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Description:

blueice 1.2.0

blueice: Build Likelihoods Using Efficient Interpolations and monte-Carlo generated Events

Source code: https://github.com/JelleAalbers/blueice
Documentation: http://blueice.readthedocs.io/en/latest/index.html

About
This 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 the laidbax repository. XENONnT is still developing alea which is based on blueice.

Contributors

Jelle Aalbers
Knut Dundas Moraa
Bart Pelssers

1.2.0 (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 methods
Most-used functions/classes available under blueice (blueice.Source, blueice.UnbinnedLogLikelihood, …)
compute_pdf auto-called, consistent handling of events_per_day
Start of documentation, readthedocs integration

0.4.0 (2016/08/22)

Big internal refactor, some API changes (#5)
DensityEstimatingSource
Bugfixes, more tests

0.3.0 (2016/08/21)

Renamed to blueice, XENON stuff renamed to laidbax
Experimental radial template morphing (#4)
Tests, several bugfixes (e.g. #3)
Rate parameters are now rate multipliers
Linear interpolation of density estimator
Parallel model initialization

0.2.0 (2016/07/31)

Complete makeover centered around LogLikelihood function
Separation of XENON stuff and general code
PDF caching
Example notebooks

0.1.0 (2016/07/14)

First release in separate repository
Model and Source, pdf sampling.

0.0.1 (2015/12/18)

First release in XeAnalysisScripts