NumPy 0.9.8 has been released. It can be downloaded from
http://numeric.scipy.org
The release notes are attached.
Best regards,
-Travis Oliphant
NumPy 0.9.8 is a bug-fix and optimization release with a
few new features. The C-API was changed so that extensions compiled
against NumPy 0.9.6 will need re-compilation to avoid errors.
The C-API should be stabilizing. The next release will be 1.0 which
will come out in a series of release-candidates during Summer 2006.
There were many users and developers who contributed to the fixes for
this release. They deserve much praise and thanks. For details see
the Trac pages where bugs are reported and fixed.
http://projects.scipy.org/scipy/numpy/
New features (and changes):
* string and unicode comparisons now work on array objects
without having to go through the chararray.
* string and unicode scalars selected from an array have
NULL bytes removed so that comparisons work correctly.
* changed fortran= keywords to order= keywords
The order= keyword accepts 'C', 'FORTRAN', or None
as arguments. The order= keyword also accepts True for
'FORTRAN' and False for 'C' for backwards compatibility.
* The error-lookup for math functions was changed to work on a
per-thread basis instead of a local, module (global), bulitin
name-space basis.
* PyArray_CHAR now works as does the 'c' code for specifying a
1-element string. This improves compatibility with Numeric
when PyArray_CHAR and typecode='c' are used.
Now array("mystr", 'c') works the same as it did in Numeric.
* where(condition) and condition.nonzero() always return
tuples. nonzero(condition) is for backwards compatibility
with Numeric and only works with 1-d arrays.
* overflow checking is nolonger done an array multiplication for
consistency with addition and subtraction.
* math module added to numpy namespace as it used to be in the Numeric
name-space. numpy.emath has extended math functions
* matrices return correctly shaped matrices for reduction-like methods
and scalars for reduction over the entire array (i.e. A.argmax()
returns a scalar.)
* numpy should install now with easy_install from setuptools
* masked array improvements including more methods added.
Speed ups:
* scalarmath module added to speed up math on array scalars (the
objects returned when indexing into arrays).
* a.flags is now a builtin object
* copying code was sped up significantly for well-behaved cases.
* indexing a 1-d array by an integer has been sped-up.
Other fixes:
* fixed problem with bad arguments to .transpose() not being caught.
* fix problem with .argmax(axis) and .argmin(axis) for multi-dimensional
arrays.
* cov and corrcoef fixed to work correctly and not
in-place modify the input.
* several fixes for numpy.distutils were applied
* errors involving reshape and fortran-order arrays fixed
* fixed several errors in optimized blasdot function
* several segfaults fixed
* record array pickling and byteswapped pickling fixed.
* fix sorting on byteswapped arrays
* fancy-indexing no longer alters the index array.
* divbyzero should work now on optimizing compilers.
* vectorize segfaults should be fixed.
* b.shape = <tuple> now fails as it should
for non-contiguous arrays
* fixed errors apperaing in use of flattened and byteswapped
arrays
* several memory leaks closed and other Valgrind-discovered
errors fixed.
* fixed attribute access for record arrays and their sub-classes
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