LALSuite

This is the main LALSuite development repository. If you would like to just use a released version, see here for IGWN conda environments including LALSuite, or the project pages on conda-forge and on PyPI.

Acknowledgment

We request that any academic report, publication, or other academic disclosure of results derived from the use of this software acknowledge the use of the software by an appropriate acknowledgment or citation.

The whole LALSuite software suite can be cited with the DOI 10.7935/GT1W-FZ16. An example BibTeX entry could look like this:

 @misc{lalsuite,
       author         = "{LIGO Scientific Collaboration} and {Virgo Collaboration} and {KAGRA Collaboration}",
       title          = "{LVK} {A}lgorithm {L}ibrary - {LALS}uite",
       howpublished   = "Free software (GPL)",
       doi            = "10.7935/GT1W-FZ16",
       year           = "2018"
 }

The Python/Octave interfaces to LALSuite are described in this paper:

 @article{swiglal,
          title     = "{SWIGLAL: Python and Octave interfaces to the LALSuite gravitational-wave data analysis libraries}",
          author    = "Karl Wette",
          journal   = "SoftwareX",
          volume    = "12",
          pages     = "100634",
          year      = "2020",
          doi       = "10.1016/j.softx.2020.100634"
 }

In addition, some codes contained in this package may be directly based on one or several scientific papers, which should be cited when using those specific codes; some of these can be discovered through the documentation.

Cloning the Repository

We now utilize Git LFS for the managament of large files and as such git-lfs needs to be installed and configured to correctly clone this repository. After installing git-lfs it can be configured using:

 $ git lfs install

This only needs to be done once for each machine you access the repository. It can then be cloned using:

 $ git clone [email protected]:lscsoft/lalsuite.git

Building from Source

The recommended way to build LALSuite from source is in a conda environment. A recipe file is available with all main dependencies. This can serve as the base for custom recipes, or be used directly via:

 $ conda env create -f common/conda/environment.yml

Pulling in dependencies may take a while depending on your internet connection. After the environment setup succeeded, you can activate it with:

 $ conda activate lalsuite-dev

The first time building LALSuite from source, you need to set up the build system by running (from the top level of the Git repository):

 $ ./00boot

The next step is to configure the LALSuite build system, which determines what components of LALSuite are built, and with what features. This is done by running (from the top level of the Git repository):

 $ ./configure [options...]

A full list of options is available by running ./configure --help=recursive. Some commonly-used options are:

• --prefix=<path>: Sets which <path> LALSuite will be installed into. By default, LALSuite is installed into a directory ./_inst/ at the top level of the Git repository.

• --enable-all-lal: Build all component libraries of LALSuite, including lalapps; the default.

• --disable-all-lal: Build only the lal library component of LALSuite.

• --enable-lal<name>: Build the lal<name> component of LALSuite. This option can be combined with the --disable-all-lal option to selectively build LALSuite components, e.g. --disable-all-lal --enable-lalframe --enable-lalinference will build only the lal, lalframe, and lalinference components.

• --enable-swig-python, --enable-swig-octave: Build Python and/or Octave interfaces to the LALSuite libraries (using the SWIG tool), which allow LALSuite library functions to be called directly from Python/Octave. By default, only the Python interface is built. Use --enable-swig to build both interfaces.

• --enable-fftw, --enable-intelfft: Perform Fast Fourier Transforms using either the FFTW library (the default) or the Intel MKL library. To enable aligned memory optimisations with FFTW, use the --enable-fftw3-memalign option.

• --enable-framel, --enable-framec: Read/write gravitational wave frame files using either the FrameL or FrameCPPC libraries. By default, the LALSuite build system will use whichever library is available on your system; if neither are available, frame file reading/writing will be disabled.

• --with-hdf5: Build support for reading/writing to HDF5 files.

• --with-cfitsio: Build support for reading/writing to FITS files.

• --with-cuda=<path>: Build CUDA code which runs on graphics processing units. <path> should specify the top-level directory of a local install of the CUDA Toolkit.

• PYTHON=<pythonX.Y>: set the Python interpreter used by LALSuite to run Python scripts and compile Python modules. By default the LALSuite build system will find the default system Python interpreter, so this is only needed if you want to build against a specific Python version X.Y.

Once LALSuite has been configured, you can then build and install LALSuite by running (from the top level of the Git repository):

 $ make [-j<processes>] && make install

where <processes> optionally specifies the number of processes used for building in parallel. If the build is successful, make install will install LALSuite into the directory given by --prefix.

After pulling updates or making your own changes, you will usually only need to call make && make install again, as reconfiguration and re-running 00boot should be handled automatically if needed.

If you prefer managing dependencies yourself without conda, see here.

Contributing to LALSuite

The guide to contributing to LALSuite explains how to report issues and contribute fixes or new features using the fork and pull workflow. Please read and follow these directions.

Nightly Documentation

The LALSuite Doxygen documentation is built under GitLab-CI every night.

Notes on Ancient History

LALSuite was transferred to git.ligo.org in December 2017. Older history has been imported, though commit hashes were rewritten during the Git LFS conversion. Please note:

1. The Original: commit IDs quoted in each commit message can be used to compare with the archived reference repo, old issue discussions on the Redmine tracker, review wiki pages etc.

2. Commits before December 2017 may also include references to issues (#number). These refer to the corresponding Redmine issue (LVC-authorized access only), and any clickable link the internal GitLab web interface produces for those old commits will therefore be spurious.

For More Information

Please visit the LALSuite project page.