Hi,
How do I find the maximum possible array size for a given data type on a given
architecture?
For example if I do the following on a 32-bit Windows machine:
matrix = np.zeros((8873,9400),np.dtype('f8'))
I get,
Traceback (most recent call last):
File pyshell#115, line 1, in module
Hi all,
Are there plans to provide official 64bit Windows installers for NumPy?
I'm aware that Christoph Gohlke had been able to do this, since
he offers unofficial plain builds and MKL builds for NumPy here:
http://www.lfd.uci.edu/~gohlke/pythonlibs/
Regards,
Peter
On Mon, Jan 17, 2011 at 06:35, Tom Holderness
tom.holdern...@newcastle.ac.uk wrote:
Hi,
How do I find the maximum possible array size for a given data type on a
given architecture?
For example if I do the following on a 32-bit Windows machine:
matrix = np.zeros((8873,9400),np.dtype('f8'))
Hi all!
I made some performance tests with numpy to compare numpy on one cpu with mpi
on 4 processesors, and something appears quite strange to me:
I have the following code:
N = 2**10*4
K = 16000
x = numpy.random.randn(N).astype(numpy.float32)
x *= 10**10
print x:, x
t1 = time.time()
#do
We are glad to announce release 3.0 of the Modular toolkit for Data
Processing (MDP).
MDP is a Python library of widely used data processing algorithms
that can be combined according to a pipeline analogy to build more
complex data processing software. The base of available algorithms
includes
On Sat, Jan 15, 2011 at 3:27 PM, josef.p...@gmail.com wrote:
After upgrading to numpy 1.5.1 I got caught by some depreciated
features. Given the depreciation policy of numpy, if we want to
support more than two versions of numpy, then we need some conditional
execution.
Does anyone have any
On 01/17/2011 10:32 AM, josef.p...@gmail.com wrote:
On Mon, Jan 17, 2011 at 11:28 AM,josef.p...@gmail.com wrote:
On Sat, Jan 15, 2011 at 3:27 PM,josef.p...@gmail.com wrote:
After upgrading to numpy 1.5.1 I got caught by some depreciated
features. Given the depreciation policy of numpy, if we
A Monday 17 January 2011 17:02:43 Stefan Reiterer escrigué:
Hi all!
I made some performance tests with numpy to compare numpy on one
cpu with mpi on 4 processesors, and something appears quite strange
to me:
I have the following code:
N = 2**10*4
K = 16000
x =
I just took a look at
http://www.katjaas.nl/chirpZ/chirpZ2.html
I'm VERY interested in the zoom. Does the code
https://github.com/cournape/numpy/tree/bluestein
implement the zoom feature?
___
NumPy-Discussion mailing list
I resolved the problem by commenting out two lines in my setup.py
#optimize:1,
#bundle_files: 2,
The defmatrix lib was inside \lib\library.zip. However, the program.exe could
not find it.
Cheers
--- On Sun, 1/16/11, zb zaub...@yahoo.com wrote:
On Mon, Jan 17, 2011 at 12:18 PM, Bruce Southey bsout...@gmail.com wrote:
On 01/17/2011 10:32 AM, josef.p...@gmail.com wrote:
On Mon, Jan 17, 2011 at 11:28 AM,josef.p...@gmail.com wrote:
On Sat, Jan 15, 2011 at 3:27 PM,josef.p...@gmail.com wrote:
After upgrading to numpy 1.5.1 I got caught
Scientific Python Tools not only for Scientists and Engineers
=
This is the title of my three-hour tutorial at PyCon US:
http://us.pycon.org/2011/schedule/sessions/164/
It is a compressed version of my much longer course about:
* NumPy
Thanks that was the problem!
You never stop to learn =)
Original-Nachricht
Datum: Mon, 17 Jan 2011 18:22:17 +0100
Von: Francesc Alted fal...@pytables.org
An: Discussion of Numerical Python numpy-discussion@scipy.org
Betreff: Re: [Numpy-discussion] Strange behaviour with for
13 matches
Mail list logo