Python fitter package for multiple computational back-ends

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  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3 or later)
  • Author: Common Partial Wave Analysis
  • Maintainer:
  • Tags HEP , PWA , amplitude analysis , partial wave analysis , particle physics , physics , tensorflow
  • Requires: Python <3.10, >=3.6
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TensorWaves

10.5281/zenodo.5526650 GPLv3+ license

PyPI package Conda package Supported Python versions

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Documentation build status pre-commit.ci status pytest Checked with mypy Test coverage Codacy Badge Spelling checked code style: prettier Code style: black Imports: isort

TensorWaves is a fitter package that optimizes mathematical models to data samples. The models can be any symbolic mathematical expression that is then converted to any computational backend. In addition, TensorWaves provides functionality to generate toy Monte Carlo data samples. The package is developed in parallel with AmpForm, which implements physics models, but its 'lambdifying' mechanisms can in principle be used independently.

All documentation can be found on tensorwaves.rtfd.io.

For an overview of upcoming releases and planned functionality, see here.

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See CONTRIBUTING.md

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  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3 or later)
  • Author: Common Partial Wave Analysis
  • Maintainer:
  • Tags HEP , PWA , amplitude analysis , partial wave analysis , particle physics , physics , tensorflow
  • Requires: Python <3.10, >=3.6
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Release history Release notifications | RSS feed

0.4.15

0.4.14

0.4.13

0.4.12

0.4.11

0.4.10

0.4.9

0.4.8

0.4.7

0.4.6

This version

0.4.5

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.7

0.3.4

0.3.3

0.3.2

0.3.1 yanked

Reason this release was yanked:

Results in AmpForm version conflicts, recommended to use >=0.3.2

0.3.0

0.2.9

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1.0a0 pre-release

0.0.0a0 pre-release

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