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Python array manipulation and computational library

Numarray provides array manipulation and computational capabilities similar to those found in IDL, Matlab, or Octave. Using numarray, it is possible to write many efficient numerical data processing applications directly in Python without using any C, C++ or Fortran code (as well as doing such analysis interactively within Python or PyRAF). For algorithms that are not well suited for efficient computation using array facilities it is possible to write C functions (and eventually Fortran) that can read and write numarray arrays that can be called from Python.
Package version:1.5.2


See the Doc directory for more numarray documentation, including
CHANGES for this release and installation instructions.

See for the source forge website
for Numeric and Numarray featuring CVS, Bug Tracking, Downloads, etc.
If you make a submission to a tracker, make sure that it has a
"Numarray" prefix, i.e. "Numarray Bugs" and not just "Bugs".
Unadorned tra


These are the LaTeX-sources for the numarray manual.

In order to process these files you need the python CVS sources and
the whole toolchain to generate python docs.

In this local directory create the following links:

  icons -> <python cvs>/dist/src/Doc/html/icons
  mkhowto -> <python cvs>/dist/src/Doc/tools/mkhowto
  mkinfo -> <python cvs>/dist/src/Doc/tools/mkinfo

Calling mkhowto creates th


* content
  - write all chapters :)
  - create module index
  - extend glossary (standing request:)
  - update index (standing request:)

* layout
  - Put part's outline on same page as the "Part X".


See __LICENSE__ in Lib/ for the numarray license or view it
at the Python prompt as follo


\section*{Legal Notice}

Please see file LICENSE.txt in the source distribu

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