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Centering the interval for vl uncertainty computation in report generator -> improving test accuracy

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This commit is contained in:
Nicolas Mounet 2023-09-01 15:21:04 +02:00
parent 27da077493
commit f8530d4724
2 changed files with 6 additions and 6 deletions
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2
caimira/apps/calculator/report_generator.py
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@ -199,7 +199,7 @@ def conditional_prob_inf_given_vl_dist(infection_probability: models._Vectorised
upper_percentiles = []
for vl_log in viral_loads:
specific_prob = infection_probability[np.where((vl_log-specific_vl)*(vl_log+step-specific_vl)<0)[0]] #type: ignore
specific_prob = infection_probability[np.where((vl_log-step/2-specific_vl)*(vl_log+step/2-specific_vl)<0)[0]] #type: ignore
pi_means.append(specific_prob.mean())
lower_percentiles.append(np.quantile(specific_prob, 0.05))
upper_percentiles.append(np.quantile(specific_prob, 0.95))

10
caimira/tests/test_conditional_probability.py
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@ -43,7 +43,7 @@ def baseline_exposure_model():
)
@retry(tries=10)
@retry(tries=2)
def test_conditional_prob_inf_given_vl_dist(baseline_exposure_model):
viral_loads = np.array([3., 5., 7., 9.,])
@ -67,11 +67,11 @@ def test_conditional_prob_inf_given_vl_dist(baseline_exposure_model):
infection_probability = mc_model.infection_probability() / 100
specific_vl = np.log10(mc_model.concentration_model.infected.virus.viral_load_in_sputum)
step = (max(viral_loads) - min(viral_loads))/100
step = 8/100
actual_pi_means, actual_lower_percentiles, actual_upper_percentiles = (
report_generator.conditional_prob_inf_given_vl_dist(infection_probability, viral_loads, specific_vl, step)
)
assert np.allclose(actual_pi_means, expected_pi_means, rtol=0.1)
assert np.allclose(actual_lower_percentiles, expected_lower_percentiles, rtol=0.1)
assert np.allclose(actual_upper_percentiles, expected_upper_percentiles, rtol=0.1)
assert np.allclose(actual_pi_means, expected_pi_means, atol=0.001)
assert np.allclose(actual_lower_percentiles, expected_lower_percentiles, atol=0.001)
assert np.allclose(actual_upper_percentiles, expected_upper_percentiles, atol=0.001)