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
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)
>
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 m
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 t
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.
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
ove
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)
>
> #
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, a
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 i
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
>> s
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
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 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
> dua
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 th
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, T
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
.
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