David Cournapeau wrote:
Hi,
The first release candidate for 1.4.0 has been released. The sources,
as well as mac and windows installers may be found here:
https://sourceforge.net/projects/numpy/files/
The main improvements compared to 1.3.0 are:
* Faster import time
* Extended array
On Tue, Dec 1, 2009 at 5:04 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi Pauli,
It looks like you doing great stuff with the py3k transition. Do you and
David have any sort of merge schedule in mind?
I have updated my py3k branch for numpy.distutils, and it is ready to merge:
On Tue, Dec 1, 2009 at 9:17 AM, Virgil Stokes v...@it.uu.se wrote:
David Cournapeau wrote:
Hi,
The first release candidate for 1.4.0 has been released. The sources,
as well as mac and windows installers may be found here:
https://sourceforge.net/projects/numpy/files/
The main improvements
On Tue, Dec 1, 2009 at 6:00 PM, Sebastian Haase seb.ha...@gmail.com wrote:
I can only agree - great work !
Thanks.
Where can one find out about the
* New Neighborhood iterator (C-level only)
?
Here:
http://docs.scipy.org/doc/numpy/reference/c-api.array.html#functions
You can find some
Anne Archibald wrote:
2009/11/30 James Bergstra bergs...@iro.umontreal.ca:
Your question involves a few concepts:
- an integer vector describing the position of an element
- the logical shape (another int vector)
- the physical strides (another int vector)
Ignoring the case of
Dag Sverre Seljebotn wrote:
Anne Archibald wrote:
2009/11/30 James Bergstra bergs...@iro.umontreal.ca:
Your question involves a few concepts:
- an integer vector describing the position of an element
- the logical shape (another int vector)
- the physical strides (another
Thanks for these references (that's a pity we currently can't find
anything related to runtime libraries versioning on the msdn database).
Eloi
David Cournapeau wrote:
On Mon, Nov 30, 2009 at 8:52 PM, Eloi Gaudry e...@fft.be wrote:
Well, I wasn't aware of Microsoft willing to giving up
I've done so, thanks for pointing the discussion.
In the meantime, I've just patched distutils/msvc9compiler.py so that it
neither embed nor create a manifest assembly. This way, I'll be sure
that the assembly information would be fetched from the main python (or
python-based) binaries (i.e.
Not to be a downer, but this problem is technically NP-complete. The
so-called knapsack problem is to find a subset of a collection of
numbers that adds up to the specified number, and it is NP-complete.
Unfortunately, it is exactly what you need to do to find the indices
to a particular
Click on Hello World twice and get a memory error. Comment out the ax.plot
call and get no error.
import numpy
import sys
import gtk
from matplotlib.figure import Figure
from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as
FigureCanvas
ax=None
fig=None
canvas=None
def
Hmm... works for me. What platform, with how much physical and virtual RAM?
One thing you may want to try is to completely destroy the figure each time:
if fig:
fig.clf()
fig=None
Mike
Yeates, Mathew C (388D) wrote:
Click on “Hello World” twice and get a memory error. Comment out the
Hi Mathew,
I saw your email and I was curious about it. I tried your code and it
does work for me without any problem.
Santanu
On Tue, Dec 1, 2009 at 2:58 PM, Michael Droettboom md...@stsci.edu wrote:
Hmm... works for me. What platform, with how much physical and virtual RAM?
One thing
On Tue, Dec 1, 2009 at 4:47 AM, David Cournapeau courn...@gmail.com wrote:
The first release candidate for 1.4.0 has been released.
Excellent! Thanks for all your effort,
Jarrod
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On 30-Nov-09, at 10:47 PM, David Cournapeau wrote:
Hi,
The first release candidate for 1.4.0 has been released. The sources,
as well as mac and windows installers may be found here:
https://sourceforge.net/projects/numpy/files/
Hi David,
All clear on my Intel Atom and Core i5 boxes,
I found a workaround. If I replace
plot_data=data[0,0:,0]
With
plot_data=numpy.copy(data[0,0:,0])
Everything is okay.
I am on Windows XP 64 with 4 Gigs ram. (Note: the data array is greater than 4
Gigs since my datatype is float64. If I decrease the size so that the array is
around 3 Gigs,
On Mon, Nov 30, 2009 at 9:47 PM, David Cournapeau courn...@gmail.com wrote:
Hi,
The first release candidate for 1.4.0 has been released. The sources,
as well as mac and windows installers may be found here:
https://sourceforge.net/projects/numpy/files/
I installed 32-bit Python 2.6.3 and
On Wed, Dec 2, 2009 at 12:17 PM, Bruce Southey bsout...@gmail.com wrote:
Traceback (most recent call last):
File E:\Python26\lib\site-packages\numpy\core\tests\test_umath_complex.py,
line 179, in test_special_values
assert_almost_equal(np.log(x), y)
File
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