PyFstat

This is a python package providing an interface to perform F-statistic based continuous gravitational wave (CW) searches, built on top of the LALSuite library.

Getting started:

This README provides information on installing, contributing to and citing PyFstat.
PyFstat usage and its API are documented at pyfstat.readthedocs.io.
We also have a number of examples, demonstrating different use cases. You can run them locally, or online as jupyter notebooks with binder.
New contributors are encouraged to have a look into how to set up a development environment
The project wiki is mainly used for developer information.
A changelog is also available.

Installation

PyFstat releases can be installed in a variety of ways, including Docker/Singularity images, pip install from PyPi, conda 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 (3.7+) on your system, then Docker or conda are the easiest paths.

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 GitHub account together with a personal access token is required. Go to the wiki page to learn how to pull them from the GitHub registry using Docker or Singularity.

conda installation

See this wiki page for installing conda itself and for a minimal .yml recipe to set up a PyFstat-specific environment.

To install into an existing conda environment, all you need to do is

conda install -c conda-forge pyfstat

If getting PyFstat from conda-forge, it already includes the required ephemerides files.

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.

Recent releases now also include a sufficient minimal set of ephemerides files.

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://git@github.com/PyFstat/PyFstat

This should pull in all dependencies in the same way as installing from PyPI, and recent lalsuite dependencies will include ephemerides files too.

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

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.

This should pull in all dependencies in the same way as installing from PyPI, and recent lalsuite dependencies will include ephemerides files too.

Dependencies

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

For a general introduction to installing modules, see here.

Optional dependencies

PyFstat manages optional dependencies through setuptool's extras_require.

Available sets of optional dependencies are:

chainconsumer (Samreay/Chainconsumer): Required to run some optional plotting methods and some of the example scripts.
pycuda (PyPI): Required for the tCWFstatMapVersion=pycuda option of the TransientGridSearch class. (Note: Installing pycuda requires a working nvcc compiler in your path.)
style: Includes the flake8 linter (flake8.pycqa) and black style checker (black.readthedocs). These checks are required to pass by the online integration pipeline.
test: For running the test suite locally using pytest (python -m pytest tests.py).
wheel: Includes wheel and check-wheel-contents.
dev: Collects style, test and wheel.
docs: Required dependencies to build the documentation.

Installation can be done by adding one or more of the aforementioned tags to the installation command.

For example, installing PyFstat including chainconsumer, pycuda and style dependencies would look like (mind the lack of whitespaces!)

pip install pyfstat[chainconsumer,pycuda,style]

This command accepts the "development mode" tag -e.

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

Ephemerides installation

PyFstat requires paths to earth and sun ephemerides files in order to use the lalpulsar.ComputeFstat module and various lalapps tools. Recent releases of the lal and lalpulsar dependencies from conda or lalsuite from PyPI include a sufficient minimal set of such files (the [earth/sun]00-40-DE405 default versions) and no further setup should be needed. The same should be true if you have built and installed LALSuite from source, and set your paths up properly through something like source $MYLALPATH/etc/lalsuite-user-env.sh.

However, if you run into errors with these files not found, or want to use different versions, you can manually download files from this directory. You then need to tell PyFstat where to find these files, by creating a ~/.pyfstat.conf file in 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 lal's default resolution logic.

You can also manually specify ephemerides files when initialising each PyFstat class with the earth_ephem and sun_ephem arguments.

The alternative of relying on environment variables (as previously recommended by PyFstat's documentation) is considered deprecated by LALSuite maintainers and will no longer be supported by PyFstat in future versions.

Contributing to PyFstat

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 [3.7,3.8,3.9,3.10] and new PRs need to pass all these.
The automated test also runs the black style checker and the flake8 linter. If at all possible, please run these two tools locally before pushing changes / submitting PRs: flake8 --count --statistics . to find common coding errors and then fix them manually, and then black --check --diff . to show the required style changes, or black . to automatically apply them.
bin/setup-dev-tools.sh gets your virtual environment ready for you. After making sure you are using a virtual environment (venv or conda), it installs black, flake8, pre-commit, pytest, wheel via pip and uses pre-commit to run the black and flake8 using a pre-commit hook. In this way, you will be prompted a warning whenever you forget to run black or flake8 before doing your commit 😉.

Contributors

Maintainers:

Greg Ashton
David Keitel

Active contributors:

Reinhard Prix
Rodrigo Tenorio

Other contributors:

Karl Wette
Sylvia Zhu
Dan Foreman-Mackey (pyfstat.gridcorner is based on DFM's corner.py)

Citing this work

If you use PyFstat in a publication we would appreciate if you cite both a release DOI for the software itself (see below) and one or more of the following scientific papers:

The recent JOSS (Journal of Open Source Software) paper summarising the package: Keitel, Tenorio, Ashton & Prix 2021 (inspire:1842895 / ADS:2021arXiv210110915K).
The original paper introducing the package and the MCMC functionality: Ashton&Prix 2018 (inspire:1655200 / ADS:2018PhRvD..97j3020A).
The methods paper introducing a Bayes factor to evaluate the multi-stage follow-up: Tenorio, Keitel, Sintes 2021 (inspire:1865975 / ADS:2021PhRvD.104h4012T)
For transient searches: Keitel&Ashton 2018 (inspire:1673205 / ADS:2018CQGra..35t5003K).
For glitch-robust searches: Ashton, Prix & Jones 2018 (inspire:1672396 / ADS:2018PhRvD..98f3011A

If you'd additionally like to cite the PyFstat package in general, 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 1.5.x upward) 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 versions can be found from the sidebar at this older Zenodo record and please amend the BibTeX entry accordingly.

PyFstat uses the ptemcee sampler, which can be cited as Vousden, Far & Mandel 2015 (ADS:2016MNRAS.455.1919V) and Foreman-Mackey, Hogg, Lang, and Goodman 2012 (2013PASP..125..306F).

PyFstat also makes generous use of functionality from the LALSuite library and it will usually be appropriate to also cite that project (see this recommended bibtex entry) and also Wette 2020 (inspire:1837108 / ADS:2020SoftX..1200634W) for the C-to-python SWIG bindings.

GraCosPA / PyFstat