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crossCompare | ||
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pipeline | ||
python_tools | ||
zobov | ||
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README | ||
run_env.sh.in | ||
run_python.sh.in |
\ / / |-\ ----- \ / | | \ | \ / / | | |-- \ / | | / | \/ / |-/ ----- *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-* This is VIDE. The Void IDEntifier pipeline. License/Copyright information ----------------------------- Copyright (C) 2010-2013 Guilhem Lavaux, 2011-2013 Paul M. Sutter. This software is put under the GNU Public License. Please see LICENSE for further information. Parts of the pipeline includes ZOBOV. See zobov/zobov_readme.txt for copyright/license information Building -------- After compiling, go to the pipeline directory. Using the pipeline ------------------ 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