NumPy

Introduction

NumPy is the fundamental package for scientific computing with Python. It contains among other things:

  • 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

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

Usage

Compute Systems Invocation Version(s)
Red Hat Linux (64-bit) 

% /util/bin/python3
Python 3.3.0 (default, Mar 26 2013, 09:56:30) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-52)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from numpy import *
>>> quit()

% /util/bin/python2
Python 2.7.3 (default, Jun  4 2012, 09:52:59) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-52)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from numpy  import *
>>> quit()
python3: 1.9.2 / python2: 1.6.2 (default)

References

  1. http://numpy.scipy.org/
  2. http://www.scipy.org/Tentative_NumPy_Tutorial