.. _INSTALLATION: ============ Installation ============ 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. ------------------ Recommended Method ------------------ .. attention:: There are many ways (described further down) to obtain the software packages necessary to run :term:`FiPy`, but the most expedient way is with the conda_ package manager. * `install Miniconda`_ on your computer * run:: $ conda create --name --channel guyer --channel conda-forge fipy nomkl .. note:: This command creates a self-contained conda_ environment and then downloads and populates the environment with the prerequisites for :term:`FiPy` from the channels guyer_ and conda-forge_ at https://anaconda.org. .. attention:: Note, this does not work on Windows. On that platform, you should be able to do:: conda create --name --channel guyer --channel conda-forge python numpy scipy matplotlib mayavi activate pip install fipy There are presently no conda packages of any solver suite but scipy available for Windows. * enable this new environment with:: $ source activate .. note:: ``$ activate `` on Windows_ * move 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. .. _install Miniconda: http://conda.pydata.org/docs/install/quick.html .. _guyer: https://anaconda.org/guyer .. _conda-forge: https://conda-forge.github.io/ -------------------------- Installing Python Packages -------------------------- In general, it is best to use the following order of precedence when installing packages: * Use the operating system package manager, if possible. * Use the conda_ package management system, which handles both :term:`Python` and non-:term:`Python` packages and provides facilities for self-contained environments with different combinations of :term:`Python` packages, libraries, and applications. * Use the `pip installs python `_ (:term:`pip`) tool to obtain software from the `Python Package Index `_ (:term:`PyPI`) repository:: $ pip install package .. warning:: :term:`pip` takes care of dependencies that are themselves :term:`Python` packages. It does not deal with non-:term:`Python` dependencies. * 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' :file:`README` and :file:`INSTALLATION` files. -------------- Obtaining FiPy -------------- :term:`FiPy` is freely available for download via Git_ or as a compressed archive from . 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). .. _Git: https://github.com/usnistgov/fipy .. _compressed archive: http://www.ctcms.nist.gov/fipy/download/ --------------- Installing FiPy --------------- Details of the `Required Packages`_ and links are given below and in `platform-specific instructions`_, 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. .. _REQUIREDPACKAGES: ----------------- Required Packages ----------------- .. warning: :term:`FiPy` will not run if the following items are not installed. Python ====== http://www.python.org/ :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 2.3 (#1, Sep 13 2003, 00:49:11) ... Type "help", "copyright", "credits" or "license" for more information. >>> If necessary, you can download_ and install it for your platform . .. note:: :term:`FiPy` requires at least version 2.4.x of :term:`Python`. See the specialized instructions if you wish to :ref:`RunUnderPython3`. .. _download: http://www.python.org/download/ :term:`Python` along with many of :term:`FiPy`'s required and optional packages is available with one of the following distributions. conda ----- http://conda.pydata.org This package manager provides a wide array of both :term:`Python`-based and general scientific packages. In addition to the default packages, many other developers (including us) provide "channels" to distribute their own builds of a variety of software. In a given conda_ environment, you can install :term:`FiPy` with:: $ conda install --channel guyer --channel conda-forge fipy .. _EPD: Enthought Python Distribution ----------------------------- http://www.enthought.com/epd This installer provides a very large number of useful scientific packages for :term:`Python`, including :term:`NumPy`, :term:`SciPy`, :term:`Matplotlib`, :term:`Mayavi`, and :term:`IPython`, as well as a :term:`Python` interpreter. Installers are available for Windows_, `Mac OS X`_ and `RedHat Linux`_, Solaris_, `Ubuntu Linux`_, and `OpenSuSE Linux`_. .. attention:: :term:`PySparse` and :term:`FiPy` are not presently included in EPD, so you will need to separately install them manually. .. _PYTHONXY: Python(x,y) ----------- http://python-xy.github.io Another comprehensive :term:`Python` package installer for scientific applications, presently only available for Windows_. .. attention:: :term:`PySparse` and :term:`FiPy` are not presently included in python(x,y), so you will need to separately install them manually. NumPy ===== http://numpy.scipy.org Obtain and install the :term:`NumPy` package. :term:`FiPy` requires at least version 1.0 of NumPy_. .. _OPTIONALPACKAGES: ----------------- Optional Packages ----------------- .. note: The following packages are not required to run :term:`FiPy`, but they can be helpful. Gmsh ==== http://www.geuz.org/gmsh/ :term:`Gmsh` is an application that allows the creation of irregular meshes. SciPy ===== http://www.scipy.org/ :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:`scipy.weave` module. .. note: A handful of test cases use functions from the :term:`SciPy` library and will throw errors if it is missing. ------------------ Level Set Packages ------------------ To use the level set components of :ref:`FiPy` one of the following is required. .. _SCIKITFMM: Scikit-fmm ========== http://packages.python.org/scikit-fmm/ Scikit-fmm_ is a python extension module which implements the fast marching method. .. _Scikit-fmm: http://packages.python.org/scikit-fmm/ .. _LSMLIBDOC: 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. .. _PyLSMLIB: https://github.com/ktchu/LSMLIB/tree/master/pylsmlib#pylsmlib .. _LSMLIB: http://ktchu.serendipityresearch.org/software/lsmlib/index.html ------------------------------ Platform-Specific Instructions ------------------------------ :term:`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 :term:`FiPy` that are likely to be platform-dependent are the :ref:`VIEWERS` but at least one viewer should work on each platform. All other aspects should function on any platform that has a recent :term:`Python` installation. Mac OS X Installation ===================== There is no official package manager for `Mac OS X`_, but there are several third-party package managers that provide many, but not all of :term:`FiPy`'s :ref:`REQUIREDPACKAGES` and :ref:`OPTIONALPACKAGES`. Options include Fink_ is based on the Debian package management system. It installs all of its dependencies into :file:`/sw`. MacPorts_ is a package manager originally part of OpenDarwin. It installs all of its dependencies into :file:`/opt`. Homebrew_ is a recent, lightweight package manager based on Ruby scripts. It installs all of its dependencies into :file:`/usr/local` (although it can be directed not to). In addition, there is an :ref:`EPD` installer for `Mac OS X`_. .. attention:: :term:`PySparse` and :term:`FiPy` are not presently included in any of these package managers or installers, so you will need to separately install them manually. We presently find that the combination of Homebrew_ and :term:`pip` is a pretty straightforward way to get most of :term:`FiPy`'s prerequesites. See the `Miscellaneous Build Recipes`_ for up-to-date directions. .. _Fink: http://www.finkproject.org/ .. _MacPorts: http://www.macports.org/ .. _Homebrew: http://mxcl.github.com/homebrew/ Windows Installation ==================== There is no official package manager for Windows_, but the :ref:`EPD` and :ref:`PYTHONXY` installers provide most of :term:`FiPy`'s prerequisites. .. attention:: :term:`PySparse` and :term:`FiPy` are not presently included in EPD or python(x,y), so you will need to separately install them manually. Ubuntu/Debian Installation ========================== :term:`FiPy` now has a `.deb` for Ubuntu/Debian systems that can be downloaded from . Simply run:: $ VERSION=x.y-z # choose the version you want $ apt-get install gmsh libsuperlu3 python-central python-sparse $ curl -O http://www.ctcms.nist.gov/fipy/download/python-fipy_${VERSION}_all.deb $ dpkg -i python-fipy_${VERSION}_all.deb to install. The `.deb` includes dependencies for all of the :ref:`REQUIREDPACKAGES` and :ref:`OPTIONALPACKAGES`. .. _tested regularly: http://matforge.org/fipy/build .. _Mac OS X: http://www.apple.com/macosx/ .. _Linux: http://www.linux.org/ .. _Debian Linux: http://www.debian.org/ .. _RedHat Linux: http://www.redhat.com/ .. _OpenSUSE Linux: http://www.opensuse.org/ .. _Ubuntu Linux: http://www.ubuntu.com/ .. _Solaris: http://oracle.com/solaris .. _Windows: http://www.microsoft.com/windows/ .. _Windows XP: http://www.microsoft.com/windowsxp/ Miscellaneous Build Recipes =========================== We often post miscellaneous installation instructions on the :term:`FiPy` blog_ and wiki_ pages. The most useful of these include: * `Installing FiPy on Mac OS X using Homebrew`_ * `Building a 64-bit scientific python environment for FiPy from source`_ * `Installing FiPy with pip`_ .. note:: We encourange you to contribute your own build recipes on the wiki_ if they are significantly different. .. _Installing FiPy on Mac OS X using Homebrew: http://matforge.org/fipy/wiki/InstallFiPy/MacOSX/HomeBrew .. _Building a 64-bit scientific python environment for FiPy from source: http://matforge.org/fipy/wiki/InstallFiPy/MacOSX/SnowLeopard .. _Installing FiPy with pip: http://matforge.org/fipy/wiki/InstallFiPy/PipInstallsPython .. _wiki: http://matforge.org/fipy .. _blog: http://matforge.org/fipy/blog .. _ENVIRONMENT: ----------------------- 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. The simplest way to use a :term:`Python` package without installing it is to work in the base directory of the unpacked package and set the :envvar:`PYTHONPATH` environment variable to "``.``". In order to work in an directory other than the package's base directory, the :envvar:`PYTHONPATH` environment variable must be set to ":file:`~/path/to/package`". This method of working is adequate for one package, but quickly becomes unmanageable with multiple :term:`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 :term:`Python` installation, most packages (including :term:`FiPy`) will allow you to install to an alternative location. Instead of installing these packages with ``python setup.py install``, you would use :samp:`python setup.py install --home={dir}`, where :samp:`{dir}` is the desired installation directory (usually "``~``" to indicate your home directory). You will then need to append :file:`{dir}/lib/python` to your :envvar:`PYTHONPATH` environment variable. See the `Alternate Installation`_ section of the :term:`Python` document "`Installing Python Modules`_" :cite:`InstallingPythonModules` for more information, such as circumstances in which you should use :option:`--prefix` instead of :option:`--home`. .. _Alternate Installation: http://docs.python.org/inst/alt-install-windows.html .. _Installing Python Modules: http://docs.python.org/inst/ An alternative to setting the :envvar:`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. .. _Stow: http://savannah.gnu.org/projects/stow/ .. _zc.buildout: http://pypi.python.org/pypi/zc.buildout .. _documentation:GIT: .. include:: documentation/GIT.txt