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add compare_infection_probabilities_vs_viral_loads

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markus 2021-02-15 17:43:48 +01:00
parent d408fbc677
commit fe00ce1b42
1 changed files with 41 additions and 0 deletions
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41
cara/montecarlo.py
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@ -692,6 +692,47 @@ def display_original_vs_english(original_pi: np.ndarray, english_pi: np.ndarray)
plt.show()
def compare_infection_probabilities_vs_viral_loads(baseline1: MCExposureModel, baseline2: MCExposureModel,
samples_per_vl: int = 20000) -> None:
mean_ratios = []
p1_means, p2_means = [], []
viral_loads = np.linspace(3, 10, 200)
for vl in tqdm(viral_loads):
infected1 = baseline1.concentration_model.infected
infected2 = baseline2.concentration_model.infected
model1, model2 = [MCExposureModel(
concentration_model=MCConcentrationModel(
room=baseline.concentration_model.room,
ventilation=baseline.concentration_model.ventilation,
infected=MCInfectedPopulation(
number=infected.number,
presence=infected.presence,
masked=infected.masked,
expiratory_activity=infected.expiratory_activity,
breathing_category=infected.breathing_category,
virus=infected.virus,
samples=samples_per_vl,
qid=infected.qid,
english_variant=infected.english_variant,
viral_load=vl
)
),
exposed=baseline.exposed) for baseline, infected in ((baseline1, infected1), (baseline2, infected2))]
p1_mean, p2_mean = [np.mean(model.infection_probability()) for model in (model1, model2)]
p1_means.append(p1_mean)
p2_means.append(p2_mean)
mean_ratios.append(p1_mean / p2_mean)
plt.plot(viral_loads, mean_ratios)
plt.show()
plt.plot(viral_loads, p1_means)
plt.plot(viral_loads, p2_means)
plt.show()
fixed_vl_exposure_models = [MCExposureModel(
concentration_model=MCConcentrationModel(
room=models.Room(volume=45),