[Numpy-discussion] [Announce] Numerical Python 22.0
Paul F Dubois
paul at pfdubois.com
Wed Aug 28 11:19:04 CDT 2002
Numerical Python release 22.0 is at Sourceforge. A Windows installer and
source zip are also available.
Version 22.0
a. Changed multiarraymodule functions to accept keywords where
documentation implies
it through the use of optional variables.
Specifically in multiarray: zeros, take, transpose, repeat,
set_string_function,
cross_correlate.
in ufuncobject: reduce and accumulate now take
keyword arguments
for the optional axis argument.
b. Added support for unsigned shorts 'w' and unsigned ints 'u'
-- Travis Oliphant with help from Darren Hart and F. Oliver
Gathmann.
Increased max permissible iterations in SVD for supplied lapack. --
Dubois
Recoded RandomArray.randint to try to see if we can work around bug
on some platforms. -- Dubois
Version 21.3 June 8, 2002
Fixed bugs:
[ #557927 ] fixed matrix slice assignment
[ #552922 ] added check for correct datatype in .astype() method.
Created new API PyArray_ValidType to handle this check
here as well as in multiarraymodule.c
[ #551808 ] fixed segfault with unicode array (Travis O.)
[ #559511 ] MLab.std now works for axis != 0 (Travis O.)
[ #542979 ] sum returns exception tuple
[ #528328 ] true division operators used to return single precision
on division of
integers and longs --- now defaults to double
precision (but only on int and
long division --- still single-precision for
ubyte, short, and byte division.
[ none ] arange(start, end, step) slightly different near end
points than
start + arange(0, N)*step where N is the length.
[ none ] a = zeros(2,'D'); a[0] = array(0.0+0.6j) would not work.
(Assigning a
rank-0 array did not work for CFLOAT_setitem or
CDOUBLE_setitem.
[ 530688 ] Python crash when transposing array (Walter Moreira)
Version 21.0 March 13, 2002
Fixed bugs:
[ #482603 ] Memory leak in MA/Numeric/Python
Reported by Reggie Dugard. Turned out to be
*two* memory leaks in one case in a routine in Numeric,
array_objectype. (Dubois)
[ none ] if vals was a null-array array([]) putmask and put would
crash. Fixed with check.
[ #469951 ] n = n1[0] gives array which shares dimension of n1
array.
This causes bugs if shape of n1 is changed (n didn't
used
to have it's own dimensions array (Travis Oliphant)
[ #514588 ] MLab.cov(x,x) != MLab.cov(x) (Travis Oliphant)
[ #518702 ] segfault when invalid typecode for asarray (Travis
Oliphant)
[ #497530 ] MA __getitem__ prevents 0 len arrays (Reggie Duggard)
[ #508363 ] outerproduct of noncontiguous arrays (Martin Wiechert)
[ #513010 ] memory leak in comparisons (Byran Nollett)
[ #512223 ] Character typecode not defined (Jochen Kupper)
[ #500784 ] MLab.py diff error (anonymous, fixed by Dubois)
[ #503741 ] accuracy of MLab.std(x) (Katsunori Waragai)
[ #507568 ] overlapping copy a[2:5] = a[3:6]
Change uses of memcpy to memmove which allows overlaps.
[ numpy-Patches-499722 ] size of buffer created from array is bad
(Michel Sanner).
[ #502186 ] a BUG in RandomArray.normal (introduced by last bug fix
in 20.3)
(Katsunori Waragai).
Fixed errors for Mac (Jack Jensen).
Make rpm's properly, better Windows installers. (Gerard Vermeulen)
Added files setup.cfg; setup calculates rpm_install.sh to use
current Python.
New setup.py, eliminate setup_all.py. Use os.path.join everywhere.
Revision in b6
added file README.RPM, further improvements.
Implement true division operations for Python 2.2. (Bruce Sherwood)
Note: true division of all integer types results in an array of
floats,
not doubles. This decision is arbitrary and there are arguments
either way,
so users of this new feature should be aware that the decision may
change in the future.
New functions in Numeric; they work on any sequence a that can be
converted to a
Numeric array. Similar change to average in MA. (Dubois)
def rank (a):
"Get the rank of a (the number of dimensions, not a matrix
rank)"
def shape (a):
"Get the shape of a"
def size (a, axis=None):
"Get the number of elements in a, or along a certain axis."
def average (a, axis=0, weights=None, returned = 0):
"""average(a, axis=0, weights=None)
Computes average along indicated axis.
If axis is None, average over the entire array.
Inputs can be integer or floating types; result is type
Float.
If weights are given, result is:
sum(a*weights)/(sum(weights))
weights must have a's shape or be the 1-d with length the
size
of a in the given axis. Integer weights are converted to
Float.
Not supplying weights is equivalent to supply weights that
are
all 1.
If returned, return a tuple: the result and the sum of the
weights
or count of values. The shape of these two results will be
the same.
raises ZeroDivisionError if appropriate when result is
scalar.
(The version in MA does not -- it returns masked values).
"""
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