blueice 1.2.1
Build Likelihoods Using Efficient Interpolations from monte-Carlo generated Events
License: MIT
Keywords: blueice

blueice: Build Likelihoods Using Efficient Interpolations and monte-Carlo generated Events
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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 <https://github.com/XENON1T/laidbax>`_ repository. XENONnT is still developing `alea <https://github.com/XENONnT/alea>`_ which is based on blueice.


Contributors
============
* Jelle Aalbers
* Knut Dundas Moraa
* Bart Pelssers


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1.2.1 (2024/12/11)
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* Source-wise interpolation by @hammannr in https://github.com/JelleAalbers/blueice/pull/46
* Fix source index mismatch by @hammannr in https://github.com/JelleAalbers/blueice/pull/47

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1.2.0 (2024/01/13)
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* 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)

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1.1.0 (2021/01/07)
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* 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)

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1.0.0 (2016/10/01)
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* 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

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0.4.0 (2016/08/22)
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* Big internal refactor, some API changes (#5)
* DensityEstimatingSource
* Bugfixes, more tests

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0.3.0 (2016/08/21)
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* 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

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0.2.0 (2016/07/31)
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* Complete makeover centered around LogLikelihood function
* Separation of XENON stuff and general code
* PDF caching
* Example notebooks

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0.1.0 (2016/07/14)
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* First release in separate repository
* Model and Source, pdf sampling.

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0.0.1 (2015/12/18)
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* First release in XeAnalysisScripts