a56ad5f77a
- 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
95 lines
3.3 KiB
Python
95 lines
3.3 KiB
Python
import pytest
|
|
|
|
from caimira.calculator.models import models
|
|
import caimira.calculator.models.data
|
|
import caimira.calculator.models.dataclass_utils
|
|
from caimira.calculator.validators.virus import virus_validator
|
|
from caimira.calculator.store.data_registry import DataRegistry
|
|
|
|
|
|
@pytest.fixture
|
|
def baseline_form_data():
|
|
return virus_validator.baseline_raw_form_data()
|
|
|
|
|
|
@pytest.fixture
|
|
def baseline_form(baseline_form_data, data_registry):
|
|
return virus_validator.VirusFormData.from_dict(baseline_form_data, data_registry)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_registry():
|
|
return DataRegistry()
|
|
|
|
|
|
@pytest.fixture
|
|
def baseline_concentration_model(data_registry):
|
|
model = models.ConcentrationModel(
|
|
data_registry=data_registry,
|
|
room=models.Room(
|
|
volume=75, inside_temp=models.PiecewiseConstant((0., 24.), (293,))),
|
|
ventilation=models.AirChange(
|
|
active=models.SpecificInterval(((0., 24.), )),
|
|
air_exch=30.,
|
|
),
|
|
infected=models.EmittingPopulation(
|
|
data_registry=data_registry,
|
|
number=1,
|
|
virus=models.Virus.types['SARS_CoV_2'],
|
|
presence=models.SpecificInterval(((0., 4.), (5., 8.))),
|
|
mask=models.Mask.types['No mask'],
|
|
activity=models.Activity.types['Light activity'],
|
|
known_individual_emission_rate=970 * 50,
|
|
host_immunity=0.,
|
|
# Superspreading event, where ejection factor is fixed based
|
|
# on Miller et al. (2020) - 50 represents the infectious dose.
|
|
),
|
|
evaporation_factor=0.3,
|
|
)
|
|
return model
|
|
|
|
|
|
@pytest.fixture
|
|
def baseline_sr_model():
|
|
return ()
|
|
|
|
|
|
@pytest.fixture
|
|
def baseline_exposure_model(data_registry, baseline_concentration_model, baseline_sr_model):
|
|
return models.ExposureModel(
|
|
data_registry=data_registry,
|
|
concentration_model=baseline_concentration_model,
|
|
short_range=baseline_sr_model,
|
|
exposed=models.Population(
|
|
number=1000,
|
|
presence=baseline_concentration_model.infected.presence,
|
|
activity=baseline_concentration_model.infected.activity,
|
|
mask=baseline_concentration_model.infected.mask,
|
|
host_immunity=0.,
|
|
),
|
|
geographical_data=models.Cases(),
|
|
)
|
|
|
|
|
|
@pytest.fixture
|
|
def exposure_model_w_outside_temp_changes(data_registry, baseline_exposure_model: models.ExposureModel):
|
|
exp_model = caimira.calculator.models.dataclass_utils.nested_replace(
|
|
baseline_exposure_model, {
|
|
'concentration_model.ventilation': models.SlidingWindow(
|
|
data_registry=data_registry,
|
|
active=models.PeriodicInterval(2.2 * 60, 1.8 * 60),
|
|
outside_temp=caimira.calculator.models.data.GenevaTemperatures['Jan'],
|
|
window_height=1.6,
|
|
opening_length=0.6,
|
|
)
|
|
})
|
|
return exp_model
|
|
|
|
|
|
@pytest.fixture
|
|
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'] = '{"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)
|