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The Numeric Extensions to Python (NumPy) add powerful multi-dimensional array objects to the wonderful general purpose programming language Python. These new objects give Python the number crunching power of numeric languages like Matlab and IDL while maintaining all of the advantages of the general-purpose programming language Python.
These extensions add two new object types to Python, and then include a number of extensions that take advantage of these two new objects:
- Multidimensional Array Objects * Efficient arrays of homogeneous machine types (floats, longs, complex doubles) * Arbitrary number of dimensions * Sophisticated structural operations - Universal Function Objects * Support mathematical functions on all Python objects * Very efficient for array objects
Numerical Python Versions after 20.0 require Python 2.0 or later. To take advantage of the "rich comparisons" (i.e., to be able to compare arrays and get back a boolean result) you need Python 2.1. Web site: http://numpy.sourceforge.net Project page: http://sourceforge.net/projects/numpy Discussion group: email@example.com ===> Silicon Grap more»
python-numeric (24.2-9) unstable; urgency=low * Remove the extra dependency from the last NMU; a direct dependency is not required. * Update debian/watch. Closes: #449617. * Rebuild using current python-central package. Closes: #473606. * Update package description mentioning the package is deprecated. Closes: 477553. -- Matthias Klose <firstname.lastname@example.org> Mon, 23 Jun 2008 20:42:5 more»
Version 24.2 Support array interface in objecttype function. Handle case where __array__ does not return a Numeric array. Fix __array_struct__ for 64-bit. [cookedm] Add ability to build Python eggs with python setup.py bdist_egg. - setuptools is *not* required; if not found, the old way is still used. - defau more»
This package was debianized by Matthias Klose email@example.com on Mon, 9 Mar 1998 11:00:24 +0100. I more»