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Minimal python version changed to 3.6

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Fabian Joswig 2021-10-15 15:51:12 +01:00
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.github/workflows/CI.yml vendored
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@ -13,7 +13,7 @@ jobs:
strategy: strategy:
fail-fast: true fail-fast: true
matrix: matrix:
python-version: ["3.5", "3.6", "3.7", "3.8", "3.9"] python-version: ["3.6", "3.7", "3.8", "3.9"]
steps: steps:
- name: Checkout source - name: Checkout source

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README.md
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@ -1,4 +1,4 @@
[![flake8 Lint](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml) [![CI](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml) [![](https://img.shields.io/badge/python-3.5+-blue.svg)](https://www.python.org/downloads/) [![flake8 Lint](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/flake8.yml) [![CI](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/CI.yml) [![](https://img.shields.io/badge/python-3.6+-blue.svg)](https://www.python.org/downloads/)
# pyerrors # pyerrors
`pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data. `pyerrors` is a python package for error computation and propagation of Markov chain Monte Carlo data.
It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are: It is based on the **gamma method** [arXiv:hep-lat/0306017](https://arxiv.org/abs/hep-lat/0306017). Some of its features are:

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setup.py
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@ -8,6 +8,6 @@ setup(name='pyerrors',
author='Fabian Joswig', author='Fabian Joswig',
author_email='fabian.joswig@ed.ac.uk', author_email='fabian.joswig@ed.ac.uk',
packages=find_packages(), packages=find_packages(),
python_requires='>=3.5.0', python_requires='>=3.6.0',
install_requires=['numpy>=1.16', 'autograd>=1.2', 'numdifftools', 'matplotlib', 'scipy', 'iminuit<2'] install_requires=['numpy>=1.16', 'autograd>=1.2', 'numdifftools', 'matplotlib', 'scipy', 'iminuit<2']
) )