In the 'Compure sensitivity in shift OOR state' part of the src/2_simulation_design/oor_design_main/oor_design_mixed.ipynb file, the code use the auprc API as auprc.auprc(nh_df, return_curve=False, bootstrap_iterations=1000, bootstrap_seed=42).
If I deleted these two parameters, there would be no CI_upper and CI_lower columns in the auprc_compare dataframe. How should I change the code to reproduce the barplot?
In the 'Compure sensitivity in shift OOR state' part of the src/2_simulation_design/oor_design_main/oor_design_mixed.ipynb file, the code use the auprc API as
auprc.auprc(nh_df, return_curve=False, bootstrap_iterations=1000, bootstrap_seed=42).We met the error 'TypeError: auprc() got an unexpected keyword argument 'bootstrap_iterations'. I checked the oor-benchmark package at https://github.com/MarioniLab/oor_benchmark/blob/e40edad23bbfa7912d5d42ab076fb7b9a7e8e2d7/src/oor_benchmark/metrics/auprc.py, and found no parameters as bootstrap_iterations and bootstrap_seed.
If I deleted these two parameters, there would be no CI_upper and CI_lower columns in the auprc_compare dataframe. How should I change the code to reproduce the barplot?