build_tools | ||
c_tools | ||
container | ||
dummy_extension | ||
examples | ||
external | ||
python_tools | ||
zobov | ||
.gitignore | ||
CMakeLists.txt | ||
README.md | ||
setup.py |
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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
It is generally advised to create a python3 virtual environment. This can be achieved as follows
python3 -m venv --system-site-packages $PLACE_OF_VENV
source $PLACE_OF_VENV/bin/activate
where $PLACE_OF_VENV
is where you decide to put your environment on your
harddrive (e.g. $HOME/my_venv
).
Note: on OSX there are some difficulties to use the native clang compiler. Please use a brew installed compiler like GCC.
brew install gcc
export CC=/usr/local/bin/gcc-10
export CXX=/usr/local/bin/g++-10
The gcc-10 is of course dependent on the version that was installed by brew.
After this step you may start the build process
python3 setup.py build
It will take a lot of time. It may also download python packages that you miss on your system. On BigSur some of them fail to compile by default.
After installing the package with
To test that the package is indeed installed you can execute
python3 -m void_pipeline
which will state
Usage: ./generateCatalog.py parameter_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