Installation

The FiPy finite volume PDE solver relies on several third-party packages. It is best to obtain and install those first before attempting to install FiPy. This document explains how to install FiPy, not how to use it. See Using FiPy for details on how to use FiPy.

Note

It may be useful to set up a Development Environment before beginning the installation process.

Note

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Pre-Installed on Binder

A full FiPy installation is available for basic exploration on Binder. The default notebook gives a rudimentary introduction to FiPy syntax and, like any Jupyter Notebook interface, tab completion will help you explore the package interactively.

Obtaining FiPy

FiPy is freely available for download via Git or as a compressed archive. Please see Git usage for instructions on obtaining FiPy with Git.

Warning

Keep in mind that if you choose to download the compressed archive you will then need to preserve your changes when upgrades to FiPy become available (upgrades via Git will handle this issue automatically).

Installing FiPy

Details of the Required Packages and links are given below, but for the courageous and the impatient, FiPy can be up and running quickly by simply installing the following prerequisite packages on your system:

  • Python
  • NumPy
  • At least one of the Solvers
  • At least one of the Viewers (FiPy’s tests will run without a viewer, but you’ll want one for any practical work)

Other Optional Packages add greatly to FiPy’s capabilities, but are not necessary for an initial installation or to simply run the test suite.

It is not necessary to formally install FiPy, but if you wish to do so and you are confident that all of the requisite packages have been installed properly, you can install it by typing:

$ pip install fipy

or by unpacking the archive and typing:

$ python setup.py install

at the command line in the base FiPy directory. You can also install FiPy in “development mode” by typing:

$ python setup.py develop

which allows the source code to be altered in place and executed without issuing further installation commands.

Alternatively, you may choose not to formally install FiPy and to simply work within the base directory instead. In this case or if you are making a non-standard install (without admin privileges), read about setting up your Development Environment before beginning the installation process.

Required Packages

Python

http://www.python.org/

FiPy is written in the Python language and requires a Python installation to run. Python comes pre-installed on many operating systems, which you can check by opening a terminal and typing python, e.g.:

$ python
Python 2.7.15 | ...
...
Type "help", "copyright", "credits" or "license" for more information.
>>>

If necessary, you can download and install it for your platform <http://www.python.org/download>.

Note

FiPy requires at least version 2.7.x of Python.

Python along with many of FiPy’s required and optional packages is available with one of the following distributions.

NumPy

http://numpy.scipy.org

Obtain and install the NumPy package. FiPy requires at least version 1.0 of NumPy.

Optional Packages

Gmsh

http://www.geuz.org/gmsh/

Gmsh is an application that allows the creation of irregular meshes. When running in parallel, FiPy requires a version of Gmsh >= 2.5 and < 4.0.

SciPy

http://www.scipy.org/

SciPy provides a large collection of functions and tools that can be useful for running and analyzing FiPy simulations. Significantly improved performance has been achieved with the judicious use of C language inlining (see the Command-line Flags and Environment Variables section for more details), via the weave module.

Level Set Packages

To use the level set ([1]) components of FiPy one of the following is required.

Scikit-fmm

http://packages.python.org/scikit-fmm/

Scikit-fmm is a python extension module which implements the fast marching method.

LSMLIB

http://ktchu.serendipityresearch.org/software/lsmlib/index.html

The Level Set Method Library (LSMLIB) provides support for the serial and parallel simulation of implicit surface and curve dynamics in two- and three-dimensions.

Install LSMLIB as per the instructions on the website. Additionally PyLSMLIB is required. To install, follow the instructions on the website, https://github.com/ktchu/LSMLIB/tree/master/pylsmlib#pylsmlib.

Development Environment

It is often preferable to not formally install packages in the system directories. The reasons for this include:

  • developing or altering the package source code,
  • trying out a new package along with its dependencies without violating a working system,
  • dealing with conflicting packages and dependencies,
  • or not having admin privileges.

To avoid tampering with the system Python installation, you can employ one of the utilities that manage packages and their dependencies independently of the system package manager and the system directories. These utilities include conda, Nix, Stow, Virtualenv and Buildout, amongst others. Conda and Nix are only ones of these we have the resources to support.

Our preferred development environment is set up with:

$ conda create --name <MYFIPYENV> --channel conda-forge python=<PYTHONVERSION> fipy
$ source activate <MYFIPYENV>
$ pip install scikit-fmm
$ conda remove --channel conda-forge --force fipy
$ git clone https://github.com/usnistgov/fipy.git
$ cd fipy
$ python setup.py develop

Git usage

All stages of FiPy development are archived in a Git repository at GitHub. You can browse through the code at https://github.com/usnistgov/fipy and, using a Git client, you can download various tagged revisions of FiPy depending on your needs.

Attention

Be sure to follow Installation to obtain all the prerequisites for FiPy.

Git client

A git client application is needed in order to fetch files from our repository. This is provided on many operating systems (try executing which git) but needs to be installed on many others. The sources to build Git, as well as links to various pre-built binaries for different platforms, can be obtained from http://git-scm.com/.

Git branches

In general, most users will not want to download the very latest state of FiPy, as these files are subject to active development and may not behave as desired. Most users will not be interested in particular version numbers either, but instead with the degree of code stability. Different branches are used to indicate different stages of FiPy development. For the most part, we follow a successful Git branching model. You will need to decide on your own risk tolerance when deciding which stage of development to track.

A fresh copy of the FiPy source code can be obtained with:

$ git clone https://github.com/usnistgov/fipy.git

An existing Git checkout of FiPy can be shifted to a different <branch> of development by issuing the command:

$ git checkout <branch>

in the base directory of the working copy. The main branches for FiPy are:

master
designates the (ready to) release state of FiPy. This code is stable and should pass all of the tests (or should be documented that it does not).

Past releases of FiPy are tagged as

x.y.z
Any released version of FiPy will be designated with a fixed tag: The current version of FiPy is 3.4. (Legacy version-x_y_z tags are retained for historical purposes, but won’t be added to.)

Tagged releases can be found with:

$ git tag --list

Any other branches will not generally be of interest to most users.

Note

For some time now, we have done all significant development work on branches, only merged back to master when the tests pass successfully. Although we cannot guarantee that master will never be broken, you can always check our Continuous Integration status to find the most recent revision that it is running acceptably.

Historically, we merged to develop before merging to master. We no longer do this, although for time being, develop is kept synchronized with master. In a future release, we will remove the develop branch altogether.

For those who are interested in learning more about Git, a wide variety of online sources are available, starting with the official Git website. The Pro Git book [2] is particularly instructive.

Nix

Nix Installation

FiPy now has a Nix expression for installing FiPy using Nix. Nix is a powerful package manager for Linux and other Unix systems that makes package management reliable and reproducible. The recipe works on both Linux and Mac OS X.

Getting Started with Nix

There are a number of tutorials on getting started with Nix. The page that I used when getting started is on the Blog of the HPC team of GRICAD,

https://gricad.github.io/calcul/nix/tuto/2017/07/04/nix-tutorial.html

I also made my own notes,

https://github.com/wd15/nixes/blob/master/NIX-NOTES.md

which are a succinct steps that I use when setting up a new system with Nix.

Installing

Once you have a working Nix installation use:

$ nix-shell --pure

in the base FiPy directory to install FiPy with Python 3 by default. Modify the shell.nix file to use another version of Python. nix-shell drops the user into a shell with a working version of FiPy. To test your installation use:

$ nix-shell --pure --command "python setup.py test"

Note

Trilinos is currently not available as part of the Nix FiPy installation.

Additional Packages

To install additional packages available from Nixpkgs include them in the nativeBuildInputs list in shell.nix.

Using Pip

Packages unavailable from Nix can be installed using Pip. In this case, the installation has been set up so that the Nix shell knows about a .local directory in the base FiPy directory used by Pip for installation. So, for example, to install the toolz package from within the Nix shell use:

$ pip install --user toolz

The .local directory will persist after the Nix shell has been closed.

Last updated on Jan 28, 2020. Created using Sphinx 1.8.5.