
+                                     f'Expected HH:MM, got {time_value}.')
             
-            # Check for the "dynamic_exposed_occupancy" uniqueness of intervals
-            if input_name == "dynamic_exposed_occupancy":
-                self.check_overlap(entry, existing_dynamic_exposed_interval)
-                existing_dynamic_exposed_interval.append(entry)
+            if presence_interval["finish_time"] <= presence_interval["start_time"]:
+                raise ValueError(f'Inconsistent times found in "presence" parameter of occupancy group "{group_id}".'
+                                 f'The "{presence_interval}" entry has a start time ("{presence_interval["start_time"]}") '
+                                 f'after the finish time ("{presence_interval["finish_time"]}").')
 
-            # Check for remaining short-range inputs
-            if input_name == "short_range_interactions":
-                # Check for time format in "start_time" and "finish_time"
-                if "start_time" not in dict_keys:
-                    raise TypeError(f'Missing "start_time" key in "short_range_interactions", "{dynamic_input_key}". Got keys: "{list(dict_keys)}".')
-                start_time = entry["start_time"]
+            # Checks for the occupancy group uniqueness of intervals
+            self.check_overlap(presence_interval, existing_occupancy_presence_interval)
+            existing_occupancy_presence_interval.append(presence_interval)
+
+    def validate_short_range_interaction_input(self, group_id: str, sr_interactions: typing.List):
+        """
+        Validates the short-range interactions within an occupancy group.
+        """
+        # Within a group, checks if the short-range input is a valid list
+        if not isinstance(sr_interactions, list):
+            raise TypeError(f'The short-range interactions in occupancy group "{group_id}" should be defined in a valid list. Got {type(sr_interactions)}.')
+        # Within a group, checks if the list is populated
+        if len(sr_interactions) == 0:
+            raise TypeError(f'The short-range interactions in occupancy group "{group_id}" should be a non-empty list. Got {type(sr_interactions)}.')
+        
+        # Already processed interactions for overlap checking
+        existing_sr_interaction_interval: typing.List = []
+
+        for interaction in sr_interactions:
+            # Checks if each interaction is a valid dict
+            if not isinstance(interaction, typing.Dict):
+                raise TypeError(f'Each short-range interaction should be a dictionary. Got {type(interaction)} in occupancy group "{group_id}".')
+            
+            # Parameters in each short-range interaction
+            interaction_params = interaction.keys()
+
+            # Checks for the expiration key and its constraints
+            if "expiration" not in interaction_params:
+                raise TypeError(f'Missing expiration key in short-range interaction for occupancy group "{group_id}". Got keys: {", ".join(interaction_params)}.')
+            else:
+                expiration = interaction["expiration"]
+                if expiration not in list(self.data_registry.expiration_particle['expiration_BLO_factors'].keys()): # type: ignore
+                    raise ValueError(f'Invalid expiration value in short-range interaction for occupancy group "{group_id}". Got "{expiration}".')
+
+            # Checks for start_time key and its format
+            if "start_time" not in interaction_params:
+                raise TypeError(f'Missing start_time key in short-range interaction for occupancy group "{group_id}". Got keys: {", ".join(interaction_params)}.')
+            else:
+                start_time = interaction["start_time"]
                 if not re.compile("^(2[0-3]|[01]?[0-9]):([0-5]?[0-9])$").match(start_time):
-                    raise ValueError(f'Invalid time format for "start_time" in "short_range_interactions", "{dynamic_input_key}". Expected "HH:MM". Got "{start_time}".')
-                
-                # Check for the "expiration" key and its constraints
-                if "expiration" not in dict_keys:
-                    raise TypeError(f'Missing "expiration" key in "short_range_interactions", "{dynamic_input_key}". Got keys: "{list(dict_keys)}".')
-                else:
-                    value = entry["expiration"]
-                    if value not in list(self.data_registry.expiration_particle['expiration_BLO_factors'].keys()):
-                        raise ValueError(f'The "expiration" in "short_range_interactions", "{dynamic_input_key}", does not exist in the registry. Got "{value}".')
-                
-                if "duration" not in dict_keys:
-                    raise TypeError(f'Missing "duration" key in "short_range_interactions", "{dynamic_input_key}". Got keys: "{list(dict_keys)}".')
-                duration = entry["duration"]
+                    raise ValueError(f'Invalid time format for start_time in short-range interaction for occupancy group "{group_id}". Expected HH:MM, got {start_time}.')
+            
+            # Checks for "duration" and its format
+            if "duration" not in interaction_params:
+                raise TypeError(f'Missing duration key in short-range interaction for occupancy group "{group_id}". Got keys: {", ".join(interaction_params)}.')
+            else:
+                duration = interaction["duration"]
                 if duration < 0:
-                    raise ValueError(f'The "duration" in "short_range_interactions", "{dynamic_input_key}", should be a non-negative integer. Got "{duration}".')
+                    raise ValueError(f'The duration value in short-range interaction for occupancy group "{group_id}" should be a non-negative integer. Got {duration}.')
+
+            # Legacy usage - occupancy input is not defined (default empty dict)
+            if not self.occupancy:
+                # It means that we have a single exposure model
+                lr_start = min(self.infected_start, self.exposed_start)/60
+                lr_stop = max(self.infected_finish, self.exposed_finish)/60
                 
-                # Occupancy format dependent inputs
-                if self.occupancy_format == 'dynamic':
-                    # Find corresponding exposure group
-                    exposure_group_obj = next(
-                        (occupancy_group for occupancy_key, occupancy_group in self.dynamic_exposed_occupancy.items()
-                        if occupancy_key == dynamic_input_key),
-                        None
+                if not self.check_interaction_is_within_long_range(interaction, existing_sr_interaction_interval, lr_start, lr_stop):
+                    raise ValueError(
+                        f'Short-range interactions must occur during simulation time. Got {interaction} in occupancy group "{group_id}".'
+                    )
+                
+                # Add interaction to the list of already processed interactions
+                existing_sr_interaction_interval.append(interaction)
+            else:
+                # Find corresponding exposure group
+                occupancy_group_obj = next(
+                    (occupancy_value for occupancy_key, occupancy_value in self.occupancy.items()
+                    if occupancy_key == group_id),
+                    None
+                )
+
+                if occupancy_group_obj is None:
+                    raise ValueError(
+                        f'Occupancy group "{group_id}" referenced in short-range interactions was not found in the occupancy input.'
                     )
 
-                    if exposure_group_obj is None:
-                        raise ValueError(
-                            f'Exposure group "{dynamic_input_key}" in short-range interaction not found in dynamic exposed occupancy.'
-                        )
+                is_within_any_lr = False
+                for presence in occupancy_group_obj['presence']:
+                    # Check for correct timing within long-range exposure and overlaps with existing interactions
+                    lr_start = time_string_to_minutes(presence['start_time'])/60
+                    lr_stop = time_string_to_minutes(presence['finish_time'])/60
+                    
+                    # Flag to check if interaction falls within any long-range exposure interval
+                    if self.check_interaction_is_within_long_range(interaction, existing_sr_interaction_interval, lr_start, lr_stop):
+                        is_within_any_lr = True
+                    
+                    # Add interaction to the list of processed interactions if within long-range
+                    existing_sr_interaction_interval.append(interaction)
 
-                    is_within_any_long_range = False
-                    for exposure_interval in exposure_group_obj['presence']:
-                        # Check for correct timing within long-range exposure and overlaps with existing interactions
-                        long_range_start = time_string_to_minutes(exposure_interval['start_time'])/60
-                        long_range_stop = time_string_to_minutes(exposure_interval['finish_time'])/60
-                        
-                        # Flag to check if interaction falls within any long-range exposure interval
-                        if self.check_time_and_overlap(
-                            entry, short_range_existing_interaction, long_range_start, long_range_stop
-                        ): is_within_any_long_range = True
-                        
-                        # Add interaction to the list of processed interactions if within long-range
-                        short_range_existing_interaction.append(entry)
-                    
-                    # If no long-range interval contains the interaction, raise an error
-                    if not is_within_any_long_range:
-                        raise ValueError(
-                            f'Short-range interaction "{entry}" does not fall within any long-range exposure interval in "{dynamic_input_key}".'
-                        )
-                    
-                elif self.occupancy_format == 'static':
-                    # It means that we have a single exposure model
-                    long_range_start = min(self.infected_start, self.exposed_start)/60
-                    long_range_stop = max(self.infected_finish, self.exposed_finish)/60
-                    
-                    if not self.check_time_and_overlap(entry, short_range_existing_interaction, long_range_start, long_range_stop):
-                        raise ValueError(
-                            f'Short-range interactions should be defined during simulation time. Got "{entry}".'
-                        )
-                    
-                    # Add interaction to the list of processed interactions
-                    short_range_existing_interaction.append(entry)
-                else:
-                    raise TypeError(
-                        f'Undefined exposure type. Got "{self.occupancy_format}", accepted formats are "dynamic" or "exposed".')
+                # If the interaction does not fall within any presence interval of the occupancy group, raise an error
+                if not is_within_any_lr:
+                    raise ValueError(
+                        f'Short-range interaction {interaction} does not fall within any presence interval in occupancy group "{group_id}".'
+                    )
     
-    def validate_dynamic_exposed_format(self, dynamic_exposed_group: dict, key: str):
+    def validate_dynamic_exposed_format(self, group_id: str, group: typing.Dict):
         """
-        Validates the expected keywords for the dynamic
-        exposed input.
-        """
-        # Total people
-        if 'total_people' not in dynamic_exposed_group:
-            raise TypeError(f'Missing "total_people" key in "dynamic_exposed_occupancy" group "{key}". Got keys: "{list(dynamic_exposed_group.keys())}".')
+        Validates the expected keywords for the occupancy input.
+        """       
+        # Parameters in each presence entry
+        group_params = group.keys()
+
+        # Total people input
+        if 'total_people' not in group_params:
+            raise TypeError(f'Missing total_people key in occupancy group "{group_id}". Got keys: {", ".join(group_params)}.')
         else:
-            total_people = dynamic_exposed_group['total_people']
+            total_people = group['total_people']
             if not isinstance(total_people, int) or total_people < 0:
-                raise ValueError(f'The "total_people" in "dynamic_exposed_occupancy" group "{key}" should be a non-negative integer. Got "{total_people}".')
-        # Presence
-        if 'presence' not in dynamic_exposed_group:
-            raise TypeError(f'Missing "presence" key in "dynamic_exposed_occupancy" group "{key}". Got keys: "{list(dynamic_exposed_group.keys())}".')
+                raise ValueError(f'The total_people input in occupancy group "{group_id}" should be a non-negative integer. Got {total_people}.')
+        
+        # Infected people input
+        if 'infected' not in group_params:
+            raise TypeError(f'Missing infected key in occupancy group "{group_id}". Got keys: {", ".join(group_params)}.')
+        else:
+            infected = group['infected']
+            if not isinstance(infected, int) or infected < 0:
+                raise ValueError(f'The infected input in occupancy group "{group_id}" should be a non-negative integer. Got {infected}.')
+            elif infected > total_people: # Validate number of infected <= number of total people
+                raise ValueError(f'The number of infected people ({infected}) cannot be greater than the total people ({total_people}).')
+
+        # Presence input
+        if 'presence' not in group_params:
+            raise TypeError(f'Missing presence key in occupancy group "{group_id}". Got keys: {", ".join(group_params)}.')
         
     def get_start_and_finish_time(self, entry: dict):
         entry_start = time_string_to_minutes(entry["start_time"])/60
@@ -245,140 +263,128 @@ class FormData:
         else:
             entry_finish = entry_start + entry['duration']/60
         return entry_start, entry_finish
-
-    def check_time_and_overlap(self, interaction, existing_interactions, lr_start, lr_stop):
+    
+    def check_interaction_is_within_long_range(self, interaction, existing_interactions, 
+                                               lr_start, lr_stop):
         """
-        Checks if the interaction overlaps with any existing interactions for the
-        same exposure group and if it falls within the long-range exposure time.
+        Check if the short-range interaction falls within the long-range exposure time.
+        Check if the short-range interaction given as input overlaps with any already 
+        existing interactions for the same occupancy group. 
         """
         interaction_start, interaction_finish = self.get_start_and_finish_time(interaction)
         # Check if the SR interaction is within the LR exposure time
         if lr_start <= interaction_start <= lr_stop and lr_start <= interaction_finish <= lr_stop:
-            for existing in existing_interactions:
-                existing_start, existing_finish = self.get_start_and_finish_time(existing)
-                # Check for overlap
-                if interaction_start < existing_finish and existing_start < interaction_finish:
-                    raise ValueError(
-                        f'Overlap detected for "short-range interaction": New interaction '
-                        f'"{interaction}" overlaps with existing interaction "{existing}".'
-                    )
-            # Return True if interaction falls within the current long-range interval
+            # Check the overlap with already existing interactions
+            self.check_overlap(interaction, existing_interactions)
             return True
         return False
     
-    def check_overlap(self, interaction, existing_interactions):
+    def check_overlap(self, entry, existing_entries):
         """
-        Checks if the dynamic entry overlaps with any already existing interaction.
+        Check if an entry overlaps with an already existing entry
+        by comparing the start and finish times of all entries.
         """
-        interaction_start = time_string_to_minutes(interaction["start_time"])/60
-        interaction_finish = time_string_to_minutes(interaction["finish_time"])/60
-        
-        for existing in existing_interactions:
-            existing_start = time_string_to_minutes(existing["start_time"])/60
-            existing_finish = time_string_to_minutes(existing["finish_time"])/60
-
+        entry_start, entry_finish = self.get_start_and_finish_time(entry)
+        for existing_entry in existing_entries:
+            existing_entry_start, existing_entry_finish = self.get_start_and_finish_time(existing_entry)
             # Check for overlap
-            if (interaction_start < existing_finish and existing_start < interaction_finish):
+            if (entry_start < existing_entry_finish and existing_entry_start < entry_finish):
                 raise ValueError(
-                    f'Overlap detected: New interaction '
-                    f'"{interaction}" overlaps with existing interaction "{existing}".'
+                    f'Overlap detected: The entry {entry} overlaps with '
+                    f'an already existing entry ({existing_entry}).'
             )
+        # In case no exception is raised, simply returns
         return
     
-    
     def validate_population_parameters(self):
-        """Validates required parameters for dynamic inputs"""
-        # Static occupancy is defined.
-        if self.occupancy_format == 'static':        
-            # Validate number of infected <= number of total people
-            if self.infected_people >= self.total_people:
-                raise ValueError(
-                    'Number of infected people cannot be greater or equal to the number of total people.')
-
-            # Validate time intervals selected by user
-            time_intervals = [
-                ['exposed_start', 'exposed_finish'],
-                ['infected_start', 'infected_finish'],
-            ]
-            if self.exposed_lunch_option:
-                time_intervals.append(
-                    ['exposed_lunch_start', 'exposed_lunch_finish'])
-            if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option:
-                time_intervals.append(
-                    ['infected_lunch_start', 'infected_lunch_finish'])
-
-            for start_name, end_name in time_intervals:
-                start = getattr(self, start_name)
-                end = getattr(self, end_name)
-                if start > end:
+        """
+        Validate required parameters for dynamic inputs.
+        """
+        if isinstance(self.occupancy, typing.Dict):
+            # Legacy usage - occupancy input is not defined (default empty dict)
+            if not self.occupancy:
+                # Validate number of infected <= number of total people
+                if self.infected_people >= self.total_people:
                     raise ValueError(
-                        f"{start_name} must be less than {end_name}. Got {start} and {end}.")
+                        'Number of infected people cannot be greater or equal to the number of total people.')
 
-            def validate_lunch(start, finish):
-                lunch_start = getattr(self, f'{population}_lunch_start')
-                lunch_finish = getattr(self, f'{population}_lunch_finish')
-                return (start <= lunch_start <= finish and
-                        start <= lunch_finish <= finish)
+                # Validate time intervals selected by user
+                time_intervals = [
+                    ['exposed_start', 'exposed_finish'],
+                    ['infected_start', 'infected_finish'],
+                ]
+                if self.exposed_lunch_option:
+                    time_intervals.append(
+                        ['exposed_lunch_start', 'exposed_lunch_finish'])
+                if self.infected_dont_have_breaks_with_exposed and self.infected_lunch_option:
+                    time_intervals.append(
+                        ['infected_lunch_start', 'infected_lunch_finish'])
 
-            def get_lunch_mins(population):
-                lunch_mins = 0
-                if getattr(self, f'{population}_lunch_option'):
-                    lunch_mins = getattr(
-                        self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start')
-                return lunch_mins
-
-            def get_coffee_mins(population):
-                coffee_mins = 0
-                if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0':
-                    coffee_mins = COFFEE_OPTIONS_INT[getattr(
-                        self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration')
-                return coffee_mins
-
-            def get_activity_mins(population):
-                return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start')
-
-            populations = [
-                'exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed']
-            for population in populations:
-                # Validate lunch time within the activity times.
-                if (getattr(self, f'{population}_lunch_option') and
-                        not validate_lunch(getattr(self, f'{population}_start'), getattr(
-                            self, f'{population}_finish'))
-                        ):
-                    raise ValueError(
-                        f"{population} lunch break must be within presence times."
-                    )
-
-                # Length of breaks < length of activity
-                if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population):
-                    raise ValueError(
-                        f"Length of breaks >= Length of {population} presence."
-                    )
-
-                for attr_name, valid_set in [('exposed_coffee_break_option', COFFEE_OPTIONS_INT),
-                                            ('infected_coffee_break_option', COFFEE_OPTIONS_INT)]:
-                    if getattr(self, attr_name) not in valid_set:
+                for start_name, end_name in time_intervals:
+                    start = getattr(self, start_name)
+                    end = getattr(self, end_name)
+                    if start > end:
                         raise ValueError(
-                            f"{getattr(self, attr_name)} is not a valid value for {attr_name}")
-        # Dynamic occupancy is defined.
-        elif self.occupancy_format == 'dynamic':
-            # Validate dynamic input format
-            self.validate_dynamic_input(self.dynamic_infected_occupancy, "dynamic_infected_occupancy")
-            # Check if dynamic exposed input is a dict
-            if isinstance(self.dynamic_exposed_occupancy, dict):
-                # Check if the dict is not empty
-                if not self.dynamic_exposed_occupancy:
-                    raise ValueError(f'The input "dynamic_exposed_occupancy" should be a valid, non-empty dict. Got "{self.dynamic_exposed_occupancy}".')
-                # The key is the actual identifier
-                for key, group in self.dynamic_exposed_occupancy.items():
-                    # For each group, validate dynamic exposed input format
-                    self.validate_dynamic_exposed_format(group, key)
-                    # ...as well as validate dynamic exposed presence data
-                    self.validate_dynamic_input(group['presence'], "dynamic_exposed_occupancy", key)
+                            f"{start_name} must be less than {end_name}. Got {start} and {end}.")
+
+                def validate_lunch(start, finish):
+                    lunch_start = getattr(self, f'{population}_lunch_start')
+                    lunch_finish = getattr(self, f'{population}_lunch_finish')
+                    return (start <= lunch_start <= finish and
+                            start <= lunch_finish <= finish)
+
+                def get_lunch_mins(population):
+                    lunch_mins = 0
+                    if getattr(self, f'{population}_lunch_option'):
+                        lunch_mins = getattr(
+                            self, f'{population}_lunch_finish') - getattr(self, f'{population}_lunch_start')
+                    return lunch_mins
+
+                def get_coffee_mins(population):
+                    coffee_mins = 0
+                    if getattr(self, f'{population}_coffee_break_option') != 'coffee_break_0':
+                        coffee_mins = COFFEE_OPTIONS_INT[getattr(
+                            self, f'{population}_coffee_break_option')] * getattr(self, f'{population}_coffee_duration')
+                    return coffee_mins
+
+                def get_activity_mins(population):
+                    return getattr(self, f'{population}_finish') - getattr(self, f'{population}_start')
+
+                populations = [
+                    'exposed', 'infected'] if self.infected_dont_have_breaks_with_exposed else ['exposed']
+                for population in populations:
+                    # Validate lunch time within the activity times.
+                    if (getattr(self, f'{population}_lunch_option') and
+                            not validate_lunch(getattr(self, f'{population}_start'), getattr(
+                                self, f'{population}_finish'))
+                            ):
+                        raise ValueError(
+                            f"{population} lunch break must be within presence times."
+                        )
+
+                    # Length of breaks < length of activity
+                    if (get_lunch_mins(population) + get_coffee_mins(population)) >= get_activity_mins(population):
+                        raise ValueError(
+                            f"Length of breaks >= Length of {population} presence."
+                        )
+
+                    for attr_name, valid_set in [('exposed_coffee_break_option', COFFEE_OPTIONS_INT),
+                                                ('infected_coffee_break_option', COFFEE_OPTIONS_INT)]:
+                        if getattr(self, attr_name) not in valid_set:
+                            raise ValueError(
+                                f"{getattr(self, attr_name)} is not a valid value for {attr_name}")
+            # Occupancy input is defined
             else:
-                raise TypeError(f'The input "dynamic_exposed_occupancy" should be a valid, non-empty dict. Got "{type(self.dynamic_exposed_occupancy)}".')
+                # Checks if occupancy input is a valid dict
+                if self.occupancy and isinstance(self.occupancy, typing.Dict):
+                    # The key is the actual identifier
+                    for group_id, group in self.occupancy.items():
+                        # For each group, validate input format
+                        self.validate_dynamic_exposed_format(group_id, group)
+                        # ...as well as the respective presence input
+                        self.validate_group_presence_input(group_id, group['presence'])
         else:
-            raise ValueError(f"'{self.occupancy_format}' is not a valid value for 'self.occupancy_format'. Accepted values are 'static' or 'dynamic'.")
+            raise TypeError(f'The occupancy input should be a valid dictionary. Got {self.occupancy}.')
 
     def validate(self):
         raise NotImplementedError("Subclass must implement")
@@ -386,72 +392,73 @@ class FormData:
     def build_model(self, sample_size: typing.Optional[int] = None):
         raise NotImplementedError("Subclass must implement")
     
-    def population_present_changes(self, population_list: typing.List[models.Interval]) -> typing.List[float]:
+    def population_present_changes(self, transition_times_list: typing.Tuple[float, ...]) -> typing.List[float]:
         """
         Returns a sorted list of unique state changes on
         a population list.
         """
-        state_change_times = set(population_list[0].transition_times())
-        for population in population_list:
-            state_change_times.update(population.transition_times())
-        return sorted(state_change_times)
+        return sorted(set(transition_times_list))
+    
+    def convert_interval_to_piecewise(self, interval: models.SpecificInterval, value: int):
+        """
+        Converts an Interval and a single value to an IntPiecewiseConstant.
+        """
+        transition_times = []
+        values = []
+
+        for start, end in interval.present_times:
+            transition_times.extend([start, end])
+            values.extend([value, 0])
+
+        # Drop the last value (0) to match number of intervals
+        if values:
+            values.pop()
+
+        return models.IntPiecewiseConstant(
+            transition_times=tuple(transition_times),
+            values=tuple(values),
+        )
 
     def build_CO2_piecewise(self):
         """
         Builds a simple IntPiecewiseConstant for the different
         population groups that are defined.
         """
-        if self.occupancy_format == 'dynamic':
-            infected_occupancy = self.generate_dynamic_occupancy(self.dynamic_infected_occupancy)
-            total_models = [models.SimplePopulation(
-                number=infected_occupancy, # IntPiecewiseConstant
-                presence=None,
-                activity=None, # type: ignore
-            )]
+        # Legacy usage - occupancy input is not defined (default empty dict)
+        if not self.occupancy:
+            infected_occupancy = self.convert_interval_to_piecewise(
+                interval=self.infected_present_interval(),
+                value=self.infected_people,
+            )
+            exposed_occupancy = self.convert_interval_to_piecewise(
+                interval=self.exposed_present_interval(),
+                value=self.total_people - self.infected_people,
+            )
+            total_models = [infected_occupancy, exposed_occupancy]
+        else:
+            infected_occupancy = self.generate_infected_occupancy(self.occupancy)
+            total_models = [infected_occupancy]
             # For all state changes
-            total_presence = [infected_occupancy.interval()]
-
-            for exposure_group in self.dynamic_exposed_occupancy.values():
-                exposed_occupancy = exposure_group['total_people']
-                exposed_presence = self.generate_dynamic_occupancy(exposure_group['presence'])
-                total_models.append(models.SimplePopulation(
-                    number=exposed_occupancy, # int
-                    presence=exposed_presence, # SpecificInterval
-                    activity=None, # type: ignore
-                ))
-                # For all state changes
-                total_presence.append(exposed_presence)
-        
-        elif self.occupancy_format == 'static':
-            infected_people = self.infected_people
-            exposed_people = self.total_people - self.infected_people
-            infected_presence = self.infected_present_interval()
-            exposed_presence = self.exposed_present_interval()
-
-            infected_population = models.SimplePopulation(
-                number=infected_people,
-                presence=infected_presence,
-                activity=None, # type: ignore
-            )
-            exposed_population=models.SimplePopulation(
-                number=exposed_people,
-                presence=exposed_presence,
-                activity=None, # type: ignore
-            )
-            
-            total_presence = [infected_presence, exposed_presence]
-            total_models = [infected_population, exposed_population]
+            for group in self.occupancy.values():
+                model_piecewise = self.convert_interval_to_piecewise(
+                    interval=self.generate_exposed_presence(group['presence']),
+                    value=group['total_people'] - group['infected']
+                )
+                total_models.append(model_piecewise)
 
         # Get all state change times from combined populations
-        all_state_changes=self.population_present_changes(total_presence)
+        all_state_changes = self.population_present_changes([t for model in total_models for t in model.transition_times])
 
         # Compute total people at each state change
         total_people = []
         for _, stop in zip(all_state_changes[:-1], all_state_changes[1:]):
-            total_people_in_group = sum(population.people_present(stop) for population in total_models)
+            total_people_in_group = sum(model.value(stop) for model in total_models)
             total_people.append(total_people_in_group)
 
-        return models.IntPiecewiseConstant(transition_times=tuple(all_state_changes), values=tuple(total_people))
+        return models.IntPiecewiseConstant(
+            transition_times=tuple(all_state_changes), 
+            values=tuple(total_people)
+        )
 
     def _compute_breaks_in_interval(self, start, finish, n_breaks, duration) -> models.BoundarySequence_t:
         break_delay = ((finish - start) -
@@ -661,66 +668,66 @@ class FormData:
             self.exposed_start, self.exposed_finish,
             breaks=breaks,
         )
+
+    def generate_exposed_presence(self, presence: typing.List) -> models.SpecificInterval:
+            """
+            Creates a model to represent exposed occupancy over time.
+            """
+            exposed_intervals = []
+
+            # Sort occupancy entries by start_time to ensure proper ordering
+            presence_sorted = sorted(
+                presence, key=lambda x: time_string_to_minutes(x['start_time'])
+            )
+            
+            for period in presence_sorted:
+                start_time = time_string_to_minutes(period['start_time']) / 60
+                finish_time = time_string_to_minutes(period['finish_time']) / 60   
+                exposed_intervals.append((start_time, finish_time))
+
+            return models.SpecificInterval(tuple(exposed_intervals))
     
-    def generate_dynamic_occupancy(self, dynamic_occupancy: typing.List[typing.Dict[str, typing.Any]]):
+    def generate_infected_occupancy(self, occupancy: typing.Dict) -> models.IntPiecewiseConstant:
         """
-        Creates a model to represent occupancy over time. If `total_people` is 
-        provided in the input, the method generates an `IntPiecewiseConstant` model, representing 
-        occupancy as a piecewise constant function with defined values for each interval. 
-        Otherwise, it generates a `SpecificInterval` model, which only tracks the presence of 
-        intervals without associating values to them.
+        Creates a model to represent infected occupancy over time.
         """
+        transition_times = set()
+        infected_intervals = []
 
-        # Initialize variables
-        if 'total_people' in dynamic_occupancy[0]: # build IntPiecewiseConstant
-            computePiecewiseConstant = True
-            transition_times = []
-            values = []
-        else:
-            computePiecewiseConstant = False
-            present_times = [] # build SpecificInterval
+        # Extract presence data
+        for group in occupancy.values():
+            infected = group["infected"]
+            for period in group["presence"]:
+                start_time = time_string_to_minutes(period['start_time']) / 60
+                finish_time = time_string_to_minutes(period['finish_time']) / 60
+                transition_times.add(start_time) # unique time points
+                transition_times.add(finish_time) # unique time points
+                infected_intervals.append((start_time, finish_time, infected))
+        
+        # Sort transition times
+        sorted_transition_times = list(sorted(transition_times))
 
-        # Sort occupancy entries by start_time to ensure proper ordering
-        dynamic_occupancy_sorted = sorted(
-            dynamic_occupancy, key=lambda x: time_string_to_minutes(x['start_time'])
+        # Values for each time segment
+        raw_values = [
+            sum(people for start, end, people in infected_intervals if start <= t1 < end)
+            for t1 in sorted_transition_times[:-1]
+        ]
+
+        # Merge consecutive intervals with the same infected count
+        opt_times = [sorted_transition_times[0]]
+        opt_values = [raw_values[0]]
+        for i in range(1, len(raw_values)):
+            if raw_values[i] != opt_values[-1]:
+                opt_times.append(sorted_transition_times[i])
+                opt_values.append(raw_values[i])
+        # Ensure the last time is included
+        opt_times.append(sorted_transition_times[-1])
+
+        return models.IntPiecewiseConstant(
+            transition_times=tuple(opt_times),
+            values=tuple(opt_values)
         )
 
-        last_finish_time = None
-
-        for occupancy in dynamic_occupancy_sorted:
-            start_time = time_string_to_minutes(occupancy['start_time']) / 60
-            finish_time = time_string_to_minutes(occupancy['finish_time']) / 60
-            
-            if computePiecewiseConstant:
-                total_people = occupancy['total_people']
-
-                # Fill in gap with a zero occupancy if there is a time gap
-                if last_finish_time is not None and start_time > last_finish_time:
-                    transition_times.append(last_finish_time)
-                    values.append(0)  # Add zero for the gap period
-
-                # Update lists with current occupancy entry
-                transition_times.extend([start_time, finish_time])
-                values.append(total_people)
-
-                # Update the last known finish time
-                last_finish_time = finish_time
-            else:
-                present_times.append((start_time, finish_time))
-                    
-        # When computing the total people, validate that we have enough values to compute the occupancy
-        if computePiecewiseConstant:
-            unique_transition_times_sorted = np.array(sorted(set(transition_times)))
-            if (len(values) != len(unique_transition_times_sorted) - 1):
-                raise ValueError("Cannot compute dynamic occupancy with the provided inputs.")
-            else:
-                return models.IntPiecewiseConstant(
-                    transition_times=tuple(unique_transition_times_sorted),
-                    values=tuple(values)
-                )            
-        else:
-            return models.SpecificInterval(tuple(present_times))
-        
 
 def _hours2timestring(hours: float):
     # Convert times like 14.5 to strings, like "14:30"

caimira/src/caimira/calculator/validators/virus/virus_validator.py

@@ -201,13 +201,14 @@ class VirusFormData(FormData):
                     f'The sum of all respiratory activities should be 100. Got {total_percentage}.')
 
         # Validate number of people with short-range interactions
-        if self.occupancy_format == 'static':
+        if not self.occupancy:
+            # Legacy usage - occupancy input is not defined (default empty dict)
             max_occupants_for_sr = self.total_people - self.infected_people
-        elif self.occupancy_format == 'dynamic':
+        else:
             max_occupants_for_sr = 0
-            for key, group in self.dynamic_exposed_occupancy.items():
-                occupants_in_group = group['total_people']
-                max_occupants_for_sr = max(max_occupants_for_sr, occupants_in_group)
+            for group_id, group in self.occupancy.items():
+                exposed_occupants_in_group = group['total_people'] - group['infected']
+                max_occupants_for_sr = max(max_occupants_for_sr, exposed_occupants_in_group)
                 
         if self.short_range_occupants > max_occupants_for_sr:
             raise ValueError(
@@ -217,14 +218,19 @@ class VirusFormData(FormData):
         # Validate short-range interactions interval
         if self.short_range_option == "short_range_yes":
             if isinstance(self.short_range_interactions, dict):
-                # Check if occupancy format is static, there should be one key-value only in short_range_interactions
-                if self.occupancy_format == "static" and len(self.short_range_interactions) > 1:
-                    raise ValueError(
-                        'When occupancy format is "static", there should be only one interaction group in "short_range_interactions".'
-                    )
-                # The key is the actual identifier
-                for key, group in self.short_range_interactions.items():
-                    self.validate_dynamic_input(group, "short_range_interactions", key)
+                # Checks if short_range_interactions input is not empty
+                if len(self.short_range_interactions) == 0:
+                    raise ValueError(f'When short_range_option input is set to "{self.short_range_option}", the short_range_interactions input should not be empty. Got {self.short_range_interactions}.')
+                # Checks that the number of groups in the short_range_interactions input is less or equal than those defined in the occupancy
+                elif not self.occupancy:
+                    # Legacy usage - occupancy input is not defined (default empty dict)
+                    if len(self.short_range_interactions) > 1:
+                        raise ValueError(f'Incompatible number of occupancy groups in the short_range_interactions input. Got {len(self.short_range_interactions)} groups when the maximum is 1.')
+                else:
+                    if len(self.short_range_interactions) > len(self.occupancy):
+                        raise ValueError(f'Incompatible number of occupancy groups in the short_range_interactions input. Got {len(self.short_range_interactions)} groups when the maximum is {len(self.occupancy)} (from the occupancy input).')
+                for group_id, interactions in self.short_range_interactions.items():
+                    self.validate_short_range_interaction_input(group_id, interactions)
     
     def initialize_room(self) -> models.Room:
         # Initializes room with volume either given directly or as product of area and height
@@ -246,8 +252,6 @@ class VirusFormData(FormData):
         return models.Room(volume=volume, inside_temp=models.PiecewiseConstant((0, 24), (inside_temp,)), humidity=humidity) # type: ignore
 
     def build_mc_model(self) -> mc.ExposureModelGroup:
-        size = self.data_registry.monte_carlo['sample_size']
-
         room: models.Room = self.initialize_room()
         ventilation: models._VentilationBase = self.ventilation()
         infected_population: models.InfectedPopulation = self.infected_population()
@@ -266,7 +270,7 @@ class VirusFormData(FormData):
                         presence=presence,
                         distance=distances,
                         expiration_def=interaction['expiration']
-                    ).build_model(size))
+                    ))
 
         concentration_model: models.ConcentrationModel = mc.ConcentrationModel(
             data_registry=self.data_registry,
@@ -274,19 +278,34 @@ class VirusFormData(FormData):
             ventilation=ventilation,
             infected=infected_population,
             evaporation_factor=0.3,
-        ).build_model(size)
+        )
 
         geographical_data: models.Cases = mc.Cases(
             geographic_population=self.geographic_population,
             geographic_cases=self.geographic_cases,
             ascertainment_bias=CONFIDENCE_LEVEL_OPTIONS[self.ascertainment_bias],
-        ).build_model(size)
+        )
 
-        if self.occupancy_format == 'dynamic':
+        if not self.occupancy:
+            # Legacy usage - occupancy input is not defined (default empty dict)
+            exposed_population = self.exposed_population()
+            short_range_tuple = tuple(item for sublist in short_range.values() for item in sublist)
+            return mc.ExposureModelGroup(
+                data_registry=self.data_registry,
+                exposure_models = (mc.ExposureModel(
+                    data_registry=self.data_registry,
+                    concentration_model=concentration_model,
+                    short_range=short_range_tuple,
+                    exposed=exposed_population,
+                    geographical_data=geographical_data,
+                    exposed_to_short_range=self.short_range_occupants,
+                ),)
+            )
+        else:
             exposure_model_set = []
-            for exposure_group in self.dynamic_exposed_occupancy.keys():
+            for exposure_group in self.occupancy.keys():
                 sr_models: typing.Tuple[models.ShortRangeModel, ...] = tuple(short_range[exposure_group])
-                exposed_population: mc.Population = self.exposed_population(exposure_group).build_model(size)
+                exposed_population = self.exposed_population(exposure_group)
 
                 exposure_model = mc.ExposureModel(
                     data_registry=self.data_registry,
@@ -301,27 +320,12 @@ class VirusFormData(FormData):
 
             return mc.ExposureModelGroup(
                 data_registry=self.data_registry,
-                exposure_models=[individual_model.build_model(size) for individual_model in exposure_model_set]
-            )
-
-        elif self.occupancy_format == 'static':
-            exposed_population = self.exposed_population()
-            short_range_tuple = tuple(item for sublist in short_range.values() for item in sublist)
-            return mc.ExposureModelGroup(
-                data_registry=self.data_registry,
-                exposure_models = [mc.ExposureModel(
-                    data_registry=self.data_registry,
-                    concentration_model=concentration_model,
-                    short_range=short_range_tuple,
-                    exposed=exposed_population,
-                    geographical_data=geographical_data,
-                    exposed_to_short_range=self.short_range_occupants,
-                ).build_model(size)]
+                exposure_models=tuple(exposure_model_set)
             )
 
     def build_model(self, sample_size=None) -> models.ExposureModelGroup:
-        size = self.data_registry.monte_carlo['sample_size'] if not sample_size else sample_size
-        return self.build_mc_model().build_model(size=size)
+        sample_size = sample_size or self.data_registry.monte_carlo['sample_size']
+        return self.build_mc_model().build_model(sample_size)
 
     def build_CO2_model(self, sample_size=None) -> models.CO2ConcentrationModel:
         """
@@ -481,7 +485,7 @@ class VirusFormData(FormData):
 
     def generate_precise_activity_expiration(self) -> typing.Tuple[typing.Any, ...]:
         # It means the precise activity is not defined by a specific input.
-        if self.precise_activity == {}:
+        if not self.precise_activity:
             return ()
         respiratory_dict = {}
         for respiratory_activity in self.precise_activity['respiratory_activity']:
@@ -499,12 +503,13 @@ class VirusFormData(FormData):
         virus = virus_distributions(self.data_registry)[self.virus_type]
 
         # Occupancy
-        if self.occupancy_format == 'dynamic':
-            infected_occupancy = self.generate_dynamic_occupancy(self.dynamic_infected_occupancy)
-            infected_presence = None
-        else:
-            infected_occupancy = self.infected_people
+        if not self.occupancy:
+            # Legacy usage - occupancy input is not defined (default empty dict)
+            infected_occupancy: typing.Union[int, models.IntPiecewiseConstant] = self.infected_people
             infected_presence = self.infected_present_interval()
+        else:
+            infected_occupancy = self.generate_infected_occupancy(self.occupancy)
+            infected_presence = None
 
         # Activity and expiration
         activity_defn = self.data_registry.population_scenario_activity[
@@ -513,8 +518,7 @@ class VirusFormData(FormData):
             self.activity_type]['expiration']
         if (self.activity_type == 'smallmeeting'):
             # Conversation of N people is approximately 1/N% of the time speaking.
-            total_people: int = max(
-                infected_occupancy.values) if self.occupancy_format == 'dynamic' else self.total_people
+            total_people: int = self.total_people if not self.occupancy else max(infected_occupancy.values) # type: ignore
             expiration_defn = {'Speaking': 1, 'Breathing': total_people - 1}
         elif (self.activity_type == 'precise'):
             activity_defn, expiration_defn = self.generate_precise_activity_expiration()
@@ -542,16 +546,15 @@ class VirusFormData(FormData):
         single group of exposed population, except when breaks are defined.
         """
         # Occupancy
-        if self.occupancy_format == 'dynamic':
-            dynamic_group = self.dynamic_exposed_occupancy[exposure_group]
-
-            exposed_occupancy = dynamic_group['total_people']
-            exposed_presence = self.generate_dynamic_occupancy(dynamic_group['presence'])
-        else:
+        if not exposure_group and not self.occupancy:
             # The number of exposed occupants is the total number of occupants
             # minus the number of infected occupants.
             exposed_occupancy = self.total_people - self.infected_people
             exposed_presence = self.exposed_present_interval()
+        elif exposure_group:
+            dynamic_group = self.occupancy[exposure_group]
+            exposed_occupancy = dynamic_group['total_people'] - dynamic_group['infected']
+            exposed_presence = self.generate_exposed_presence(dynamic_group['presence'])
 
         # Activity
         activity_defn = (self.precise_activity['physical_activity']
@@ -608,8 +611,6 @@ def baseline_raw_form_data() -> typing.Dict[str, typing.Union[str, float]]:
         'calculator_version': calculator_version,
         'ceiling_height': '',
         'conditional_probability_viral_loads': '0',
-        'dynamic_exposed_occupancy': '{}',
-        'dynamic_infected_occupancy': '[]',
         'event_month': 'January',
         'exposed_coffee_break_option': 'coffee_break_4',
         'exposed_coffee_duration': '10',
@@ -640,7 +641,7 @@ def baseline_raw_form_data() -> typing.Dict[str, typing.Union[str, float]]:
         'mask_type': 'Type I',
         'mask_wearing_option': 'mask_off',
         'mechanical_ventilation_type': '',
-        'occupancy_format': 'static',
+        'occupancy': '{}',
         'opening_distance': '0.2',
         'room_heating_option': '0',
         'room_number': '123',

caimira/tests/apps/calculator/test_model_generator.py

@@ -590,71 +590,52 @@ def test_form_timezone(baseline_form_data, data_registry, longitude, latitude, m
     assert offset == expected_offset
 
 
-@pytest.mark.parametrize(
-    ["occupancy_format_input", "error"],
-    [
-        ['dynamc', "'dynamc' is not a valid value for 'self.occupancy_format'. Accepted values are 'static' or 'dynamic'.",],
-        ['stact', "'stact' is not a valid value for 'self.occupancy_format'. Accepted values are 'static' or 'dynamic'.",],
-        ['random', "'random' is not a valid value for 'self.occupancy_format'. Accepted values are 'static' or 'dynamic'.",]
-    ]
-)
-def test_occupancy_format_input(occupancy_format_input, error, baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = occupancy_format_input
-    with pytest.raises(ValueError, match=re.escape(error)):
-        baseline_form.validate()
-
-
-def test_dynamic_input_format_ValueError(baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"        
-    # Check empty list for infected occupancy
-    baseline_form.dynamic_infected_occupancy = []
-    error = 'The input "dynamic_infected_occupancy" should be a valid, non-empty list. Got "[]".'
-    with pytest.raises(ValueError, match=re.escape(error)):
-        baseline_form.validate()
-    # Check empty dict for exposed occupancy
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {}
-    error = 'The input "dynamic_exposed_occupancy" should be a valid, non-empty dict. Got "{}".'
-    with pytest.raises(ValueError, match=re.escape(error)):
-        baseline_form.validate()
-
-
-@pytest.mark.parametrize(
-    ["exposed_format", "error"],
-    [   
-        [
-            {"tal_people": 10, "presence": [{"start_time": "10:00", "finish_time": "11:00"}],},
-            'Missing "total_people" key in "dynamic_exposed_occupancy" group "group_1". Got keys: "[\'tal_people\', \'presence\']".'
-        ],
-        [
-            {"total_people": 10, "pesence": [{"start_time": "10:00", "finish_time": "11:00"}],},
-            'Missing "presence" key in "dynamic_exposed_occupancy" group "group_1". Got keys: "[\'total_people\', \'pesence\']".'
-        ],
-    ]
-)
-def test_dynamic_exposed_format_TypeError(exposed_format, error, baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {"group_1": exposed_format}
+def test_occupancy_TypeError(baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = [] # type: ignore
+    error = 'The occupancy input should be a valid dictionary. Got [].'
     with pytest.raises(TypeError, match=re.escape(error)):
         baseline_form.validate()
 
 
 @pytest.mark.parametrize(
-    ["exposed_presence", "error"],
+    ["occupancy", "error"],
     [   
-        [[["start_time", "10:00", "finish_time", "11:00"]], 'Each entry in "dynamic_exposed_occupancy" should be a dictionary. Got "<class \'list\'>".'],
-        [[{"art_time": "10:00", "finish_time": "11:00"}], 'Missing "start_time" key in "dynamic_exposed_occupancy" in "group_1" ("presence"). Got keys: "[\'art_time\', \'finish_time\']".'],
-        [[{"start_time": "10:00", "ish_time": "11:00"}], 'Missing "finish_time" key in "dynamic_exposed_occupancy" in "group_1" ("presence"). Got keys: "[\'start_time\', \'ish_time\']".'],
+        [
+            {"tal_people": 10, "infected": 5, "presence": [{"start_time": "10:00", "finish_time": "11:00"}],},
+            'Missing total_people key in occupancy group "group_A". Got keys: tal_people, infected, presence.'
+        ],
+        [
+            {"total_people": 10, "infeted": 5, "presence": [{"start_time": "10:00", "finish_time": "11:00"}],},
+            'Missing infected key in occupancy group "group_A". Got keys: total_people, infeted, presence.'
+        ],
+        [
+            {"total_people": 10, "infected": 5, "pesence": [{"start_time": "10:00", "finish_time": "11:00"}],},
+            'Missing presence key in occupancy group "group_A". Got keys: total_people, infected, pesence.'
+        ],
     ]
 )
-def test_dynamic_exposed_presence_TypeError(exposed_presence, error, baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
+def test_occupancy_general_params_TypeError(occupancy, error, baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {"group_A": occupancy}
+    with pytest.raises(TypeError, match=re.escape(error)):
+        baseline_form.validate()
+
+
+@pytest.mark.parametrize(
+    ["occupancy_presence", "error"],
+    [   
+        [{"start_time": "10:00", "finish_time": "11:00"}, 'The presence parameter in occupancy group "group_A" should be a valid list. Got <class \'dict\'>.'],
+        [[], 'The presence parameter in occupancy group "group_A" should be a valid, non-empty list. Got [].'],
+        [[["start_time", "10:00", "finish_time", "11:00"]], 'Each presence interval should be a valid dictionary. Got <class \'list\'> in occupancy group "group_A".'],
+        [[{"art_time": "10:00", "finish_time": "11:00"}], 'Missing start_time key in presence parameter of occupancy group "group_A". Got keys: art_time, finish_time.'],
+        [[{"start_time": "10:00", "ish_time": "11:00"}], 'Missing finish_time key in presence parameter of occupancy group "group_A". Got keys: start_time, ish_time.'],
+    ]
+)
+def test_occupancy_presence_TypeError(occupancy_presence, error, baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {
+        "group_A": {
             "total_people": 10,
-            "presence": exposed_presence,
+            "infected": 5,
+            "presence": occupancy_presence,
         }
     }
     with pytest.raises(TypeError, match=re.escape(error)):
@@ -662,42 +643,60 @@ def test_dynamic_exposed_presence_TypeError(exposed_presence, error, baseline_fo
 
 
 @pytest.mark.parametrize(
-    ["exposed_presence", "error"],
+    ["occupancy_presence", "error"],
     [
-        [[{"start_time": "10", "finish_time": "11:00"}], 'Invalid time format for "start_time" in "dynamic_exposed_occupancy" in "group_1" ("presence"). Expected "HH:MM". Got "10".'],
-        [[{"start_time": "10:00", "finish_time": "11"}], 'Invalid time format for "finish_time" in "dynamic_exposed_occupancy" in "group_1" ("presence"). Expected "HH:MM". Got "11".'],
+        [[{"start_time": "10", "finish_time": "11:00"}], 'Invalid time format found in presence parameter of occupancy group "group_A". Expected HH:MM, got 10.'],
+        [[{"start_time": "10:00", "finish_time": "11"}], 'Invalid time format found in presence parameter of occupancy group "group_A". Expected HH:MM, got 11.'],
     ]
 )
-def test_dynamic_exposed_presence_ValueError(exposed_presence, error, baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
+def test_occupancy_presence_ValueError(occupancy_presence, error, baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {
+        "group_A": {
             "total_people": 10,
-            "presence": exposed_presence
+            "infected": 5,
+            "presence": occupancy_presence
         }
     }
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
 
+
 @pytest.mark.parametrize(
-    ["exposed_total_people", "error"],
+    ["total_people", "error"],
     [
-        ["10", 'The "total_people" in "dynamic_exposed_occupancy" group "group_1" should be a non-negative integer. Got "10".'],
-        [9.8, 'The "total_people" in "dynamic_exposed_occupancy" group "group_1" should be a non-negative integer. Got "9.8".'],
-        [[10], 'The "total_people" in "dynamic_exposed_occupancy" group "group_1" should be a non-negative integer. Got "[10]".'],
-        [-1, 'The "total_people" in "dynamic_exposed_occupancy" group "group_1" should be a non-negative integer. Got "-1".'],
+        ["10", 'The total_people input in occupancy group "group_A" should be a non-negative integer. Got 10.'],
+        [9.8, 'The total_people input in occupancy group "group_A" should be a non-negative integer. Got 9.8.'],
+        [[10], 'The total_people input in occupancy group "group_A" should be a non-negative integer. Got [10].'],
+        [-1, 'The total_people input in occupancy group "group_A" should be a non-negative integer. Got -1.'],
     ]
 )
-def test_dynamic_exposed_total_people_ValueError(exposed_total_people, error, baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [
-        {"total_people": 1, "start_time": "08:00", "finish_time": "10:00"},
-        {"total_people": 2, "start_time": "10:00", "finish_time": "18:00"},
+def test_occupancy_total_people_ValueError(total_people, error, baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {
+        "group_A": {
+            "total_people": total_people,
+            "infected": 10,
+            "presence": [{"start_time": "08:00", "finish_time": "18:00"},],
+        },
+    }
+    with pytest.raises(ValueError, match=re.escape(error)):
+        baseline_form.validate()
+
+
+@pytest.mark.parametrize(
+    ["infected", "error"],
+    [
+        ["10", 'The infected input in occupancy group "group_A" should be a non-negative integer. Got 10.'],
+        [9.8, 'The infected input in occupancy group "group_A" should be a non-negative integer. Got 9.8.'],
+        [[10], 'The infected input in occupancy group "group_A" should be a non-negative integer. Got [10].'],
+        [-1, 'The infected input in occupancy group "group_A" should be a non-negative integer. Got -1.'],
+        [30, 'The number of infected people (30) cannot be greater than the total people (20).']
     ]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
-            "total_people": exposed_total_people,
+)
+def test_occupancy_infected_ValueError(infected, error, baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {
+        "group_A": {
+            "total_people": 20,
+            "infected": infected,
             "presence": [{"start_time": "08:00", "finish_time": "18:00"},],
         },
     }
@@ -705,42 +704,11 @@ def test_dynamic_exposed_total_people_ValueError(exposed_total_people, error, ba
         baseline_form.validate()
         
 
-def test_dynamic_infected_overlap(baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [
-        {"total_people": 10, "start_time": "08:00", "finish_time": "18:00"},
-        {"total_people": 10, "start_time": "10:00", "finish_time": "18:00"},
-    ]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
-            "total_people": 10,
-            "presence": [{"start_time": "08:00", "finish_time": "18:00"}],
-        },
-        "group_2": {
-            "total_people": 10,
-            "presence": [{"start_time": "10:00", "finish_time": "11:00"}],
-        },
-        "group_3": {
-            "total_people": 10,
-            "presence": [{"start_time": "15:00", "finish_time": "18:00"}],
-        },
-    }
-    error = (
-        'Overlap detected: New interaction '
-        '"{\'total_people\': 10, \'start_time\': \'10:00\', \'finish_time\': \'18:00\'}" '
-        'overlaps with existing interaction '
-        '"{\'total_people\': 10, \'start_time\': \'08:00\', \'finish_time\': \'18:00\'}".'
-    )
-    with pytest.raises(ValueError, match=re.escape(error)):
-        baseline_form.validate()
-        
-
-def test_dynamic_exposure_group_duplication(baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = "dynamic"
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
+def test_occupancy_presence_overlap(baseline_form: virus_validator.VirusFormData):
+    baseline_form.occupancy = {
+        "group_A": {
             "total_people": 10,
+            "infected": 5,
             "presence": [
                 {"start_time": "08:00", "finish_time": "17:00"},
                 {"start_time": "13:00", "finish_time": "14:00"},
@@ -748,10 +716,10 @@ def test_dynamic_exposure_group_duplication(baseline_form: virus_validator.Virus
         },
     }
     error = (
-        'Overlap detected: New interaction '
-        '"{\'start_time\': \'13:00\', \'finish_time\': \'14:00\'}"'
-        ' overlaps with existing interaction '
-        '"{\'start_time\': \'08:00\', \'finish_time\': \'17:00\'}".'
+        'Overlap detected: The entry '
+        '{\'start_time\': \'13:00\', \'finish_time\': \'14:00\'}'
+        ' overlaps with an already existing entry '
+        '({\'start_time\': \'08:00\', \'finish_time\': \'17:00\'}).'
     )
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
@@ -760,32 +728,32 @@ def test_dynamic_exposure_group_duplication(baseline_form: virus_validator.Virus
 @pytest.mark.parametrize(
     ["short_range_input", "error"],
     [
-        [[["expiration", "Shouting", "start_time", "09:00", "duration", 30]], 'Each entry in "short_range_interactions" should be a dictionary. Got "<class \'list\'>".'],
-        [[{"expiratio": "Shouting", "start_time": "09:00", "duration": 30}], 'Missing "expiration" key in "short_range_interactions", "group_1". Got keys: "[\'expiratio\', \'start_time\', \'duration\']".'],
-        [[{"expiration": "Shouting", "start_tim": "09:00", "duration": 30}], 'Missing "start_time" key in "short_range_interactions", "group_1". Got keys: "[\'expiration\', \'start_tim\', \'duration\']".'],
-        [[{"expiration": "Shouting", "start_time": "09:00", "duratio": 30}], 'Missing "duration" key in "short_range_interactions", "group_1". Got keys: "[\'expiration\', \'start_time\', \'duratio\']".'],
+        [[["expiration", "Shouting", "start_time", "09:00", "duration", 30]], 'Each short-range interaction should be a dictionary. Got <class \'list\'> in occupancy group "group_A".'],
+        [[{"expiratio": "Shouting", "start_time": "09:00", "duration": 30}], 'Missing expiration key in short-range interaction for occupancy group "group_A". Got keys: expiratio, start_time, duration.'],
+        [[{"expiration": "Shouting", "start_tim": "09:00", "duration": 30}], 'Missing start_time key in short-range interaction for occupancy group "group_A". Got keys: expiration, start_tim, duration.'],
+        [[{"expiration": "Shouting", "start_time": "09:00", "duratio": 30}], 'Missing duration key in short-range interaction for occupancy group "group_A". Got keys: expiration, start_time, duratio.'],
     ]
 )
 def test_short_range_TypeError(short_range_input, error, baseline_form: virus_validator.VirusFormData):
     baseline_form.short_range_option = "short_range_yes"
-    baseline_form.short_range_interactions = {"group_1": short_range_input}
+    baseline_form.short_range_interactions = {"group_A": short_range_input}
     with pytest.raises(TypeError, match=re.escape(error)):
         baseline_form.validate()
 
 
 def test_short_range_exposure_group(baseline_form: virus_validator.VirusFormData):
-    baseline_form.occupancy_format = 'dynamic'
-    baseline_form.dynamic_infected_occupancy = [{"total_people": 10, "start_time": "10:00", "finish_time": "11:00"}]
-    baseline_form.dynamic_exposed_occupancy = {
-        "group_1": {
-            "total_people": 10,
+    baseline_form.occupancy = {
+        "group_A": {
+            "total_people": 20,
+            "infected": 10,
             "presence": [
                 {"start_time": "10:00", "finish_time": "12:00"},
                 {"start_time": "13:00", "finish_time": "17:00"},
             ],
         },
-        "group_2": {
-            "total_people": 10,
+        "group_B": {
+            "total_people": 20,
+            'infected': 10,
             "presence": [
                 {"start_time": "10:00", "finish_time": "11:00"},
             ],
@@ -795,19 +763,19 @@ def test_short_range_exposure_group(baseline_form: virus_validator.VirusFormData
     # Check for existence of the dictionary key
     baseline_form.short_range_option = 'short_range_yes'
     baseline_form.short_range_interactions = {
-        "group_4": [{"expiration": "Shouting", "start_time": "10:30", "duration": 30}],
+        "group_C": [{"expiration": "Shouting", "start_time": "10:30", "duration": 30}],
     }
-    error = 'Exposure group "group_4" in short-range interaction not found in dynamic exposed occupancy.'
+    error = 'Occupancy group "group_C" referenced in short-range interactions was not found in the occupancy input.'
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
 
     # Check if interaction time is within simulation time
     baseline_form.short_range_interactions = {
-        "group_1": [{"expiration": "Shouting", "start_time": "18:00", "duration": 30}],
+        "group_A": [{"expiration": "Shouting", "start_time": "18:00", "duration": 30}],
     }
     error = (
-        'Short-range interaction "{\'expiration\': \'Shouting\', \'start_time\': \'18:00\', \'duration\': 30}"'
-        ' does not fall within any long-range exposure interval in "group_1".'
+        'Short-range interaction {\'expiration\': \'Shouting\', \'start_time\': \'18:00\', \'duration\': 30}'
+        ' does not fall within any presence interval in occupancy group "group_A".'
     )
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
@@ -816,52 +784,82 @@ def test_short_range_exposure_group(baseline_form: virus_validator.VirusFormData
 @pytest.mark.parametrize(
     ["short_range_input", "error"],
     [
-        [[{"expiration": "Shouting", "start_time": "9", "duration": 30}], 'Invalid time format for "start_time" in "short_range_interactions", "group_1". Expected "HH:MM". Got "9".'],
-        [[{"expiration": "Whisper", "start_time": "09:00", "duration": 30}], 'The "expiration" in "short_range_interactions", "group_1", does not exist in the registry. Got "Whisper".'],
-        [[{"expiration": "Shouting", "start_time": "09:00", "duration": -30}], 'The "duration" in "short_range_interactions", "group_1", should be a non-negative integer. Got "-30".'],
+        [[{"expiration": "Shouting", "start_time": "9", "duration": 30}], 'Invalid time format for start_time in short-range interaction for occupancy group "group_A". Expected HH:MM, got 9.'],
+        [[{"expiration": "Whisper", "start_time": "09:00", "duration": 30}], 'Invalid expiration value in short-range interaction for occupancy group "group_A". Got "Whisper".'],
+        [[{"expiration": "Shouting", "start_time": "09:00", "duration": -30}], 'The duration value in short-range interaction for occupancy group "group_A" should be a non-negative integer. Got -30.'],
     ]
 )
 def test_short_range_value_error(short_range_input, error, baseline_form: virus_validator.VirusFormData):
     baseline_form.short_range_option = "short_range_yes"
-    baseline_form.short_range_interactions = {"group_1": short_range_input}
+    baseline_form.short_range_interactions = {"group_A": short_range_input}
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
 
 
-def test_short_range_with_static_occupancy(baseline_form: virus_validator.VirusFormData):
-    # By default the occupancy format is 'static'
+def test_short_range_with_occupancy_format(baseline_form: virus_validator.VirusFormData):
     baseline_form.short_range_option = "short_range_yes"
-    baseline_form.short_range_interactions = {"group_1": [{"expiration": "Shouting", "start_time": "07:00", "duration": 30}]}
+    baseline_form.short_range_interactions = {"group_A": [{"expiration": "Shouting", "start_time": "07:00", "duration": 30}]}
 
-    # Check if interaction is defined during simulation time
+    # Checks if interaction is defined during simulation time
     error = (
-        'Short-range interactions should be defined during simulation time. Got '
-        '"{\'expiration\': \'Shouting\', \'start_time\': \'07:00\', \'duration\': 30}".'
+        'Short-range interactions must occur during simulation time. Got'
+        ' {\'expiration\': \'Shouting\', \'start_time\': \'07:00\', \'duration\': 30}'
+        ' in occupancy group "group_A".'
     )
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
 
-    # Check overlap of interactions
+    # Checks overlap of short-range interactions
     baseline_form.short_range_interactions = {
-        "group_1": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30},
+        "group_A": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30},
                     {"expiration": "Shouting", "start_time": "10:10", "duration": 15}],
     }
     error = (
-        'Overlap detected for "short-range interaction": New interaction '
-        '"{\'expiration\': \'Shouting\', \'start_time\': \'10:10\', \'duration\': 15}"'
-        ' overlaps with existing interaction "{\'expiration\': \'Shouting\', \'start_time\': \'10:00\', \'duration\': 30}".'
+        'Overlap detected: The entry '
+        '{\'expiration\': \'Shouting\', \'start_time\': \'10:10\', \'duration\': 15}'
+        ' overlaps with an already existing entry '
+        '({\'expiration\': \'Shouting\', \'start_time\': \'10:00\', \'duration\': 30}).'
     )
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()
 
-    # Check if more than one group is defined
-    baseline_form.short_range_interactions = {
-        "group_1": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30},
-                    {"expiration": "Shouting", "start_time": "10:10", "duration": 15}],
-        "group_2": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30}]
-    }
+    # Checks if short_range_option relates with the short_range-interactions input
+    baseline_form.short_range_option = "short_range_yes"
+    baseline_form.short_range_interactions = {}
     error = (
-        'When occupancy format is "static", there should be only one interaction group in "short_range_interactions".'
+        'When short_range_option input is set to "short_range_yes", the short_range_interactions '
+        'input should not be empty. Got {}.'
+    )
+    with pytest.raises(ValueError, match=re.escape(error)):
+        baseline_form.validate()
+    
+    # Checks if more than one group is defined (legacy)
+    baseline_form.short_range_interactions = {
+        "group_A": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30}],
+        "group_B": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30}]
+    }
+    error = (
+        'Incompatible number of occupancy groups in the short_range_interactions input. '
+        'Got 2 groups when the maximum is 1.'
+    )
+    with pytest.raises(ValueError, match=re.escape(error)):
+        baseline_form.validate()
+
+    # Checks if more than one group is defined
+    baseline_form.occupancy = {
+        "group_A": {"total_people": 20, "infected": 10, "presence": [
+                {"start_time": "10:00", "finish_time": "12:00"},
+                {"start_time": "13:00", "finish_time": "17:00"},
+            ],
+        }
+    }
+    baseline_form.short_range_interactions = {
+        "group_A": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30}],
+        "group_B": [{"expiration": "Shouting", "start_time": "10:00", "duration": 30}]
+    }
+    error = (
+        'Incompatible number of occupancy groups in the short_range_interactions input. '
+        'Got 2 groups when the maximum is 1 (from the occupancy input).'
     )
     with pytest.raises(ValueError, match=re.escape(error)):
         baseline_form.validate()

caimira/tests/models/test_dynamic_population.py

@@ -213,7 +213,7 @@ def test_exposure_model_group_structure(data_registry, full_exposure_model: mode
     """
     another_full_exposure_model = dc_utils.nested_replace(full_exposure_model,
         {'concentration_model.infected.number': 2, })
-    with pytest.raises(ValueError, match=re.escape("All ExposureModels must have the same ConcentrationModel.")):
+    with pytest.raises(ValueError, match=re.escape("All ExposureModels must have the same infected number and presence in the ConcentrationModel.")):
         models.ExposureModelGroup(data_registry, exposure_models=(full_exposure_model, another_full_exposure_model, ))
 
 

cern_caimira/src/cern_caimira/apps/calculator/report/virus_report.py

@@ -122,8 +122,8 @@ class VirusReportGenerator:
         model: models.ExposureModel = report_data['model']
         data_registry_version: typing.Optional[str] = f"v{model.data_registry.version}" if model.data_registry.version else None
 
-        # Alternative scenarios data
-        if form.occupancy_format == 'static':
+        # Alternative scenarios data (only generated in the legacy version - when occupancy input is empty)
+        if not form.occupancy:
             context.update(alternative_scenarios_data(form, report_data, executor_factory)) 
 
         # Alternative viral load data

cern_caimira/src/cern_caimira/apps/calculator/static/js/co2_form.js

@@ -1,8 +1,6 @@
 // Input data for CO2 fitting algorithm 
 const CO2_data_form = [
   "CO2_data",
-  "dynamic_exposed_occupancy",
-  "dynamic_infected_occupancy",
   "exposed_coffee_break_option",
   "exposed_coffee_duration",
   "exposed_finish",
@@ -20,7 +18,7 @@ const CO2_data_form = [
   "infected_lunch_start",
   "infected_people",
   "infected_start",
-  "occupancy_format",
+  "occupancy",
   "room_capacity",
   "room_volume",
   "specific_breaks",

cern_caimira/src/cern_caimira/apps/calculator/static/js/form.js

@@ -1238,7 +1238,7 @@ $(document).ready(function () {
 
           <div class='form-group row d-none'>
             <div class="col-sm-6"><label class="col-form-label col-form-label-sm"> Exposure group:</label></div>
-            <div class="col-sm-6"><input type="text" id="sr_group_no_${index}" value="${value.exposure_group}" class="form-control form-control-sm short_range_option" name="short_range_exposure_group" placeholder="A" onchange="validate_sr_time(this)" form="not-submitted"><br></div>
+            <div class="col-sm-6"><input type="text" id="sr_group_no_${index}" value="${value.exposure_group}" class="form-control form-control-sm short_range_option" name="short_range_exposure_group" placeholder="group_1" onchange="validate_sr_time(this)" form="not-submitted"><br></div>
           </div>
 
           <div class="form-group" style="max-width: 8rem">
@@ -1258,11 +1258,11 @@ $(document).ready(function () {
   // When short_range_yes option is selected, we want to inject rows for each expiractory activity, start_time and duration.
   $("body").on("click", ".add_node_btn_frm_field", function(e) {
     let last_row = $(".form_field_outer").find(".form_field_outer_row");
-    if (last_row.length == 0) $("#dialog_sr").append(inject_sr_interaction(1, value = { activity: "", start_time: "", duration: "15", exposure_group: "A" }));
+    if (last_row.length == 0) $("#dialog_sr").append(inject_sr_interaction(1, value = { activity: "", start_time: "", duration: "15", exposure_group: "group_1" }));
     else {
         last_index = last_row.last().find(".short_range_option").prop("id").split("_").slice(-1)[0];
         index = parseInt(last_index) + 1;
-        $("#dialog_sr").append(inject_sr_interaction(index, value = { activity: "", start_time: "", duration: "15", exposure_group: "A"}));
+        $("#dialog_sr").append(inject_sr_interaction(index, value = { activity: "", start_time: "", duration: "15", exposure_group: "group_1"}));
     }
   });
 

cern_caimira/src/cern_caimira/apps/templates/base/calculator.form.html.j2

@@ -454,9 +454,7 @@
         <span class="tooltip_text">?</span>
     </div><br>
 
-    <input type="text" class="form-control d-none" name="occupancy_format" value="static" required> {# "static" vs. "dynamic" #}
-    <input type="text" class="form-control d-none" name="dynamic_exposed_occupancy" value="{}">
-    <input type="text" class="form-control d-none" name="dynamic_infected_occupancy" value="[]">
+    <input type="text" class="form-control d-none" name="occupancy" value="{}">
 
     <div class="form-group row">
       <div class="col-sm-4"><label class="col-form-label">Total number of occupants:</label></div>

cern_caimira/src/cern_caimira/apps/templates/base/calculator.report.html.j2

@@ -72,7 +72,7 @@
 				
 				{% block report_results scoped %}
 					<div class="card bg-light mb-3" id="results-div">
-						<div class="card-header"><strong>Results{% if form.occupancy_format == 'dynamic' %} - {{ group_id }}{% endif %}</strong>
+						<div class="card-header"><strong>Results{% if form.occupancy == {} %} - {{ group_id }}{% endif %}</strong>
 							<button class="icon_button p-0 float-right" data-toggle="collapse" href="#collapseResults-group_{{ group_id }}" role="button" aria-expanded="true" aria-controls="collapseResults">
 								<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" class="bi bi-chevron-expand" viewBox="0 0 16 16">
 									<path fill-rule="evenodd" d="M3.646 9.146a.5.5 0 0 1 .708 0L8 12.793l3.646-3.647a.5.5 0 0 1 .708.708l-4 4a.5.5 0 0 1-.708 0l-4-4a.5.5 0 0 1 0-.708zm0-2.292a.5.5 0 0 0 .708 0L8 3.207l3.646 3.647a.5.5 0 0 0 .708-.708l-4-4a.5.5 0 0 0-.708 0l-4 4a.5.5 0 0 0 0 .708z"/>
@@ -147,7 +147,7 @@
 														{% if form.exposure_option == "p_probabilistic_exposure" %}
 															<br>
 															<div class="align-self-center alert alert-dark mb-0" role="alert">
-																{% if form.occupancy_format == "static" %}
+																{% if form.occupancy == {} %}
 																	The above {{ "result assumes" if form.short_range_option == "short_range_no" else "results assume" }} that <b>{{ form.infected_people }}
 																	{{ "occupant is infected" if form.infected_people == 1 else "occupants are infected" }}
 																	</b> in the room.
@@ -204,7 +204,7 @@
 						</div>
 					</div>
 					<div class="card bg-light mb-3" id="results-div">
-						<div class="card-header"><strong>Result uncertainties{% if form.occupancy_format == 'dynamic' %} - {{ group_id }}{% endif %}</strong>
+						<div class="card-header"><strong>Result uncertainties{% if form.occupancy == {} %} - {{ group_id }}{% endif %}</strong>
 							<button class="icon_button p-0 float-right" data-toggle="collapse" href="#collapseUncertainties-group_{{ group_id }}" role="button" aria-expanded="true" aria-controls="collapseUncertainties">
 								<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" class="bi bi-chevron-expand" viewBox="0 0 16 16">
 									<path fill-rule="evenodd" d="M3.646 9.146a.5.5 0 0 1 .708 0L8 12.793l3.646-3.647a.5.5 0 0 1 .708.708l-4 4a.5.5 0 0 1-.708 0l-4-4a.5.5 0 0 1 0-.708zm0-2.292a.5.5 0 0 0 .708 0L8 3.207l3.646 3.647a.5.5 0 0 0 .708-.708l-4-4a.5.5 0 0 0-.708 0l-4 4a.5.5 0 0 0 0 .708z"/>
@@ -242,7 +242,7 @@
 							</div>
 						</div>
 					</div>
-					{% if form.short_range_option == "short_range_no" and form.occupancy_format == "static" %}
+					{% if form.short_range_option == "short_range_no" and form.occupancy == {} %}
 						<div class="card bg-light mb-3">
 							<div class="card-header"><strong>Alternative scenarios</strong>
 								<button class="icon_button p-0 float-right" data-toggle="collapse" href="#collapseAlternativeScenarios" role="button" aria-expanded="false" aria-controls="collapseAlternativeScenarios">
@@ -353,7 +353,7 @@
 												<input type="text" class="form-control form-control-sm col-sm-4 ml-2" id="CO2_Concentration__rename" placeholder="CO₂ Concentration" value="CO₂ Concentration">
 											</div>
 										</div>
-										{% if form.short_range_option == "short_range_no" and form.occupancy_format == "static" %}
+										{% if form.short_range_option == "short_range_no" and form.occupancy == {} %}
 											</li>
 											<li>
 												Alternative Scenarios

cern_caimira/src/cern_caimira/apps/templates/cern/calculator.report.html.j2

@@ -11,7 +11,7 @@
   {% set long_range_prob_inf = group_results.prob_inf %}
 {% endif %}
 
-{% if ((long_range_prob_inf > red_prob_lim) or (form.occupancy_format == "static" and group_results.expected_new_cases >= 1)) %} 
+{% if ((long_range_prob_inf > red_prob_lim) or (form.occupancy == {} and group_results.expected_new_cases >= 1)) %} 
   {% set long_range_scale_warning = 'red' %}
   {% set long_range_warning_color= 'bg-danger' %}
 {% elif (orange_prob_lim <= long_range_prob_inf <= red_prob_lim) %}
@@ -22,7 +22,7 @@
   {% set long_range_warning_color = 'bg-success' %} 
 {% endif %}
 
-{% if ((group_results.prob_inf > red_prob_lim) or (form.occupancy_format == "static" and group_results.expected_new_cases >= 1)) %} {% set scale_warning = 'red' %}
+{% if ((group_results.prob_inf > red_prob_lim) or (form.occupancy == {} and group_results.expected_new_cases >= 1)) %} {% set scale_warning = 'red' %}
 {% elif (orange_prob_lim <= group_results.prob_inf <= red_prob_lim) %} {% set scale_warning = 'orange' %} 
 {% else %} {% set scale_warning = 'green' %} 
 {% endif %}
@@ -139,12 +139,12 @@
                 <tr>
                     <th>Scenario</th>
                     <th>P(i)</th>
-                    {% if form.occupancy_format == "static" %}<th>Expected new cases</th>{% endif %}
+                    {% if form.occupancy == {} %}<th>Expected new cases</th>{% endif %}
                 </tr>
             </thead>
             <tbody>
             {% for scenario_name, scenario_stats in alternative_scenarios.stats.items() %}
-                {%if (( scenario_stats.probability_of_infection  > red_prob_lim) or (form.occupancy_format == "static" and scenario_stats.expected_new_cases >= 1)) %}
+                {%if (( scenario_stats.probability_of_infection  > red_prob_lim) or (form.occupancy == {} and scenario_stats.expected_new_cases >= 1)) %}
                   <tr class="alert-danger">
                 {% elif (orange_prob_lim <= scenario_stats.probability_of_infection <= red_prob_lim) %}
                   <tr class="alert-warning">
@@ -153,7 +153,7 @@
                 {% endif%}
                     <td> {{ scenario_name }}</td>
                     <td> {{ scenario_stats.probability_of_infection | non_zero_percentage }}</td>
-                    {% if form.occupancy_format == "static" %}<td style="text-align:right">{{ scenario_stats.expected_new_cases | float_format }}</td>{% endif %}
+                    {% if form.occupancy == {} %}<td style="text-align:right">{{ scenario_stats.expected_new_cases | float_format }}</td>{% endif %}
                 </tr>
             {% endfor %}
             </tbody>

cern_caimira/tests/conftest.py

@@ -90,6 +90,6 @@ def exposure_model_w_outside_temp_changes(data_registry, baseline_exposure_model
 def baseline_form_with_sr(baseline_form_data, data_registry):
     form_data_sr = baseline_form_data
     form_data_sr['short_range_option'] = 'short_range_yes'
-    form_data_sr['short_range_interactions'] = '{"static": [{"expiration": "Shouting", "start_time": "10:30", "duration": 30}]}'
+    form_data_sr['short_range_interactions'] = '{"group_1": [{"expiration": "Shouting", "start_time": "10:30", "duration": 30}]}'
     form_data_sr['short_range_occupants'] = 5
     return virus_validator.VirusFormData.from_dict(form_data_sr, data_registry)

cern_caimira/tests/test_report_generator.py

@@ -112,8 +112,8 @@ def test_expected_new_cases(baseline_form_with_sr: VirusFormData):
 
     # Short- and Long-range contributions
     report_data = rep_gen.calculate_report_data(baseline_form_with_sr, executor_factory)
-    sr_lr_expected_new_cases = report_data['groups']['static']['expected_new_cases']
-    sr_lr_prob_inf = report_data['groups']['static']['prob_inf']/100
+    sr_lr_expected_new_cases = report_data['groups']['group_1']['expected_new_cases']
+    sr_lr_prob_inf = report_data['groups']['group_1']['prob_inf']/100
     
     # Long-range contributions alone
     alternative_scenarios = rep_gen.manufacture_alternative_scenarios(baseline_form_with_sr)
@@ -123,3 +123,27 @@ 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_alternative_scenarios(baseline_form):
+    """
+    Tests if the alternative scenarios are only generated when
+    the occupancy input is empty ({}) - legacy usage.
+    """
+    generator: VirusReportGenerator = make_app().settings['report_generator']
+    report_data = generator.prepare_context("", baseline_form, partial(
+        concurrent.futures.ThreadPoolExecutor, 1,
+    ))
+    assert "alternative_scenarios" in report_data.keys()
+
+    baseline_form.occupancy = {
+        "group_A": {
+            "total_people": 10,
+            "infected": 5,
+            "presence": [{"start_time": "10:00", "finish_time": "11:00"}]
+        }
+    }
+    report_data = generator.prepare_context("", baseline_form, partial(
+        concurrent.futures.ThreadPoolExecutor, 1,
+    ))
+    assert "alternative_scenarios" not in report_data.keys()