[SciPy-User] ANN: FiPy 3.0

Jonathan Guyer guyer@nist....
Thu Aug 16 12:42:41 CDT 2012

We are pleased to announce the release of FiPy 3.0.


The bump in major version number reflects more on the substantial increase in capabilities and ease of use than it does on a break in compatibility with FiPy 2.x. Few, if any, changes to your existing scripts should be necessary.

The significant changes since version 2.1 are:

• Coupled and vector equations are now supported.
• A more robust mechanism for specifying boundary conditions is now used.
• Most Meshes can be partitioned by meshing with Gmsh.
• PyAMG and SciPy have been added to the solvers.
• FiPy is capable of running under Python 3.
• “getter” and “setter” methods have been pervasively changed to Python properties.
• The test suite now runs much faster.
• Tests can now be run on a full install using fipy.test().

This release addresses 66 tickets.


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.

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