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flamedisx-2.0.0


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توضیحات

Fast likelihood analysis in more dimensions for xenon TPCs
ویژگی مقدار
سیستم عامل -
نام فایل flamedisx-2.0.0
نام flamedisx
نسخه کتابخانه 2.0.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Flamedisx developers
ایمیل نویسنده -
آدرس صفحه اصلی https://github.com/FlamTeam/flamedisx
آدرس اینترنتی https://pypi.org/project/flamedisx/
مجوز -
Flamedisx ========== Fast likelihood analysis in more dimensions for xenon TPCs. ![Build Status](https://github.com/FlamTeam/flamedisx/actions/workflows/test_flamedisx.yml/badge.svg) [![Documentation Status](https://readthedocs.org/projects/flamedisx/badge/?version=latest)](https://flamedisx.readthedocs.io/en/latest/?badge=latest) [![DOI](https://zenodo.org/badge/176141558.svg)](https://zenodo.org/badge/latestdoi/176141558) [![ArXiv number](https://img.shields.io/badge/physics.ins--det-arXiv%3A2003.12483-%23B31B1B)](https://arxiv.org/abs/2003.12483) [![Join the chat at https://gitter.im/AxFoundation/strax](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/FlamTeam/flamedisx) Flamedisx aims to increase the practical number of dimensions and parameters in likelihoods for liquid-xenon (LXe) detectors, which are leading the field of direct dark matter detection. Traditionally, particle physicists compute signal and background models by filling histogram 'templates' with high-statistics Monte Carlo (MC) simulations. However, the LXe model can also be computed with a series of (large) matrix multiplications, equivalent to the integral approximated by the MC simulation. Using TensorFlow makes this computation differentiable and GPU-scalable, so it can be used practically for fitting and statistical inference. The result is a better sensitivity, since the likelihood can use all observables, and more robust fits, because using simultaneous correlated nuisance parameters no longer requires challenging interpolation and template morphing. Getting started --------------------------- To get started, [Launch our tutorial on Colaboratory](https://colab.research.google.com/github/FlamTeam/flamedisx-notebooks/blob/master/Tutorial.ipynb), or view it statically on [GitHub](https://github.com/FlamTeam/flamedisx-notebooks/blob/master/Tutorial.ipynb) or [ReadTheDocs](https://flamedisx.readthedocs.io/en/latest/tutorial.html). Our [paper](https://arxiv.org/abs/2003.12483) gives a detailed description of Flamedisx, and compares Flamedisx quantitatively to traditional template-based methods. If you want all the details, see the [Flamedisx Documentation](https://flamedisx.readthedocs.io) and our [Notebooks repository](https://github.com/FlamTeam/flamedisx-notebooks). FlameNEST ----------- [![arXiv](https://img.shields.io/badge/arXiv-2204.13621-b31b1b.svg)](https://arxiv.org/abs/2204.13621) Since version 2.0.0, flamedisx includes an implementation of electronic and nuclear recoil models from the [Noble Element Simulation Technique](https://nest.physics.ucdavis.edu/) version 2.2.2. To use this, use sources from the ``fd.nest`` subpackage, e.g. ``fd.nest.ERSource``. See the [flameNEST paper](https://arxiv.org/abs/2204.13621) for a detailed description and validation. 2.0.0 / 2022-05-20 ------------------ - FlameNEST models fully implemented (https://arxiv.org/abs/2204.13621) - NEST models for pre-quanta processes (#205) - Bayesian bounds estimation (#174) - NEST source fixes (#152) - Fix covariance used in `LogLikelihood.summary` (#176) - Avoid calculating `produced_quanta = 0` probability (#181) - `electron_loss` model function (#193) - Add exposure parameter to WIMPEnergySpectrum (#223) - Always reset data index (#225) - XENON sources: - Wall events model (#143) - `double_pe_fraction` model function (#208) - Updates to config defaults (#209) - Spatially dependent drift field map (#221) - Configurable drift field, S2 AFT (#213, #218) 1.5.0 / 2021-06-29 ------------------ - Variable stepping, support for high-energy models (#127) - NEST models for post-quanta processes (#136) - Configuration system (#140, #147) - XENON1T: Fix S2 acceptance (#138) and unused imports (#128) - Update block system documentation (#139) 1.4.1 / 2021-04-20 ------------------ - Stabilize default optimizer with better parameter scaling (#114) - XENONnT: Support reading data from private repository (#115) - XENON1T: Variable elife (#118) - XENON1T: Npz resource reading (#123) 1.4.0 / 2021-03-05 ------------------ - Fix 'sticky defaults' bug (#110) - Enable GitHub Actions and Dependabot (#109) - Documentation updates (#92, [notebooks#3](https://github.com/FlamTeam/flamedisx-notebooks/pull/3)) - Likelihood `defaults` support, simulate argument fixes (#103) - SpatialRateEnergySpectrum: Simplify API (#100) and fix draw_positions (#105) - WIMPEnergySpectrum: Accept event times slightly out of range (#99) - Do not round photons_detected_mle (#91) - XENON1T: fix S2 acceptance (#97) and name reconstruction efficiency pivots (#102) 1.3.0 / 2020-08-25 ------------------ - Block system (#81) - Documentation (#81) - Bugfixes (#83, #87, #89) 1.2.0 / 2020-07-21 ------------------ - Access BBF data and XENON-utilities (#80) - Double photoelectron emission modeling (#78) - Optimization improvements (#76) - Bugfix (#79) 1.1.0 / 2020-07-09 ------------------ - Nonlinear constraint limit setting (experimental) (#70) - Dimension scaling inside optimizers (#72) - Auto-guess rate multipliers (#74) - Python 3.8 builds (#73) - Add sanity checks on input and guess (#69) 1.0.0 / 2020-03-26 ------------------ - Fiducial volume specification (#64) - Added default cS1 cut (#63) - Cleanup and optimizations (#63, #64, #65) 0.5.0 / 2020-01-31 ------------------ - Autographed Hessian; use Hessian in the optimizer (#62) - Check for optimizer failures (#61) - Trace single-batch likelihood, but use numpy thereafter (#61) - Fix simulation/data discrepancy in recombination fluctuation - Adjust optimizer defaults - Option to use time-averaged WIMP spectra 0.4.0 / 2020-01-15 ------------------- - Many changes to objectives and inference (#59, #60) - Add tilt to objective for interval/limit searches - one_parameter_interval -> limit and interval methods - Optimizers use bounds - Tolerance option homogenization (first pass) - Auto-guess limits 0.3.1 / 2019-11-26 ------------------ - Performance improvements and cleanup (#58) - Improve one_parameter_interval arguments (#56) - Add Tutorial output to flamedisx-notebooks (#56) - Bugfixes (#57) 0.3.0 / 2019-11-19 ------------------ - Split off notebook folder to flamedisx-notebooks - Pass source specific parameters correctly (#51) - Flexible event padding (#54) - SciPy optimizer and optimizer settings (#54) - one_parameter_interval (#54) - Bugfixes (#46, #55, #51) - Unify optimizers (#54) 0.2.2 / 2019-10-30 ------------------ - Minuit optimizer (#40) - Likelihood simulator (#43, #44) - Updates to NRSource (#40) 0.2.1 / 2019-10-24 ------------------ - Workaround for numerical errors (#38, #39) 0.2.0 / 2019-10-11 ------------------ - Spatially dependent rates (#27) - Time dependent energy spectra (#24) - XENON1T SR1-like model / fixes (#22, #32) - Switch optimizer to BFGS + Hessian (#19) - Multiple source support (#14) - Optimization (#13) - Bugfixes / refactor (#18, #20, #21, #28, #30, #31, #35) 0.1.2 / 2019-07-24 ------------------- - Speedup ER computation, add tutorial (#11) - Optimize lookup-axis1 (#10) 0.1.1 / 2019-07-21 ------------------- - 5x speedup for Hessian (#9) - Fix pip install 0.1.0 / 2019-07-16 ------------------- - Batching (#7) - Inference (#6) - Ported to tensorflow / GPU support (#1, #2, #3, #5) 0.0.1 / 2019-03-17 ------------------ - Initial numpy-based version


نیازمندی

مقدار نام
- numpy
- scipy
- pandas
- multihist
>=0.3.1 wimprates
- tqdm
>=2.2.0 tensorflow
>=0.8.0 tensorflow-probability
- iminuit
- sphinx
- sphinx-rtd-theme
- nbsphinx
- recommonmark
==1.22.3 numpy
==1.8.0 scipy
==1.4.2 pandas
==0.6.5 multihist
==0.3.2 wimprates
==4.64.0 tqdm
==2.8.0 tensorflow
==0.16.0 tensorflow-probability
==2.11.2 iminuit


زبان مورد نیاز

مقدار نام
>=3.6 Python


نحوه نصب


نصب پکیج whl flamedisx-2.0.0:

    pip install flamedisx-2.0.0.whl


نصب پکیج tar.gz flamedisx-2.0.0:

    pip install flamedisx-2.0.0.tar.gz