Tutorials

For the installation of NMMA on smaller servers (e.g. our Uni Potsdam machines) a conda environment can be used for installation, while for larger cluster such as HAWK or Supermuc, a python virtual-environment is the better way to install NMMA. The main reason for the latter is that the mpi4py python package installed within a conda environment can be incompatible with default modules given by a specific cluster.

While it is not strictly necessary, it reduces possible conflicts if one installs python packages that do not need to be available system-wide into local, virtual environments. An easy option to setup such virtual environments is the venv module.

python3 -m venv /path/to/new/virtual/environment

This creates a local environment under /path/to/new/virtual/environment, which can be loaded via:

source /path/to/new/virtual/environment/bin/activate

Another way is to install a mini conda environment, in which separate virtual environments can be created with:

conda create --name <name> python=<version>

In order to activate the conda environment, you can use:

conda activate <name_of_env>

With activated virtual environment, basic packages need to be installed with:

pip install afterglowpy extinction dill multiprocess bilby lalsuite

In order to allow python programs to exploit multiple processors, the mpi4py packages needs to be installed using:

conda install mpi4py

In addition, install:

conda install -c conda-forge parallel_bilby

NMMA can be source cloned from the git repo with the following command:

git clone git@github.com:nuclear-multimessenger-astronomy/nmma.git

This will create an nmma folder, in which you can install the NMMA package using:

pip install .

Several tasks require the Bayesian inference tool Multinest, which can be installed using:

conda install pymultinest