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Rapid Bayesian sky localization for gravitational wave inspiral events. NOTE: DEVELOPMENT MOVED TO <http://www.lsc-group.phys.uwm.edu/cgit/lalsuite/tree/lalinference/python/bayestar>.
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gravitationalarry/bayestar-localization
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BAYESTAR-LOCALIZATION ===================== Rapid Bayesian sky localization for gravitational wave inspiral events. Dependencies ============ - BAYESTAR <https://www.lsc-group.phys.uwm.edu/daswg/projects/bayestar.html> - HEALPix >= 3.00 <http://sourceforge.net/projects/healpix/> - Healpy >= 1.4.1 <http://code.google.com/p/healpy/> - PyFITS <http://www.stsci.edu/institute/software_hardware/pyfits> - NumPy <http://numpy.scipy.org/> - SciPy <http://www.scipy.org/> - an OpenMP-enabled C/C++ compiler (optional, for parallelization) (GCC >= 4.2 on most Linux systems, or >= 4.1 on CentOS; MS Visual C++ on Windows) - pylal <https://www.lsc-group.phys.uwm.edu/daswg/projects/pylal.html> - lal and lalsimulation with SWIG bindings enabled <https://www.lsc-group.phys.uwm.edu/daswg/projects/lalsuite.html> - Glue <https://www.lsc-group.phys.uwm.edu/daswg/projects/glue.html> - GraceDb <https://www.lsc-group.phys.uwm.edu/daswg/projects/gracedb.html>, for optional integration with LIGO's GraceDb and LValert Debian packaging ================ To build the Debian package, run `sudo apt-get install python-stdeb' and then run 'python setup.py bdist_deb'.
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Rapid Bayesian sky localization for gravitational wave inspiral events. NOTE: DEVELOPMENT MOVED TO <http://www.lsc-group.phys.uwm.edu/cgit/lalsuite/tree/lalinference/python/bayestar>.
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