Giter VIP home page Giter VIP logo

pycalphad's Introduction

pycalphad, a library for the CALculation of PHAse Diagrams

Join the chat at https://gitter.im/pycalphad/pycalphad Test Coverage Windows Build Status Build Status Development Status Latest version Supported Python versions License

Note: Unsolicited pull requests are _happily_ accepted!

pycalphad is a free and open-source Python library for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria within the CALPHAD method. It provides routines for reading Thermo-Calc TDB files and for solving the multi-component, multi-phase Gibbs energy minimization problem.

The purpose of this project is to provide any interested people the ability to tinker with and improve the nuts and bolts of CALPHAD modeling without having to be a computer scientist or expert programmer.

For assistance in setting up your Python environment and/or collaboration opportunities, please contact the author by e-mail or using the issue tracker on GitHub.

pycalphad is licensed under the MIT License. See LICENSE.txt for details.

Required Dependencies:

  • Python 2.7+ or 3.5+
  • matplotlib, numpy, scipy, sympy, xarray, pyparsing, tinydb, cyipopt

Installation

See Installation Instructions.

Examples

Jupyter notebooks with examples are available on NBViewer and pycalphad.org.

Documentation

See the documentation on pycalphad.org.

Getting Help

Questions about installing and using pycalphad can be addressed in the pycalphad Google Group. Technical issues and bugs should be reported on on GitHub. A public chat channel is available on Gitter.

Citing

If you use pycalphad in your research, please consider citing the following work:

Otis, R. & Liu, Z.-K., (2017). pycalphad: CALPHAD-based Computational Thermodynamics in Python. Journal of Open Research Software. 5(1), p.1. DOI: http://doi.org/10.5334/jors.140

Acknowledgements

Development has been made possible in part through NASA Space Technology Research Fellowship (NSTRF) grant NNX14AL43H, and is supervised by Prof. Zi-Kui Liu in the Department of Materials Science and Engineering at the Pennsylvania State University. We would also like to acknowledge technical assistance on array computations from Denis Lisov.

pycalphad's People

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.