Metadata-Version: 1.1
Name: pycalphad
Version: 0.1.1.post1
Summary: CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
Home-page: https://github.com/richardotis/pycalphad
Author: Richard Otis
Author-email: richard.otis@outlook.com
License: MIT
Description: pycalphad, a library for the CALculation of PHAse Diagrams
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        **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 on GitHub.
        
        pycalphad is licensed under the MIT License.
        See LICENSE.txt for details.
        
        Required Dependencies:
        Python 2.7+ or 3.3+ (Python 2.6 is not supported)
        Matplotlib, NumPy, SciPy, SymPy, Pandas, PyParsing, TinyDB
        
        Optional Dependencies:
        Numexpr (calculation speed-up for multi-core CPUs)
        
        Installation
        ------------
        For the latest stable release, use ``pip install pycalphad``
        
        Examples
        --------
        IPython notebooks with examples are hosted on NBViewer.
        http://nbviewer.ipython.org/github/richardotis/pycalphad/tree/master/examples/
        
        Documentation
        -------------
        Full documentation is a work in progress. Most routines are documented in
        their docstrings, and example code can be found in the 'Examples' section.
        
        Acknowledgements
        ----------------
        Development has been made possible in part through a NASA Space Technology Research Fellowship (NSTRF) grant.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
