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  #
  #   See COPYING file distributed along with the PyMVPA package for the
  #   copyright and license terms.
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**********************************
 PDF version of the PyMVPA Manual
**********************************

The PDF version of the manual is available for download_.

.. _download: PyMVPA-Manual.pdf


.. toctree::

   intro
   overview
   datasets
   classifiers
   measures
   featsel
   scenarios
   misc
   glossary
   matlab
   faq
   examples
   legal
   changelog

.. <gjd> high-level comments

.. incorporate a standalone section on file formats and
   interoperability. clearly, Nifti is one, but i'm still
   unclear about what else PyMVPA can/can't import

.. for us (Matlab MVPA), the tutorial_easy quickstart was an enormous
   success. i strongly recommend having some similar quick,
   hands-on guide. feel free to borrow/steal/adapt anything from
   tutorial_easy for your needs if you like it (though you should probably
   check with jim before re-distributing the sample data).

.. you dive straight into the nitty-gritty of the different
   kinds of datasets, attributes and other data structures. having a high-level
   summary of the most important points might make it easier for a new
   reader to get the big
   picture, and makes it more likely that people who don't
   like documentation will at least read the most important
   points

.. use more examples

.. i know that i would personally benefit from a 'PyMVPA for
   Matlab MVPA users' section. perhaps this is something that
   per and i will end up hammering out over the next few months

.. i'm a big fan of Howtos... it sounds like you're creating
   a collection of snippets, but maybe consider embedding them
   into the manual with a little description of what they're
   doing, alternatives etc.

.. maybe a glossary might help. i'm starting to see how
   you're using 'samples' vs 'datasets' etc. but it would be
   nice to have a quick reference

.. this is a really, really good start for a 0.1 release. good job!
