Travis E. Oliphant wrote:
...
* Thus 1.2 will not break ABI compatibility but will add new API features.
This is really great news (amongst the other good things). Many thanks
for keeping the ABI compatible!
All the best,
Jon
.
___
Hi,
I think this is a great idea but I am curious about what NumPy will be
doing with Python 3. The Python 3 final is scheduled for 1st October
release so is there a policy on handling the migration to Python 3 or
dual support of the 2 and 3 series?
Thanks
Bruce
On Sat, Aug 23, 2008 at 6:39 PM,
Bruce Southey wrote:
I think this is a great idea but I am curious about what NumPy will be
doing with Python 3. The Python 3 final is scheduled for 1st October
release so is there a policy on handling the migration to Python 3 or
dual support of the 2 and 3 series?
As a footnote to this
On Sun, Aug 24, 2008 at 10:58, Bruce Southey [EMAIL PROTECTED] wrote:
Hi,
I think this is a great idea but I am curious about what NumPy will be
doing with Python 3. The Python 3 final is scheduled for 1st October
release so is there a policy on handling the migration to Python 3 or
dual
On Fri, Aug 22, 2008 at 10:26 AM, Stéfan van der Walt [EMAIL PROTECTED] wrote:
Hi all,
This is my personal recollection of the documentation BoF. Feel free to
comment or correct the text below.
Regards
Stéfan
Summary of the Documentation Birds-of-a-Feather Session
On Sat, Aug 23, 2008 at 10:23 PM, Alan McIntyre [EMAIL PROTECTED] wrote:
Actually, it was removed right after the nose framework was working,
but I think a decision was made to keep it around until 1.3 in case
somebody was using it, so I put it back. :) After the 1.2 release it
can just be
On Sun, Aug 24, 2008 at 3:20 PM, Jarrod Millman [EMAIL PROTECTED] wrote:
On Sat, Aug 23, 2008 at 10:23 PM, Alan McIntyre [EMAIL PROTECTED] wrote:
Actually, it was removed right after the nose framework was working,
but I think a decision was made to keep it around until 1.3 in case
somebody
On Sun, Aug 24, 2008 at 15:05, Ondrej Certik [EMAIL PROTECTED] wrote:
Currently sphinx can't handle scipy docstrings, can it? It didn't for
me at least. It'd be nice if whatever format you agre upon, could work
with sphinx's autodoc.
We do some preprocessing, I believe.
Also I am very
Hi all,
Is there a good reason why the weights parameter of np.average() doesn't
broadcast properly? This is with the Ubuntu Hardy x86_64 numpy package,
version 1.0.4.
In [293]: a=arange(100).reshape(10,10)
# Things work fine when weights have the exact same shape as a
In [297]: average(a,
On Sun, Aug 24, 2008 at 8:03 PM, Dan Lenski [EMAIL PROTECTED] wrote:
Hi all,
Is there a good reason why the weights parameter of np.average() doesn't
broadcast properly? This is with the Ubuntu Hardy x86_64 numpy package,
version 1.0.4.
In [293]: a=arange(100).reshape(10,10)
# Things
Hi all,
I need to take the determinants of a large number of 3x3 matrices, in
order to determine for each of N points, in which of M tetrahedral cells
they lie. I arrange the matrices in an ndarray of shape (N,M,5,3,3).
As far as I can tell, Numpy doesn't have a function to do determinants
On Sun, 24 Aug 2008 20:57:43 -0600, Charles R Harris wrote:
On Sun, Aug 24, 2008 at 8:03 PM, Dan Lenski [EMAIL PROTECTED] wrote:
This has been fixed in later versions:
In [2]: a=arange(100).reshape(10,10)
In [3]: average(a, axis=1, weights=ones(10)) Out[3]: array([ 4.5,
14.5, 24.5,
On Mon, 25 Aug 2008 03:48:54 +, Daniel Lenski wrote:
* it's fast enough for 100,000 determinants, but it bogs due to
all the temporary arrays when I try to do 1,000,000 determinants
(=72 MB array)
I've managed to reduce the memory usage significantly by getting the
number of
2008/8/25 Daniel Lenski [EMAIL PROTECTED]:
On Mon, 25 Aug 2008 03:48:54 +, Daniel Lenski wrote:
* it's fast enough for 100,000 determinants, but it bogs due to
all the temporary arrays when I try to do 1,000,000 determinants
(=72 MB array)
I've managed to reduce the memory
On Sun, Aug 24, 2008 at 9:56 PM, Daniel Lenski [EMAIL PROTECTED] wrote:
On Sun, 24 Aug 2008 20:57:43 -0600, Charles R Harris wrote:
On Sun, Aug 24, 2008 at 8:03 PM, Dan Lenski [EMAIL PROTECTED] wrote:
This has been fixed in later versions:
In [2]: a=arange(100).reshape(10,10)
In [3]:
On Sun, Aug 24, 2008 at 9:48 PM, Daniel Lenski [EMAIL PROTECTED] wrote:
Hi all,
I need to take the determinants of a large number of 3x3 matrices, in
order to determine for each of N points, in which of M tetrahedral cells
they lie. I arrange the matrices in an ndarray of shape (N,M,5,3,3).
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