[Numpy-discussion] [ANN] NumPy 0.9.6 released
Sven Schreiber
svetosch at gmx.net
Tue Mar 14 13:20:03 EST 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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