Install and run

  • Installing from pip:

    $ pip install pyRingGW
    
  • Installing from conda:

    $ conda install -c conda-forge pyringgw
    
  • Installing the source code:

    In your ~/.bashrc add:

    $ export PYRING_PREFIX=/home/installation_directory/pyring
    

    where installation_directory is the directory where you will be placing the pyRing source code. This path is needed for advanced functionalities such as QNM interpolation or injection of NR data.

    $ git clone https://git.ligo.org/lscsoft/pyring.git
    $ cd pyring
    $ git lfs install
    $ git lfs pull
    $ pip install -r requirements.txt
    $ pip install .
    

    Add --user to the last command in case you don’t have administrator’s permissions (for example if you are installing on a cluster). Alternatives to the last command are python -m pip install . or python setup.py install

  • Running the code:

    The one-liner you are searching for is:

    $ pyRing --config-file config.ini
    
  • Examples:

    The config_files directory contains a variety of example files to analyse GW detections and injections (both ringdown templates and IMR injections). There is one example file for each waveform model supported, included all modifications to the Kerr hypothesis. The configuration files directory can either be found on the source code repository or under the path installation_path/pyRing/config_files. To discover your installation_path, type on the terminal:

    $ import pyRing
    $ pyRing.__file__
    

    that will output the path under which the package was built.

    A very fast example, to get you up to speed, can be launched by:

    $ pyRing --config-file installation_path/pyRing/config_files/Quickstart_configs/quick_gw150914_DS.ini
    

    This allows the beginner to obtain a quick and rough measurement of GW150914 ringdown spectrum in under 3 minutes on a laptop (using aggressive priors and very light sampler settings). Other similar examples are available inside the Quickstart_configs directory. These examples are mainly meant to give beginners a sense of the output of the code for various models.

    A fast analysis, with settings more reliable than the above, can be obtained by launching:

    $ pyRing --config-file repopath/pyRing/config_files/config_gw150914_local_data.ini
    

    This run still uses a simplified noise estimation and simplified sampler settings, but allows to obtain a decent measurement in ~20 minutes.

    Instead, a proper configuration file for the same run using production settings (hence obtaining publication-level results) can be launched by:

    $ pyRing --config-file repopath/pyRing/config_files/config_gw150914_production.ini
    

    Never forget that the sampler settings may need adjustment based on the problem you want to tackle. See the Usage section for further discussion.

  • Explore:

    The software supports a variety of analysis and injection options, all of which can be explored by running:

    $ pyRing --help
    
  • Requirements:

    The software is guaranteed to be compatible with 3.6=<python=<3.9.