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PyLAL

The PyLAL package is best described as the Python LIGO Algorithm Library.  It was originally a Python wrapping of parts of the LAL library, and although it continues to provide that function it has aquired a large collection of independent code of its own so that it is no longer exclusively a Python interface to LAL.

In this package you will find convenience code to assist with manipulating XML documents using the glue.ligolw I/O library, you will find a wrapping to libframe to enable GWF frame-file reading, you will find binning and smoothing code, and you will find (partial) wrappings of LAL's burstsearch, date, inject, tools, and window packages.  Additionally, you will find most, if not all, of the inspiral pipeline's follow-up and summary tools, and several burst-related trigger post-production tools.

Project Librarian

Kipp Cannon <kipp.cannon@ligo.org> and Nick Fotopoulos <nickolas.fotopoulos@ligo.org> are PyLAL's librarians, but e-mail the DASWG <daswg@gravity.phys.uwm.edu> or lal-discuss <lal-discuss@gravity.phys.uwm.edu> mailing lists for discussion.

Documentation

You can browse the online documentation for the Python modules in PyLAL. This is automatically generated, every night, from the contents of the Git repository.

Download

PyLAL releases are available in source code form (.tar.gz) and as pre-built Debian and RedHat packages via the standard LSCSoft repositories.

Git Repository

The PyLAL source is located in the LALSuite Git repository. See the following instructions on how to get started. You may also browse the PyLAL Git repository using the web interface.

Bug Reporting

PyLAL's bug database is shared with LAL and LALApps.  Instructions can be found here.  PyLAL bugs belong in the categories whose names begin with "pylal".

Enter the LAL Bug Report Gnats Database.

Build Instructions

PyLAL requires you to have lal, lalmetaio, lalframe, lalsimulation, lalburst, and lalinspiral, all parts of lalsuite, and numpy installed in order to compile the extension modules.  Many of the programs in PyLAL also have run-time dependencies of glue, scipy, matplotlib, and/or basemap.  PyLAL's target platform is Python 2.4 with the HEAD of the master branch of lalsuite and the versions of numpy and scipy found in our CentOS 5.3 and Debian Lenny repositories.

One can build and install PyLAL using the setup.py script included in the source tree, for example python setup.py install --prefix=${wherever}.  This will install a number of executables into ${wherever}/bin, and the library codes into something like ${wherever}/lib/python2.4/site-packages/pylal.  The library install path is platform-dependent (for example, 64-bit Redhat systems might place some code in a lib64 subdirectory instead, and if you have a different Python version then obviously that part of the path will be different).

To use PyLAL after it is installed, you should set up your PATH and PYTHONPATH by sourcing ${wherever}/etc/pylal-user-env.sh or pylal-user-env.csh, depending on your shell type.

Mailing Lists

There are several mailing lists related to PyLAL:

Contributors

Lots of people have contributed to PyLAL.  Add your name here if you don't see it.

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