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The following commands should be working for you at the unix shell, if not | ||
see if you can install them with your favorite package tool. | ||
This file is also part of our pitp2016 git repo (see below on how to update | ||
this) as "packages.txt" | ||
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git --version | ||
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we also use this to distribute notes, scripts, software for PITP 2016. | ||
To get a copy: | ||
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git clone http://github.com/teuben/pitp2016 | ||
cd pitp2016 | ||
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and to get a fresh version with the latest updates: | ||
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cd pitp2016 | ||
git pull | ||
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gcc | ||
g++ | ||
gfortran | ||
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The C/C++/Fortran(90) compiler suite. Others may be available as well that work | ||
also, e.g. "clang", the Intel compiler and the PGI compiler. | ||
The C compiler needs to suport OpenMP (which gcc does) | ||
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python | ||
ipython | ||
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Although the python command may be present for you, what we really want here is | ||
an integrated scientific python environment, e.g. via anaconda. | ||
Within python, the following modules are recommended: | ||
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numpy | ||
scipy | ||
matplotlib | ||
yt | ||
astropy | ||
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ffmpeg -version | ||
This tool creates movies from still images that simulations often create on the fly. | ||
Great for presentations. We will use this for a few of the homeworks. | ||
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In ubuntu linux: | ||
sudo apt install ffmpeg imagemagick vlc | ||
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gsl | ||
This is the Gnu Scientific Library. Use your package manager to install it, e.g. | ||
In Ubuntu linux: | ||
sudo apt install libgsl-dev | ||
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gnuplot | ||
A simple, basic but effective way to plot data. | ||
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ygraph | ||
Another simple and basic graph plotter. | ||
See for example http://cactuscode.org/documentation/visualization/yGraph/ | ||
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yt | ||
Versatile visualization environment in python. Probably easiest to install within | ||
your python environment via the commands | ||
conda install yt | ||
or | ||
pip install yt | ||
depending which type of python environment you have | ||
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visit | ||
A more graphical based visualization environment | ||
See | ||
https://wci.llnl.gov/simulation/computer-codes/visit/ |