print("Index:", index) X_train, X_test, y_train, y_test = data_split_cache.load() results, rf = cross_val_cache.load() job_samples = 50 tree_path_dependent_shap_interact_cache = SimpleCache( f"tree_path_dependent_shap_interact_{index}_{job_samples}", cache_dir=os.path.join(CACHE_DIR, "shap_interaction"), ) @tree_path_dependent_shap_interact_cache def get_interact_shap_values(model, X): return get_shap_values(model, X, interaction=True) get_interact_shap_values( rf, X_train[index * job_samples : (index + 1) * job_samples] ) if __name__ == "__main__": handle_array_job_args( Path(__file__).resolve(), func, ncpus=1, mem="5gb", walltime="10:00:00", max_index=1, )
fig, axes = pdp.pdp_interact_plot( pdp_interact_out, features, x_quantile=True, figsize=(7, 8) ) axes["pdp_inter_ax"].xaxis.set_tick_params(rotation=45) figure_saver.save_figure(fig, "__".join(features), sub_directory="pdp_2d") X_train, X_test, y_train, y_test = data_split_cache.load() results, rf = cross_val_cache.load() columns_list = list(combinations(X_train.columns, 2)) index = int(os.environ["PBS_ARRAY_INDEX"]) print("Index:", index) print("Columns:", columns_list[index]) ncpus = get_ncpus() print("NCPUS:", ncpus) # Use the array index to select the desired columns. save_pdp_plot_2d(rf, X_train, columns_list[index], ncpus) if __name__ == "__main__": handle_array_job_args( Path(__file__).resolve(), func, ncpus=8, mem="90gb", walltime="50:00:00", max_index=1224, )
figsize=(7, 8)) axes["pdp_inter_ax"].xaxis.set_tick_params(rotation=45) figure_saver.save_figure(fig, "__".join(features), sub_directory="pdp_2d") X_train, X_test, y_train, y_test = data_split_cache.load() results, rf = cross_val_cache.load() columns_list = list(combinations(X_train.columns, 2)) index = int(os.environ["PBS_ARRAY_INDEX"]) print("Index:", index) print("Columns:", columns_list[index]) ncpus = get_ncpus() print("NCPUS:", ncpus) # Use the array index to select the desired columns. save_pdp_plot_2d(rf, X_train, columns_list[index], ncpus) if __name__ == "__main__": handle_array_job_args( Path(__file__).resolve(), func, ncpus=7, mem="60gb", walltime="24:00:00", max_index=104, )