For the purposes of this class we will use an anaconda installation of python as opposed to system python. This will allow us to use additional packages and keep a consistent python experience across machines/operating systems. To get started open a terminal on a UNC linux machine type
unc_anaconda
This will load you into a bash (differences with tcsh are negligible for general use) subshell with anaconda python as the default python. You should see your terminal prompt change to (anaconda_bash)user@machine:~$ or similar. Once in this subshell you can make your own anaconda environment by typing
conda create --name astro scikit-learn matplotlib astropy pymc spyder pandas
This will create an anaconda environment named astro in your home directory (~/.conda/envs/astro), with the packages that you need for this class. To activate this environment type
source activate astro
You are now your own anaconda environment, and your terminal prompt should start with (astro)(anaconda_bash).... To finish installing packages we will use for this class type the following
conda install -c OpenAstronomy healpy
pip install git+https://github.com/astroML/astroML
conda install nb_conda_kernels
The first line installs healpy through anaconda.org, and the second installs the most up to data version of astroML through the github repository.
Note that the above steps are a one time setup. If you ever want to use the anaconda environment you have set up all you have to do is type
unc_anaconda
source activate astro