On Thu, 20 Dec 2007, Jarrod Millman apparently wrote:
> If you are having problems with NumPy and SciPy on Pentium III
> machines running Windows, please try the newly released binaries:
I used the Python 2.5 binaries (.exe) on my home P3 and all
seems well in use. I got no failures of numpy.te
Stefan,
I think the description of the putmask difference is missing the point.
The real difference is not in the way the third argument is handled,
or its required shape, but in whether the mask is updated or not.
numpy.ma.putmask updates the mask; that is, if it "puts" something into
the
On Dec 21, 2007 12:37 AM, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
> 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
Thanks for your work on this.
I can confirm that the numpy-1.0.4.win32-p3-py2.5.msi binary works as
advertised on my crufty PIII test platform. numpy.test() passes all
tests.
Cheers,
Stuart Brorson
Interactive Supercomputing, inc.
135 Beaver Street | Waltham | MA | 02452 | USA
http://www.intera
On Dec 21, 2007 6:45 AM, David Cournapeau <[EMAIL PROTECTED]>
wrote:
> Hans Meine wrote:
> > Am Freitag, 21. Dezember 2007 13:23:49 schrieb David Cournapeau:
> >
> >>> Instead of saying "memmap is ALL about disc access" I would rather
> >>> like to say that "memap is all about SMART disk access" -
To learn array basics:
http://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/python/arrays.html>
http://www.scipy.org/Numpy_Example_List#head-a8a8874581c2ebfc69a37ab513974a229ff3bfaa>
http://www.scipy.org/Numpy_Example_List#head-a261b8dd10bda6a5fc268fe4f4171acee2f83968>
http://homes
Hans Meine wrote:
> Am Freitag, 21. Dezember 2007 13:23:49 schrieb David Cournapeau:
>
>>> Instead of saying "memmap is ALL about disc access" I would rather
>>> like to say that "memap is all about SMART disk access" -- what I mean
>>> is that memmap should run as fast as a normal ndarray if it
Am Freitag, 21. Dezember 2007 13:23:49 schrieb David Cournapeau:
> > Instead of saying "memmap is ALL about disc access" I would rather
> > like to say that "memap is all about SMART disk access" -- what I mean
> > is that memmap should run as fast as a normal ndarray if it works on
> > the cached
Sebastian Haase wrote:
> On Dec 21, 2007 12:11 AM, Martin Spacek <[EMAIL PROTECTED]> wrote:
>
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
On Dec 21, 2007 9:40 AM, Charles R Harris <[EMAIL PROTECTED]> wrote:
>
>
>
>
> On Dec 20, 2007 9:32 AM, Ondrej Certik <[EMAIL PROTECTED]> wrote:
> > > > when compiled on Debian, numpy segfaults when used with ATLAS sse2,
> > > > but works when used against ATLAS sse. More information here:
> > >
>
On Thu, Dec 20, 2007 at 06:52:38PM -0500, Pierre GM wrote:
> > If we can document exactly what the compatibility issues are (and it
> > looks like we are almost there), we should move forward.
>
> OK, I'll take care of that this week-end. Stefan, feel free to beat me to
> it...
A first draft is
On Fri, Dec 21, 2007 at 10:43:28AM +0200, Stefan van der Walt wrote:
> On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote:
> > > * bool(x) raises a ValueError, as it does for ndarrays.
> > >
> > What does bool(x) raise for numpy.core.ma.
Sorry, I realise you were talking about t
On Dec 21, 2007 12:11 AM, Martin Spacek <[EMAIL PROTECTED]> wrote:
> >> 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 spee
Hi Travis
On Thu, Dec 20, 2007 at 05:24:44PM -0600, Travis E. Oliphant wrote:
> > * bool(x) raises a ValueError, as it does for ndarrays.
> >
> What does bool(x) raise for numpy.core.ma.
It now behaves the same way as numpy does, raising a ValueError:
In [1]: bool(N.ma.array([0,1]))
-
On Dec 20, 2007 9:32 AM, Ondrej Certik <[EMAIL PROTECTED]> wrote:
> > > 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
or, you can either use fill.
In [53]: M = numpy.matrix(numpy.zeros((3,5)))
In [55]: M.fill(999)
In [56]: M
Out[56]:
matrix([[ 999., 999., 999., 999., 999.],
[ 999., 999., 999., 999., 999.],
[ 999., 999., 999., 999., 999.]])
L.
On 12/21/07, [EMAIL PROTECTED] <[EMAIL PR
Hi,
forwarding more information about the problem + backtrace.
Ondrej
-- Forwarded message --
From: Jan Medlock <[EMAIL PROTECTED]>
Date: Dec 21, 2007 4:17 AM
Subject: Re: Bug#448530: bug reproduced
To: Ondrej Certik <[EMAIL PROTECTED]>
Cc: [EMAIL PROTECTED], Kumar Appaiah <[EMA
Hi,
You can use ones as well if the array (not matrix) has the same values, or
the array function to create an array from a sequence, or matrix for matrix
and a sequence of sequences
a = n.ones((3,5)) * 9
b = n.array((1, 2, 3), (4, 5, 6), (6, 7, 8))
c = n.matrix((1, 2, 3), (4, 5, 6), (6, 7, 8
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