We are pleased to announce the release of FiPy 3.3. http://www.ctcms.nist.gov/fipy
This release brings support for Python 2 and Python 3 from the same source, without any 2to3 translation. Thanks to @pya and @woodscn for getting things started. This transition secures FiPy for the scheduled [drop of support for Python 2.7 on January 1, 2020](https://www.python.org/dev/peps/pep-0373/#update). Be aware that performance suffers substantially under Py3k, as neither Pysparse (fast serial) nor PyTrilinos (parallel) is available for Py3k. As a result, our next priority will be to add support for petsc4py solvers. Note that, with this release, we are dropping the `develop` branch, adopting more of a [GitHub flow](https://guides.github.com/introduction/flow/) development model. If you track our repository on GitHub, please switch to `master`. As a convenience, we will endeavor to keep `develop` up-to-date with `master` in the short term, but we will be deleting the `develop` branch in the not-too-distant future. Pulls ----- - Automate spell check (#657) - Fix gmsh on windows (#648) - Fix sphinx documentation (#647) - Migrate to Py3k (#645) - `gmshMesh.py` compatibility with Gmsh > 3.0.6 (#644) Thanks to @xfong. Fixes ----- - #655: When Python 2 and 3 are installed, Mayavi wont work. Thanks to @Hendrik410. - #646: Deprecate develop branch - #643: Automate release process - #601: `contents.rst` and `manual.rst` are a recursive mess - #597: Use GitHub link for the compressed archive in documentation - #557: `faceGradAverage` is stupid - #552: documentation integration - #458: Documentation wrong for precedence of `Lx` and `dx` for `NonUniformGrids` - #457: Special methods are not included in Sphinx documentation - #432: Python 3 issues - #340: Don't upload packages to PyPi, just add the master url ======================================================================== FiPy is an object oriented, partial differential equation (PDE) solver, written in Python, based on a standard finite volume (FV) approach. The framework has been developed in the Metallurgy Division and Center for Theoretical and Computational Materials Science (CTCMS), in the Material Measurement Laboratory (MML) at the National Institute of Standards and Technology (NIST). The solution of coupled sets of PDEs is ubiquitous to the numerical simulation of science problems. Numerous PDE solvers exist, using a variety of languages and numerical approaches. Many are proprietary, expensive and difficult to customize. As a result, scientists spend considerable resources repeatedly developing limited tools for specific problems. Our approach, combining the FV method and Python, provides a tool that is extensible, powerful and freely available. A significant advantage to Python is the existing suite of tools for array calculations, sparse matrices and data rendering. The FiPy framework includes terms for transient diffusion, convection and standard sources, enabling the solution of arbitrary combinations of coupled elliptic, hyperbolic and parabolic PDEs. Currently implemented models include phase field treatments of polycrystalline, dendritic, and electrochemical phase transformations as well as a level set treatment of the electrodeposition process. _______________________________________________ fipy mailing list fipy@nist.gov http://www.ctcms.nist.gov/fipy [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ]
