[Numpy-discussion] [ANN] NumPy 0.9.6 released

Sven Schreiber svetosch at gmx.net
Tue Mar 14 13:20:03 CST 2006


Hi,
are the following issues of the new release known?
(This is on winxp.)

>>> import numpy as n
>>> n.__version__
'0.9.6'
>>> a = n.asmatrix(n.eye(3))
>>> a
matrix([[1, 0, 0],
       [0, 1, 0],
       [0, 0, 1]])
>>> n.linalg.inverse(a)
array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.]])

I was asked to report if functions in linalg still don't honor the
matrix input type; voila.

>>> n.linalg.cholesky(a)
Traceback (most recent call last):
  File "<interactive input>", line 1, in ?
  File "C:\Python24\Lib\site-packages\numpy\linalg\linalg.py", line 135,
in cholesky_decomposition
    return transpose(triu(a,k=0)).copy()
NameError: global name 'triu' is not defined

I think I've seen this error before, was it in 0.9.4? This is a real
show-stopper.

Happy bug-hunting,
sven


Travis Oliphant schrieb:
> This post is to announce the release of NumPy 0.9.6 which fixes some
> important bugs and has several speed improvments.
> 
> NumPy is a multi-dimensional array-package for Python that allows rapid
> high-level array computing with Python.  It is successor to both Numeric
> and Numarray.  More information at http://numeric.scipy.org
> 
> The release notes are attached:
> 
> Best regards,
> 
> NumPy Developers
> 
> 
> 
> 
> ------------------------------------------------------------------------
> 
> 
> 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
> 
> 





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