ScientificPython is a collection of Python modules that are useful for
scientific applications. Most of them need the Numerical Python
extension (aka NumPy), which is available from SourceForge; see
http://numpy.sourceforge.net for details.

This is release 2.4 of ScientificPython. The major new feature since
the last stable release, 2.2, is the high-level parallelization module
Scientific.BSP. Please read the BSP tutorial (in Doc/PDF) before using
this, the reference manual by itself is probably not sufficient to
understand the functioning of this module. Another new module is
Scientific.Signals.Models, which implements autoregressive modeling of
time series.

Note that in order to use the module Scientific.BSP with more than one
processor, you must compile either the BSPlib or the MPI interface.
See README.BSPlib and README.MPI for installation details. The BSPlib
interface is probably more efficient (I haven't done extensive tests
yet), and allows the use of the BSP toolset, on the other hand MPI is
more widely available and might thus already be installed on your
machine. For serious use, you should probably install both and make
comparisons for your own applications. Application programs do not
have to be modified to switch between MPI and BSPlib, only the method
to run the program on a multiprocessor machine must be adapted.

If you find bugs, please tell me, and if you improve something, please
send me the modified version. I don't promise anything, but since I
use these modules a lot for my own work, I have an interest in keeping
them bug-free and usable.

For updates, check

  http://dirac.cnrs-orleans.fr/ScientificPython/

from time to time.


Konrad Hinsen
Centre de Biophysique Moleculaire (CNRS)
Rue Charles Sadron
45071 Orleans Cedex 2
France

E-Mail: hinsen@cnrs-orleans.fr

---------------------------------------------------------------------------

Installation:
-------------

Required: Python 1.5 or higher, the BSP module requires Python 2.1 or
higher. Most modules also require Numerical Python. If you want to use
the netCDF interface module, you also need the netCDF library, version
3.0 or higher.

Installation is as simple as

    python setup.py build
    python setup.py install

(the second command requires root priviledges on many installations).
This will build the netCDF module if it can find a netCDF installation
in either /usr/local or in /usr. If you you have installed netCDF
somewhere else, you must edit the file setup.py and replace "None" in
line 10 by the name of the base directory in quotes.

---------------------------------------------------------------------------

Manual:
-------

The reference manual is provided in HTML and PDF formats:

HTML: Doc/HTML/Scientific.html 

PDF:  Doc/PDF/manual.pdf

The DocBook XML source is also provided in Doc/XML. The BSP tutorial
is in Doc/PDF/BSP_Tutorial.pdf.


Examples:
---------

The directory Examples provides a few simple example applications,
including a C extension module that uses the netCDF C-API.
