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The 4th European meeting on Python
Dear numpy experts,
I have noticed that with Numpy 1.5.1 the operation
m[::2] += 1.0
takes twice as long as
t = m[::2]
t += 1.0
where m is some large matrix. This is of course because the first
snippet is equivalent to
t = m[::2]
t += 1.0
m[::2] = t
I wonder whether it would not be a good
On Wed, May 4, 2011 at 08:19, Christoph Groth c...@falma.de wrote:
Dear numpy experts,
I have noticed that with Numpy 1.5.1 the operation
m[::2] += 1.0
takes twice as long as
t = m[::2]
t += 1.0
where m is some large matrix. This is of course because the first
snippet is equivalent
On Wed, May 4, 2011 at 6:19 AM, Christoph Groth c...@falma.de wrote:
Dear numpy experts,
I have noticed that with Numpy 1.5.1 the operation
m[::2] += 1.0
takes twice as long as
t = m[::2]
t += 1.0
where m is some large matrix. This is of course because the first
snippet is
Hi,
On Tue, May 3, 2011 at 7:58 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, May 3, 2011 at 12:07, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
On Sat, Apr 30, 2011 at 5:21 AM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Wed, Apr 27, 2011 at 8:52 PM, Matthew Brett
On Wed, May 4, 2011 at 11:14, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
On Tue, May 3, 2011 at 7:58 PM, Robert Kern robert.k...@gmail.com wrote:
I can't speak for the rest of the group, but as for myself, if you
would like to draft such a letter, I'm sure I will agree with its
Hi,
I can imagine that this is low-priority, but I have just been enjoying
pytox for automated virtualenv testing:
http://codespeak.net/tox/index.html
which revealed that numpy download-build-install via easy_install
(distribute) fails with the appended traceback ending in ValueError:
On Wed, May 4, 2011 at 6:53 PM, Matthew Brett matthew.br...@gmail.comwrote:
Hi,
I can imagine that this is low-priority, but I have just been enjoying
pytox for automated virtualenv testing:
http://codespeak.net/tox/index.html
which revealed that numpy download-build-install via
On Tue, May 3, 2011 at 11:24 PM, josef.p...@gmail.com wrote:
On Tue, May 3, 2011 at 5:06 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Tue, May 3, 2011 at 10:35 PM, Christoph Gohlke cgoh...@uci.edu
wrote:
On 5/3/2011 11:18 AM, Ralf Gommers wrote:
Hi,
I am pleased to
On Wed, May 4, 2011 at 2:29 AM, Charles R Harris
charlesr.har...@gmail.comwrote:
On Tue, May 3, 2011 at 4:58 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
Hi Ralf,
I am pleased to announce the availability of the second release
candidate of NumPy 1.6.0.
Compared to
Hi,
On Wed, May 4, 2011 at 1:23 PM, Ralf Gommers
ralf.gomm...@googlemail.com wrote:
On Wed, May 4, 2011 at 6:53 PM, Matthew Brett matthew.br...@gmail.com
wrote:
Hi,
I can imagine that this is low-priority, but I have just been enjoying
pytox for automated virtualenv testing:
On Tue, May 3, 2011 at 11:22 PM, Ilan Schnell ischn...@enthought.comwrote:
I'm seeing these three failures on Solaris 5.10 (x86_64, using Python
2.7.1):
==
FAIL: Test basic arithmetic function errors
On 04.05.2011, at 8:42PM, Ralf Gommers wrote:
==
FAIL: test_return_character.TestF90ReturnCharacter.test_all
--
Traceback (most recent call last):
File
On Tue, May 3, 2011 at 1:18 PM, Ralf Gommers ralf.gomm...@googlemail.comwrote:
Hi,
I am pleased to announce the availability of the second release
candidate of NumPy 1.6.0.
Compared to the first release candidate, one segfault on (32-bit
Windows + MSVC) and several memory leaks were fixed.
Hi Paul,
I've got back to your suggestion re. the ndmin flag for loadtxt from a few
weeks ago...
On 27.03.2011, at 12:09PM, Paul Anton Letnes wrote:
1562:
I attach a possible patch. This could also be the default
behavior to my mind, since the function caller can simply call
On 4. mai 2011, at 17.34, Derek Homeier wrote:
Hi Paul,
I've got back to your suggestion re. the ndmin flag for loadtxt from a few
weeks ago...
On 27.03.2011, at 12:09PM, Paul Anton Letnes wrote:
1562:
I attach a possible patch. This could also be the default
behavior to my mind,
On 05.05.2011, at 2:40AM, Paul Anton Letnes wrote:
But: Isn't the numpy.atleast_2d and numpy.atleast_1d functions written for
this? Shouldn't we reuse them? Perhaps it's overkill, and perhaps it will
reintroduce the 'transposed' problem?
Yes, good point, one could replace the
X.shape =
On Wed, May 4, 2011 at 7:54 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 05.05.2011, at 2:40AM, Paul Anton Letnes wrote:
But: Isn't the numpy.atleast_2d and numpy.atleast_1d functions written
for this? Shouldn't we reuse them? Perhaps it's overkill, and perhaps it
will
On 4. mai 2011, at 20.33, Benjamin Root wrote:
On Wed, May 4, 2011 at 7:54 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 05.05.2011, at 2:40AM, Paul Anton Letnes wrote:
But: Isn't the numpy.atleast_2d and numpy.atleast_1d functions written for
this? Shouldn't we
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