Package: blueice
blueice: Build Likelihoods Using Efficient Interpolations and monte-Carlo generated EventsSource code:https://github.com/JelleAalbers/blueiceDocumentation:http://blueice.readthedocs.io/en/latest/index.htmlAboutThis package allows you to do parametric inference using likelihood functions, in particular likelihoods derived from Monte-Carlo or calibration sources.Especially when connected to a Monte Carlo, blueice lets you make likelihood functions which measure agreement between data and theory with flexibility: you choose which settings to vary (which parameters the likelihood functions has) and in which space the agreement is measured.This package contains only generic code: you’ll need a few things to make it useful for a particular experiment. Originally this code was developed for XENON1T only; the XENON1T models have since been split off to thelaidbaxrepository. XENONnT is still developingaleawhich is based on blueice.ContributorsJelle AalbersKnut Dundas MoraaBart Pelssers1.2.0 (2024/01/13)Prevent negative rates being passed to Barlow-Beeston equation, and allow per-event weights (#32)Add likelihood that takes coupling as shape parameters (#34)Patch for tests (#37)Use scipy stats for PoissonLL (#40)Do not scale mus when livetime_days is 0 (#41)1.1.0 (2021/01/07)Likelihood sum wrapper (#17)emcee bestfit and multicore precomputation (#18)LogAncillaryLikelihood for constraint terms (#19)HistogramPDFSource simulation, order shape parameter dict (#20)Efficiency shape parameter, LogLikelihoodSum enhancements (#23)Use scipy as default optimizer (#24)Minuit support for bounds and errors (#26, #27)Per-source efficiencies, weighted LogLikelihoodSum (#28)Use atomicwrites for cache to prevent race conditions (#30)1.0.0 (2016/10/01)Binned likelihoods (#7)Argument validation for LogLikelihood function (#8)Automatic handling of statistical uncertainty due to finite MC/calibration statistics (#9):
* Adjustment of expected counts per bin using Beeston-Barlow method for one source
* Generalized to multiple sources, but only one with finite statistics.
* Only for binned likelihoods.iminuit integration, use as default minimizer if installed (#10, #13)compute_pdf option to do full likelihood model computation on the fly (#11)HistogramPDF to provide just histogram lookup/interpolation from DensityEstimatingSource (#12)inference functions -> LogLikelihood methodsMost-used functions/classes available under blueice (blueice.Source, blueice.UnbinnedLogLikelihood, …)compute_pdf auto-called, consistent handling of events_per_dayStart of documentation, readthedocs integration0.4.0 (2016/08/22)Big internal refactor, some API changes (#5)DensityEstimatingSourceBugfixes, more tests0.3.0 (2016/08/21)Renamed to blueice, XENON stuff renamed to laidbaxExperimental radial template morphing (#4)Tests, several bugfixes (e.g. #3)Rate parameters are now rate multipliersLinear interpolation of density estimatorParallel model initialization0.2.0 (2016/07/31)Complete makeover centered around LogLikelihood functionSeparation of XENON stuff and general codePDF cachingExample notebooks0.1.0 (2016/07/14)First release in separate repositoryModel and Source, pdf sampling.0.0.1 (2015/12/18)First release in XeAnalysisScripts