Metadata-Version: 2.1
Name: scheil
Version: 0.1.4
Summary: Scheil-Gulliver simulations using pycalphad.
Home-page: https://pycalphad.org/
Author: Brandon Bocklund
Author-email: brandonbocklund@gmail.com
License: MIT
Description: ======
        scheil
        ======
        
        A Scheil-Gulliver simulation tool using `pycalphad`_.
        
        .. image:: https://zenodo.org/badge/150358281.svg
           :target: https://zenodo.org/badge/latestdoi/150358281
        
        
        .. _pycalphad: http://pycalphad.org
        
        .. code-block:: python
        
           import matplotlib.pyplot as plt
           from pycalphad import Database, variables as v
           from scheil import simulate_scheil_solidification
        
           # setup the simulation parameters
           dbf = Database('alzn_mey.tdb')
           comps = ['AL', 'ZN', 'VA']
           phases = sorted(dbf.phases.keys())
        
           liquid_phase_name = 'LIQUID'
           initial_composition = {v.X('ZN'): 0.3}
           start_temperature = 850
        
           # perform the simulation
           sol_res = simulate_scheil_solidification(dbf, comps, phases, initial_composition, start_temperature, step_temperature=1.0)
        
           # plot the result
           for phase_name, amounts in sol_res.cum_phase_amounts.items():
               plt.plot(sol_res.temperatures, amounts, label=phase_name)
           plt.plot(sol_res.temperatures, sol_res.fraction_liquid, label='LIQUID')
           plt.ylabel('Phase Fraction')
           plt.xlabel('Temperature (K)')
           plt.title('Al-30Zn Scheil simulation, phase fractions')
           plt.legend(loc='best')
           plt.show()
        
        .. image:: https://raw.githubusercontent.com/pycalphad/scheil/master/docs/_static/Al-30Zn_Scheil_simulation.png
            :align: center
            :alt: Phase fraction evolution during a Scheil simulation of Al-30Zn
        
        Installation
        ============
        
        Anaconda (recommended)
        ----------------------
        
        scheil is suggested to be installed from conda-forge.
        
        .. code-block:: bash
        
            conda install -c pycalphad -c conda-forge --yes scheil
        
        Development versions
        --------------------
        
        To make improvements to scheil, it is suggested to use
        Anaconda to download all of the required dependencies. This
        method installs scheil with Anaconda, removes specifically the
        scheil package, and replaces it with the package from GitHub.
        
        .. code-block:: bash
        
            git clone https://github.com/pycalphad/scheil.git
            cd scheil
            conda install scheil
            conda remove --force scheil
            pip install --no-deps -e .
        
        Upgrading scheil later requires you to run ``git pull`` in this directory.
        
        
        Theory
        ======
        
        Uses classic Scheil-Gulliver theory (see G.H. Gulliver, *J. Inst. Met.* 9 (1913) 120–157 and Scheil, *Zeitschrift Für Met.* 34 (1942) 70–72.) with assumptions of
        
        1. Perfect mixing in the liquid
        2. Local equilibrium between solid and liquid
        3. No diffusion in the solid
        
        
        Getting Help
        ============
        
        For help on installing and using scheil, please join the `pycalphad/pycalphad Gitter room <https://gitter.im/pycalphad/pycalphad>`_.
        
        Bugs and software issues should be reported on `GitHub <https://github.com/pycalphad/scheil/issues>`_.
        
        License
        =======
        
        scheil is MIT licensed. See LICENSE.
        
        
        Citing
        ======
        
        .. image:: https://zenodo.org/badge/150358281.svg
           :target: https://zenodo.org/badge/latestdoi/150358281
        
        
        If you use the ``scheil`` package in your work, please cite the relevant version.
        
        The following DOI, `doi:10.5281/zenodo.3630656 <https://doi.org/10.5281/zenodo.3630656>`_, will link to the latest released version of the code on Zenodo where you can cite the specific version that you haved used. For example, version 0.1.2 can be cited as:
        
        ::
        
           Bocklund, Brandon, Bobbio, Lourdes D., Otis, Richard A., Beese, Allison M., & Liu, Zi-Kui. (2020, January 29). pycalphad-scheil: 0.1.2 (Version 0.1.2). Zenodo. http://doi.org/10.5281/zenodo.3630657
        
        ::
        
           @software{bocklund_brandon_2020_3630657,
             author       = {Bocklund, Brandon and
                             Bobbio, Lourdes D. and
                             Otis, Richard A. and
                             Beese, Allison M. and
                             Liu, Zi-Kui},
             title        = {pycalphad-scheil: 0.1.2},
             month        = jan,
             year         = 2020,
             publisher    = {Zenodo},
             version      = {0.1.2},
             doi          = {10.5281/zenodo.3630657},
             url          = {https://doi.org/10.5281/zenodo.3630657}
           }
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
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 :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Provides-Extra: dev
