The :term:`FiPy` finite volume PDE solver relies on several third-party packages. It is best to obtain and install those first before attempting to install :term:`FiPy`. This document explains how to install :term:`FiPy`, not how to use it. See :ref:`USAGE` for details on how to use :term:`FiPy`.
Note
It may be useful to set up a :ref:`ENVIRONMENT` before beginning the installation process.
.. only:: html
.. note::
By selecting the links on this page, you will be leaving NIST
webspace. We have provided these links to other web sites because
they may have information that would be of interest to you. No
inferences should be drawn on account of other sites being
referenced, or not, from this page. There may be other web sites that
are more appropriate for your purpose. NIST does not necessarily
endorse the views expressed, or concur with the facts presented on
these sites. Further, NIST does not endorse any commercial products
that may be mentioned on these sites. Please address comments about
this page to fipy@nist.gov.
A full :term:`FiPy` installation is available for basic exploration on Binder. The default notebook gives a rudimentary introduction to :term:`FiPy` syntax and, like any Jupyter Notebook interface, tab completion will help you explore the package interactively.
Attention!
There are many ways to obtain the software packages necessary to run :term:`FiPy`, but the most expedient way is with the conda package manager. In addition to the scientific :term:`Python` stack, conda also provides virtual environment management. Keeping separate installations is useful e.g. for comparing :term:`Python` 2 and :term:`Python` 3 software stacks, or when the user does not have sufficient privileges to install software system-wide.
In addition to the default packages, many other developers provide "channels" to distribute their own builds of a variety of software. These days, the most useful channel is conda-forge, which provides everything necessary to install :term:`FiPy`.
install Miniconda on your computer
run:
$ conda create --name <MYFIPYENV> --channel conda-forge python=<PYTHONVERSION> fipy
Note
This command creates a self-contained conda environment and then downloads and populates the environment with the prerequisites for :term:`FiPy` from the conda-forge channel at https://anaconda.org.
Attention!
Windows x86_64 is fully supported, but this does not work on Windows x86_32, as conda-forge no longer supports that platform. For Python 2.7.x, you should be able to do:
conda create --name <MYFIPYENV> --channel conda-forge python=2.7 numpy scipy matplotlib pysparse mayavi weave
and for Python 3.x, you should be able to do:
conda create --name <MYFIPYENV> --channel conda-forge python=3.6 numpy scipy matplotlib pysparse
followed, for either, by:
activate <MYFIPYENV> pip install fipy
enable this new environment with:
$ source activate <MYFIPYENV>
Note
$ activate <MYFIPYENV>on Windowsmove on to :ref:`USAGE`.
Note
On Linux and Mac OS X, you should have a pretty complete system to run and visualize :term:`FiPy` simulations. On Windows, there are fewer packages available via conda, particularly amongst the sparse matrix :ref:`SOLVERS`, but the system still should be functional. Significantly, you will need to download and install :term:`Gmsh` manually when using Python 2.7.
Attention!
When installed via conda or :term:`pip`, :term:`FiPy` will not include its :ref:`examples <part:examples>`. These can be obtained by `cloning the repository`_ or downloading a compressed archive.
:term:`FiPy` is freely available for download via Git or as a compressed archive. Please see :ref:`documentation:GIT` for instructions on obtaining :term:`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 :term:`FiPy` become available (upgrades via Git will handle this issue automatically).
Details of the Required Packages and links are given below, but for the courageous and the impatient, :term:`FiPy` can be up and running quickly by simply installing the following prerequisite packages on your system:
- Python
- NumPy
- At least one of the :ref:`SOLVERS`
- At least one of the :ref:`VIEWERS` (:term:`FiPy`'s tests will run without a viewer, but you'll want one for any practical work)
Other :ref:`OPTIONALPACKAGES` add greatly to :term:`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 :term:`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 :term:`FiPy` directory. You can also install :term:`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 :term:`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 :ref:`ENVIRONMENT` before beginning the installation process.
:term:`FiPy` is written in the :term:`Python` language and requires a
:term:`Python` installation to run. :term:`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
:term:`FiPy` requires at least version 2.7.x of :term:`Python`.
:term:`Python` along with many of :term:`FiPy`'s required and optional packages is available with one of the following distributions.
Obtain and install the :term:`NumPy` package. :term:`FiPy` requires at least version 1.0 of NumPy.
:term:`Gmsh` is an application that allows the creation of irregular meshes. When running in parallel, :term:`FiPy` requires a version of :term:`Gmsh` >= 2.5 and < 4.0.
:term:`SciPy` provides a large collection of functions and tools that can be useful for running and analyzing :term:`FiPy` simulations. Significantly improved performance has been achieved with the judicious use of C language inlining (see the :ref:`FlagsAndEnvironmentVariables` section for more details), via the :mod:`weave` module.
To use the level set (:cite:`levelSetBook`) components of :term:`FiPy` one of the following is required.
http://packages.python.org/scikit-fmm/
Scikit-fmm is a python extension module which implements the fast marching method.
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.
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