matplotlib Code

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@header@ 
<h2>Installing matplotlib</h2>

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.<p>

There are two kinds of matplotlib backends: vector based and raster
based.  The vector based backends, SVG and PS, produce ASCII text
output files *.svg and *.ps.  The core raster based renderer is the <a
href=http://antigrain.com>antigrain</a> (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, FLTKAgg or QtAgg.  All of these features are
included in the windows installer<p>

<h2><a name=compiling>Compiling</a></h2>

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).<p>

The top of setup.py contains some flags controlling which backends
will be built.  If you want to use a GUI backend, you will obviously
need the GUI toolkit and python extension installed on your system,
and for some GUIs you'll need the devel packages as well.  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
<tt>False</tt>.<p>

As discussed above, most users will want to set <tt>BUILD_AGG = 1</tt>
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 vector graphics.<p>

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

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.<p>

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

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

<pre>
      python setup.py build
      python setup.py install
</pre>
    
<h2><a name=windows>Windows</a></h2>

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 - <a
href=http://www.enthought.com/python> enthought python</a> .  With the
enthought edition of python + matplotlib installer, the following
backends should work out of the box: agg, wx, wxagg, tkagg, ps and
svg.<p>

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

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 <a
href=backends.html>backends</a>.  This is fairly easy, as both
wxpython and pygtk come with windows friendly installers.  The latter
includes an additional requirement of the GTK runtime.<p>

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 <a
href=examples>examples</a> 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.<p>

<i>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 <a
href=backends.html>backends</a> 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.</i>

<h3><a name=osx>OS X</a></h3>

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 <a
href=http://pythonmac.org/packages>pythonmac</a>, and works with Agg,
Wx and Tk.  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.<p>



There are a couple of other binary packages to look at.  Charlie Moad
has bundled matplotlib for OS X which includes freetype, png, wx,
numarray, numeric and doesn't rely on fink or darwinports; available
in the <a href=http://sda.iu.edu/projects.html>Tools Section</a>.
Another bundle is <a
href=http://www.stecf.org/macosxscisoft>scisoft</a> which packages
many scientific packages for python on OS X, including matplotlib,
although it is designed for astronomical analysis.</p>

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 <a href=http://ii2.sourceforge.net>i-Installer</a>.  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 <a href=backends.html>backends</a>
for a more comprehensive discussion of the various backend
requirements.  Edit setup.py to configure the backends you want to
build as described above.<p>

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

<h2>Package Managers: (rpms, apt, fink)</h2>

<h3><a name=rpms>RPMS</a></h3>

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
<ul> 
	
  <li>matplotlib core: zlib, zlib-devel, libpng, libpng-devel,
      freetype, freetype-devel, freetype-utils</li>

  <li>gtk/gtkagg backend: gtk2-devel, gtk+-devel, pygtk2, glib-devel,
      pygtk2-devel, gnome-libs-devel, pygtk2-libglade</li>

  <li>tk backend: tcl, tk, tkinter</li>

  <li>wx/wxagg backends - the wxpython rpms from <a
  href=http://wxpython.org</a>wxpython</a></li>

</ul>

<h3><a name=debian>Debian</a></h3>

Vittorio Palmisano <redclay@email.it> maintails the debian
packages at http://mentors.debian.net


<ul>
    <li> add these lines to your /etc/apt/sources.list: 
<pre>
  deb http://anakonda.altervista.org/debian packages/
  deb-src http://anakonda.altervista.org/debian sources/
</pre> 
    </li>
   
      <li> then run:
<pre>   
  # apt-get update
  # apt-get install python-matplotlib python-matplotlib-doc
</pre>         
  </li>
</ul>

<h3><a name=gentoo>Gentoo</a></h3>

The gentoo packagers do a good job of keeping current matplotlib
builds <a href=http://www.gentoo-portage.com/dev-python/matplotlib>here</a>

<h3><a name=freebsd>FreeBSD</a></h3>

The FreeBSD matplotlib repository is <a
href=http://www.freshports.org/math/py-matplotlib/>here</a>.


<h3><a name=fink>Fink</a></h3>

fink users should use Jeffrey Whitaker's fink distribution, which
supports the GTK, TkAgg, GTKAgg, PS, WX, WXAgg and Agg backends. See
<a
href=http://fink.sourceforge.net/pdb/package.php/matplotlib-py23>matplotlib
fink</a>
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