BayesWave
Welcome to the BayesWave software repository. This wiki provides instructions for:
Please see the BayesWave wiki for further information
Quick Start
See here for quick start instructions to installing and running a simple GW150914 analysis
Contributing
Procedures for developing and contributing to this repository match those for lalsuite. The contribution guide for lalsuite can be found here
Documentation is most conveniently provided via markdown (.md) files in the
repository itself. The page you are now reading is the README.md
at the root
of the master branch. All other documentation should live in doc
.
TLDR
- We use the fork/merge development model
- Development projects should take place on feature branches (NOT adhoc sub-directories!)
This eliminates conflicts, ensures the master branch is always useable (no one breaks the build etc) and means different features/branches are easily found, used and contributed to.
So:
- create your own fork of this repository
- create a branch to develop some feature on the fork
- make and commit changes
- push that branch upstream
- when development is complete, merge that branch's changes back into master
Full details of how to do this can be found in the lalsuite contribution guide
This is, first and foremost, a source repository. To reduce bloat and simplify development, data products and analysis-specific scripts/configuration files should really be hosted in separate repositories or archives which document those analyses.
Repository Structure
This repository has been cloned from the original svn repository at https://svn.ligo.caltech.edu/svn/bayeswave. Commit history, branches and tags have been preserved and non-source directories have been excised from the history. Some details of the svn->git transition can be found here.
The git master branch looks like:
-
src
: The main source directory. Includes all C code, header files and build tools -
test
: Test scripts to check successful compilation and linking. -
utils
: Python and bash utility scripts. -
postprocess
: Python and bash post-processing (e.g., plots, webpages) scripts -
BayesWavePipe
: A standalone python module for HTCondor workflow generation
Note that different branches in the original svn do not share a uniform structure; if you cannot find the directory or file you're looking for, check you're on the correct branch.