This page documents the various file formats and how they are used.
outdir/label.log: On importing pyfstat, two logging streams are setup:
one stream which is written to the terminal, and a second which is saved to a
file outdir/label.log where the outdir and label are given when
initialising the search. While the terminal output can be suppressed with the
-q flag, the file is always written with a log-level set to INFO. This file
is never overwritten, so can be used to search for changes in the setup or old
outdir/label.par: A parameter file containing the maximum detection stat.
value, and estimates of the best-fit parameters. This can be read in with
read_par() and written with write_par().
outdir/label_saved_data.p: Upon succesful completion of an MCMC search, the
results will be saved to a pythonpickle file. This pickle file can
subsequently be read back and contains many useful outputs such as the
sampler object, the lnprobs and lnlikes from the run, and of course the
chains themselves. Rerunning a script with different parameters, the pickle
is overwritten once the simulation completes, however, a backup is saved with
an appended .old label.
outdir/label_walkers.png: The position of all temperature 0 walkers
during the burn-in + production stage. In addition, the final panel plots a
histogram of the detection statistic from all temperature 0 walkers; if
a burn-in period is defined this is computed separately and colored red.
outdir/label_init_i_walkers.png: The same as the walkers, but for the
ith initialisation stage.
outdir/label_corner.png: A corner plot of the production samples using
the corner package. This file is
generated by plot_corner().
outdir/label_prior_posterior.png: A plot showing the prior and a KDE of
the posterior, generated by plot_prior_posterior()
outdir/label_grid_FS.txt: Upon succesful completion of a grid search, the
grid points are saved in plain text format. The order is set by
get_input_data_array with an additional column being the output detection
outdir/label_2D.png: A 2D contour plot of the detection statitistic over
the range of parameters; options exist to flatten higher dimension
searches. Generated using plot_2D().