hi
i am a beginner with numpy and python,so pardon me if this doubt seems
silly
i want to create a matrix with say 3 rows and 5 columns..and then set
the values of each item in it .for this i did something like below
myarray=zeros((3,5))
#then set the items
for row in range(3):
for col in rang
hi
i am a beginner with numpy and python,so pardon me if this doubt seems
silly
i want to create a matrix with say 3 rows and 5 columns..and then set
the values of each item in it .for this i did something like below
myarray=zeros((3,5))
#then set the items
for row in range(3):
for col in rang
On Dec 20, 2007 10:29 AM, Travis E. Oliphant <[EMAIL PROTECTED]> wrote:
> David Cournapeau wrote:
> > Hi,
> >
> > as discussed with some other numpy developers, in particular Travis, I
> > started to prepare my work related to scons for step-by-step merging
> > into the trunk. The first step is don
> > * cumsum(cumprod) works as if the _data array was filled with 0 (1). The
> > mask is preserved, but not updated. (the output of numpy.core.ma has
> > nomask).
>
> I don't understand what you mean here.So, the mask effectively
> removes those elements from the sum(product) computation? What
Pierre GM wrote:
> All,
>
>
>> I'd like to move forward with it sooner (for 1.0.5) if the API changes
>> are not drastic. Although ideally 0 API changes would be desireable,
>> I'm not sure if that is feasible. Are put and putmask the only changes
>> in the API. What are the rest of them?
>>
>> By the way, I installed 64-bit linux (ubuntu 7.10) on the same machine,
>> and now numpy.memmap works like a charm. Slicing around a 15 GB file is fun!
>>
> Thanks for the feedback !
> Did you get the kind of speed you need and/or the speed you were hoping for ?
Nope. Like I wrote earlier, it s
Hey,
If you are having problems with NumPy and SciPy on Pentium III
machines running Windows, please try the newly released binaries:
numpy-1.0.4.win32-p3-py2.3.exe
numpy-1.0.4.win32-p3-py2.4.exe
numpy-1.0.4.win32-p3-py2.5.exe
numpy-1.0.4.win32-p3-py2.5.msi
scipy-0.6.0.win32-p3-py2.3.exe
scipy-0
On Donnerstag 20 Dezember 2007, Christopher Barker wrote:
> > In [9]: print where( (logical_or(a<1, b<3)), b,c)
> > [4 2 2 1]
> > (Think of the Zen.)
>
> I'm not sure the Zen answers this one for us.
As you have guessed correctly, I was thinking of "explicit is better than
implicit".
> It's real
On Dec 20, 2007 3:22 AM, Martin Spacek <[EMAIL PROTECTED]> wrote:
> Sebastian Haase wrote:
> > b) To my knowledge, any OS Linux, Windows an OSX can max. allocate
> > about 1GB of data - assuming you have a 32 bit machine.
> > The actual numbers I measured varied from about 700MB to maybe 1.3GB.
>
On Dec 20, 2007 3:22 AM, Martin Spacek <[EMAIL PROTECTED]> wrote:
> Sebastian Haase wrote:
> > b) To my knowledge, any OS Linux, Windows an OSX can max. allocate
> > about 1GB of data - assuming you have a 32 bit machine.
> > The actual numbers I measured varied from about 700MB to maybe 1.3GB.
>
to, 2007-12-20 kello 17:32 +0100, Ondrej Certik kirjoitti:
> > > when compiled on Debian, numpy segfaults when used with ATLAS sse2,
> > > but works when used against ATLAS sse. More information here:
> >
> > What is the machine on which you are getting the segfault? Is it
>
> I don't know which
Travis E. Oliphant wrote:
> Currently, this
> board consists of (alphabetically)
>
> Eric Jones
> Robert Kern
> Jarrod Millman
> Travis Oliphant
Excellent team -- thanks guys!
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R(206) 526-6
Hans Meine wrote:
>> where( (a<1 or b<3), b,c)
>
> Now + and | have been proposed to you, but it looks to me as if the "correct
> way" would be logical_or. All solutions give the same result, but logical_or
> better expresses what you're trying to do:
>
> In [9]: print where( (logical_or(a<1,
All,
> I'd like to move forward with it sooner (for 1.0.5) if the API changes
> are not drastic. Although ideally 0 API changes would be desireable,
> I'm not sure if that is feasible. Are put and putmask the only changes
> in the API. What are the rest of them?
* put, putmask, take should be
I'm not sure whether this is a Numpy problem or a Boost problem, so I'm
posting to both communities.
In old Numeric, type(sqrt(5.5)) was float, but in numpy, type(sqrt(5.5))
is numpy.float64. This leads to a big performance hit in calculations in
a beta version of VPython, using the VPython 3D
>> x = M.rand(3,1) < 3x1
>> x[M.isfinite(x)]
matrix([[ 0.36541551, 0.6305087 , 0.66054899]]) <-- Should
this be 3x1?
My workaround is awkward:
>> x[M.where(M.isfinite(x).A)[0]]
matrix([[ 0.36541551],
[ 0.6305087 ],
[ 0.66054899]])
_
> > when compiled on Debian, numpy segfaults when used with ATLAS sse2,
> > but works when used against ATLAS sse. More information here:
>
> What is the machine on which you are getting the segfault? Is it
I don't know which machine the reporter of this bug in Debian uses, but I use
Intel Core D
Stefan van der Walt wrote:
> Hi Travis,
>
> During the sprint I also merged Pierre's MaskedArray code into the
> maskedarray branch. That is nearly done, with only a few unit tests
> still failing -- ones brought over from the old numpy.ma.
>
> This is mainly due to some changes in the API, for ex
Am Sonntag, 16. Dezember 2007 20:10:41 schrieb Ross Harder:
> What's the correct way to do something like this?
>
> a=array( (0,1,1,0) )
> b=array( (4,3,2,1) )
> c=array( (1,2,3,4) )
>
> where( (a<1 or b<3), b,c)
Now + and | have been proposed to you, but it looks to me as if the "correct
way" wo
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