After compiling, go to the pipeline directory.

Create a dataset parameter file. Look at datasets/multidark.py for 
an example. Describe the simulation, where to put outputs, how many 
redshift slices, subvolumes, etc. etc.

prepareCatalogs will produce a pipeline script for each
subsampling you choose. If you have multiple redshift particle files,
and choose multiple slices and/or subdivisions, they will be packaged
in the same pipeline script.

Run "./generateCatalog.py [name of pipeline script]" for each script
written by prepareGadgetCatalog. This will run generateMock, zobov,
and pruneVoids. At the end of it, you should have a void catalog for
each redshift, slice, and subdivision.

Check the logfiles for any error messages.

See the README of the public void catalog for the format of the
outputs.

Please do not change the outputs of pruneVoids etc. without
discussion, since further analysis relies on the current formats.

If you're wondering why these scripts are rather complex, it's because
it can also support A-P analysis, which is much more complicated :)

Good luck!

Important directories:

pipeline: scripts to set up and generate void catalogs
crossCompare: analysis and plotting tools designed to work with disparate catalogs