Andrew Friedley wrote:
> David Cournapeau wrote:
>
>> Francesc Alted wrote:
>>
>>> No, that seems good enough. But maybe you can present results in
>>> cycles/item.
>>> This is a relatively common unit and has the advantage that it does not
>>> depend
>>> on the frequency of your cor
On May 27, 2009, at 7:29 PM, Stéfan van der Walt wrote:
> Hi Fernando
>
> 2009/5/28 Fernando Perez :
>> Well, since dtypes allow for nesting full arrays in this fashion,
>> where I can say that the 'block' field can have (2,3) shape, it seems
>> like it would be nice to be able to express this ne
On Thu, May 28, 2009 at 10:14 AM, Nicolas Rougier
wrote:
>
> Obviously, the last computation is not a dot product, but I got no
> warning at all. Is that the expected behavior ?
>
Sparse matrices make no attempt to work with numpy functions like
dot(), so I'm not sure what is happening there.
>
Sorry, I still don't understand how to use FortranFile ...
The fortran code
program writeArray
implicit none
integer,parameter:: nx=2,ny=5
real(4),dimension(nx,ny):: ux,uy,p
integer :: i,j
do i = 1,nx
do j = 1,ny
ux(i,j) = 100. + j+(i-1.)*10.
uy(i,j) = 200. + j+
A Wednesday 27 May 2009 17:31:20 Nicolas Rougier escrigué:
> Hi,
>
> I've written a very simple benchmark on recarrays:
>
> import numpy, time
>
> Z = numpy.zeros((100,100), dtype=numpy.float64)
> Z_fast = numpy.zeros((100,100), dtype=[('x',numpy.float64),
> ('y',numpy.int32)])
> Z_slow = numpy.zer
On 2009-05-28 12:11 , David Froger wrote:
> Thank you very much :-)
Things should be cleared up now on the wiki as well. Peace,
-Neil
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Thank you very much :-)
2009/5/28 Neil Martinsen-Burrell
> On 2009-05-28 09:32 , David Froger wrote:
>
>> Hy Neil Martinsen-Burrell,
>>
>> I'm trying the FortranFile class,
>> http://www.scipy.org/Cookbook/FortranIO/FortranFile
>>
>> It looks like there are some bug in the last revision (7):
>>
On 2009-05-28 09:32 , David Froger wrote:
Hy Neil Martinsen-Burrell,
I'm trying the FortranFile class,
http://www.scipy.org/Cookbook/FortranIO/FortranFile
It looks like there are some bug in the last revision (7):
* There are errors cause by lines 60,61,63 in
* There are indentation e
hi,
sorry, i'm new to the list, and if this is a frequently asked question, please
point me in the right direction.
say, for some reason i've got two numpy structure arrays
that both contain the same fields with the same types
but in a different order, is there a simple way to convert
one to the
Hy Neil Martinsen-Burrell,
I'm trying the FortranFile class,
http://www.scipy.org/Cookbook/FortranIO/FortranFile
It looks like there are some bug in the last revision (7):
* There are errors cause by lines 60,61,63 in
* There are indentation errors on lines 97 and 113.
___
I'd be interested to see the benchmark ;)
On Thu, May 28, 2009 at 4:14 PM, Nicolas Rougier
wrote:
>
> Hi,
>
> I'm now testing dot product and using the following:
>
> import numpy as np, scipy.sparse as sp
>
> A = np.matrix(np.zeros((5,10)))
> B = np.zeros((10,1))
> print (A*B).shape
> print np
I just created the account.
Nicolas
On Thu, 2009-05-28 at 11:21 +0200, Stéfan van der Walt wrote:
> Hi Nicolas
>
> 2009/5/27 Nicolas Rougier :
> > No, I don't have permission to edit.
>
> Thanks for helping out with the docs! Please create an account on
> docs.scipy.org and give me a shout
Hi,
I'm now testing dot product and using the following:
import numpy as np, scipy.sparse as sp
A = np.matrix(np.zeros((5,10)))
B = np.zeros((10,1))
print (A*B).shape
print np.dot(A,B).shape
A = sp.csr_matrix(np.zeros((5,10)))
B = sp.csr_matrix((10,1))
print (A*B).shape
print np.dot(A,B).shape
David Cournapeau wrote:
> Francesc Alted wrote:
>> No, that seems good enough. But maybe you can present results in
>> cycles/item.
>> This is a relatively common unit and has the advantage that it does not
>> depend
>> on the frequency of your cores.
Sure, cycles is fine, but I'll argue th
Hi Nicolas
2009/5/27 Nicolas Rougier :
> No, I don't have permission to edit.
Thanks for helping out with the docs! Please create an account on
docs.scipy.org and give me a shout when you're done.
Cheers
Stéfan
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> I don't know anything about PIL and its implementation, but I would not
> be surprised if the cost is mostly accessing items which are not
> contiguous in memory and bounds checking ( to check where you are in the
> subimage). Conditional inside loops often kills performances, and the
> actual co
cp wrote:
>>> The image I tested initially is 2000x2000 RGB tif ~11mb in size.
>>>
> I continued testing, with the initial PIL approach
> and 3 alternative numpy scripts:
>
> #Script 1 - indexing
> for i in range(10):
> imarr[:,:,0].mean()
> imarr[:,:,1].mean()
> imarr[:,:,2].mea
>> The image I tested initially is 2000x2000 RGB tif ~11mb in size.
I continued testing, with the initial PIL approach
and 3 alternative numpy scripts:
#Script 1 - indexing
for i in range(10):
imarr[:,:,0].mean()
imarr[:,:,1].mean()
imarr[:,:,2].mean()
#Script 2 - slicing
for i in ran
> This is the first report. I'll guess it is related to icc. What happens if
> you use gcc?
Indeed, with gcc4.1, the error isn't there.
Matthieu
--
Information System Engineer, Ph.D.
Website: http://matthieu-brucher.developpez.com/
Blogs: http://matt.eifelle.com and http://blog.developpez.com/?b
Francesc Alted wrote:
> A Tuesday 26 May 2009 15:14:39 Andrew Friedley escrigué:
>
>> David Cournapeau wrote:
>>
>>> Francesc Alted wrote:
>>>
Well, it is Andrew who should demonstrate that his measurement is
correct, but in principle, 4 cycles/item *should* be feasible whe
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