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added test for dynamic occupancy from input form

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This commit is contained in:
lrdossan 2024-07-19 16:12:03 +02:00
parent 2f8b053bb1
commit f4c9c5fa96
5 changed files with 70 additions and 6 deletions
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4
caimira/src/caimira/calculator/report/virus_report_data.py
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@ -176,7 +176,7 @@ def calculate_report_data(form: VirusFormData, executor_factory: typing.Callable
# Probabilistic exposure
if form.exposure_option == "p_probabilistic_exposure" and form.occupancy_format == "static":
prob_probabilistic_exposure = np.array(model.total_probability_rule()).mean()
else: prob_probabilistic_exposure = 0
else: prob_probabilistic_exposure = -1
# Expected new cases
if (form.occupancy_format == "static"):
expected_new_cases = np.array(model.expected_new_cases()).mean()
@ -425,7 +425,7 @@ def scenario_statistics(
# It means we have data to calculate the total_probability_rule
prob_probabilistic_exposure = model.total_probability_rule()
else:
prob_probabilistic_exposure = 0.
prob_probabilistic_exposure = -1
if (compute_expected_new_cases):
expected_new_cases = np.mean(model.expected_new_cases())

6
caimira/src/caimira/calculator/validators/co2/co2_validator.py
View file

@ -60,8 +60,10 @@ class CO2FormData(FormData):
self.data_registry = DataRegistry()
def validate(self):
# Validate population parameters
self.validate_population_parameters()
# Validate population parameters when static occupancy is defined.
# Dynamic population is validated in the generate_dynamic_occupancy method.
if self.occupancy_format == 'static':
self.validate_population_parameters()
# Validate room capacity
if self.room_capacity:

2
caimira/src/caimira/calculator/validators/defaults.py
View file

@ -37,7 +37,7 @@ DEFAULTS = {
'infected_lunch_option': True,
'infected_lunch_start': '12:30',
'infected_people': 1,
'dynamic_infected_occupancy': '[]',
'dynamic_infected_occupancy': NO_DEFAULT,
'infected_start': '08:30',
'inside_temp': NO_DEFAULT,
'location_latitude': NO_DEFAULT,

5
caimira/src/caimira/calculator/validators/virus/virus_validator.py
View file

@ -73,7 +73,10 @@ class VirusFormData(FormData):
_DEFAULTS: typing.ClassVar[typing.Dict[str, typing.Any]] = DEFAULTS
def validate(self):
self.validate_population_parameters()
# Validate population parameters when static occupancy is defined.
# Dynamic population is validated in the generate_dynamic_occupancy method.
if self.occupancy_format == 'static':
self.validate_population_parameters()
validation_tuples = [('activity_type', self.data_registry.population_scenario_activity.keys()),
('mechanical_ventilation_type',

59
cern_caimira/tests/test_report_generator.py
View file

@ -2,6 +2,7 @@ import concurrent.futures
from functools import partial
import os
import time
import json
import numpy as np
import pytest
@ -123,4 +124,62 @@ def test_expected_new_cases(baseline_form_with_sr: VirusFormData):
lr_expected_new_cases = alternative_statistics['stats']['Base scenario without short-range interactions']['expected_new_cases']
np.testing.assert_almost_equal(sr_lr_expected_new_cases, lr_expected_new_cases + sr_lr_prob_inf * baseline_form_with_sr.short_range_occupants, 2)
def test_static_vs_dynamic_occupancy_from_form(baseline_form_data, data_registry):
"""
Assert that the results between a static and dynamic occupancy model (from form inputs) are similar.
"""
executor_factory = partial(
concurrent.futures.ThreadPoolExecutor, 1,
)
# By default the baseline form accepts static occupancy
static_occupancy_baseline_form: VirusFormData = VirusFormData.from_dict(baseline_form_data, data_registry)
static_occupancy_model = static_occupancy_baseline_form.build_model()
static_occupancy_report_data = rep_gen.calculate_report_data(static_occupancy_baseline_form, executor_factory)
# Update the initial form data to include dynamic occupancy (please note the 4 coffee and 1 lunch breaks)
baseline_form_data['occupancy_format'] = 'dynamic'
baseline_form_data['dynamic_infected_occupancy'] = json.dumps([
{'total_people': 1, 'start_time': '09:00', 'finish_time': '10:03'},
{'total_people': 0, 'start_time': '10:03', 'finish_time': '10:13'},
{'total_people': 1, 'start_time': '10:13', 'finish_time': '11:16'},
{'total_people': 0, 'start_time': '11:16', 'finish_time': '11:26'},
{'total_people': 1, 'start_time': '11:26', 'finish_time': '12:30'},
{'total_people': 0, 'start_time': '12:30', 'finish_time': '13:30'},
{'total_people': 1, 'start_time': '13:30', 'finish_time': '14:53'},
{'total_people': 0, 'start_time': '14:53', 'finish_time': '15:03'},
{'total_people': 1, 'start_time': '15:03', 'finish_time': '16:26'},
{'total_people': 0, 'start_time': '16:26', 'finish_time': '16:36'},
{'total_people': 1, 'start_time': '16:36', 'finish_time': '18:00'},
])
baseline_form_data['dynamic_exposed_occupancy'] = json.dumps([
{'total_people': 9, 'start_time': '09:00', 'finish_time': '10:03'},
{'total_people': 0, 'start_time': '10:03', 'finish_time': '10:13'},
{'total_people': 9, 'start_time': '10:13', 'finish_time': '11:16'},
{'total_people': 0, 'start_time': '11:16', 'finish_time': '11:26'},
{'total_people': 9, 'start_time': '11:26', 'finish_time': '12:30'},
{'total_people': 0, 'start_time': '12:30', 'finish_time': '13:30'},
{'total_people': 9, 'start_time': '13:30', 'finish_time': '14:53'},
{'total_people': 0, 'start_time': '14:53', 'finish_time': '15:03'},
{'total_people': 9, 'start_time': '15:03', 'finish_time': '16:26'},
{'total_people': 0, 'start_time': '16:26', 'finish_time': '16:36'},
{'total_people': 9, 'start_time': '16:36', 'finish_time': '18:00'},
])
baseline_form_data['total_people'] = 0
baseline_form_data['infected_people'] = 0
dynamic_occupancy_baseline_form: VirusFormData = VirusFormData.from_dict(baseline_form_data, data_registry)
dynamic_occupancy_model = dynamic_occupancy_baseline_form.build_model()
dynamic_occupancy_report_data = rep_gen.calculate_report_data(dynamic_occupancy_baseline_form, executor_factory)
assert (list(sorted(static_occupancy_model.concentration_model.infected.presence.transition_times())) ==
list(dynamic_occupancy_model.concentration_model.infected.number.transition_times))
assert (list(sorted(static_occupancy_model.exposed.presence.transition_times())) ==
list(dynamic_occupancy_model.exposed.number.transition_times))
np.testing.assert_almost_equal(static_occupancy_report_data['prob_inf'], dynamic_occupancy_report_data['prob_inf'], 1)
assert dynamic_occupancy_report_data['expected_new_cases'] == -1
assert dynamic_occupancy_report_data['prob_probabilistic_exposure'] == -1