changed files directory and added remaining store items

caimira/apps/calculator/__init__.py

@@ -28,7 +28,6 @@
 from . import markdown_tools
 from . import model_generator
 from .report_generator import ReportGenerator, calculate_report_data
-from .data_service import DataService
 from .user import AuthenticatedUser, AnonymousUser
 
 # The calculator version is based on a combination of the model version and the
@@ -106,17 +105,6 @@ async def post(self) -> None:
             pprint(requested_model_config)
             start = datetime.datetime.now()
 
-        # Data Service API Integration
-        fetched_service_data = None
-        data_service: DataService = self.settings["data_service"]
-        if self.settings["data_service"]:
-            try:
-                fetched_service_data = await data_service.fetch()
-            except Exception as err:
-                error_message = f"Something went wrong with the data service: {str(err)}"
-                LOG.error(error_message, exc_info=True)
-                self.send_error(500, reason=error_message)
-
         try:
             form = model_generator.FormData.from_dict(requested_model_config)
         except Exception as err:
@@ -429,15 +417,6 @@ def make_app(
     )
     template_environment.globals['get_url']=get_root_url
     template_environment.globals['get_calculator_url']=get_root_calculator_url
-
-    data_service_credentials = {
-        'data_service_client_email': os.environ.get('DATA_SERVICE_CLIENT_EMAIL', None),
-        'data_service_client_password': os.environ.get('DATA_SERVICE_CLIENT_PASSWORD', None),
-    }
-    data_service = None
-    data_service_enabled = os.environ.get('DATA_SERVICE_ENABLED', 'False').lower() == 'true'
-    if data_service_enabled:
-        data_service = DataService(data_service_credentials)
 
     if debug:
         tornado.log.enable_pretty_logging()
@@ -456,9 +435,6 @@ def make_app(
         arve_client_secret=os.environ.get('ARVE_CLIENT_SECRET', None),
         arve_api_key=os.environ.get('ARVE_API_KEY', None),
 
-        # Data Service Integration
-        data_service=data_service,
-
         # Process parallelism controls. There is a balance between serving a single report
         # requests quickly or serving multiple requests concurrently.
         # The defaults are: handle one report at a time, and allow parallelism

caimira/apps/calculator/model_generator.py

@@ -315,10 +315,10 @@ def initialize_room(self) -> models.Room:
 
         if self.arve_sensors_option == False:
             if self.room_heating_option:
-                humidity = 0.3
+                humidity = constants.room['defaults']['humidity_with_heating']
             else:
-                humidity = 0.5
-            inside_temp = 293.
+                humidity = constants.room['defaults']['humidity_without_heating']
+            inside_temp = constants.room['defaults']['inside_temp']
         else:
             humidity = float(self.humidity)
             inside_temp = self.inside_temp
@@ -472,7 +472,8 @@ def ventilation(self) -> models._VentilationBase:
         # This is a minimal, always present source of ventilation, due
         # to the air infiltration from the outside.
         # See CERN-OPEN-2021-004, p. 12.
-        infiltration_ventilation = models.AirChange(active=always_on, air_exch=0.25)
+        residual_vent: float = constants.ventilation['infiltration_ventilation'] # type: ignore
+        infiltration_ventilation = models.AirChange(active=always_on, air_exch=residual_vent)
         if self.hepa_option:
             hepa = models.HEPAFilter(active=always_on, q_air_mech=self.hepa_amount)
             return models.MultipleVentilation((ventilation, hepa, infiltration_ventilation))

caimira/global_store/constants.py

@@ -219,6 +219,46 @@
     'sigma': {'B': 0.262364, 'L': 0.506818, 'O': 0.585005},
 }
 
+short_range_model = {
+    'exhalation_coefficient': 2,
+    'mouth_diameter': 0.02,
+    'penetration_coefficients': {'𝛽r1': 0.18, '𝛽r2': 0.2, '𝛽x1': 2.4},
+    'tstar': 2
+}
+
+concentration_model = {
+    'CO2_concentration_model': {
+        'CO2_atmosphere_concentration': 440.44,
+        'CO2_fraction_exhaled': 0.042
+    },
+    'min_background_concentration': 0.0
+}
+
+population_with_virus = {
+    'fraction_of_infectious_virus': 1,
+}
+
+particle = {
+    'evaporation_factor': 0.3,
+}
+
+ventilation = {
+    'natural': {
+        'discharge_factor': {
+            'sliding': 0.6,
+        },
+    },
+    'infiltration_ventilation': 0.25,
+}
+
+room = {
+    'defaults': {
+        'inside_temp': 293,
+        'humidity_with_heating': 0.3,
+        'humidity_without_heating': 0.5,
+    },
+}   
+
 def update_local_reference(local_data, api_data: typing.Union[dict, typing.Any]):
     '''
     Recursive function that iterates through the keys and values of local and remote dictionaries.
@@ -240,11 +280,12 @@ def update_local_reference(local_data, api_data: typing.Union[dict, typing.Any])
 async def populate_data():
     global data_fetched, BLOmodel, covid_overal_vl_data, infectious_dose_distribution, viable_to_RNA_ratio_distribution, virus_distributions, activity_distributions
     global mask_distributions, expiration_BLO_factors, long_range_expiration_distributions, short_range_expiration_distributions, short_range_distances
-    global infected_population_scenario_activity, monte_carlo_sample_size, conditional_prob_inf_given_viral_load, exposure_model
+    global infected_population_scenario_activity, monte_carlo_sample_size, conditional_prob_inf_given_viral_load, exposure_model, short_range_model
+    global concentration_model, population_with_virus, particle, ventilation, room
 
     if not data_fetched and os.environ.get('DATA_SERVICE_ENABLED', 'False').lower() == 'true':
         # Fetch data if it hasn't been fetched yet
-        from caimira.global_store.data_store import GlobalStore
+        from caimira.global_store.global_store import GlobalStore
 
         await GlobalStore.populate_from_api()
         data = GlobalStore.get_data()['data']
@@ -279,7 +320,19 @@ async def populate_data():
             conditional_prob_inf_given_viral_load, data['conditional_prob_inf_given_viral_load'])
         exposure_model = update_local_reference(
             exposure_model, data['exposure_model'])
-
+        short_range_model = update_local_reference(
+            short_range_model, data['short_range_model'])
+        concentration_model = update_local_reference(
+            concentration_model, data['concentration_model'])
+        population_with_virus = update_local_reference(
+            population_with_virus, data['population_with_virus'])
+        particle = update_local_reference(
+            particle, data['particle'])
+        ventilation = update_local_reference(
+            ventilation, data['ventilation'])
+        room = update_local_reference(
+            room, data['room'])
+
         data_fetched = True
 
 # Executed when this module is imported

caimira/global_store/data_store.py → caimira/global_store/global_store.py

@@ -1,6 +1,6 @@
 import os
 
-from caimira.apps.calculator.data_service import DataService
+from caimira.global_store.data_service import DataService
 
 
 class GlobalStore:

caimira/models.py

@@ -46,6 +46,8 @@
     # by providing a no-op cache decorator when type-checking.
     cached = lambda *cached_args, **cached_kwargs: lambda function: function  # noqa
 
+import caimira.global_store.constants as constants
+
 from .utils import method_cache
 
 from .dataclass_utils import nested_replace
@@ -347,7 +349,7 @@ def discharge_coefficient(self) -> _VectorisedFloat:
         Average measured value of discharge coefficient for sliding or
         side-hung windows.
         """
-        return 0.6
+        return float(constants.ventilation['natural']['discharge_factor']['sliding']) # type: ignore
 
 
 @dataclass(frozen=True)
@@ -860,7 +862,7 @@ def fraction_of_infectious_virus(self) -> _VectorisedFloat:
         The fraction of infectious virus.
 
         """
-        return 1.
+        return float(constants.population_with_virus['fraction_of_infectious_virus']) # type: ignore
 
     def aerosols(self):
         """
@@ -1032,7 +1034,7 @@ def min_background_concentration(self) -> _VectorisedFloat:
         (in the same unit as the concentration). Its the value towards which 
         the concentration will decay to.
         """
-        return 0.
+        return float(constants.concentration_model['min_background_concentration']) # type: ignore
 
     def normalization_factor(self) -> _VectorisedFloat:
         """
@@ -1220,7 +1222,7 @@ class ConcentrationModel(_ConcentrationModelBase):
     #: evaporation factor: the particles' diameter is multiplied by this
     # factor as soon as they are in the air (but AFTER going out of the,
     # mask, if any).
-    evaporation_factor: float = 0.3
+    evaporation_factor: float = constants.particle['evaporation_factor'] # type: ignore
 
     @property
     def population(self) -> InfectedPopulation:
@@ -1260,10 +1262,10 @@ class CO2ConcentrationModel(_ConcentrationModelBase):
     CO2_emitters: SimplePopulation
 
     #: CO2 concentration in the atmosphere (in ppm)
-    CO2_atmosphere_concentration: float = 440.44
+    CO2_atmosphere_concentration: float = constants.concentration_model['CO2_concentration_model']['CO2_atmosphere_concentration'] # type: ignore
 
     #: CO2 fraction in the exhaled air
-    CO2_fraction_exhaled: float = 0.042
+    CO2_fraction_exhaled: float = constants.concentration_model['CO2_concentration_model']['CO2_fraction_exhaled'] # type: ignore
 
     @property
     def population(self) -> SimplePopulation:
@@ -1284,7 +1286,6 @@ def normalization_factor(self) -> _VectorisedFloat:
         return (1e6*self.population.activity.exhalation_rate
                 *self.CO2_fraction_exhaled)
 
-
 @dataclass(frozen=True)
 class ShortRangeModel:
     '''
@@ -1309,14 +1310,14 @@ def dilution_factor(self) -> _VectorisedFloat:
         The dilution factor for the respective expiratory activity type.
         '''
         # Average mouth opening diameter (m)
-        mouth_diameter = 0.02
+        mouth_diameter: float = constants.short_range_model['dilution_factor']['mouth_diameter'] # type: ignore
 
         # Breathing rate, from m3/h to m3/s
         BR = np.array(self.activity.exhalation_rate/3600.)
 
         # Exhalation coefficient. Ratio between the duration of a breathing cycle and the duration of 
         # the exhalation.
-        φ = 2
+        φ: float = constants.short_range_model['dilution_factor']['exhalation_coefficient'] # type: ignore
 
         # Exhalation airflow, as per Jia et al. (2022)
         Q_exh: _VectorisedFloat = φ * BR
@@ -1328,12 +1329,12 @@ def dilution_factor(self) -> _VectorisedFloat:
         u0 = np.array(Q_exh/Am)
 
         # Duration of the expiration period(s), assuming a 4s breath-cycle
-        tstar = 2.0
+        tstar: float = constants.short_range_model['dilution_factor']['tstar'] # type: ignore
 
         # Streamwise and radial penetration coefficients
-        𝛽r1 = 0.18
-        𝛽r2 = 0.2
-        𝛽x1 = 2.4
+        𝛽r1: float = constants.short_range_model['dilution_factor']['penetration_coefficients']['𝛽r1'] # type: ignore
+        𝛽r2: float = constants.short_range_model['dilution_factor']['penetration_coefficients']['𝛽r2'] # type: ignore
+        𝛽x1: float = constants.short_range_model['dilution_factor']['penetration_coefficients']['𝛽x1'] # type: ignore
 
         # Parameters in the jet-like stage
         # Position of virtual origin
@@ -1489,7 +1490,7 @@ class ExposureModel:
     geographical_data: Cases
 
     #: The number of times the exposure event is repeated (default 1).
-    repeats: int = 1
+    repeats: int = constants.exposure_model['repeats']
 
     def __post_init__(self):
         """

caimira/tests/test_data_service.py

@@ -4,7 +4,7 @@
 from unittest.mock import patch, MagicMock
 from tornado.httpclient import HTTPError
 
-from caimira.apps.calculator.data_service import DataService
+from caimira.global_store.data_service import DataService
 
 @dataclass
 class MockResponse: