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added vl_data on percentiles

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Luis Aleixo 2023-08-03 16:16:26 +02:00
parent 1abfe3cfe5
commit 77143c13c0
3 changed files with 16 additions and 0 deletions
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1
caimira/apps/calculator/defaults.py
View file

@ -19,6 +19,7 @@ DEFAULTS = {
'calculator_version': NO_DEFAULT, 'calculator_version': NO_DEFAULT,
'ceiling_height': 0., 'ceiling_height': 0.,
'conditional_probability_plot': False, 'conditional_probability_plot': False,
'conditional_probability_viral_loads': False,
'exposed_coffee_break_option': 'coffee_break_0', 'exposed_coffee_break_option': 'coffee_break_0',
'exposed_coffee_duration': 5, 'exposed_coffee_duration': 5,
'exposed_finish': '17:30', 'exposed_finish': '17:30',

2
caimira/apps/calculator/model_generator.py
View file

@ -35,6 +35,7 @@ class FormData:
precise_activity: dict precise_activity: dict
ceiling_height: float ceiling_height: float
conditional_probability_plot: bool conditional_probability_plot: bool
conditional_probability_viral_loads: bool
exposed_coffee_break_option: str exposed_coffee_break_option: str
exposed_coffee_duration: int exposed_coffee_duration: int
exposed_finish: minutes_since_midnight exposed_finish: minutes_since_midnight
@ -802,6 +803,7 @@ def baseline_raw_form_data() -> typing.Dict[str, typing.Union[str, float]]:
'air_supply': '', 'air_supply': '',
'ceiling_height': '', 'ceiling_height': '',
'conditional_probability_plot': '0', 'conditional_probability_plot': '0',
'conditional_probability_viral_loads': '0',
'exposed_coffee_break_option': 'coffee_break_4', 'exposed_coffee_break_option': 'coffee_break_4',
'exposed_coffee_duration': '10', 'exposed_coffee_duration': '10',
'exposed_finish': '18:00', 'exposed_finish': '18:00',

13
caimira/apps/calculator/report_generator.py
View file

@ -328,6 +328,18 @@ def non_zero_percentage(percentage: int) -> str:
return "99.9%" return "99.9%"
else: else:
return "{:0.1f}%".format(percentage) return "{:0.1f}%".format(percentage)
def manufacture_viral_load_scenarios_percentiles(model: mc.ExposureModel) -> typing.Dict[str, mc.ExposureModel]:
viral_load = model.concentration_model.infected.virus.viral_load_in_sputum
scenarios = {}
for percentil in (0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99):
vl = np.quantile(viral_load, percentil)
specific_vl_scenario = dataclass_utils.nested_replace(model,
{'concentration_model.infected.virus.viral_load_in_sputum': vl}
)
scenarios[round(np.log10(vl))] = np.mean(specific_vl_scenario.infection_probability())
return scenarios
def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.ExposureModel]: def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.ExposureModel]:
@ -477,6 +489,7 @@ class ReportGenerator:
context.update(report_data) context.update(report_data)
alternative_scenarios = manufacture_alternative_scenarios(form) alternative_scenarios = manufacture_alternative_scenarios(form)
context['alternative_viral_load'] = manufacture_viral_load_scenarios_percentiles(model) if form.conditional_probability_viral_loads else None
context['alternative_scenarios'] = comparison_report( context['alternative_scenarios'] = comparison_report(
form, report_data, alternative_scenarios, scenario_sample_times, executor_factory=executor_factory, form, report_data, alternative_scenarios, scenario_sample_times, executor_factory=executor_factory,
) )