{"id":19863453,"url":"https://github.com/sandialabs/pancax","last_synced_at":"2025-02-28T23:16:14.227Z","repository":{"id":261454628,"uuid":"884308094","full_name":"sandialabs/pancax","owner":"sandialabs","description":"A set of tools for developing new methods and techniques in physics informed neural networks written in jax.","archived":false,"fork":false,"pushed_at":"2025-02-27T15:54:25.000Z","size":6888,"stargazers_count":4,"open_issues_count":13,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-02-27T22:26:48.194Z","etag":null,"topics":["equinox","jax","physics","physics-informed-neural-networks","physics-simulation","pinn","pinns","sciml","scr-3050","snl-applications"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sandialabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-06T14:17:33.000Z","updated_at":"2025-02-27T15:51:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"eecab51d-fe80-40cd-82ac-ed8c6f406dc6","html_url":"https://github.com/sandialabs/pancax","commit_stats":null,"previous_names":["sandialabs/pancax"],"tags_count":4,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fpancax","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fpancax/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fpancax/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fpancax/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sandialabs","download_url":"https://codeload.github.com/sandialabs/pancax/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241272625,"owners_count":19937091,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["equinox","jax","physics","physics-informed-neural-networks","physics-simulation","pinn","pinns","sciml","scr-3050","snl-applications"],"created_at":"2024-11-12T15:14:43.537Z","updated_at":"2025-02-28T23:16:14.218Z","avatar_url":"https://github.com/sandialabs.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![book](https://img.shields.io/badge/pancax-Book-blue?logo=mdbook\u0026logoColor=000000)](https://sandialabs.github.io/pancax)\n[![Build Status](https://github.com/sandialabs/pancax/workflows/CI/badge.svg)](https://github.com/sandialabs/pancax/actions?query=workflow%3ACI)\n[![Coverage](https://codecov.io/gh/sandialabs/pancax/branch/main/graph/badge.svg)](https://codecov.io/gh/sandialabs/pancax)\n[![PyPI version](https://badge.fury.io/py/pancax.svg)](https://pypi.org/project/pancax/)\n\n# Pancax (\"PANCAKES\")\nPhysics augmented neural computations in jax\n\n## Table of Contents\n1. [Installation](#installation)\n2. [Usage](#usage)\n3. [Citation](#citation)\n\n## Installation\n### CPU installation instructions\nTo install pancax using pip (recommended) for CPU usage you can type the following command\n\n``pip install pancax[cpu]``\n\n### GPU installation instructions\nCurrently only CUDA has been tested, so only a CUDA option is supplied.\n#### CUDA installation instructions\nTo install pancax using pip (recommended) for CPU usage you can type the following command\n\n``pip install pancax[cuda]``\n\n### Developer installation instructions\nIf you would like to do development in pancax, please first clone the repo and in the pancax \nfolder, run the following command\n\n``pip install -e .[cuda,docs,test]``\n\n## Usage\nCurrently the main entry point to pancax is through a python script (although a yaml input file is also in the works).\nTo run a script you can run the following command\n\n``python -m pancax -i my_script.py``\n\nwhere ``my_script.py`` is the name of the scipt you've written. This will run the python script while also \nrespecting several environment variables which can be supplied after the ``pancax`` keyword above. A list of\nthese can be displayed with the help message\n\n``python -m pancax -h``\n\nIf you leverage these tools for your own research, please cite the following article\n\n## Citation\n```bibtex\n@article{hamel2023calibrating,\n  title={Calibrating constitutive models with full-field data via physics informed neural networks},\n  author={Hamel, Craig M and Long, Kevin N and Kramer, Sharlotte LB},\n  journal={Strain},\n  volume={59},\n  number={2},\n  pages={e12431},\n  year={2023},\n  publisher={Wiley Online Library}\n}\n```\nSCR #3050.0\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fpancax","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsandialabs%2Fpancax","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fpancax/lists"}