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This is VIDE, the Void IDentification and Examination toolkit.

For more information, see http://www.cosmicvoids.net

Please cite arXiv:1406.1191 and arXiv:0712.0349 if you use this software, using the following suggested sentence:

"This work uses voids identified with VIDE\footnote{\url{http:www.cosmicvoids.net}} (Sutter et al. 2014), which implements an enhanced version of ZOBOV (Neyrinck 2008) to construct voids with a watershed algorithm."

License/Copyright information

Copyright (C) 2010-2020 Guilhem Lavaux, 2011-2014 P.M. Sutter. This software is put under the GNU Public License. Please see LICENSE for further information.

Mainline VIDE contributions from Ben Wandelt, Nico Hamaus, Alice Pisani, Paul Zivick, and Qingqing Mao. This toolkit includes ZOBOV, originally developed by Mark Neyrinck. See zobov/zobov_readme.txt for copyright/license information. SDF library provided by Michael S. Warren and John Salmon. HOD fitting code provided by Francisco Navarro. HOD halo population code provided by Jeremy Tinker. RAMSES module provided by Benjamin B. Thompson.

Requirements

The package swig needs to be installed and available in the PATH (http://www.swig.org/). It is required by scipy and we have not decided to bundle it with VIDE at the moment.

Quick Start Guide

After installing the package with python3 setup.py install --user, you can execute

python3 -m void_pipeline  your_config_file.py

The VIDE tools are all packaged in the vide package.

Running with simulation

Using simulation requires a preliminary step, consisting in using the script vide_prepare_simulation which is installed during the installation procedure. The script generates mock catalog and a default pipeline to handle simulations. An example of the complete procedure is given here-below:

mkdir $HOME/my_vide_test
cp python_tools/void_pipeline/datasets/example_simulation.py $HOME/my_vide_test
mkdir $HOME/my_vide_test/examples
cp examples/example_simulation_z0.0.dat $HOME/my_vide_test/examples
cd $HOME/my_vide_test
vide_prepare_simulation   --all --parm example_simulation.py
python3 -m void_pipeline example_simulation/sim_ss1.0.py

The example copies the required data in a separate directory. Then, we execute the vide_prepare_simulation script to generate the auxiliary pipeline. The void_pipeline is finally executed on this generated script.

Notes for CONDA

If you use a conda installation, you have to be sure to use all the building tools that are consistent. On linux that means for example installing the conda packages gcc_linux-64 and gxx_linux-64. In addition to that it is recommended to define the environment variable LIBRARY_PATH=the_path_of_your_conda_environment_with_/lib. For example if your environment is in '/home/user/conda' you should define

export LIBRARY_PATH=/home/user/conda/lib

You can then initiate the construction with

python3 setup.py build

Version Summary

v1.0 - Initial Release v2.0 - Ported to python3, revisited build system