The fundamental package needed for scientific computing with Python is
called NumPy. This package contains:
* a powerful N-dimensional array object
* sophisticated (broadcasting) functions
* basic linear algebra functions
* basic Fourier transforms
* sophisticated random number capabilities
* tools for integrating Fortran code.
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
quickly integrate with a wide-variety of databases.
Maintained by: Aleksandar B. Samardzic
Keywords: Python,scientific computing,array,matrix, mathematical functions,Fortran wrapper,academic,math
ChangeLog: numpy
Homepage:
http://numpy.scipy.org/
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