Hi,
I found an unexpected difference from numpy 1.7.1 and 1.8.0rc2 with Python
3.3.2 on Ubuntu 12.04 (amd64). Here is the test program:
import numpy as np
print(np.__version__)
K = np.array([[ 0., 0., 0., 0.],
[-0., 0., 0.
Taylor.
Best,
Andrew
On Fri, Oct 25, 2013 at 7:52 PM, Nathaniel Smith n...@pobox.com wrote:
It's py3 only, see the discussion in #3977.
On 25 Oct 2013 17:45, Charles R Harris charlesr.har...@gmail.com
wrote:
On Fri, Oct 25, 2013 at 7:07 AM, Andrew Straw
dr.andrew.st...@gmail.comwrote
I added a ticket for Francesc's enhancement:
http://projects.scipy.org/scipy/numpy/ticket/403
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Numpy-discussion@scipy.org
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Robert Kern wrote:
On Windows, you may be out of luck. I don't know of any
fully-Unicode-capable terminal.
The lack of a decent console application is one of the most problematic
issues I face whenever attempting to do serious programming in Windows.
I wish I knew of a better terminal program.
Alexander Schmolck wrote:
2. Despite this overhead, copying around large arrays (e.g. =1e5 elements) in
above way causes notable additional overhead. Whilst I don't think there's
a sane way to avoid copying by sharing data between numpy and matlab the
copying could likely be done
Bill Baxter wrote:
On 3/15/07, Bill Baxter [EMAIL PROTECTED] wrote:
Thanks, Sebastian. I'll take a look at Pyro. Hadn't heard of it.
I'm using just xmlrpclib with pickle right now.
I took a look at Pyro -- it looks nice.
The only thing I couldn't find, though, is how decouple the
Bill, very cool. Also, thanks for showing me how Twisted can be used
like Pyro, more-or-less, I think. (If I understand your code from my 1
minute perusal.)
On Mac OS X, there's one issue I don't have time to follow any further:
sys.executable points to
Christian K wrote:
David Cournapeau wrote:
On Ubuntu and debian, you do NOT need any site.cfg to compile numpy with
atlas support. Just install the package atlas3-base-dev, and you are
done. The reason is that when *compiling* a software which needs atlas,
the linker will try to find
rex wrote:
Keith Goodman [EMAIL PROTECTED] [2007-04-18 10:49]:
I'd like to compile atlas so that I can take full advantage of my core
2 duo.
If your use is entirely non-commercial you can use Intel's MKL with
built-in optimized BLAS and LAPACK and avoid the need for ATLAS.
The May/June issue of Computing in Science and Engineering
http://computer.org/cise: is out and has a Python theme. Many folks we
know and love from the community and mailing lists contribute to the
issue. Read articles by Paul Dubois and Travis Oliphant for free online.
No, the nth index of a Python sequence is a[n], where n starts from
zero. Thus, if I want the nth dimension of array a, I want a.shape[n].
I reverted the page to its original form and added a couple explanatory
comments about zero vs one based indexing.
dmitrey wrote:
now there is
MATLAB
Charles R Harris wrote:
I'll pitch in a few donuts (and my eternal gratitude) for an
example of
shared memory use using numpy arrays that is cross platform, or at
least
works in linux, mac, and windows.
I wonder if you could mmap a file and use it as common memory?
Charles R Harris wrote:
On 5/24/07, *Ryan Krauss* [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
I am trying to use Numpy/Scipy for a class I am teaching this summer.
I have one student running Vista. Is there an installer that works
for Vista? Running the exe file from
Hi Ryan,
I use VMware server on my linux box to host several more linux images. I
will see if I can whip you up a Ubuntu Feisty i386 image with the big
4 - numpy/scipy/matplotlib/ipython. If I understand their docs
correctly, I have virtual appliances for previously existing images
already...
than the one
which I created the virtual appliance on. I'm posting now because it
will take me a while to download the file (it's 1 GB) in order to test.
-Andrew
Andrew Straw wrote:
Hi Ryan,
I use VMware server on my linux box to host several more linux images. I
will see if I can whip you
Andrew Straw wrote:
OK, I have placed an Ubuntu 7.04 image with stock numpy, scipy,
matplotlib, and ipython at
http://mosca.caltech.edu/outgoing/Ubuntu%207.04%20for%20scientific%20computing%20in%20Python.zip
The md5sum is 4191e13abda1154c94e685ffdc0f829b.
Note: I haven't tested
This is a note to announce the availability of a VMWare Virtual
Appliance with Ubuntu linux with numpy, scipy, matplotlib, and ipython
installed.
This should make it relatively easy to try out the software. The VMWare
Player and VMWare Server are available for no cost from
Giorgio F. Gilestro wrote:
I find myself in a situation where an array may contain not-Numbers
that I set as NaN.
Yet, whatever operation I do on that array( average, sum...) will
threat the NaN as infinite values rather then ignoring them as I'd
like it'd do.
Am I missing something? Is
Torgil Svensson wrote:
OS-specific routines (probably the c-library, haven't looked). I
think python should be consistent regarding this across platforms but
I don't know if different c-libraries generates different strings for
special numbers. Anyone?
Windows and Linux certainly generate
john,
there was a bug that made it into debian sarge whereby a SIGFPE wasn't
trapped in the appropriate place and ended up causing problems similar
to what you describe. the difficulty in debugging is that you're after
whatever triggers the FPE in the first place (or the bug that lets it go
Gael Varoquaux wrote:
On Thu, Jul 19, 2007 at 09:42:42PM -0500, Vincent Nijs wrote:
I'd luv to hear from people using sqlite, pytables, and cPickle about
their experiences.
I was about to point you to this discussion:
Thomas Schreiner wrote:
Am I doing anything wrong in this program? It's crashing immediately
after the before line, using Borland C++ Builder 6 and
numpy-1.0.3.1.win32-py2.4.
You have to call import_array() before using the C API.
___
Christopher Barker wrote:
For data interpolation: 2D-Delaunay triangulation based method (I think you
can find one in the scipy cookbook).
yup -- but then you need the decimation to remove the unneeded
points. I don't think Scipy has that.
The sandbox does, thanks to Robert Kern. (And I
Hi all,
I haven't done any serious testing in the past couple years, but for
this particular task -- drawing frames using OpenGL without ever
skipping a video update -- it is my impression that as of a few Ubuntu
releases ago (Edgy?) Windows still beat linux.
Just now, I have investigated on
An idea that occurred to me after reading Fernando's email. A function
could be called at numpy import time that specifically checks for the
instruction set on the CPU running and makes sure that is completely
covers the instruction set available through all the various calls,
including to BLAS.
According to the QEMU website, QEMU does not (yet) emulate SSE on x86
target, so a Windows installation on a QEMU virtual machine may be a
good way to build binaries free of these issues.
http://fabrice.bellard.free.fr/qemu/qemu-tech.html
-Andrew
Travis E. Oliphant wrote:
Fernando Perez wrote:
or is logical or. You want | which is bitwise/elementwise or. Also,
watch the order of operations -- | has higher precedence than .
Thus, you want
where( (a1) | (b3), b,c)
Ross Harder wrote:
What's the correct way to do something like this?
a=array( (0,1,1,0) )
b=array( (4,3,2,1) )
Apologies if I've missed the discussion of this, but I was recently
surprised by the following behavior (in svn trunk 4673). The following
code runs without triggering the assertion.
import numpy as np
print np.__version__
a=np.int32(42)
b=np.array([],dtype=np.int32)
assert np.allclose(a,b)
Is
Matthew Brett wrote:
So, currently we have all and allclose giving the same answer:
In [19]: a = array([])
In [20]: b = array([1])
In [21]: all(a == b)
Out[21]: True
In [22]: allclose(a, b)
Out[22]: True
Would we want the answers to be different?
No. I wasn't thinking
array like b. The default truth value of a
zero-dimensional array is True, so the following holds and illustrates
how the above result is consistent with numpy's rules.
Andrew Straw wrote:
Apologies if I've missed the discussion of this, but I was recently
surprised by the following behavior
Thanks, I updated the page.
Charles R Harris wrote:
On Jan 4, 2008 12:27 PM, Andrew Straw [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
I have added a page to the wiki describing this issue:
http://scipy.org/numpy_warts_and_gotchas
I'll link it into the main
Hi,
I'm forwarding a bug from PyOpenGL. The developer, Mike Fletcher, is
having troubles accessing a numpy scalar with the __array_interface__.
Is this supposed to work? Or should __array_interface__ trigger an
AttributeError on a numpy scalar? Note that I haven't done any digging
on this
Travis E. Oliphant wrote:
Andrew Straw wrote:
Hi,
I'm forwarding a bug from PyOpenGL. The developer, Mike Fletcher, is
having troubles accessing a numpy scalar with the __array_interface__.
Is this supposed to work? Or should __array_interface__ trigger an
AttributeError on a numpy scalar
dmitrey wrote:
The only one thing I'm very interested in for now - why the most
simplest matrix operations are not implemented to be parallel in numpy
yet (for several-CPU computers, like my AMD Athlon X2).
For what it's worth, sometimes I *want* my numpy operations to happen
only on one
Considering that many of the statistical functions (mean, std, median)
must iterate over all the data and that people (or at least myself)
typically call them sequentially on the same data, it may make sense to
make a super-function with less repetition.
Instead of:
x_mean = np.mean(x)
x_median =
I'm pretty sure there's code floating around the pyglet mailing list.
I'd be happy to add it to
http://code.astraw.com/projects/motmot/wiki/pygarrayimage if it seems
reasonable. (pygarrayimage goes from numpy array to pyglet texture).
Brian Blais wrote:
On Jan 29, 2008, at Jan 29:8:24 PM, Andrew
[EMAIL PROTECTED] wrote:
Robin wrote
I'm not sure why they would be doing this - to me it looks they might
be using Image as a convenient way to store some other kind of data...
thanks Robin,
I am wondering if there is a more straightforward way to do these..
especially the vector to image
Matthieu Brucher wrote:
2008/4/3, Chris Barker [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED]:
Robert Kern wrote:
Just since that has been discussed a LOT, for years, I want to be
clear:
Different versions of Microsoft's compiler use different
libraries for
the
This is off-topic and should be directed to the pyrex/cython list, but
since we're on the subject:
I suppose the following is true, but let me ask, since I have not used
Cython. Please correct me if I'm wrong.
I have a bunch of pyrex compiled .pyx code. If I start adding some
Cython compiled
Hi Zach,
I have a similar loop which I wrote using scipy.weave. This was my first
foray into weave, and I had to dig through the intermediate C sources to
find the macros that did the indexing in the way I make use of here, but
this snipped may get you started. There are 2 functions, which each
Robin wrote:
Hi,
I am starting to push the limits of the available memory and I'd like
to understand a bit better how Python handles memory...
This is why I switched to 64 bit linux and never looked back.
If I try to allocate something too big for the available memory I
often get a
I've got a big element array (25 million int64s) that searchsorted()
takes a long time to grind through. After a bit of digging in the
literature and the numpy source code, I believe that searchsorted() is
implementing a classic binary search, which is pretty bad in terms of
cache misses. There
architectures.
-Andrew
Andrew Straw wrote:
I've got a big element array (25 million int64s) that searchsorted()
takes a long time to grind through. After a bit of digging in the
literature and the numpy source code, I believe that searchsorted() is
implementing a classic binary search, which
I will post any new insights as I continue to work on this...
OK, I save isolated a sample of my data that illustrates the terrible
performance with the binarysearch. I have uploaded it as a pytables file
to http://astraw.com/framenumbers.h5 in case anyone wants to have a look
themselves.
Charles R Harris wrote:
On Wed, May 14, 2008 at 8:09 AM, Andrew Straw [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
Quite a difference (a factor of about 3000)! At this point, I haven't
delved into the dataset to see what makes it so pathological --
performance is nowhere
Charles R Harris wrote:
On Wed, May 14, 2008 at 2:00 PM, Andrew Straw [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
Charles R Harris wrote:
On Wed, May 14, 2008 at 8:09 AM, Andrew Straw
[EMAIL PROTECTED] mailto:[EMAIL PROTECTED]
mailto:[EMAIL PROTECTED
Jarrod Millman wrote:
Please test the release candidate:
svn co http://svn.scipy.org/svn/numpy/tags/1.1.0rc1 1.1.0rc1
Thanks, Jarrod.
I have packaged SVN trunk from r5189 and made a Debian source package
(based on a slightly old version the Debian Python Modules Team's numpy
package with
Thanks, Jarrod.
Should I replace the old numpy 1.0.4 information at
http://www.scipy.org/Download with the 1.1.0? It's still listing 1.0.4,
but I wonder if there's some compatibility with scipy 0.6 issue that
should cause it to stay at 1.0.4. In either case, I think the page
should be updated
Alan McIntyre wrote:
On Mon, Jun 9, 2008 at 3:41 AM, Stéfan van der Walt [EMAIL PROTECTED] wrote:
I suggest we also remove ParametricTestCase now.
I don't mind converting the existing uses (looks like it's only used 5
times) to something else, it was causing trouble for me with nose
Charles R Harris wrote:
Dear Friends,
Our wonderful buildbot is in declining health. The Mac can't update
from svn, Andrew's machines are offline, the Sparcs have lost their
spark, and bsd_64 is suffering from tolist() syndrome:
AFAIK, I don't have any machines on the buildbot... Is there
Stéfan van der Walt wrote:
2008/6/18 Alan McIntyre [EMAIL PROTECTED]:
Is next release referring to 1.2 or the release after that? If it's
the release after 1.2, then I assume that 1.2 must still be able to
run all its tests without nose.
Alternatively, we could distribute Nose
Mike Sarahan wrote:
I agree that the components are very small, and in a numeric sense, I
wouldn't worry at all about them, but the image result is simply noise,
albeit periodic-looking noise.
Fernando Perez and John Hunter have written a nice FFT image denoising
example:
Robert Kern wrote:
On Wed, Jul 23, 2008 at 16:56, Fernando Perez [EMAIL PROTECTED] wrote:
Howdy,
I was just trying to explain to a new user how to build numpy from
source on ubuntu and I realized that there's not much info on this
front in the source tree. Scipy has a nice INSTALL.txt that
Eric Firing wrote:
Andrew Straw wrote:
Just for reference, you can find the build dependencies of any Debian
source package by looking at its .dsc file. For numpy, that can be found
at http://packages.debian.org/sid/python-numpy
Currently (version 1.1.0, debian version 1:1.1.0-3
Looking at the code, but not testing it -- this looks fine to me. (I
wrote the original NPY_VERSION stuff and sent it to Travis, who modified
and included it.)
I have added a couple of extremely minor points to the code review tool
-- as much as a chance to play with the tool as to comment on
Robert Kern wrote:
On Sat, Aug 16, 2008 at 04:34, Jon Wright [EMAIL PROTECTED] wrote:
Travis, Stéfan,
I missed Travis mail previously. Are you *really* sure you want force
all C code which uses numpy arrays to be recompiled? If you mean that
all your matplotlib/PIL/pyopengl/etc users are
Jarrod Millman wrote:
On Thu, Aug 28, 2008 at 7:48 AM, Travis E. Oliphant
[EMAIL PROTECTED] wrote:
+1 on what Andrew said.
I don't really care that much, but I do think API is better than
FEATURE. I would think that there may be times when we change the API
but not the features
Alan Jackson wrote:
Looking for advice on a good way to handle this problem.
I'm dealing with large tables (Gigabyte large). I would like to
efficiently subset values from one column based on the values in
another column, and get arrays out of the operation. For example,
say I have 2
Hi, with numpy 1.2.0rc1 running 'python -c import numpy; numpy.test()'
on my Ubuntu Hardy amd64 machine results in 1721 tests being run and 1
skipped. So far, so good.
However, if I run numpy.test(10,10,all=True), I get 1846 tests with:
the message FAILED (SKIP=1, errors=8, failures=68)
Hanno Klemm wrote:
Hi,
I the following problem: I have a relatively long array of points
[(x0,y0), (x1,y1), ...]. Apparently, I have some duplicate entries, which
prevents the Delaunay triangulation algorithm from completing its task.
Question, is there an efficent way, of getting rid of
John Hunter wrote:
Andrew, since you are the original author of the isnan port, could you
patch the branch and the trunk to take care of this?
Done in r6791 and r6792.
Sorry for the trouble.
Now I just hope we don't get a problem with long long, although now if
_ISOC99_SOURCE is defined,
Hi, I just noticed that the N-D array interface page is outdated and
doesn't mention the buffer interface that is standard with Python 2.6
and Python 3.0:
http://numpy.scipy.org/array_interface.shtml
This page is linked to from http://numpy.scipy.org/
I suggest, at the minimum, modifying the
or give me the
appropriate permissions so I can do it? I think even deleting the page
is better than keeping it as-is.
-Andrew
Andrew Straw wrote:
Hi, I just noticed that the N-D array interface page is outdated and
doesn't mention the buffer interface that is standard with Python 2.6
Fernando Perez wrote:
On Wed, Feb 11, 2009 at 6:17 PM, David Cournapeau courn...@gmail.com wrote:
Unfortunately, it does require some work, because hardy uses g77
instead of gfortran, so the source package has to be different (once
hardy is done, all the one below would be easy, though). I
David Cournapeau wrote:
Andrew Straw wrote:
Fernando Perez wrote:
On Wed, Feb 11, 2009 at 6:17 PM, David Cournapeau courn...@gmail.com
wrote:
Unfortunately, it does require some work, because hardy uses g77
instead of gfortran, so the source package has
OK, I think you're concerned about compatibility of Python extensions
using fortran. We don't use any (that I know of), so I'm going to stop
worrying about this and upload .debs from your .dsc (or very close) to
my repository...
...except for one last question: If Hardy uses the g77 ABI but I'm
David Cournapeau wrote:
* Integration with setuptools and eggs, which enables things like
namespace packages.
This is not. eggs are not specified, and totally implementation defined.
I tried some time ago to add an egg builder to scons, but I gave up.
And I don't think you can reuse
David Cournapeau wrote:
On Thu, Feb 19, 2009 at 3:24 PM, Andrew Straw straw...@astraw.com wrote:
It's an interesting idea to build Python package distributions without
distutils. For pure Python installables, if all you seek better is
distutils, the bar seems fairly low.
:) Being
Darren,
What's the difference between asanyarray(y) and array(y, copy=False,
subok=True)? I thought asanyarray would also do what you want.
-Andrew
Darren Dale wrote:
On Sun, Feb 22, 2009 at 3:22 PM, Darren Dale dsdal...@gmail.com
mailto:dsdal...@gmail.com wrote:
On Sun, Feb 22, 2009
Given what you're doing, may I also suggest having a look at
http://code.astraw.com/projects/motmot/wxglvideo.html
-Andrew
Chris Colbert wrote:
As an update for any future googlers:
the problem was with revpixels = pixeldata[::-1,:,;:-1] which apparently
returns an array that is
everything is actually correct.
Thanks,
Andrew
Stéfan van der Walt wrote:
2009/2/3 Andrew Straw straw...@astraw.com:
Can someone with appropriate permissions fix the page or give me the
appropriate permissions so I can do it? I think even deleting the page
is better than keeping
Hi,
I created a login for the numpy documentation editor but cannot remember
my password. Would it be possible to have it sent to me or a new one
generated? It would be great to have a button on the website so that I
could do this myself, but if that's too much pain, my username is
AndrewStraw.
Pauli Virtanen wrote:
Hi,
Fri, 06 Mar 2009 09:16:33 -0800, Andrew Straw wrote:
I have updated http://numpy.scipy.org/array_interface.shtml to have a
giant warning first paragraph describing how that information is
outdated. Additionally, I have updated http://numpy.scipy.org/ to point
Hi all,
I have been doing some editing of http://numpy.scipy.org . In general,
however, lots of this page is redundant and outdated compared to lots of
other documentation that has now sprung up. Shall we kill this page off,
redirect it to another page, or continue updating it? (For this latter
Andrew Straw wrote:
Pauli Virtanen wrote:
Hi,
Fri, 06 Mar 2009 09:16:33 -0800, Andrew Straw wrote:
I have updated http://numpy.scipy.org/array_interface.shtml to have a
giant warning first paragraph describing how that information is
outdated. Additionally, I have updated http
Gael Varoquaux wrote:
On Sun, Mar 08, 2009 at 10:18:11PM -0700, Andrew Straw wrote:
OK, I now have a password (thanks Gaël), but I don't have edit
permissions on that page. So I'm attaching a patch against that page
source that incorporates the stuff that was on the old page that's
Matthieu Brucher wrote:
One thing about git-svn is that this is not really needed if you just
use git and I installed git from source on many linuxes and clusters
and it just works, as it is just pure C. I usually just use git-svn on
my laptop/workstation, where I install the Debian/Ubuntu
Eric Firing wrote:
Sure enough, that is what I was looking for. (gitweb doesn't seem to
have the annotate [or blame, in git-speak] option, or the graph.)
gitweb does, you have to turn it on, though...
You need to add this to your gitweb.conf, though:
$feature{'blame'}{'default'} = [1];
Fadhley Salim wrote:
Thomasm,
What want is the current latest Numpy as a win32 .egg file for Python
2.4.4. I'm not bothered how I get there. We've been able to compile
* Dont care how I make it as long as it works!
Are you aware that the reason numpy is not distributed as an .egg is so
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