On Fri, Feb 21, 2014 at 11:09 PM, Charles R Harris
wrote:
>
>
>
> On Fri, Feb 21, 2014 at 10:35 PM, Ondřej Čertík
> wrote:
>>
>> On Mon, Feb 17, 2014 at 11:40 AM, Charles R Harris
>> wrote:
>> >
>> >
>> >
>> > On Mon, Feb 17, 2014 at 11:32 AM, Julian Taylor
>> > wrote:
>> >>
>> >> On 17.02.2014
On Fri, Feb 21, 2014 at 10:35 PM, Ondřej Čertík wrote:
> On Mon, Feb 17, 2014 at 11:40 AM, Charles R Harris
> wrote:
> >
> >
> >
> > On Mon, Feb 17, 2014 at 11:32 AM, Julian Taylor
> > wrote:
> >>
> >> On 17.02.2014 15:18, Francesc Alted wrote:
> >> > On 2/17/14, 1:08 AM, josef.p...@gmail.com wr
On Mon, Feb 17, 2014 at 11:40 AM, Charles R Harris
wrote:
>
>
>
> On Mon, Feb 17, 2014 at 11:32 AM, Julian Taylor
> wrote:
>>
>> On 17.02.2014 15:18, Francesc Alted wrote:
>> > On 2/17/14, 1:08 AM, josef.p...@gmail.com wrote:
>> >> On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
>> >>> On 16 Febru
On Mon, Feb 17, 2014 at 11:32 AM, Julian Taylor <
jtaylor.deb...@googlemail.com> wrote:
> On 17.02.2014 15:18, Francesc Alted wrote:
> > On 2/17/14, 1:08 AM, josef.p...@gmail.com wrote:
> >> On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
> >>> On 16 February 2014 23:43, wrote:
> What's the f
On 17.02.2014 15:18, Francesc Alted wrote:
> On 2/17/14, 1:08 AM, josef.p...@gmail.com wrote:
>> On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
>>> On 16 February 2014 23:43, wrote:
What's the fastest argsort for a 1d array with around 28 Million
elements, roughly uniformly distributed,
On Mon, Feb 17, 2014 at 9:18 AM, Francesc Alted wrote:
> On 2/17/14, 1:08 AM, josef.p...@gmail.com wrote:
>> On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
>>> On 16 February 2014 23:43, wrote:
What's the fastest argsort for a 1d array with around 28 Million
elements, roughly uniformly
On 2/17/14, 1:08 AM, josef.p...@gmail.com wrote:
> On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
>> On 16 February 2014 23:43, wrote:
>>> What's the fastest argsort for a 1d array with around 28 Million
>>> elements, roughly uniformly distributed, random order?
>>
>> On numpy latest version:
>>
>
On Sun, Feb 16, 2014 at 4:12 PM, Daπid wrote:
> On 16 February 2014 23:43, wrote:
>
>> What's the fastest argsort for a 1d array with around 28 Million
>> elements, roughly uniformly distributed, random order?
>>
>
> On numpy latest version:
>
> for kind in ['quicksort', 'mergesort', 'heapsort']
>> the
>> >> argsort is continuously making completely random memory accesses.
>> >>
>> >>
>> >> -Original Message-
>> >> From: josef.p...@gmail.com
>> >> Sent: Sunday, February 16, 2014 11:43 PM
>> >>
sage-
> >> From: josef.p...@gmail.com
> >> Sent: Sunday, February 16, 2014 11:43 PM
> >> To: Discussion of Numerical Python
> >> Subject: [Numpy-discussion] argsort speed
> >>
> >> currently using numpy 1.6.1
> >>
> >> What&#
On Sun, Feb 16, 2014 at 6:12 PM, Daπid wrote:
> On 16 February 2014 23:43, wrote:
>>
>> What's the fastest argsort for a 1d array with around 28 Million
>> elements, roughly uniformly distributed, random order?
>
>
> On numpy latest version:
>
> for kind in ['quicksort', 'mergesort', 'heapsort']:
nplace sort gains locality as it is being sorted, whereas the
>> argsort is continuously making completely random memory accesses.
>>
>>
>> -Original Message-
>> From: josef.p...@gmail.com
>> Sent: Sunday, February 16, 2014 11:43 PM
>> To: Discussion of
uously making completely random memory accesses.
>
>
> -Original Message-
> From: josef.p...@gmail.com
> Sent: Sunday, February 16, 2014 11:43 PM
> To: Discussion of Numerical Python
> Subject: [Numpy-discussion] argsort speed
>
> currently using numpy 1.6.1
>
&
On 17 February 2014 00:12, Daπid wrote:
> I seem unable to find the code for ndarray.sort, so I can't check. I have
> tried to grep it tring all possible combinations of "def ndarray",
> "self.sort", etc. Where is it?
Nevermind, it is in core/src/multiarray/methods.c
__
On 16 February 2014 23:43, wrote:
> What's the fastest argsort for a 1d array with around 28 Million
> elements, roughly uniformly distributed, random order?
>
On numpy latest version:
for kind in ['quicksort', 'mergesort', 'heapsort']:
print kind
%timeit np.sort(data, kind=kind)
%t
...@gmail.com
Sent: Sunday, February 16, 2014 11:43 PM
To: Discussion of Numerical Python
Subject: [Numpy-discussion] argsort speed
currently using numpy 1.6.1
What's the fastest argsort for a 1d array with around 28 Million
elements, roughly uniformly distributed, random order?
Is there a r
currently using numpy 1.6.1
What's the fastest argsort for a 1d array with around 28 Million
elements, roughly uniformly distributed, random order?
Is there a reason that np.argsort is almost 3 times slower than np.sort?
I'm doing semi-systematic timing for a stats(models) algorithm.
Josef
On Wed, Jan 16, 2013 at 9:30 AM, Mads Ipsen wrote:
> Hi,
>
> Thanks everybody for all the answers that make perfect sense when axis=0.
>
> Now suppose I want to sort the array in such a way that each row is sorted
> individually. Then I suppose I should do this:
>
> from numpy import *
>
>
> v = a
Hi,
Thanks everybody for all the answers that make perfect sense when axis=0.
Now suppose I want to sort the array in such a way that each row is
sorted individually. Then I suppose I should do this:
from numpy import *
v = array([[4,3],
[1,12],
[23,7],
[11,6
Hi,
On Tue, Jan 15, 2013 at 1:50 PM, Mads Ipsen wrote:
> Hi,
>
> I simply can't understand this. I'm trying to use argsort to produce
> indices that can be used to sort an array:
>
> from numpy import *
>
> indices = array([[4,3],[1,12],[23,7],[11,6],[8,9]])
> args = argsort(indices, axis
On Tue, Jan 15, 2013 at 3:44 PM, Charles R Harris
wrote:
> Fancy indexing is a funny creature and not easy to understand in more than
> one dimension. What is happening is that each index is replaced by the
> corresponding row of a and the result is of shape (5,2,2). To do what you
> want to do:
>
On Tue, Jan 15, 2013 at 4:50 AM, Mads Ipsen wrote:
> Hi,
>
> I simply can't understand this. I'm trying to use argsort to produce
> indices that can be used to sort an array:
>
> from numpy import *
>
> indices = array([[4,3],[1,12],[23,7],[11,6],[8,9]])
> args = argsort(indices, axis=0)
>
Hi,
I simply can't understand this. I'm trying to use argsort to produce
indices that can be used to sort an array:
from numpy import *
indices = array([[4,3],[1,12],[23,7],[11,6],[8,9]])
args = argsort(indices, axis=0)
print indices[args]
gives:
[[[ 1 12]
[ 4 3]]
[[ 4 3]
[1
On Thu, Feb 5, 2009 at 17:06, Ryan May wrote:
> Hi,
>
> Ok, what am I missing here:
>
> x = np.array([[4,2],[5,3]])
> x[x.argsort(1)]
>
> array([[[5, 3],
>[4, 2]],
>
> [[5, 3],
>[4, 2]]])
>
> I was expecting:
>
> array([[2,4],[3,5]])
>
> Certainly not a 3D array. What am I d
Hi,
Ok, what am I missing here:
x = np.array([[4,2],[5,3]])
x[x.argsort(1)]
array([[[5, 3],
[4, 2]],
[[5, 3],
[4, 2]]])
I was expecting:
array([[2,4],[3,5]])
Certainly not a 3D array. What am I doing wrong?
Ryan
--
Ryan May
Graduate Research Assistant
School of Met
On Fri, 05 Sep 2008 07:02:38 -0700, SimonPalmer wrote:
> another newb question I suspect, but is there a way to instruct argsort
> to sort in descending order or should I just sort and reverse?
Just sort and subtract to get the reverse order. I can think of two
reasonable ways to do it with no
On Fri, Sep 5, 2008 at 8:02 AM, SimonPalmer <[EMAIL PROTECTED]> wrote:
> another newb question I suspect, but is there a way to instruct
> argsort to sort in descending order or should I just sort and reverse?
You'll just have to reverse the indices.
Chuck
__
another newb question I suspect, but is there a way to instruct
argsort to sort in descending order or should I just sort and reverse?
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
* Robin <[EMAIL PROTECTED]> [2008-01-29 19:23:11 +]:
> On Jan 29, 2008 7:16 PM, Lou Pecora <[EMAIL PROTECTED]> wrote:
> > Hmmm... Interesting. I am using Python 2.4.4. It
> > would be nice to have other Mac people with same/other
> > Python and numpy versions try the argsort "bug" code.
>
>
On Jan 29, 2008 7:16 PM, Lou Pecora <[EMAIL PROTECTED]> wrote:
> Hmmm... Interesting. I am using Python 2.4.4. It
> would be nice to have other Mac people with same/other
> Python and numpy versions try the argsort "bug" code.
I don't see any memory leak with the test code.
Mac OS X 10.5.1
Pytho
Hmmm... Interesting. I am using Python 2.4.4. It
would be nice to have other Mac people with same/other
Python and numpy versions try the argsort "bug" code.
-- Lou Pecora
--- Francesc Altet <[EMAIL PROTECTED]> wrote:
> A Tuesday 29 January 2008, Lou Pecora escrigué:
> > This still occurs in
A Tuesday 29 January 2008, Lou Pecora escrigué:
> This still occurs in numpy 1.0.3.1 so must have been
> fixed between that and your 1.0.4-5 version.
It works here and I'm using NumPy 1.0.3, Python 2.5.1 on a Ubuntu 7.10 /
Pentium4 machine.
> By the way the memory problem crashes my Intel Mac
>
This still occurs in numpy 1.0.3.1 so must have been
fixed between that and your 1.0.4-5 version.
By the way the memory problem crashes my Intel Mac
Book Pro (system 10.4.11) with the gray screen and
black dialog box telling me to restart my computer. A
very UN-unix like and UN-Mac like way of
On Tue, Jan 29, 2008 at 02:58:15PM +0100, Oriol Vendrell wrote:
> Hi all,
>
> I've noticed something that looks like an odd behaviour in array.argsort().
>
>
> # test1 -
> from numpy import array
> while True:
> a=array([8.0,7.0,6.0,5.0,4.0,2.0])
> i=a.argsort()
> # -
Hi all,
I've noticed something that looks like an odd behaviour in array.argsort().
# test1 -
from numpy import array
while True:
a=array([8.0,7.0,6.0,5.0,4.0,2.0])
i=a.argsort()
# ---
# test2 -
from numpy import array
a=ar
On 5/14/07, Zachary Pincus <[EMAIL PROTECTED]> wrote:
>> I've got a few questions that came up as I tried to calculate various
>> statistics about an image time-series. For example, I have an array
>> of shape (t,x,y) representing t frames of a time-lapse of resolution
>> (x,y).
>>
>> Now, say I
>> I've got a few questions that came up as I tried to calculate various
>> statistics about an image time-series. For example, I have an array
>> of shape (t,x,y) representing t frames of a time-lapse of resolution
>> (x,y).
>>
>> Now, say I want to both argsort and sort this time-series, pixel-
>
On 5/13/07, Zachary Pincus <[EMAIL PROTECTED]> wrote:
Hello all,
I've got a few questions that came up as I tried to calculate various
statistics about an image time-series. For example, I have an array
of shape (t,x,y) representing t frames of a time-lapse of resolution
(x,y).
Now, say I want
Hello all,
I've got a few questions that came up as I tried to calculate various
statistics about an image time-series. For example, I have an array
of shape (t,x,y) representing t frames of a time-lapse of resolution
(x,y).
Now, say I want to both argsort and sort this time-series, pixel-
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