Costless correction of chain based nested sampling parameter estimaion in gravitational wave data and beyond (supplementary material)

These are the nested sampling inference products used to obtain the results for arXiv:2404.16428. The chains are given as pickled dataframes as there are over 1000 runs provided here. The script for reproducing the plots in the paper is also given. Folders: outdir_simulated_BBH - contains 200 runs on the same simulated signal. 'samples' contains the full sets of weighted samples from each run and 'full_dfs' contains the dataframes with the weighted samples AND the phantom points from the run. The samples in 'full_dfs' with chain_no=0 are the weighted samples, and all others are phantoms. outdir_test - contains the single run on the above simulated signal which was performed with num_repeats=25*ndims=100. outdir_coverage - contains 1000 runs on different simulated signals, with parameters drawn from the prior. The drawn values are saved as '{}_params.npy' for each run.