Am Montag, 10. Dezember 2007 17:23:07 schrieb Matthieu Brucher:
I had the same problem sooner today, someone told me the answer : use
numpy.info object ;)
I saw this shortly after posting (what a coincidence), and I planned to reply
to myself, but my mail did not make it to the list very
Am Montag, 10. Dezember 2007 23:46:17 schrieb Timothy Hochberg:
TypeError: function takes at least 2 arguments (1 given)
(I could simulate that by passing max = maximum_value_of(a.dtype), if
that existed, see my other mail.)
Why not just use minimum or maximum as needed instead of
On Dec 11, 2007 3:16 PM, Fernando Perez [EMAIL PROTECTED] wrote:
On Dec 10, 2007 11:04 PM, David Cournapeau [EMAIL PROTECTED] wrote:
On Dec 11, 2007 12:46 PM, Andrew Straw [EMAIL PROTECTED] wrote:
According to the QEMU website, QEMU does not (yet) emulate SSE on x86
target, so a Windows
Hello
I think this idea is the way to go (maybe along with an ACML build, but my
limited testing seemed to indicate that MKL works on AMD CPUs).
In fact, I apparently proposed it about a year ago:
https://svn.enthought.com/enthought/ticket/899
No takers so far...
Cheers,
Albert
P.S. NumPy
On Dec 11, 2007 8:47 PM, Albert Strasheim [EMAIL PROTECTED] wrote:
Hello
I think this idea is the way to go (maybe along with an ACML build, but my
limited testing seemed to indicate that MKL works on AMD CPUs).
I am personally totally against it. It is one thing to support
proprietary
At 02:32 AM 12/11/2007, you wrote:
If so I'd be happy to contribute part of the purchase price,
and I assume others would too.
What's more, I *have* an old PIII at home.
The main company I consult for is set to buy the Intel compiler and
FFT lib for Windows, for the express purpose of compiling
On Dienstag 11 Dezember 2007, Timothy Hochberg wrote:
You mean one of the following?
a.clip(min = 10, max = numpy.finfo(a.dtype).max)
a.clip(min = 10, max = numpy.iinfo(a.dtype).max)
No. I mean:
numpy.maximum(a, 10)
To correspond to the above example.
Great, thanks for the hints.
Hans Meine wrote:
On Dienstag 11 Dezember 2007, Timothy Hochberg wrote:
You mean one of the following?
a.clip(min = 10, max = numpy.finfo(a.dtype).max)
a.clip(min = 10, max = numpy.iinfo(a.dtype).max)
No. I mean:
numpy.maximum(a, 10)
To correspond to the above example.
On Dec 12, 2007 2:58 AM, Christopher Barker [EMAIL PROTECTED] wrote:
David Cournapeau wrote:
I think this idea is the way to go (maybe along with an ACML build, but my
limited testing seemed to indicate that MKL works on AMD CPUs).
I am personally totally against it. It is one thing to
On Dec 12, 2007 3:04 AM, Christopher Barker [EMAIL PROTECTED] wrote:
Fernando Perez wrote:
a simple, reasonable solution that is likely to work: ship TWO
binaries of Numpy/Scipy each time:
1. {numpy,scipy}-reference: built with the reference blas from netlib,
no atlas, period.
2.
Near as I can tell, this is still unresolved for people with non-sse2
machines. Is that right?
I have a student trying to get started with such a machine. Numpy is
causing Python to crash. What is the easiest solution? Does he need
to build numpy from source on that machine (I actually still
Hello all,
I'm not sure the licensing really makes it possible though. Numpy isn't
exactly an application, but rather a development tool, so I'm not sure
how Intel would feel about it being distributed. Also, it looks like
they require each developer to have license, rather than only the
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