
NumPy 0.9.6 is a bug-fix and optimization release with a
    few new features: 


  New features (and changes):

  - bigndarray removed and support for Python2.5 ssize_t added giving
     full support in Python2.5 to very-large arrays on 64-bit systems.

  - Strides can be set more arbitrarily from Python (and checking is done 
     to make sure memory won't be violated). 

  - __array_finalize__ is now called for every array sub-class creation.

  - kron and repmat functions added

  - .round() method added for arrays
  
  - rint, square, reciprocal, and ones_like ufuncs added.

  - keyword arguments now possible for methods taking a single 'axis'
     argument

  - Swig and Pyrex examples added in doc/swig and doc/pyrex

  - NumPy builds out of the box for cygwin

  - Different unit testing naming schemes are now supported.

  - memusage in numpy.distutils works for NT platforms

  - numpy.lib.math functions now take vectors

  - Most functions in oldnumeric now return intput class where possible


  Speed ups:
 
  - x**n for integer n signficantly improved

  - array(<python scalar>) much faster

  - .fill() method is much faster


  Other fixes:

  - Output arrays to ufuncs works better. 

  - Several ma (Masked Array) fixes.

  - umath code generation improved

  - many fixes to optimized dot function (fixes bugs in 
	matrix-sub-class multiply)

  - scalartype fixes

  - improvements to poly1d

  - f2py fixed to handle character arrays in common blocks

  - Scalar arithmetic improved to handle mixed-mode operation.

  - Make sure Python intYY types correspond exactly with C PyArray_INTYY


