Commit 05a8542b authored by Alexander Urban's avatar Alexander Urban
Browse files

Adding the GPL license, a README file, an INSTALL file, and a Manifest.in file

parent d0c1af91
MANIFEST
*.pyc
build
dist
*.egg-info
.DS_Store
This diff is collapsed.
RAVEN installation instructions
===============================
Prerequisites
-------------
* Python 2.6 or 2.7
Should be provided by the distribution.
* python-decorator >= 3.3
Should be available in the distribution.
* argparse >= 1.2.0
Should be available in the distribution.
* Numpy >= 1.4.1 and Scipy >= 0.7.2
Should be installable either via the distribution packaging system,
pip or easy_install.
* LALSuite
See https://www.lsc-group.phys.uwm.edu/daswg/docs/howto/lal-install.html
for installation instructions. LALSuite must be configured with the
--enable-swig-python option.
* HEALPy >= 1.4.1
See http://code.google.com/p/healpy/ for installation instructions.
* VOEventLib
See http://www.astropython.org/resource/2011/5/VOEventLib for a source tarball,
or contact Roy Williams at roy.williams@ligo.org.
Installing RAVEN
----------------
To install from the git repository hosted on LIGO-VCS, use the albert.einstein
credentials via:
git clone albert.einstein@ligo-vcs.phys.uwm.edu:/usr/local/git/raven.git
cd raven
python setup.py build
python setup.py install --user
python setup.py test
To install system-wide, replace the 'setup.py install' command with
sudo python setup.py install
include COPYING
include bin/*
Welcome to RAVEN, the Rapid, on-source VOEvent Coincidence Monitor.
More information can be found at the website:
<link to be provided>
To install RAVEN locally:
python setup.py install --prefix=/path/to/install/directory
To run the RAVEN unit tests:
python setup.py test
(This functionality is to come.)
Finally, the most current RAVEN development version is always available from the
git repository:
git clone albert.einstein@ligo-vcs.phys.uwm.edu:/usr/local/git/raven.git
......@@ -69,7 +69,7 @@ if opts.direction == 'forward':
if short_coincs != []:
# Produce plots of skymaps and report statistics if coincs exist.
from lalinference.bayestar import fits
from workflow_helper import directory
from raven.workflow import directory
arglist = " -o skymap_with_short_triggers.png --colormap=OrRd"
for coinc in short_coincs:
working = directory(coinc['graceid'])
......@@ -105,7 +105,7 @@ if opts.direction == 'forward':
if long_coincs != []:
# Produce plots of skymaps and report statistics if coincs exist.
from lalinference.bayestar import fits
from workflow_helper import directory
from raven.workflow import directory
arglist = " -o skymap_with_long_triggers.png --colormap=OrRd"
for coinc in long_coincs:
working = directory(coinc['graceid'])
......
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