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fixed variable name error

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This commit is contained in:
lrdossan 2024-06-13 09:55:54 +02:00
parent a11a559710
commit e3472edd7e
1 changed files with 9 additions and 9 deletions
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18
caimira/apps/calculator/report_generator.py
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@ -176,10 +176,10 @@ def calculate_report_data(form: VirusFormData, model: models.ExposureModel, exec
if (form.conditional_probability_viral_loads and
model.data_registry.virological_data['virus_distributions'][form.virus_type]['viral_load_in_sputum'] == ViralLoads.COVID_OVERALL.value): # type: ignore
# Generate all the required data for the conditional probability plot
conditional_prob_data = manufacture_conditional_probability_data(model, prob)
conditional_probability_data = manufacture_conditional_probability_data(model, prob)
# Generate the matplotlib image based on the received data
uncertainties_plot_src = img2base64(_figure2bytes(uncertainties_plot(prob, conditional_prob_data)))
uncertainties_plot_src = img2base64(_figure2bytes(uncertainties_plot(prob, conditional_probability_data)))
return {
"model_repr": repr(model),
"times": list(times),
@ -267,13 +267,13 @@ def manufacture_conditional_probability_data(
def uncertainties_plot(infection_probability: models._VectorisedFloat,
conditional_prob_data: dict):
conditional_probability_data: dict):
viral_loads: models._VectorisedFloat = conditional_prob_data['viral_loads']
pi_means: models._VectorisedFloat = conditional_prob_data['pi_means']
lower_percentiles: models._VectorisedFloat = conditional_prob_data['lower_percentiles']
upper_percentiles: models._VectorisedFloat = conditional_prob_data['upper_percentiles']
log10_vl_in_sputum: models._VectorisedFloat = conditional_prob_data['log10_vl_in_sputum']
viral_loads: models._VectorisedFloat = conditional_probability_data['viral_loads']
pi_means: models._VectorisedFloat = conditional_probability_data['pi_means']
lower_percentiles: models._VectorisedFloat = conditional_probability_data['lower_percentiles']
upper_percentiles: models._VectorisedFloat = conditional_probability_data['upper_percentiles']
log10_vl_in_sputum: models._VectorisedFloat = conditional_probability_data['log10_vl_in_sputum']
fig, axes = plt.subplots(2, 3,
gridspec_kw={'width_ratios': [5, 0.5] + [1],