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Installing matplotlib

matplotlib requires at a minimum python 2.2+, Numeric or numarray and freetype. To get the most out of matplotlib, you will want to build some of the optional GUI and image extensions, discussed below. Matplotlib is known to work on linux, unix, win32 and OS X platforms.

There are two kinds of matplotlib backends: vector based and raster based. Two vector based backends, SVG and PS, produce ASCII text output files *.svg and *.ps; the other vector based backend, EMF, produces binary output files *.emf. The core raster based renderer is the antigrain (agg) backend. This is a high quality 2D library that supports fast antialiasing, alpha blending and much more. If you want to produce PNGs or GUI images that support all of matplotlib's features, you should compile matplotlib with agg support and use one of the GUI agg backends as described below: GTKAgg, WXAgg, TkAgg or FLTKAgg. All of these features are included in the windows installer

Compiling

You probably don't need to compile matplotlib unless you want to or work on an obscure platform. There are binary builds for Windows, OS X and many major linux distributions; see below. If you do want to compile, read on.

You will need to have recent versions of freetype (>= 2.1.7), libpng and zlib installed on your system. If you are using a package manager, also make sure the devel versions of these packages are also installed (eg freetype-devel).

The top of setup.py contains some flags controlling which backends will be built. If you want to use a GUI backend, you may need to install dev headers for the GUI toolkits you want to build with (eg gtk2-dev). You can choose which backends to enable by setting the flags in setup.py, but the 'auto' flags will work in most cases, as matplotlib tries to find a GUI and build the backend acccordingly. If you know you don't want a particular backend or extension, you can set that flag to False.

Most users will want to set BUILD_AGG = 1 and one or more of the GUI backends to True. Exceptions to this are if you know you don't need a GUI (eg a web server) or you only want to produce postscript or SVG for example.

If you have installed prerequisites to nonstandard places and need to inform matplotlib where they are, edit setupext.py an add the base dirs to the basedir dictionary entry for your sys.platform. Eg, if the header to some required library is in /some/path/include/somheader.h, put /some/path in the basedir list for your platform.

matplotlib works with with Numeric or numarray. At compile time, setup.py will look for both packages and compile the appropriate extensions into matplotlib. At runtime, the correct extension code will be chosen based on your numerix setting in matplotlibrc. If you want to be able to use either Numeric or numarray efficiently with matplotlib, it is important that you have *both* present and in your PYTHONPATH when you compile matplotlib.

Note that if you install matplotlib anywhere other than the default location, you will need to set the MATPLOTLIBDATA environment variable to point to the install base dir.

Once you have everything above set to your liking,for just do the usual thing 

      python setup.py build
      python setup.py install
There are many defaults that you can control in matplotlib in the matplotlibrc file. As for installation, the most important of these are the backend and numerix settings. Please set these parameters for your particular build after you install because they are not automatically configured for your particular installation.

Windows

If you don't already have python installed, you may want to consider using the enthought edition of python, which has scipy, Numeric, and wxpython, plus a lot of other goodies, preinstalled - enthought python . With the enthought edition of python + matplotlib installer, the following backends should work out of the box: agg, wx, wxagg, tkagg, ps and svg.

For standard python installations, you will also need to install either Numeric or numarray in addition to the matplotlib installer. matplotlib provides installers for Numeric and numarray users. matplotlib has a numerix setting in the matplotlib rc file (which by default resides in c:\python23\share\matplotlitb\matplotlibrc) and you should make sure this setting corresponds to your preferred array package.

With a standard python + Numeric/numarray + matplotlib, the following backends should work on windows: agg, tkagg, ps, svg. If you want others, eg a wx, wxagg, gtk or gtkagg, you'll need to install the requisite GUI toolkits, as described on backends. This is fairly easy, as both wxpython and pygtk come with windows friendly installers. The latter includes an additional requirement of the GTK runtime.

All of the GUI backends run on windows, but TkAgg is probably the best for interactive use from the standard python shell or ipython. The windows installer (*.exe) on the download page contains all the code you need to get up and running. However, there are many examples that are not included in the windows installer. If you want to try the many demos that come in the matplotlib src distribution, download the zip file and look in the examples subdir.

Important: There are known conflicts with some of the backends with some python IDEs such as pycrust, idle. If you want to use matplotlib from an IDE, please consult backends for compatibility information. You will have the greatest likelihood of success if you run the examples from the command shell or by double clicking on them, rather than from an IDE. If you are interactively generating plots, your best bet is TkAgg from the standard python shell or ipython.

OS X

All of the backends run on OS X. Chris Barker has built a binary package (fink users see below) for matplotlib which is hosted on pythonmac, and works with Agg, Wx and Tk; see the step-by-step instructions kindly provided by Michael Tobis. It does not included the GTK* backends, because pygtk is usually provided through fink and/or darwinport. This version should work on an stock OS-X 10.3.*, and you need Numeric or numarray (available on the same site), and TK or wxPython, if you want to use those back ends.

There are other binary packages to look at which each have different components included. Robery Kern has built an all-in-one installer which includes scipy, Numeric, numarray, matplotlib, ipython, VTK, MayaVi, PIL, the enthought tool suite and much more; see >MacEnthon. Charlie Moad has bundled matplotlib with freetype, png, wx, numarray, numeric and doesn't rely on fink or darwinports; available in the Tools Section. Another bundle is scisoft which packages many scientific packages for python on OS X, including matplotlib, although it is designed for astronomical analysis.

If you want to compile yourself on OS X, make sure you read the compiling instructions above. You will need to install freetype2, libpng and zlib via fink or from src, or from a package manager such as fink or i-Installer. You will also need the base libraries for a given backend. Eg, if you want to run TkAgg, you will need a python with Tkinter; if you want to use WxAgg, install wxpython. See backends for a more comprehensive discussion of the various backend requirements. Edit setup.py to configure the backends you want to build as described above.

Note when running a GUI backend in OSX, you should launch your programs with pythonw rather than python, or you may get nonresponsive GUIs.

Package Managers: (rpms, apt, fink)

RPMS

To build all the backends on a binary linux distro such as redhat, you need to install a number of the devel libs (and whatever dependencies they require), I suggest

Debian

Vittorio Palmisano maintails the debian packages

Fink

fink users should use Jeffrey Whitaker's fink distribution, which supports the GTK, TkAgg, GTKAgg, PS, WX, WXAgg and Agg backends. See matplotlib fink @footer@