PyFstat 1.6.0

a python package for gravitational wave analysis with the F-statistic

PyFstat

This is a python package providing an interface to perform F-statistic based continuous gravitational wave (CW) searches.

Getting started:

• This README provides information on installation, contributing to and citing PyFstat.
• Additional usage documentation will be added to the project wiki (work in progress).
• We also have a number of examples, demonstrating different use cases.

A changelog is also available (only maintained from v1.2 onwards).

Installation

PyFstat releases can be installed in a variety of ways, including Docker/Singularity images, pip install from PyPi, and from source releases on Zenodo. Latest development versions can also be installed with pip or from a local git clone.

If you don't have a recent python installation (3.6+) on your system or prefer conda environments over system-wide installation / venvs, please start with the conda installation section.

In either case, be sure to also check out the notes on dependencies, ephemerides files and citing this work.

Docker container

Ready-to-use PyFstat containers are available at the Packages page. A git-hub account together with a personal access token is required. Go to the wiki page to learn how to pull them from the git-hub registry using Docker or Singularity.

pip install from PyPi

PyPi releases are available from https://pypi.org/project/PyFstat/.

Note that the PyFstat installation will fail at the LALSuite dependency stage if your pip is too old (e.g. 18.1); to be on the safe side, before starting do

pip install --upgrade pip

Then, a simple

pip install pyfstat

should give you the latest release version with all dependencies.

If you are not installing into a venv or conda environment, on many systems you may need to use the --user flag.

conda installation

PyFstat requires python3.6+. While many systems come with a system-wide python installation, it may not be sufficiently recent for this package; anyway, it can often be easier to manage a user-specific python installation (this way one does not require root access to install or remove modules). One method to do this is to use the conda system, either through the stripped down Miniconda installation, or the full-featured Anaconda (these are essentially the same, but the Anaconda version installs a variety of useful packages such as numpy and scipy by default). The fastest/easiest method is to follow your OS instructions here which will install Miniconda.

After you have installed a version of conda and set up an environment, pip can also be used to install modules into this environment. (There is no direct conda release of PyFstat at the moment.) This can be installed with

conda install pip

and then you can continue with the pip instructions, either a release version from PyPi as described above or the latest development version directly from github as described below.

A simple way to get started with an otherwise clean environment is to use a minimal .yml recipe file as explained here.

Alternatively, you may consider starting from an igwn environment, which contains most packages relevant to gravitational waves, instead of doing it from scratch, and just adding PyFstat to it through pip as described above. But be advised that the downloads for the igwn environments are huge.

pip install from github

Development versions of PyFstat can also be easily installed by pointing pip directly to this git repository, which will give you the latest version of the master branch:

pip install git+https://github.com/PyFstat/PyFstat

or, if you have an ssh key installed in github:

pip install git+ssh://[e-mail]/PyFstat/PyFstat

Dependencies

PyFstat uses the following external python modules, which should all be pulled in automatically if you use pip:

• numpy
• matplotlib >= 2.1
• scipy
• ptemcee
• corner
• dill
• tqdm
• bashplotlib
• peakutils
• pathos
• lalsuite >= 6.72
• versioneer

In case the automatic install doesn't properly pull in all dependencies, to install all of these modules manually, you can also run

pip install -r /PATH/TO/THIS/DIRECTORY/requirements.txt

For a general introduction to installing modules, see here.

Optional dependencies:

• pycuda, required for the tCWFstatMapVersion=pycuda option of the TransientGridSearch class. (Note: pip install pycuda requires a working nvcc compiler in your path.)
• pytest for running the test suite locally (python -m pytest tests.py)
• Developers are also highly encouraged to use the black style checker locally (black --check --diff .), as it is required to pass by the online integration pipeline.
• Some of the examples require gridcorner; for pip users this is most conveniently installed by

pip install git+https://gitlab.aei.uni-hannover.de/GregAshton/gridcorner

• If you prefer to make your own LALSuite installation from source, make sure it is swig-enabled and contains at least the lalpulsar and lalapps packages. A minimal configuration line to use would be e.g.:

./configure --prefix=${HOME}/lalsuite-install --disable-all-lal --enable-lalpulsar --enable-lalapps --enable-swig

install PyFstat from source (Zenodo or git clone)

You can download a source release tarball from Zenodo and extract to an arbitrary temporary directory. Alternatively, clone this repository:

git clone https://github.com/PyFstat/PyFstat.git

The module and associated scripts can be installed system wide (or to the currently active venv), assuming you are in the (extracted or cloned) source directory, via

python setup.py install

As a developer, alternatively

python setup.py develop

or

pip install -e /path/to/PyFstat

can be useful so you can directly see any changes you make in action. Alternatively (not recommended!), add the source directory directly to your python path.

To check that the installation was successful, run

python -c 'import pyfstat'

if no error message is output, then you have installed pyfstat. Note that the module will be installed to whichever python executable you call it from.

Ephemerides installation

PyFstat requires paths to earth and sun ephemerides files in order to use the lalpulsar.ComputeFstat module and various lalapps tools.

If you have done pip install lalsuite (or it got pulled in automatically as a dependency), you need to manually download at least these two files:

• earth00-40-DE405.dat.gz
• sun00-40-DE405.dat.gz

(Other ephemerides versions exist, but these two files should be sufficient for most applications.) You then need to tell PyFstat where to find these files, by either setting an environment variable $LALPULSAR_DATADIR or by creating a ~/.pyfstat.conf file as described further below. If you are working with a virtual environment, you should be able to get a full working ephemerides installation with these commands:

mkdir $VIRTUAL_ENV/share/lalpulsar
wget https://git.ligo.org/lscsoft/lalsuite/raw/master/lalpulsar/lib/earth00-40-DE405.dat.gz -P $VIRTUAL_ENV/share/lalpulsar
wget https://git.ligo.org/lscsoft/lalsuite/raw/master/lalpulsar/lib/sun00-40-DE405.dat.gz -P $VIRTUAL_ENV/share/lalpulsar
echo 'export LALPULSAR_DATADIR=$VIRTUAL_ENV/share/lalpulsar' >> ${VIRTUAL_ENV}/bin/activate
deactivate
source path/to/venv/bin/activate

If instead you have built and installed lalsuite from source, and set your path up properly through something like source $MYLALPATH/etc/lalsuite-user-env.sh, then the ephemerides path should be automatically picked up from the $LALPULSAR_DATADIR environment variable. Similarly, if you have installed lalsuite from conda-forge, it should come with ephemerides included and properly set up.

Alternatively, you can place a file ~/.pyfstat.conf into your home directory which looks like

earth_ephem = '/home/<USER>/lalsuite-install/share/lalpulsar/earth00-19-DE405.dat.gz'
sun_ephem = '/home/<USER>/lalsuite-install/share/lalpulsar/sun00-19-DE405.dat.gz'

Paths set in this way will take precedence over the environment variable.

Finally, you can manually specify ephemerides files when initialising each PyFstat search (as one of the arguments).

Contributors

Maintainers:

• Greg Ashton
• David Keitel

Other contributors:

• Reinhard Prix
• Rodrigo Tenorio
• Karl Wette
• Sylvia Zhu

This project is open to development, please feel free to contact us for advice or just jump in and submit an issue or pull request.

Here's what you need to know:

• The github automated tests currently run on python [3.6,3.7,3.8] and new PRs need to pass all these.
• The automated test also runs the black style checker. If possible, please run this locally before pushing changes / submitting PRs: black --check --diff . to show the required changes, or black . to automatically apply them.

Citing this work

If you use PyFstat in a publication we would appreciate if you cite both a DOI for the software itself (see below) and the original paper introducing the code: Ashton&Prix 2018 [inspire] [ADS]. If you use the transient module, please also cite: Keitel&Ashton 2018 [inspire] [ADS].

If you'd like to cite the PyFstat package in general, or versions from 1.5.x upwards, please refer to the version-independent Zenodo listing or use directly the following BibTeX entry:

@misc{pyfstat,
  author       = {Ashton, Gregory and
                  Keitel, David and
                  Prix, Reinhard,
                  and Tenorio, Rodrigo},
  title        = {PyFstat},
  month        = jul,
  year         = 2020,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.3967045},
  url          = {https://doi.org/10.5281/zenodo.3967045}
  note         = {\url{https://doi.org/10.5281/zenodo.3967045}}
}

You can also obtain DOIs for individual versioned releases from the right sidebar at Zenodo.

Alternatively, if you've used PyFstat up to version 1.4.x in your works, the DOIs for those version can be found from the sidebar at this older Zenodo record and please amend the BibTeX entry accordingly.