On Thu, Nov 20, 2008 at 07:58:52AM +0200, Scott Sinclair wrote:
A Notes section giving an overview of the algorithm has been added to
the docstring http://docs.scipy.org/numpy/docs/numpy.linalg.linalg.solve/.
I thank you very much for doing this, and I reckon many users should be
grateful. This
Hi,
Sorry; my first message wasn't under 40 KB with the attachments, so
here's the same message but with the log files at
http://www.stat.washington.edu/~hoytak/logs.tar.bz2.
Which ones ?
Sorry; ATLAS = 3.9.4 and lapack=3.2. I'll give 3.8.2 a shot per your advice.
You should not do that,
On Thu, 2008-11-20 at 00:26 -0800, Hoyt Koepke wrote:
Hi,
Sorry; my first message wasn't under 40 KB with the attachments, so
here's the same message but with the log files at
http://www.stat.washington.edu/~hoytak/logs.tar.bz2.
Which ones ?
Sorry; ATLAS = 3.9.4 and lapack=3.2.
Hi,
I honestly don't think those flags matter much in the case of
numpy/scipy. In particular, using SSE and co automatically is simply
impossible in numpy case, since the C code is very generic (non-aligned
- non contiguous items) and the compiler has no way to know at compile
time which
On Thu, Nov 20, 2008 at 6:14 PM, Hoyt Koepke [EMAIL PROTECTED] wrote:
I believe the logs I attached (or rather linked to) don't involve
atlas or lapack or any compiler flags.
Ah, yes, sorry, I missed the build.log one. The only thing which
surprises me a bit is the size of long double (I have
On Thu, Nov 20, 2008 at 2:29 AM, David Cournapeau [EMAIL PROTECTED]wrote:
On Thu, Nov 20, 2008 at 6:14 PM, Hoyt Koepke [EMAIL PROTECTED] wrote:
I believe the logs I attached (or rather linked to) don't involve
atlas or lapack or any compiler flags.
Ah, yes, sorry, I missed the build.log
Christopher Barker wrote:
thanks! good stuff.
It would be great if you could put that in the numpy (scipy?) wiki
though, so more folks will find it.
-Chris
Hello Chris,
no problems, you are absolutely right, this is where the documents will
have to eventually end up for maximum
On Thursday 20 November 2008 11:11:14 Hans Meine wrote:
I have a 2D matrix comprising a sequence of vectors, and I want to compute
the norm of each vector. np.linalg.norm seems to be the best bet, but it
does not support axis. Wouldn't this be a nice feature?
Here's a basic implementation.
Excellent, thank you all for your input. I don't actually have a specific
problem that I need it for I just wanted to be able to work through some
book examples. I'll take a look at Sage and Sympy.
Thanks
Rob
On Wed, Nov 19, 2008 at 10:14 AM, Stéfan van der Walt [EMAIL PROTECTED]wrote:
Hi
On 11/20/2008 12:58 AM Scott Sinclair apparently wrote:
A Notes section giving an overview of the algorithm has been added to
the docstring http://docs.scipy.org/numpy/docs/numpy.linalg.linalg.solve/.
You beat me to it.
(I was awaiting editing privileges,
which I just received.)
Thanks!
Alan
All,
That time of a month again: could anybody (and I'm thinking about you
in particular, Travis O.) can explain me what the priority rules are
between a 0d ndarray and a np.scalar ?
OK, I understand there are no real rules. However, the bug I was
describing in a previous thread
All,
I've recently introduced some little fixes in the SVN version of
numpy.ma.core
Is there any plan for a 1.2.2 release, or will we directly switch to
1.3.0 ? Do I need to backport these fixes to 12x ?
Thx a lot in advance
P.
___
Numpy-discussion
On Thu, Nov 20, 2008 at 07:58:52AM +0200, Scott Sinclair wrote:
A Notes section giving an overview of the algorithm has been added to
the docstring http://docs.scipy.org/numpy/docs/numpy.linalg.linalg.solve/.
Doc goals: We would like each function and class to have docs that
compare favorably
This, and your previous question, are mostly off-topic for
numpy-discussion. You may want to ask such questions in the future on
more general Python mailing lists.
http://www.python.org/community/lists/
--
Robert Kern
Yes of course. Sorry for the spam. The numpy list is just so
I frequently want to break a 1D array into regions above and below
some threshold, identifying all such subslices where the contiguous
elements are above the threshold. I have two related implementations
below to illustrate what I am after. The first crossings is rather
naive in that it doesn't
John Hunter schrieb:
I frequently want to break a 1D array into regions above and below
some threshold, identifying all such subslices where the contiguous
elements are above the threshold. I have two related implementations
below to illustrate what I am after. The first crossings is rather
Hi All,
I have reached the point where I really need to get some sort of
optimised/accelerated BLAS/LAPACK for windows 64 so have been trying a few
different things out to see whether I can get anything usable, today i
stumbled across this:
http://icl.cs.utk.edu/lapack-for-windows/index.html
Hi,
Does anyone know why numpy.loadtxt(), in checking the validity of a
filehandle, checks for the seek() method, which appears to have no
bearing on whether an object will work?
I'm trying to use loadtxt() directly with the file-like object returned
by urllib2.urlopen(). If I change the check
On Donnerstag 20 November 2008, Alan G Isaac wrote:
On 11/20/2008 5:11 AM Hans Meine apparently wrote:
I have a 2D matrix comprising a sequence of vectors, and I want to
compute the norm of each vector. np.linalg.norm seems to be the best
bet, but it does not support axis. Wouldn't this
Stéfan van der Walt wrote:
2008/11/20 Ryan May [EMAIL PROTECTED]:
Does anyone know why numpy.loadtxt(), in checking the validity of a
filehandle, checks for the seek() method, which appears to have no
bearing on whether an object will work?
I think this is simply a naive mistake on my part.
The following shows a bug in numpy.ma.allclose:
import numpy
import numpy.ma
a = numpy.arange(100)
b=numpy.reshape(a,(10,10))
print b
c=numpy.ma.masked_greater(b,98)
print c.count()
numpy.ma.allclose(b,1)
numpy.ma.allclose(c,1)
Since c is masked it fails
I think it should pass returning
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