semvec/pypi-packages huggingface dataset:
aiida-gromacs 2.1.2
A plugin for using GROMACS with AiiDA for molecular dymanics simulations.
Requires Python: >=3.8
Keywords: aiida, plugin, gromacs, aiida-gromacs

# aiida-gromacs
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The GROMACS plugin for AiiDA aims to enable the capture and sharing of the full
provenance of data when parameterising and running molecular dynamics
simulations. This plugin is being developed as part of the Physical Sciences
Data Infrastructure programme to improve the practices around data within the
Physical Sciences remit area within the UK.

This package is currently a work in progress and we will be adding much more
complete functionality to this plugin in the coming months.

The design pattern we are aiming for is to simply allow researchers to capture
the full data provenance for their simulations by only switching on an AiiDA
conda environment, along with modifying your command lines very slightly.

This means that you should gain access to powerful FAIR data practices without
wholesale cultural or usage pattern shifts in your daily work.

## Documentation

See [here](https://aiida-gromacs.readthedocs.io/en/latest/) for documentation for users and developers.

## License

MIT

## Contact

- james.gebbie@stfc.ac.uk
- jas.kalayan@stfc.ac.uk
dpm-tools 1.0.2
A collection of tools and workflows to streamline the processing and visualization of porous media images.
Requires Python: >=3.8
Keywords: digital porous media, image analysis

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.16987906.svg)](https://doi.org/10.5281/zenodo.16987906)
[![image](https://img.shields.io/pypi/v/dpm-tools.svg)](https://pypi.org/project/dpm-tools/)
[![Tests](https://github.com/digital-porous-media/dpm_tools/actions/workflows/tests.yml/badge.svg?branch=master)](https://github.com/digital-porous-media/dpm_tools/actions/workflows/tests.yml)
[![Docs](https://github.com/digital-porous-media/dpm_tools/actions/workflows/docs.yml/badge.svg?branch=master)](https://github.com/digital-porous-media/dpm_tools/actions/workflows/docs.yml)

# Digital Porous Media (DPM) Tools
Welcome to DPM Tools! Our team at The University of Texas at Austin has put together a collection of Python modules for processing and visualizing porous media images. Integrated as workflows, the combination of all module functions provide end-to-end capabilities that streamline pre- and post- processing of porous media images. Individual and combined functions can be used to curate images for publication, prepare images for simulation and machine learning (ML) applications, and analyze simulation and ML results. 

By design, DPM Tools integrate functions from open Python packages to implement common digital porous media as workflows.

DPM Tools is implemented within the Digital Porous Media Portal (formerly Digital Rocks Portal) and as a standalone image processing workflow that users can download.

Current Modules:
---

- ``Input/Output (IO)``: Tools for reading and writing digital porous media images from raw, tiff, hdf5, netCDF and matlab files. The tools can edit and convert the files. 

- ``Metrics``: includes several functions for quantifying geometric properties of images.

- ``Segmentation``: algorithms for classifying phases within an image.

- ``Visualization``: workflows for 3D visualization with PyVista.

Further documentation and descriptions of how to use the different modules are available in the related links of this document and in the landing page where the software is published in Zenodo. Our team is continuously maintaining the software and adding new modules. 


## Installation
To install from PyPI:

    pip install dpm-tools

## Documentation:
For further information and examples on how to get started, please see our [documentation](https://digital-porous-media.github.io/dpm_tools/html/)