pypmc
=====

.. include:: abstract.txt

How to use this documentation
=============================

If you don't know yet whether ``pypmc`` is the right tool for your
needs, you should first read through the overview. There, we introduce
the basic algorithms implemented by ``pypmc``. If you want to give
``pypmc`` a try, just follow the installation instructions. The user
guide then explains adaptive importance sampling. In the examples
section, we show how to use the algorithms on simple problems. Take
them as a starting point to work on your problem. Finally, look
through the reference guide if you need help on a specific function or
class.

.. toctree::
   :numbered:
   :maxdepth: 3

   introduction
   installation
   user_guide
   examples
   references
   api


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`