gstlal_inspiral_marginalize_likelihood ====================================== A program to marginalize the likelihood pdfs in noise across mass bins for a gstlal inspiral analysis. Review status ------------- +-----------------------------+------------------------------------------+------------+ | Names | Hash | Date | +=============================+==========================================+============+ | Florent, Jolien, Kipp, Chad | 1dbbbd963c9dc076e1f7f5f659f936e44005f33b | 2015-05-14 | +-----------------------------+------------------------------------------+------------+ Command line options -------------------- .. code-block:: none Usage: gstlal_inspiral_marginalize_likelihood [options] Options: -h, --help show this help message and exit --ignore-missing Ignore and skip missing input documents. --marginalize={ranking-stat|ranking-stat-pdf} Set which set of PDFs to marginalize, the ranking statistics themselves, or the distributions of ranking statistic values (default: ranking-stat). --density-estimate-zero-lag Apply density estimation algorithm to zero-lag PDFs (default: do not). Requires --marginalize=ranking- stat-pdf. In the online analysis, the ingested zero- lag histograms contain raw bin counts, but the consumer of this program's output requires the PDFs to be properly density-estimated, so we provide the option of performing that operation here as a courtesy. This will probably work differently one day. -o filename, --output=filename Set the output file name (default = write to stdout). --likelihood-cache=filename Set the cache file name from which to read likelihood files. --verbose Be verbose.