Read Me

DO YOU REALLY WANT TO DO THIS?

    This directory contains the code to build the matplotlib web page,
    which can be found at http://matplotlib.sourceforge.net.  In other
    words, unless you want to edit the web page docs, there is not much
    need to build them yourself since they are available online.

    If all you want is the pydoc documentation, this is online at

      http://matplotlib.sourceforge.net/matlab_commands.html  and
      http://matplotlib.sourceforge.net/classdocs.html

    If you really want to build the html docs yourself, you will need to
    have all backends working.


OK, YOU'RE STILL HERE?  

    The html for the matplotlib web site is generated using yaptu, a
    simple (71 lines of code!) but powerful templating engine

      http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52305

    All of the web pages are templates, eg, index.html.template in which I
    combine arbitrary python data structures with yaptu templating.

    process_docs.py is a script to generate the pydocs for the class
       library, and munge the generated output into a format suitable for
       inclusion into the web page.  

    convert.py is the workhorse that runs all the templates and generates
      the html with the appropriate headers and footers.

    screenshots/makeshots.py is a script that creates all the screenshots
      that can be generated dyamically (some cannot be because, for
      example, they are screenshots of figure windows with the navigation
      toolbar).  Caution, the mri and pcolor screenshots currently take a
      long time to generate because the are high resolution.  Best run on
      a fast computer!


BUILDING THE DOCS IN A NUTSHELL

    So in a nutshell, here is what you need to do to generate the docs.

      0) Build the matplotlib html class documentation with Make htmldocs

      1) Make sure the CVS matplotlib tree is in your PYTHONPATH and 
         > cd htdocs

      2) > python process_docs.py

      3) > python convert.py

      4) > cd screenshots

      5) > python makeshots.py  # this could take a while for pcolor and  mri

      6) Point your browser at file:///your/dev/matplotlb/htdocs/index.html

    You can also run

      # in the matplotlib dev root (doesn't rebuild screenshots)
      > make htmldocs