pygalaxy

pygalaxy is an analytic formalism based on Correa et al. (2018a,b) to calculate the best fitting expression of hot halo gas heating & cooling rates, gas mass histories, hot gas fractions and cooling radius.

Note that pygalaxy assumes halo virial mass (M200) is 200 times critical overdensity, and concentration is the ratio of halo virial mass (R200) over scale radius (obtained from best-fit NFW profile)

Requirements

Written in python, it uses routines in numpy and scipy to create a structured dataset. The package requires:

python3.6 or above
see requirements.txt

Installing

To get started using the package you need to set up a python virtual environment. The steps are as follows:

Clone pygalaxy

git clone https://github.com/correac/pygalaxy.git

cd pygalaxy

python3 -m venv pygalaxy_env

Now activate the virtual environment.

source pygalaxy_env/bin/activate

Update pip just in case

pip install pip --upgrade

pip install -r requirements.txt

How to use it

To run the script type

 cd pygalaxy

 python3 pygalaxy.py -z input_redshift \
                     -o path_to_output_directory

For example:

 python3 pygalaxy.py -z 0.0 -o /user/home/output/

Acknowledgement

We kindly ask users publishing scientific results using pygalaxy to cite Correa et al. (2018a) and Correa et al. (2018b).

Support and Contact

If you have trouble with pygalaxy or you have feature requests/suggestions please open an issue at https://github.com/correac/pygalaxy/issues