On Apr 21, 2010, at 10:47 AM, Ken Basye wrote:
Folks,
Apologies for asking here, but I ran across this problem yesterday
and probably need to file a bug. The problem is I don't know if
this is
a Numpy bug, a Python bug, or both. Here's an illustration, platform
information follows.
Hi,
I am pleased to announce the release of NumPy 1.4.1. This maintenance
release removes datetime support, which fixes the binary incompatibility
issues between NumPy 1.4.0 and SciPy and other extension packages. Several
other bug fixes are also included.
Binaries, sources and release notes can
On Wed, Apr 21, 2010 at 14:41, Matthew Turk matthewt...@gmail.com wrote:
Hi there,
I've quite a bit of unformatted fortran data that I'd like to use as
input to a memmap, as sort of a staging area for selection of
subregions to be loaded into RAM. Unfortunately, what I'm running
into is
On 04/21/2010 02:45 PM, Robert Kern wrote:
On Wed, Apr 21, 2010 at 10:34, Bruce Southeybsout...@gmail.com wrote:
On 04/21/2010 08:36 AM, Robert Kern wrote:
On Tue, Apr 20, 2010 at 18:45, Charles R Harris
charlesr.har...@gmail.comwrote:
On Tue, Apr 20, 2010 at 7:03
On 21 April 2010 15:41, Matthew Turk matthewt...@gmail.com wrote:
Hi there,
I've quite a bit of unformatted fortran data that I'd like to use as
input to a memmap, as sort of a staging area for selection of
subregions to be loaded into RAM. Unfortunately, what I'm running
into is that the
Hi Matt,
I don't think the memmap code support this. However, you can stack memmaps
just as easily as arrays, so if you define individual memmaps for each slice
and stack them (numpy.vstack), the resulting array will behave as a regular
3D array.
HTH,
David H.
On Wed, Apr 21, 2010 at 3:41
Hi there,
I was wondering if there's a way to speedup loadtxt/savetxt for big
arrays? So far, I'm plainly using something like this::
file = open(array.txt,w)
a = np.loadtxt(file)
file.close()
However, since my files are pretty big (~200M), that's taking a long
time... Perhaps
Hi there,
I would like to use savetxt() to write a 2d array to a txt file. It
should be written row-wise, but there should only be 10 values per line.
So, if I want to write an array a((2,12)), the file should read like this:
X X X X X X X X X X
X X
X X X X X X X X X X
X X
Is there any way
On Wed, Apr 21, 2010 at 1:21 PM, Dag Sverre Seljebotn
da...@student.matnat.uio.no wrote:
Dan Roberts wrote:
Thanks for the reply. You're certainly right that your work is
extremely beneficial to mine. At present I'm afraid a great deal of
NumPy C code isn't easily reusable and it's
(The toydist manual says to use this list, so here I go...)
Is it possible to invoke toydist manually to install something built
manually with a build system? How is the final .info specification
supposed to look like when toysetup is coupled with a build system?
I tried this:
Library:
On Wed, Apr 21, 2010 at 9:04 PM, Adrien Guillon aj.guil...@gmail.comwrote:
Thank you for your questions... I'll answer them now.
The motivation behind using Python and NumPy is to be able to double
check that the numerical algorithms work okay in an
engineer/scientist friendly language.
Is there a reason why ma.std(ddof=1) does not calculated the std if
there are 2 valid values?
example
nan = np.nan
x1 = np.array([[9.0, 3.0, nan, nan, 9.0, nan],
[1.0, 1.0, 1.0, nan, nan, nan],
[2.0, 2.0, 0.01, nan, 1.0, nan],
[3.0, 9.0, 2.0, nan, nan,
On 04/21/2010 09:47 AM, Adrien Guillon wrote:
Hello all,
I've recently started to use NumPy to prototype some numerical
algorithms, which will eventually find their way to a GPU (where I
want to limit myself to single-precision operations for performance
reasons). I have recently switched
Wow, that's a very cool idea. I think that's an excellent approach to
allowing user RPython functions. Maciej expressed concern this could create
a support burden for RPython for the core PyPy developers (There aren't many
of them). I think, handled correctly, this could help create a community
Adrien Guillon wrote:
Thank you for your questions... I'll answer them now.
The motivation behind using Python and NumPy is to be able to double
check that the numerical algorithms work okay in an
engineer/scientist friendly language. We're basically prototyping a
bunch of algorithms in
Hi folks,
There are a lot of patches sitting around waiting for review. I think most
can be taken care of pretty quickly and closed. There are, however, a half
dozen or so small patches relating to distutils that someone familiar with
that part of numpy should go over (David?). Anyway, lets get
On Fri, Apr 23, 2010 at 10:29 PM, Dag Sverre Seljebotn
da...@student.matnat.uio.no wrote:
(The toydist manual says to use this list, so here I go...)
Is it possible to invoke toydist manually to install something built
manually with a build system?
This is not yet supported, but is basically
On Thu, Apr 22, 2010 at 12:04 PM, Adrien Guillon aj.guil...@gmail.com wrote:
The idea here, is that if I can ensure there is never extended
precision in the Python code...
This is totally out of reach with numpy is you use the float32 dtype,
for the reasons I have given before. The only
(some) numpy functions take floats as valid axis argument. Is this a feature?
np.ones((2,3)).sum(1.2)
array([ 3., 3.])
np.ones((2,3)).sum(1.99)
array([ 3., 3.])
np.mean((1.5,0.5))
1.0
np.mean(1.5,0.5)
1.5
Keith pointed out that scipy.stats.nanmean has a different behavior
On Sun, Apr 25, 2010 at 6:16 AM, josef.p...@gmail.com wrote:
(some) numpy functions take floats as valid axis argument. Is this a feature?
np.ones((2,3)).sum(1.2)
array([ 3., 3.])
np.ones((2,3)).sum(1.99)
array([ 3., 3.])
np.mean((1.5,0.5))
1.0
np.mean(1.5,0.5)
1.5
Keith pointed
On Sun, Apr 25, 2010 at 10:45 AM, Keith Goodman kwgood...@gmail.com wrote:
On Sun, Apr 25, 2010 at 6:16 AM, josef.p...@gmail.com wrote:
(some) numpy functions take floats as valid axis argument. Is this a feature?
np.ones((2,3)).sum(1.2)
array([ 3., 3.])
np.ones((2,3)).sum(1.99)
array([
On Thu, Apr 22, 2010 at 21:57, David Huard david.hu...@gmail.com wrote:
Hi Matt,
I don't think the memmap code support this. However, you can stack memmaps
just as easily as arrays, so if you define individual memmaps for each slice
and stack them (numpy.vstack), the resulting array will
Hello,
I recently uninstalled the NumPy 1.4.0 superpack for Python 2.6 on Windows 7,
and afterward a dialog popped up that said 1 file or directory could not be
removed. Does anyone have any idea which file/directory this is? The dialog
gave no indication. Is an uninstall log with details
On Thu, Apr 22, 2010 at 16:23, Bruce Southey bsout...@gmail.com wrote:
On 04/21/2010 02:45 PM, Robert Kern wrote:
On Wed, Apr 21, 2010 at 10:34, Bruce Southeybsout...@gmail.com wrote:
If the sum of axis to be removed equals zero then you can conditionally
remove that axis.
No. Negative
On Sun, Apr 25, 2010 at 16:17, Robert Kern robert.k...@gmail.com wrote:
On Thu, Apr 22, 2010 at 16:23, Bruce Southey bsout...@gmail.com wrote:
On 04/21/2010 02:45 PM, Robert Kern wrote:
On Wed, Apr 21, 2010 at 10:34, Bruce Southeybsout...@gmail.com wrote:
If the sum of axis to be removed
On Mon, Apr 26, 2010 at 2:42 AM, threexk threexk thre...@hotmail.com wrote:
Hello,
I recently uninstalled the NumPy 1.4.0 superpack for Python 2.6 on Windows
7, and afterward a dialog popped up that said 1 file or directory could not
be removed. Does anyone have any idea which file/directory
26 matches
Mail list logo
