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.
It may be useful to set up a Development Environment before beginning the installation process.
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In general, it is best to use the following order of precedence when installing packages:
Use the operating system package manager, if possible.
- $ pip install package
Download the packages manually, unpack and run:$ python setup.py install
Further information about each setup.py script is available by typing:$ python setup.py --help
Many of the packages listed below have prebuilt installers for different platforms (particularly for Windows). These installers can save considerable time and effort compared to configuring and building from source, although they frequently comprise somewhat older versions of the respective code. Whether building from source or using a prebuilt installer, please read and follow explicitly any instructions given in the respective packages’ README and INSTALLATION files.
Details of the Required Packages and links are given below and in platform-specific instructions, but for the courageous and the impatient, FiPy can be up and running quickly by simply installing the following prerequisite packages on your system:
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
$ 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.
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 2.3 (#1, Sep 13 2003, 00:49:11) ... Type "help", "copyright", "credits" or "license" for more information. >>>
This installer provides a very large number of useful scientific packages for Python, including NumPy, SciPy, Matplotlib, Mayavi, and IPython, as well as a Python interpreter. Installers are available for Windows, Mac OS X and RedHat Linux, Solaris, Ubuntu Linux, and OpenSuSE Linux.
Gmsh is an application that allows the creation of irregular meshes.
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 scipy.weave module.
To use the level set components of FiPy one of the following is required.
Scikit-fmm is a python extension module which implements the fast marching method.
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.
FiPy is tested regularly on Mac OS X, Debian Linux, Ubuntu Linux, and Windows XP. We welcome reports of compatibility with other systems, particularly if any additional steps are necessary to install (see Miscellaneous Build Recipes for user contributed installation tips).
The only elements of FiPy that are likely to be platform-dependent are the Viewers but at least one viewer should work on each platform. All other aspects should function on any platform that has a recent Python installation.
- is based on the Debian package management system. It installs all of its dependencies into /sw.
- is a package manager originally part of OpenDarwin. It installs all of its dependencies into /opt.
- is a recent, lightweight package manager based on Ruby scripts. It installs all of its dependencies into /usr/local (although it can be directed not to).
$ dpkg -i python-fipy_x.y.z-1_all.deb
We encourange you to contribute your own build recipes on the wiki if they are significantly different.
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.
The simplest way to use a Python package without installing it is to work in the base directory of the unpacked package and set the PYTHONPATH environment variable to “.”. In order to work in an directory other than the package’s base directory, the PYTHONPATH environment variable must be set to “~/path/to/package”. This method of working is adequate for one package, but quickly becomes unmanageable with multiple Python packages. In order to manage multiple packages, it is better to choose a standard location other than the default installation path.
If you do not have administrative privileges on your computer, or if for any reason you don’t want to tamper with your existing Python installation, most packages (including FiPy) will allow you to install to an alternative location. Instead of installing these packages with python setup.py install, you would use python setup.py install --home=dir, where dir is the desired installation directory (usually “~” to indicate your home directory). You will then need to append dir/lib/python to your PYTHONPATH environment variable. See the Alternate Installation section of the Python document “Installing Python Modules” [InstallingPythonModules] for more information, such as circumstances in which you should use --prefix instead of --home.
An alternative to setting the PYTHONPATH is to employ one of the utilities that manage packages and their dependencies independently of the system package manager and the system directories. These utilities include Stow, Virtualenv and zc.buildout, amongst others. Here we’ll describe the use of Virtualenv, which we highly recommend.
Virtualenv enables the installation of packages in multiple isolated environments. It organizes the installation of Python packages especially well and also provides a handy location for installing non-Python packages. In addition Virtualenv works seamlessly with the PyPI package manager (pip).
In general, the initial installation of Virtualenv and Virtualenvwrapper requires admin privileges, but thereafter, creating new virtual environments and installing packages into them does not require admin privileges.
All stages of FiPy development are archived in a Git repository at MatForge. You can browse through the code at http://matforge.org/fipy/browser/fipy and, using a Git client, you can download various tagged revisions of FiPy depending on your needs.
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/.
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 git://code.matforge.org/nist/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:
Past releases of FiPy are tagged as
Tagged releases can be found with:
$ git tag --list
Any other branches will not generally be of interest to most users.
For some time now, we have done all significant development work on branches, only merged back to develop when the tests pass successfully. Although we cannot guarantee that develop will never be broken, you can always check our build status page
to find the most recent revision that it is running acceptably.