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This is a very modest release which primarily consists of bug fixes to
numarray's implementation of the numpy array interface.
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changes:
-fix a NumArray Operator Optimization Bug
-Better NumPy dtype Support.
-more bugfixes
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changes:
-better interoperability with py-Numeric and scipy (uses "scipy newcore")
-bugfixes
-speed improvements
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changes:
-many bugfixes
-code cleanup, speedup
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Support Python 2.4
1.1.1 changes:
numarray-1.1.1 is a bugfix release to numarray-1.1. Notable bugs
fixed include memory leaks in matrixmultiply and comparison ufuncs.
1.1 changes:
I. ENHANCEMENTS
CharArray eval() sped up
Document memmap.py (memory mapping)
Unsigned int type support limited
Add kroenecker product
II. BUGS FIXED / CLOSED
max.reduce of byteswapped array
numeric compatibility byteoffset
matrixmultiply (a,b) leaves b transposed
random_array.randint exceeds boundaries
buffer not aligned on 8 byte boundary (Windows-98 broken)
Object Array repr for >1000 elements
Invalid sequences errors
Segfault in array element deletion
Incorrect handling of overlapping assignments in Numarray
Weirdness with 'new' method
searchsorted bug and fix
randint bug fix patch
a.is_c_array() mixed int/bool results
argsort of string arrays
III. CAUTIONS
1. This release is binary incompatible with numarray-1.0. Writers of
C-extensions which directly reference the byteoffset field of the
PyArrayObject should be aware that the data pointer is now the sum of
byteoffset and the buffer base pointer. All C extensions which use
the numarray C-API must be recompiled. This incompatibility was an
unfortunate consequence of the fix for "numeric compatibility
byteoffset".
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important changes:
- Ports of Numeric functions
A bunch of Numeric functions were ported to numarray in the new
libnumeric module. To get these import from numarray.numeric. Most
notable among these are put, putmask, take, argmin, and argmax. Also
added were sort, argsort, concatenate, repeat and resize. These are
independent ports/implementations in C done for the purpose of best
Numeric compatibility and small array performance. The numarray
versions, which handle additional cases, still exist and are the
default in numarray proper.
- Faster matrix multiply
The setup for numarray's matrix multiply was moved into C-code. This
makes it faster for small matrices.
- bug fixes
For a complete list of changes see:
http://sourceforge.net/project/shownotes.php?release_id=250453
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py-Numeric
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