Travis E. Oliphant wrote:
> I've finally caught up with the discussion on aligned allocators for
> NumPy. In general I'm favorable to the idea, although it is not as
> easy to implement in 1.0.X because of the need to possibly change the C-API.
>
> The Python solution is workable and would just
Travis E. Oliphant wrote:
> We can't change the C-API for PyArray_FromAny to accept an alignment
> flag, and I'm pretty loath to do that even for 1.1.
>
Ooops! Pleas read that as can't accept an alignment *argument*
-Travis
___
Numpy-discussion ma
I've finally caught up with the discussion on aligned allocators for
NumPy. In general I'm favorable to the idea, although it is not as
easy to implement in 1.0.X because of the need to possibly change the C-API.
The Python solution is workable and would just require a function call
on the P
Travis E. Oliphant wrote:
> David Cournapeau wrote:
>>>
>>>
>> Hi Jarrod,
>>
>> Would it be possible to merge some of the work I have done recently
>> concerning cleaning configuration and so on (If nobody is against it, of
>> course) ? If this is considerer too big of a change, what
David Cournapeau wrote:
>
>>
>>
>>
> Hi Jarrod,
>
> Would it be possible to merge some of the work I have done recently
> concerning cleaning configuration and so on (If nobody is against it, of
> course) ? If this is considerer too big of a change, what is the plan
> for a 1.1 relea
Jarrod Millman wrote:
> Hi all,
>
> After speaking with Travis, I think that we can release NumPy 1.0.4 by
> the end of the month. 1.0.3 came out almost 5 months ago and there
> have been a number of bug-fixes and other improvements since then.
>
> Please take a look at the 1.0.4 roadmap:
> http:/
Hi all,
After speaking with Travis, I think that we can release NumPy 1.0.4 by
the end of the month. 1.0.3 came out almost 5 months ago and there
have been a number of bug-fixes and other improvements since then.
Please take a look at the 1.0.4 roadmap:
http://scipy.org/scipy/numpy/milestone/1.0
Geoffrey Zhu wrote:
> Hi All,
>
> Given three vectors of the same lengths, X, Y, and Z, I am looking for
> an efficient way to calculate the following:
>
> sum(x[i]*y[i]*z[i], for i=1..n )
(x*y*z).sum()
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigm
I think I figured out: sum(X*Y*Z).
Never mind.
On 10/18/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
> Hi All,
>
> Given three vectors of the same lengths, X, Y, and Z, I am looking for
> an efficient way to calculate the following:
>
> sum(x[i]*y[i]*z[i], for i=1..n )
>
>
> I am not sure if there
Hi All,
Given three vectors of the same lengths, X, Y, and Z, I am looking for
an efficient way to calculate the following:
sum(x[i]*y[i]*z[i], for i=1..n )
I am not sure if there is a vectorized way to do this.
Thanks,
Geoffrey
___
Numpy-discussion
Albert Strasheim wrote:
> Hello
>
> Firstly, great work. I always thought SCons was the way to go for
> NumPy and SciPy, and you've pulled it off.
>
>> So basically, I believe most of the things planned in
>> http://projects.scipy.org/scipy/numpy/wiki/DistutilsRevamp are now
>> available because th
Hi Axel,
On 10/11/07, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
>
>
> Hi,
>
> I tried the function numpy.linalg.svd(X) on an array X with 100 rows and
> 50
> columns.
>
> I got an Error message:
> ** On entry to DGESDD parameter number 12 has an illegal value
> Then I got kicked out of python.
Hi,
I am trying to install numpy with lapack/altas library support and got
following error on a solaris 9 box.
http://www.scipy.org/Download
The error I got during compiling is as following:
**
ATL_dset0x1494
/usr/local/lib/atlas/libatlas.a(ATL_zCtrsmKL.o)
Hi,
I tried the function numpy.linalg.svd(X) on an array X with 100 rows and 50
columns.
I got an Error message:
** On entry to DGESDD parameter number 12 has an illegal value
Then I got kicked out of python.
I tried numarray.mlab.svd(X) and it worked fine.
Is there a workaround to perform svd
Hello all,
I have the following function, with print statements inserted for
debugging:
import numpy
def file2mat(inFile, sep=None, T=True):
try:
input = inFile.readlines()
print "input=%s" % input
except:
raise
finally:
inFile.close()
data = [line.
Hello
Firstly, great work. I always thought SCons was the way to go for
NumPy and SciPy, and you've pulled it off.
> So basically, I believe most of the things planned in
> http://projects.scipy.org/scipy/numpy/wiki/DistutilsRevamp are now
> available because they are available in scons, if numpy
Hi,
I am happy to announce a second milestone in scons support in numpy.
This one is much bigger than the first one, since now I can build the
whole numpy using scons (e.g. distutils is not used at all to build non
python code).
How to use it:
==
just do as before for installin
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