.. _introduction:

============
Introduction
============

.. contents::

History
*******

PySAL grew out of a collaborative effort between Luc Anselin's group
previously located at the University of Illinois, Champaign-Urbana, and Serge
Rey who was at San Diego State University.  It was born out of a recognition that
the respective projects at the two institutions,  `PySpace (now GeoDaSpace) 
<http://geodacenter.asu.edu/pyspaceimg>`_  and `STARS
<http://regionalanalysislab.org/index.php/Main/STARS>`_ - Space Time Analysis
of Regional Systems, could benefit from a shared analytical core, since
this would limit code duplication and free up additional developer time to
focus on enhancements of the respective applications.

This recognition also came at a time when Python was starting to make major
inroads in geographic information systems as represented by projects such as
the `Python Cartographic Library <http://zmapserver.sourceforge.net/PCL/>`_,
`Shapely <http://trac.gispython.org/lab/wiki/Shapely>`_ and ESRI's adoption of
Python as a scripting language, among others. At the same time there was a
dearth of Python modules for spatial statistics, spatial econometrics, location
modeling and other areas of spatial analysis, and the role for PySAL was then
expanded beyond its support of STARS and GeoDaSpace to provide a library of core
spatial analytical functions that could support the next generation of spatial
analysis applications.

In 2008 the home for PySAL moved to the `GeoDa Center for Geospatial Analysis
and Computation <http://geodacenter.asu.edu/>`_ at Arizona State University.

Scope
*****

It is important to underscore what PySAL is, and is not, designed to do. First
and foremost, PySAL is a **library** in the fullest sense of the word.
Developers looking for a suite of spatial analytical methods that they can
incorporate into application development should feel at home using PySAL.
Spatial analysts who may be carrying out research projects requiring customized
scripting, extensive simulation analysis, or those seeking to advance the state
of the art in spatial analysis should also find PySAL to be a useful
foundation for their work.

End users looking for a user friendly graphical user interface for spatial
analysis should not turn to PySAL directly. Instead, we would direct them to
projects like STARS and the GeoDaX suite of software products which wrap PySAL
functionality in GUIs.  At the same time, we expect that with developments such
as the Python based plug-in architectures for `QGIS
<http://www.qgis.org/wiki/Python_Plugin_Repositories>`_, `GRASS
<http://grass.osgeo.org/wiki/GRASS_and_Python>`_, and the toolbox extensions
for `ArcGIS
<http://training.esri.com/gateway/index.cfm?fa=catalog.courseDetail&CourseID=50089911_9.X>`_,
that end user access to PySAL functionality will be widening in the near
future.


Research Papers and Presentations
*********************************
    * Rey, Sergio J. (2012) `PySAL: A Python Library for Exploratory Spatial Data Analysis and Geocomputation <http://www.youtube.com/watch?v=FN1nH4Fkd_Y>`_ (Movie) SciPy 2012.
    * Rey, Sergio J. and Luc Anselin. (2010) `PySAL: A Python Library of
      Spatial Analytical Methods. <http://books.google.com/books?hl=en&lr=&id=c0EP_6eYsjAC&oi=fnd&pg=PA174&dq=pysal&ots=JzI8vk8D4T&sig=J6FEAnbG5Wzw2nn2-0nfj4B6c3Q#v=onepage&q=pysal&f=false>`_ In M. Fischer and A. Getis (eds.) Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications. Springer, Berlin. 
    * Rey, Sergio J. and Luc Anselin. (2009) `PySAL: A Python Library for Spatial Analysis and Geocomputation <http://www.archive.org/details/scipy09_day2_10-Serge_Rey>`_. (Movie) Python for Scientific Computing. Caltech, Pasadena, CA August 2009.
    * Rey, Sergio J. (2009). `Show Me the Code: Spatial Analysis and Open Source <http://www.springerlink.com/content/91u84l471h043282/>`_. *Journal of Geographical Systems* 11: 191-2007.
    * Rey, S.J., Anselin, L., & M. Hwang. (2008). `Dynamic Manipulation of Spatial Weights Using Web Services. <http://geodacenter.asu.edu/node/174>`_ GeoDa Center Working Paper 2008-12.
