On Mon, Apr 26, 2010 at 2:42 AM, threexk threexk 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 this is? The
On Sun, Apr 25, 2010 at 16:17, Robert Kern wrote:
> On Thu, Apr 22, 2010 at 16:23, Bruce Southey wrote:
>> On 04/21/2010 02:45 PM, Robert Kern wrote:
>>> On Wed, Apr 21, 2010 at 10:34, Bruce Southey wrote:
>
If the sum of axis to be removed equals zero then you can conditionally
remove
On Thu, Apr 22, 2010 at 16:23, Bruce Southey wrote:
> On 04/21/2010 02:45 PM, Robert Kern wrote:
>> On Wed, Apr 21, 2010 at 10:34, Bruce Southey wrote:
>>> If the sum of axis to be removed equals zero then you can conditionally
>>> remove that axis.
>>>
>> No. Negative numbers can cancel out pos
Hi Everyone,
Thanks for your suggestions and replies. I initially tried what Anne
suggested, modifying the strides in the third dimension to account for
the 8-byte delimiters between slabs, but I couldn't control the
performance as much as I'd like, and I wasn't entirely sure when and
where "real
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 g
Andreas wrote:
> 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
On Thu, Apr 22, 2010 at 21:57, David Huard 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 behave as a regular
> 3
On Sun, Apr 25, 2010 at 10:45 AM, Keith Goodman wrote:
> On Sun, Apr 25, 2010 at 6:16 AM, 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.
On Sun, Apr 25, 2010 at 6:16 AM, 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 pointe
(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 Thu, Apr 22, 2010 at 12:04 PM, Adrien Guillon 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 solutions I could see
a
On Fri, Apr 23, 2010 at 10:29 PM, Dag Sverre Seljebotn
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 the main feature for 0.0
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 th
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
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
k
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 switc
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, na
On 21 April 2010 23:04, 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 prototypin
On Wed, Apr 21, 2010 at 9:04 PM, 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 p
(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:
Pac
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 i
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 to
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 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 PM,
On 21 April 2010 15:41, Matthew Turk 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 data was output a
On 04/21/2010 02:45 PM, Robert Kern wrote:
> On Wed, Apr 21, 2010 at 10:34, Bruce Southey wrote:
>
>> On 04/21/2010 08:36 AM, Robert Kern wrote:
>>
>>> On Tue, Apr 20, 2010 at 18:45, Charles R Harris
>>> wrote:
>>>
>>>
On Tue, Apr 20, 2010 at 7:03 AM, Andreas Hilboll
On Wed, Apr 21, 2010 at 14:41, Matthew Turk 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 data was o
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 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 follo
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