pyplaid 0.1.2

A package that implements a data model tailored for AI and ML in the context of physics problems

Physics Learning AI Datamodel (PLAID)

• Physics Learning AI Datamodel (PLAID)
  • 1. Description
  • 2. Getting started
  • 3. Call for Contributions
  • 4. Documentation

1. Description

This library proposes an implementation for a datamodel tailored for AI and ML learning of physics problems. It has been developped at SafranTech, the research center of Safran group.

• Documentation: https://plaid-lib.readthedocs.io/
• Source code: https://github.com/PLAID-lib/plaid
• Contributing: https://github.com/PLAID-lib/plaid/blob/main/CONTRIBUTING.md
• License: https://github.com/PLAID-lib/plaid/blob/main/LICENSE.txt
• Bug reports: https://github.com/PLAID-lib/plaid/issues
• Report a security vulnerability: https://github.com/PLAID-lib/plaid/issues

2. Getting started

2.1 Using the library

To use the library, the simplest way is to install the conda package:

conda install -c conda-forge plaid

2.2 Contributing to the library

To contribute to the library, you need to clone the repo using git:

git clone https://github.com/PLAID-lib/plaid.git

Configure an environment manually following the dependencies listed in conda_dev_env.yml, or generate it using conda:

conda env create -f conda_dev_env.yml

Then, to install the library:

pip install -e .

To check the installation, you can run the unit test suite:

pytest tests

To test further and learn about simple use cases, you can run and explore the examples:

cd examples
bash run_examples.sh  # [unix]
run_examples.bat      # [win]

3. Call for Contributions

The PLAID project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated.

Writing code isn’t the only way to contribute to PLAID. You can also:

• review pull requests
• help us stay on top of new and old issues
• develop tutorials, presentations, and other educational materials
• maintain and improve our documentation
• help with outreach and onboard new contributors

If you are new to contributing to open source, this guide helps explain why, what, and how to successfully get involved.

4. Documentation

A documentation is available in readthedocs.