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Add and document pip installation path
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.github/workflows/publish.yaml

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# This workflow will upload a Python Package using Twine when a release is created
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# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
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# This workflow uses actions that are not certified by GitHub.
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# They are provided by a third-party and are governed by
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# separate terms of service, privacy policy, and support
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# documentation.
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name: Upload Python Package
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on:
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release:
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types: [published]
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jobs:
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deploy:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.10
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uses: actions/setup-python@v5
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with:
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python-version: "3.10"
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install build
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- name: Build package
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run: python -m build
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- name: Publish package
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uses: pypa/gh-action-pypi-publish@v1.9.0
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with:
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user: __token__
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password: ${{ secrets.PYPI_API_TOKEN }}

README.md

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[![Paper](http://img.shields.io/badge/arXiv-2405.14108-B31B1B.svg)](https://arxiv.org/abs/2405.14108)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11477766.svg)](https://doi.org/10.5281/zenodo.11477766)
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[![PyPI version](https://badge.fury.io/py/posebench.svg)](https://badge.fury.io/py/posebench)
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[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
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[![Docs](https://assets.readthedocs.org/static/projects/badges/passing-flat.svg)](https://bioinfomachinelearning.github.io/PoseBench/)
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<a href="https://hydra.cc/"><img alt="Config: Hydra" src="https://img.shields.io/badge/config-hydra-89b8cd"></a>
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<details>
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Install `mamba` for dependency management (as a fast alternative to Anaconda)
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### Portable installation
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To reuse modules and utilities within `PoseBench` in other projects, one can simply use `pip`
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```bash
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pip install posebench
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```
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### Full installation
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To reproduce, customize, or extend the `PoseBench` benchmark, we recommend fully installing `PoseBench` using `mamba` as follows:
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First, install `mamba` for dependency management (as a fast alternative to Anaconda)
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```bash
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wget "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"

docs/source/acknowledgements.rst

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================
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.. mdinclude:: ../../README.md
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docs/source/available_methods.rst

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.. mdinclude:: ../../README.md
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.. note::
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Have a new method to add? Please let us know by creating a pull request. We would be happy to work with you to integrate new methodology into this benchmark!

docs/source/bonus.rst

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================
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.. mdinclude:: ../../README.md
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.. image:: ./_static/WorkBench.jpeg
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:alt: My brain after building PoseBench

docs/source/citing_this_work.rst

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docs/source/comparative_plots.rst

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docs/source/data_preparation.rst

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.. mdinclude:: ../../README.md
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docs/source/ensemble_inference.rst

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.. note::
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In addition to having `consensus` as an available value for `ensemble_ranking_method`, one can also set `ensemble_ranking_method=ff` to have the method ensemble's top-ranked predictions selected using the criterion of "minimum (molecular dynamics) force field energy" (albeit while incurring a very large runtime complexity).

docs/source/for_developers.rst

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