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numpy

A fast multidimensional array facility for Python

NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type.

There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation. Also included in this package is a version of f2py that works properly with NumPy.

Homepage:
Package version:1.4.1
Architecture:x86_64
Distribution:CentOS
Filename:numpy-1.4.1-9.el6.x86_64.rpm

/usr/share/doc/numpy-1.4.1/README.txt

NumPy is the fundamental package needed for scientific computing with Python. 
This package contains:

    * a powerful N-dimensional array object
    * sophisticated (broadcasting) functions
    * tools for integrating C/C++ and Fortran code
    * useful linear algebra, Fourier transform, and random number capabilities. 

It derives from the old Numeric code base and can be used as a replacement 
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/usr/share/doc/numpy-1.4.1/docs-f2py/README.txt

.. -*- rest -*-

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 F2PY: Fortran to Python interface generator
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

:Author: Pearu Peterson <pearu@cens.ioc.ee>
:License: NumPy License
:Web-site: http://cens.ioc.ee/projects/f2py2e/
:Discussions to: `f2py-users mailing list`_
:Documentation: `User's Guide`__, FAQ__
:Platforms: All
:Date: $Date: 2005/01/30 18:54
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/usr/share/doc/numpy-1.4.1/docs-f2py/FAQ.txt

======================================================================
               F2PY Frequently Asked Questions
======================================================================

.. contents::

General information
===================

Q: How to get started?
----------------------

First, install__ F2PY. Then check that F2PY installation works
properly (see below__). Try out a `simple e
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/usr/share/doc/numpy-1.4.1/THANKS.txt

Travis Oliphant for the NumPy core, the NumPy guide, various
    bug-fixes and code contributions.
P
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/usr/share/doc/numpy-1.4.1/docs-f2py/THANKS.txt

=================
 Acknowledgments
=================

F2PY__ is an open source Python package and c
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/usr/share/doc/numpy-1.4.1/LICENSE.txt

Copyright (c) 2005-2009, NumPy Developers.
All rights reserved.

Redistribution and use in source an
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