A Dimecres 20 Desembre 2006 07:59, David Cournapeau escrigué:
Could you detail a bit how you did the profiling with oprofile ? I don't
manage to get the same results than you (that is on per application
basis when the application is a python script and not a 'binary' program)
Sure. You need
My question is then: is there any plan to change this ? If not, is
this
for some reasons I don't see, or is this just because of lack of
manpower ?
I raised the possibility of breaking up the files before and Travis
was agreeable to the idea. It is still in the back of my
David Cournapeau wrote:
en I went back to home, I started taking a close look a numpy/core C
sources, with the help of the numpy ebook. The huge source files make it
really difficult for me to follow some things: I was wondering if there
is some rationale behind it, or if this is just a
Francesc Altet wrote:
A Dimecres 20 Desembre 2006 07:59, David Cournapeau escrigué:
Could you detail a bit how you did the profiling with oprofile ? I don't
manage to get the same results than you (that is on per application
basis when the application is a python script and not a 'binary'
Travis Oliphant wrote:
David Cournapeau wrote:
en I went back to home, I started taking a close look a numpy/core C
sources, with the help of the numpy ebook. The huge source files make it
really difficult for me to follow some things: I was wondering if there
is some rationale behind it,
Hi all,
I noticed that the set of ``where()`` functions defined by Numexpr all
have a signature like ``xfxx``, i.e. the first argument is a float and
the return, second and third arguments are of the same type (whatever it
is).
Since the first argument effectively represents a condition,
A Dimecres 20 Desembre 2006 03:36, David Cournapeau escrigué:
Francesc Altet wrote:
A Dimarts 19 Desembre 2006 08:12, David Cournapeau escrigué:
Hi,
Following the discussion on clip and other functions which *may* be
slow in numpy, I would like to know if there is a way to easily
On 12/20/06, Travis Oliphant [EMAIL PROTECTED] wrote:
My question is then: is there any plan to change this ? If not, is
this
for some reasons I don't see, or is this just because of lack of
manpower ?
I raised the possibility of breaking up the files before and Travis
David == David Cournapeau [EMAIL PROTECTED] writes:
David Of this 300 ms spent in Colormap functor, 200 ms are taken
David by the take function: this is the function which I think
David can be speed up considerably.
Sorry I had missed this in the previous conversations. It is
Ivan Vilata i Balaguer wrote:
Hi all,
I noticed that the set of ``where()`` functions defined by Numexpr all
have a signature like ``xfxx``, i.e. the first argument is a float and
the return, second and third arguments are of the same type (whatever it
is).
Since the first argument
I added a ticket for Francesc's enhancement:
http://projects.scipy.org/scipy/numpy/ticket/403
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Tim Hochberg (el 2006-12-20 a les 09:20:01 -0700) va dir::
Actually, this is on purpose. Numpy.where (and most other switching
constructs in Python) will switch on almost anything. In particular, any
number that is nonzero is considered True, zero is considered False. By
changing the
Francesc Altet wrote:
seems to tell us that memmove/memcopy are not called at all, but
instead the DOUBLE_copyswap function. This is in fact an apparence,
because if we look at the code of DOUBLE_copyswap (found in
arraytypes.inc.src):
@[EMAIL PROTECTED] (void *dst, void *src, int swap, void
A Dimecres 20 Desembre 2006 19:32, Andrew Straw escrigué:
I added a ticket for Francesc's enhancement:
http://projects.scipy.org/scipy/numpy/ticket/403
Thanks Andrew, but I realized that my patch is not safe for dealing
with unaligned arrays (Sun machines would segfault). After thinking
several
Ivan Vilata i Balaguer wrote:
Tim Hochberg (el 2006-12-20 a les 09:20:01 -0700) va dir::
Actually, this is on purpose. Numpy.where (and most other switching
constructs in Python) will switch on almost anything. In particular, any
number that is nonzero is considered True, zero is
On 12/20/06, Francesc Altet [EMAIL PROTECTED] wrote:
A Dimecres 20 Desembre 2006 03:36, David Cournapeau escrigué:
Francesc Altet wrote:
A Dimarts 19 Desembre 2006 08:12, David Cournapeau escrigué:
Hi,
snip
@[EMAIL PROTECTED] (void *dst, void *src, int swap, void *arr)
{
Hello all,
Is there a way to get probability values for the various families of
distributions in numpy? I.e. ala R:
pnorm(1.96, mean = 0 , sd = 1)
[1] 0.9750021
# for the normal
pt(1.65, df=100)
[1] 0.9489597
# for student t
Any suggestions would be greatly
If you want the n largest item i would recommend quicksort but at each
partition you only recurse into the side of the pivot that has the
values you care about. This is easy to determine because you know
how many items are on either side of the pivot and you know that you
want the nth item.
On Wednesday 20 December 2006 18:02, Tom Denniston wrote:
If you want the n largest item i would recommend quicksort
...
I don't know of a way to do this in numpy. I think it would require
adding a cfunction to numpy. Perhaps an argnth function?
Does anyone else know of an existing
Pierre GM wrote:
On Wednesday 20 December 2006 18:02, Tom Denniston wrote:
If you want the n largest item i would recommend quicksort
...
I don't know of a way to do this in numpy. I think it would require
adding a cfunction to numpy. Perhaps an argnth function?
Does anyone else know of
Hi!
I have problem with this function call under FC6 X86_64 for my own
numpy extension
printf(\n %d %d %d, PyArray_DIM(imgi,0),PyArray_DIM(imgi,
1),PyArray_DIM(imgi,2))
it gave me
166 256 256
if I tried:
int *dim;
dim = PyArray_DIMS(imgi)
printf(\n %d %d %d, dim[0], dim[1], dim[2]);
Gennan Chen wrote:
Hi!
I have problem with this function call under FC6 X86_64 for my own
numpy extension
printf(\n %d %d %d,
PyArray_DIM(imgi,0),PyArray_DIM(imgi,1),PyArray_DIM(imgi,2))
it gave me
166 256 256
if I tried:
int *dim;
dim = PyArray_DIMS(imgi)
printf(\n %d %d %d,
On Wed, 20 Dec 2006, Robert Kern apparently wrote:
We have a full complement of PDFs, CDFs, etc. in scipy.
This is my most missed functionality in NumPy.
(For now I feel cannot ask students to install SciPy.)
Although it is a slippery slope, and I definitely do not
want NumPy to slide down
zhang yunfeng wrote:
Hi, I'm newbie to Numpy.
When reading tutorials at
http://www.scipy.org/Tentative_NumPy_Tutorial
http://www.scipy.org/Tentative_NumPy_Tutorial, I found a snippet about
addition of two arrays with different shape, Does it make sense? If
array shapes are not same, why
On Dec 20, 2006, at 8:41 PM, Alan G Isaac wrote:
On Wed, 20 Dec 2006, Robert Kern apparently wrote:
We have a full complement of PDFs, CDFs, etc. in scipy.
This is my most missed functionality in NumPy.
(For now I feel cannot ask students to install SciPy.)
If they're already installing
On 12/20/06, Gennan Chen [EMAIL PROTECTED] wrote:
Hi!
I have problem with this function call under FC6 X86_64 for my own numpy
extension
printf(\n %d %d %d,
PyArray_DIM(imgi,0),PyArray_DIM(imgi,1),PyArray_DIM(imgi,2))
it gave me
166 256 256
if I tried:
int *dim;
dim =
Here is the definition of that call from ndarrayobject.h
#define PyArray_DIMS(obj) (((PyArrayObject *)(obj))-dimensions)
I believe the memory has been allocated. It just return a pointer.
Gen
On Dec 20, 2006, at 7:43 PM, Sebastian Haase wrote:
On 12/20/06, Gennan Chen [EMAIL PROTECTED]
On 20/12/06, Alan G Isaac [EMAIL PROTECTED] wrote:
On Wed, 20 Dec 2006, Robert Kern apparently wrote:
We have a full complement of PDFs, CDFs, etc. in scipy.
This is my most missed functionality in NumPy.
(For now I feel cannot ask students to install SciPy.)
Although it is a slippery
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