Peach


Peach is a pure Python module for computational intelligence, including, but not
limited to, neural networks, fuzzy logic, genetic algorithms, stochastic
optimization, nonlinear optimization, simulated annealing, particle swarm and
other techniques. The main goal of this project is to build a pure Python module
that can be easily understood and improved. Although it is not the primary
concern, care was taken to make the code as efficient as possible. But be aware
that there might be some optimizations that could be done, so if you find that a
piece of code is running to slow, let us know (if you have a solution, this is
even better).

The other main goal of the project is to allow people to study and understand
the code. The development began with the most basic techniques in the listed
topics, so that a person who is starting his studies in the field can see and --
hopefully -- understand the code. Some very basic scripts with the aims of
serving as tutorials are included with the code. Some more elaborated programs
are also included, so the full power of the module can be appreciated.

This module uses some software that must be installed to be used:

* The Python programming language, available at http://www.python.org/ -- if you
  need to deal with scientific programming, you will like it a lot, so I suggest
  you to try it even if using this module is not of your interest.

* The NumPy numeric processing package for the language, available at
  http://www.scipy.org/NumPy -- it is not, unfortunatelly, made available with
  the standard distribution of the language. But there are some Python
  distributions that embed it by default. Anyway, installing it is not difficult
  and should pose no problem.

* The bitarray module, available at http://pypi.python.org/pypi/bitarray/0.3.5
  -- its installation is a little more difficult than the other packages, but it
  can be done very easily. Please, follow the guidelines in the module's page.

* Although it is not required, it is strongly suggested that the Matplotlib
  module is used. It is used to plot 2D graphics, and their data model is
  compatible with the one used in Peach (the NumPy array), so you can easily
  plot your results when needed. Some of the scripts in the tutorial section
  make use of it, if available.

There is no special script or method to install this module, but if you follow
these steps, no problem should arise:

* First, make sure that the above listed modules are installed and working with
  your Python distribution. In general, all you need to do is download the
  installation file and run it; or, if you are using Linux, install the packages
  using your package manager;

* Unpack the Peach file in a folder. Within this folder, look for the `peach`
  folder. Copy this folder to the site-packages folder on you Python
  installation. You can test if these procedures worked by going to the Python
  command line interface and typing:

  >>> import peach

Please, read the documentation on the module for more information. For those who
are starting now, it is recomended that your study begins with the tutorials in
the tutorial folder. This folder is divided in subfolders, each one dedicated to
one of the techniques implemented in Peach. Feel free to modify them at your
taste.

If you build a demo program that you think is worth being used as a tutorial,
please, write us and send the source. We will be delighted to see what you have
done with Peach.

This module is published under the LGPL license, please see the COPYING file. We
apologize in advance for any bug that this module might have, and if you can
describe us what happened and how to reproduce the error, we will do our best to
fix it. Also, any suggestions are more than welcome.