[Numpy-discussion] Numerical Python 21.0 released
Paul F Dubois
paul at pfdubois.com
Wed Mar 13 15:02:06 CST 2002
Version 21.0 March 13, 2002
[ #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,
[ none ] if vals was a null-array array() putmask and put would
crash. Fixed with check.
[ #469951 ] n = n1 gives array which shares dimension of n1
This causes bugs if shape of n1 is changed (n didn't
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
[ #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
[ #502186 ] a BUG in RandomArray.normal (introduced by last bug fix
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
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
not doubles. This decision is arbitrary and there are arguments
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
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
If weights are given, result is:
weights must have a's shape or be the 1-d with length the
of a in the given axis. Integer weights are converted to
Not supplying weights is equivalent to supply weights that
If returned, return a tuple: the result and the sum of the
or count of values. The shape of these two results will be
raises ZeroDivisionError if appropriate when result is
(The version in MA does not -- it returns masked values).
More information about the Numpy-discussion