Tools for data analysis and
numerical computation and/or greater
dimensional abstraction than native Python affords is needed, NumPy is
a "standard" by which other tools can be judged.
(Numeric Python) is an
extensive array data processing tools. It contains useful procedures
for numerical computation. It can be used for fast manipulation of
NumPy also supports a Fortran-to-Python interface generator and other
Fortran compiler tools.
(fast Fourier transform)
||The SciPy (scientific
python) website: http://www.scipy.org/
//www.scipy.org/Documentation/ has a comprehensive list of documents.
T.E. 2006. Guide to NumPy. This book
has been released into the public domain after three years of
restricted distribution. http://www.tramy.us/
The SciPy community is quite active and they maintain a good range of
downloads. Make sure you get the right version for your hardware,
Operating System and SoniPy's current Python version.
||OSI-Approved Open Source software
correct version for HW and SW is
scientific routines have been
written using these tools. Over its evolution, NumPy has also been
known as both Numeric and Numarray and references to it as such can be
found both in the documentation and in third-party code. Earlierthis
year (2007) there was some discussion on the Python SIG about reasons
for a Numeric package still being available, however I believe that for
those using it for the first time, NumPy is the correct package. In
fact some of the code examples in the package download still try to
"import numeric". I have yet to find an example which doesn't run if
"numeric" is replaced with "numpy" in the python code.
Do you have other
suggestions for tools in this
category? For example, there there is also a Python interface to Matlab
called PyLab. See details on the matplotlib home page. If you'd like to
contribute your experience, contact us via the FORUM link.