at
holoviews.org today!
Jean-Luc R. Stevens
Philipp Rudiger
James A. Bednar
Continuum Analytics, Inc., Austin, TX, USA
School of Informatics, The University of Edinburgh, UK
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336
ilding on
CentOS 5-6 BTW (I believe the former is about to be unsupported).
Just skimming the thread...
Cheers,
James.
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comment that
not every installation is someone trying to get numpy on their
laptop...
Cheers,
James.
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, the project can be forked as an
option of last resort. Nothing is set in stone, nor code lost.
Just saying (I probably won't reply to any criticism or corrections,
to avoid adding peripheral noise/heat to the thread).
Cheers,
James (from, but not on behalf of, a non-profit research facility
upcoming SciPy and EuroSciPy
talks in Austin and Cambridge (or read the paper at http://goo.gl/NH9FTB)!
Philipp Rudiger
Jean-Luc R. Stevens
James A. Bednar
The University of Edinburgh
School of Informatics
--
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Scotland, with registration
obscuring the underlying data objects
- Includes interfaces to pandas and Seaborn
- Winner of the 2015 UK Open Source Award
For the rest, check out ioam.github.io/holoviews!
Jean-Luc Stevens
Philipp Rudiger
James A. Bednar
The University of Edinburgh
School of Informatics
--
The University
| Date: Fri, 05 Sep 2014 13:19:57 -0400
| From: Neal Becker ndbeck...@gmail.com
|
| I think it's somewhat debatable whether generating a different
| sequence of random numbers counts as breaking backward
| compatibility.
Please don't ever, ever break the sequence of numpy's random numbers!
, Aug 21, 2014 at 2:34 AM, James Crist crist...@umn.edu wrote:
All,
I have a C function func that takes in scalar arguments, and an array of
fixed dimension that is modified in place to provide the output. The
prototype is something like:
`void func(double a, double b, double c, double
All,
I have a C function func that takes in scalar arguments, and an array of
fixed dimension that is modified in place to provide the output. The
prototype is something like:
`void func(double a, double b, double c, double *arr);`
I've wrapped this in Cython and called it from python with no
:
On Fri, Sep 6, 2013 at 10:19 AM, James Bergstra bergs...@iro.umontreal.ca
wrote:
Hi, could someone help me understand why this assertion fails?
def test_is(self):
a = np.empty(1)
b = np.empty(1)
if a.data is not b.data:
assert id(a.data) != id(b.data) # -- fail
I'm
Hi, could someone help me understand why this assertion fails?
def test_is(self):
a = np.empty(1)
b = np.empty(1)
if a.data is not b.data:
assert id(a.data) != id(b.data) # -- fail
I'm trying to write an alternate may_share_memory function.
Thanks,
- James
Thanks, this is exactly what I was looking for. I'll look into what this
Diophantine equation is. Also, relatedly, a few months ago Julian Taylor at
least wrote what was there in C, which made it faster, if not better.
- James
On Fri, Sep 6, 2013 at 1:27 PM, Robert Kern robert.k...@gmail.com
at 12:48 PM, James Bergstra
bergs...@iro.umontreal.cawrote:
Thanks for the tips! FWIW my guess is that since '.data' is dynamically
generated property rather than an attribute, it is being freed and
re-allocated in the loop, and once for each of my id() expressions.
On Fri, Sep 6, 2013 at 12
the section which does the initialization of
the array it could use that fill value instead of 1 or 0. Is this a
naive assumption?
Thanks in advance for your help with this issue.
--James
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Note: I started a thread in StackOverflow a few days ago with this
question, but I have not received any response yet (the link is:
http://stackoverflow.com/questions/16093910/numpy-and-scipy-static-vs-dynamic-loading
)
The question is the following:
Say that I build ATLAS with LAPACK as
| From: Rebekah Pratt
| Date: Jun 25 23:59:59 2012 -0400
|
| Hey, greetings from orlando! How has re entry to texas been? Our
| holiday is going well, although a little fast. The whole disney
| experience is cooler than I was expecting. We are all a bit tired
| out though, and adah moody
On Thu, Jun 14, 2012 at 4:00 AM, Olivier Grisel
olivier.gri...@ensta.org wrote:
2012/6/13 James Bergstra bergs...@iro.umontreal.ca:
Further to the recent discussion on lazy evaluation numba, I moved
what I was doing into a new project:
PyAutoDiff:
https://github.com/jaberg/pyautodiff
On Thu, Jun 14, 2012 at 3:38 PM, Nathaniel Smith n...@pobox.com wrote:
On Thu, Jun 14, 2012 at 7:53 PM, James Bergstra
bergs...@iro.umontreal.ca wrote:
On Thu, Jun 14, 2012 at 11:01 AM, Nathaniel Smith n...@pobox.com wrote:
Indeed that would be great as sympy already has already excellent
the original function wrong
b) that autodiff is mis-computing a gradient.
- James
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graph optimizations work their magic). It's not clear from the
code fragment what the various types in play are (see previous rant on
static analysis!), but an autodiff PR with a test case would help sort
out any remaining problems if you want to follow up on this.
- James
or a theano bytecode front-end. For now it just compiles
and runs the Theano graph that it built.
It's still pretty rough (you'll see if you look at the code!) but I'm
excited about it.
- James
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On Mon, Jun 11, 2012 at 12:03 AM, James Bergstra
bergs...@iro.umontreal.ca wrote:
If anyone is interested in my ongoing API bytecode adventure in why
/ how lazy computing could be useful, I've put together a few tiny
hypothetically-runnable examples here:
https://github.com/jaberg/numba/tree
was recently using Theano as a backend. I don't think it works
right now but FWIW it is still close to running.
Sorry for the long post,
- James
On Wed, Jun 6, 2012 at 5:22 AM, Dag Sverre Seljebotn
d.s.seljeb...@astro.uio.no wrote:
On 06/06/2012 12:06 AM, mark florisson wrote:
On 5 June 2012 22:36
bincount([]) makes no sense, but if a minlength argument is provided,
then the routine should succeed.
It fails in 1.6.1, has it been fixed in master?
- James
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On Sat, Feb 25, 2012 at 5:13 PM, Alan G Isaac alan.is...@gmail.com wrote:
On 2/25/2012 4:44 PM, James Bergstra wrote:
bincount([]) makes no sense,
I disagree:
http://permalink.gmane.org/gmane.comp.python.numeric.general/42041
gmane is down to me at the moment, but if this argues
# re-run the compiled expression on the new value
a, b = expr.run()
- JB
--
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Research Scientist
Rowland Institute, Harvard University
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On Mon, Feb 20, 2012 at 1:01 PM, James Bergstra james.bergs...@gmail.comwrote:
On Mon, Feb 20, 2012 at 12:28 PM, Francesc Alted franc...@continuum.iowrote:
On Feb 20, 2012, at 6:18 PM, Dag Sverre Seljebotn wrote:
You need at least a slightly different Python API to get anywhere, so
numexpr
Looks like Dag forked the discussion of lazy evaluation to a new thread
([Numpy-discussion] ndarray and lazy evaluation).
There are actually several projects inspired by this sort of design: off
the top of my head I can think of Theano, copperhead, numexpr, arguably
sympy, and some non-public
On Mon, Feb 20, 2012 at 2:57 PM, Lluís xscr...@gmx.net wrote:
James Bergstra writes:
[...]
I should add that the biggest benefit of expressing things as compound
expressions in this way is not in saving temporaries (though that is
nice) it's
being able to express enough computation work
On Thu, Jul 7, 2011 at 4:59 PM, James Bergstra
bergs...@iro.umontreal.ca wrote:
On Thu, Jul 7, 2011 at 1:10 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Thu, Jul 7, 2011 at 11:03 AM, James Bergstra bergs...@iro.umontreal.ca
wrote:
In numpy 1.5.1, the functions PyArray_MoveInto
of the
underlying matrix instead of the first two columns. PyArray_CopyInto
does the same.
Is there something subtle going on here?
James
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On Thu, Jul 7, 2011 at 1:10 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Thu, Jul 7, 2011 at 11:03 AM, James Bergstra bergs...@iro.umontreal.ca
wrote:
In numpy 1.5.1, the functions PyArray_MoveInto and PyArray_CopyInto
don't appear to treat strides correctly.
Evidence
On my mac (10.6.5) I'm running python2.6 with numpy 1.5.0.
While using f2py with
f2py -c --fcompiler=gnu95 --f77flags='-m32 -O1 -fno-second-underscore
-fbounds-check' src/mars.pyf src/mars.f
It compiles but has link warnings.
-m32 is not being passed to gcc.
ld: warning: in
| Date: Thu, 27 Jan 2011 16:32:22 -0700
| From: Charles R Harris charlesr.har...@gmail.com
|
| On Thu, Jan 27, 2011 at 4:23 PM, Robert Kern robert.k...@gmail.com wrote:
|
| On Thu, Jan 27, 2011 at 17:17, Travis Oliphant teoliph...@gmail.com
wrote:
|
|Hey all,
|
|What is the
I find that numpy.max(0, 1e-6) == 0 is confusing, because it makes bugs
hard to spot. The doc says that the second argument to max is an optional
integer. My bad.
But could the function raise an error if it is passed an invalid 'axis'
argument? That would have helped.
James
--
http://www
I have two vectors of integers of not necessarily the same length.
Consider the hypothetical function match (or if you are familiar to R
then consider that function).
match(v1, v2) = returns a boolean array of length len(v1) indicating
whether element i in v1 is in v2.
I cannot find this
Ping?
On 5/13/2010 6:34 PM, Jim Porter wrote:
Ok, let's try sending this message again, since it looks like I can't
send from gmane...
(See discussion on python-list at
http://permalink.gmane.org/gmane.comp.python.general/661328 for context)
numpy.zeros_like contains the following code:
indexing... at least the array-type fancy indexing, if not the boolean
kind. If someone knows of an implementation please let me know. I'll
email the list again if I make any serious progress on it.
James
--
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and it will instead use an available CUDA-
capable Nvidia GPU instead of the CPU. I'll admit, when James Bergstra
initially told me about this plan to make it possible to transparently
switch to running stuff on the GPU, I thought it was so ambitious that
it would never happen. Then it did
Thanks all for your help, I think I'm on my way again.
The catch in the first place was not being confident that a
PyArray_Scalar was the thing I needed. I grep'd the code for uint8,
int8 and so on and could not find their definitions.
On first reading I overlooked the PyArray_Scalar link in
On Mon, Mar 1, 2010 at 1:44 AM, David Cournapeau courn...@gmail.com wrote:
On Mon, Mar 1, 2010 at 1:35 PM, James Bergstra
bergs...@iro.umontreal.ca wrote:
Could someone point me to documentation (or even numpy src) that shows
how to allocate a numpy.int8 in C, or check to see if a PyObject
On Tue, Mar 2, 2010 at 3:09 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
James Bergstra wrote:
Maybe I'm missing something... but I don't think I want to create an array.
In [3]: import numpy
In [4]: type(numpy.int8())
Out[4]: type 'numpy.int8'
In [5]: isinstance(numpy.int8
On Tue, Mar 2, 2010 at 7:18 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
James Bergstra wrote:
On Tue, Mar 2, 2010 at 3:09 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
James Bergstra wrote:
Maybe I'm missing something... but I don't think I want to create an array
On Tue, Mar 2, 2010 at 7:32 PM, David Warde-Farley d...@cs.toronto.edu wrote:
On 2-Mar-10, at 7:23 PM, James Bergstra wrote:
Sorry... again... how do I make such a scalar... *in C* ? What would
be the recommended C equivalent of this python code? Are there C
type-checking functions
Could someone point me to documentation (or even numpy src) that shows
how to allocate a numpy.int8 in C, or check to see if a PyObject is a
numpy.int8?
Thanks,
James
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length 3.
A 32bit computer gives an error:
TypeError: array cannot be safely cast to required type
If I change the int64 cast to an int32 cast then it works on both machines.
Thanks,
James
--
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--
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at an odd offset... it would
be impossible. It would even be impossible if there were a dimension
with stride 1 but it had shape of 1 too.
I can't think of an algorithm off the top of my head that would do
this in a quick and elegant way.
James
On Sun, Nov 29, 2009 at 10:36 AM, Zachary Pincus
Pearu,
Thanks. a follow question.
Using fortran
subroutine calc(j)
Cf2py intent(callback) pycalc
external pycalc
Cf2py integer dimension(1), intent(in,out):: j
integer j(1)
print *, 'in fortran before pycalc ',
'j=', j(1)
call pycalc(j)
print *, 'in fortran after pycalc ', '
j=', j(1)
While using the call-back feature of
f2py I stumbled across what appears
to be a bug and I'm asking the community to look into this.
Background: I'm in the middle of converting some legacy fortran to
python.
There is one routine that is particulary thorny that calls more
easily
convertible
On Tue, Nov 17, 2009 at 9:53 PM, Robert Kern robert.k...@gmail.com wrote:
On Tue, Nov 17, 2009 at 20:48, James Bergstra bergs...@iro.umontreal.ca
wrote:
Is it by design that numpy.sqrt(None) raises an AttributeError: sqrt?
Yes. numpy.sqrt() is a ufunc. Ufuncs take their arguments and try
(here None, as opposed to the
numpy module).
Now I'm off to delete all the getattr(numpy, 'sqrt') calls I littered
through a few files...
James
--
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--
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On Tue, Nov 10, 2009 at 7:07 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
Hi all,
I have a bunch of points in 2-d space, and I need to find out which
pairs of points are within a certain distance of one-another (regular
old Euclidean norm).
scipy.spatial.KDTree.query_ball_tree()
On Tue, Nov 10, 2009 at 8:17 PM, Christopher Barker
chris.bar...@noaa.gov wrote:
James Bergstra wrote:
In some cases a brute-force approach is also good.
true.
If r is a matrix of shape Nx2:
(r*r).sum(axis=1) -2 * numpy.dot(r, r.T) +
(r*r).sum(axis=1).reshape((r.shape[0], 1)) thresh**2
be
adding lots of random noise to your hash key by doing this. This
could cause equal ndarrays to hash to different values -- not good.
Make sure memory is contiguous before hashing the .data. Flatten()
does this i think, as does copy(), array(), and many others.
James
--
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):
tmp = u[j,i]
u[j,i] = ((u[j-1, i] + u[j+1, i])*dx2 +
(u[j, i-1] + u[j, i+1])*dy2)*dnr_inv
diff = u[j,i] - tmp
err += diff*diff
return np.sqrt(err)
--
James Snyder
Biomedical Engineering
Northwestern University
?) will use an integrated memory system that might make
'copying to the GPU' a non-issue... but we're not there yet I think...
James
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://www.pylearn.org/theano
http://code.google.com/p/theano-cuda-ndarray/
http://code.google.com/p/cuda-ndarray/
James
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I could do.
Cheers,
James.
Hi Stefan,
Never mind. I just found the Sprint website and read the
description. I'm sorry I hadn't found this sooner. I would have made
plans to stay and help. My apologizes.
Sorry,
Chris
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appreciate it if someone who knows of a similar project would let me
know about it. Otherwise we'll keep plugging away at replicating core
ndarray interface elements (operators, math.h-type functions, array
indexing, etc.)
http://code.google.com/p/cuda-ndarray/
James
generation mechanism similar to
weave. This algorithm is used in theano-cuda-ndarray.
Scipy.weave could be very useful for generating code for specific
shapes/ndims on demand, if weave could use nvcc.
James
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graph you can do cute stuff
like automatic differentiation. We're currently working on the bridge
between theano and cuda so that you declare certain inputs as residing
on the GPU instead of the host memory, so you don't have to transfer
things to and from host memory as much.
James
note that the distribution directory being created is build/
src.linux-x86_64-2.4 - not i386. Can I force the architecture in the
configure step, as it appears this would be the problem (hinted at by
LONG_BIG wrong for platform error).
Any hints gratefully received!
Regards,
James
In revision 6609, numpy fails to build on linux x86_64 due to an extra
comma on line 779 of numpy/core/src/scalartypes.inc.src.
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' raises an ImportError, but this does not happen with the
release version, where multiarray functions seem to work.
Could this be related to the PyImport_Import and PyImport_ImportModule
changes made in 2.6 (bottom of
http://docs.python.org/whatsnew/2.6.html)?
James
Windows debug extensions have a suffix, d. If you don't install the
debug version of numpy, you can't use it with debug Python.
Ah, thank you. Sorry for the newb question: how do you install the
debug version (for msvc)?
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/recommendations, I would be glad to fix this (e.g. how is this
supposed to work ?)
I'm not sure if there's a better way, but I've found it easiest to run
python via a debug run from within VS, installing and testing numpy
from there. The 2.6.1 sources build fine with VS2008.
James
The following are very simple changes that allow the 2to3 program to
run on numpy without warnings. Can someone check / commit?
numpy/linalg/lapack_lite/make_lite.py:
144c144
if 'BLAS' in filename
---
if 'BLAS' in filename:
numpy/distutils/misc_util.py:
957c957,958
There are also other (possibly many, still working on this) files that
require syntactic changes to run post 2to3.
Is there anywhere specific I should upload these changes? Is this
list appropriate? Is there a developer I can send these and future
patches to?
James.
Date: Tue, 3 Feb 2009 01
Hi,
I am interested in contributing to the port of NumPy to Python 3. Who
I should coordinate effort with?
I have started at the Python end of the problem (as opposed to
http://www.scipy.org/Python3k), e.g. I have several patches to get
2to3 to work on NumPy's Python source code.
James
Scott Sinclair wrote:
2008/12/9 Angus McMorland [EMAIL PROTECTED]:
Hi James,
2008/12/8 James [EMAIL PROTECTED]:
I have a very simple plot, and the lines join point to point, however i
would like to add a line of best fit now onto the chart, i am really new
to python etc, and didnt
Hi,
I am trying to plot a line of best fit for some data i have, is there a
simple way of doing it?
Cheers
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([ 20.08553696], dtype=float32)
If it helps:
$ uname -a
Linux lewis 2.6.27-7-generic #1 SMP Tue Nov 4 19:33:06 UTC 2008 x86_64 GNU/Linux
James
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curious to know
what's wrong.
James
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and never progresses further.
James
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(%rax,%rax,1)
292cc: 00 00 00 00
---
Not sure if i'm reading this correctly, but the first line seems to be
an unconditional jump to itself, hence an infinite loop?
James
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cflags, just running 'python setup.py build'.
James
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It's working on the buildbots. Did you remove the build directory first?
Oops. Great, all working now!
James
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I also get the same on my 64-bit linux Fedora rawhide with
...
Thanks, I've submitted this as ticket #952.
James
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Anyone?
James
On Thu, Nov 6, 2008 at 2:53 PM, James Philbin [EMAIL PROTECTED] wrote:
Hi,
I might be doing something stupid so I thought i'd check here before
filing a bug report.
Firstly:
In [8]: np.__version__
Out[8]: '1.3.0.dev5883'
Basically, pickling an element from a recarray seems
'), ('b', 'f4')])
In [5]: arr[0]
Out[5]: (1.0, 1.0, 1.0)
In [6]: import cPickle; cPickle.loads(cPickle.dumps(arr[0]))
Out[6]: (0.0, 0.0, 1.8643547392640242e-38)
Thanks,
James
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One operator which could be used is '%'. We could keep the current
behaviour for ARRAY%SCALAR but have ARRAY%ARRAY as being matrix
multiplication. It has the same precedence as *,/.
James
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This hack for defining infix operators might be relevant:
http://code.activestate.com/recipes/384122/
James
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might be useful?
James
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On Sat, 23 Aug 2008, Stéfan van der Walt wrote:
2008/8/23 Travis E. Oliphant [EMAIL PROTECTED]:
By the way, as promised, the NumPy book is now available for download
and the source to the book is checked in to the numpy SVN tree:
http://svn.scipy.org/svn/numpy/trunk/numpy/doc/numpybook
We
will find those in SciPy too.
Would someone point me to 1-D cubic spline functions either in numarray
or numpy? and their help pages?
Try looking at the cookbook:
http://scipy.org/Cookbook
I use python 2.3.5 and numpy 1.0.1. Are they too old to use cubic spline?
I doubt it.
Cheers,
James
as an
attachment? Let me know if I can provide any more info.
Thanks a lot,
James.
---
[EMAIL PROTECTED] DRSetupScripts]$ python
Python 2.5.1 (r251:54863, Jul 28 2008, 19:08:11)
[GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-20)] on linux2
Type help, copyright, credits or license for more information
and got the following. Does that help?
Thanks,
James.
---
GNU gdb Red Hat Linux (5.3.90-0.20030710.40rh)
Copyright 2003 Free Software Foundation, Inc.
GDB is free software, covered by the GNU General Public License, and you are
welcome to change it and/or distribute copies of it under certain
things uniform across our sites though.
Thanks!
James.
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Thanks everyone. I think I might try using the Netlib BLAS, since
it's a server installation... but please let me know if you'd like
me to troubleshoot this some more (the sooner the easier).
James.
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.
James.
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workstation. Anyway, I have submitted an ATLAS
support request so they're aware of it:
https://sourceforge.net/tracker/index.php?func=detailaid=2032011group_id=23725atid=379483
Cheers,
James.
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. Should NumPy coding style cater for my eccentric C
compiler or is this all above board?
Hope I'm not being stupid with the first thing.
Thanks,
James.
---
cc: _configtest.c
cc _configtest.o -L/astro/iraf/solsparc/gempylocal/lib -L/usr/local/lib
-L/usr/lib -o _configtest
_configtest
success
it being due to the ctypes
problem so I'd be grateful if someone can confirm that. In
fact, ctypes is not listed under NumPy prerequisites (which,
incidentally, is mistyped) in the FAQ and I believe it wasn't
part of Python either until 2.5.
Thanks,
James
.
-jsnyder
--
James Snyder
Biomedical Engineering
Northwestern University
[EMAIL PROTECTED]
PGP: http://fanplastic.org/key.txt
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PM, James Snyder [EMAIL PROTECTED] wrote:
I've been running out of trunk recently, and I've noted that an rc release
has appeared and the 1.1.x branch has been regenerated.
Which would be most helpful to provide feedback from?
Hmmm. I deleted the 1.1.x branch and it doesn't appear to exist
self.theta[idx_spk] = self.theta[idx_spk] + self.b
self.prev_u = self.u
self.prev_theta = self.theta
--
James Snyder
Biomedical Engineering
Northwestern University
[EMAIL PROTECTED]
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:
2008/5/19 James Snyder [EMAIL PROTECTED]:
I can provide the rest of the code if needed, but it's basically just
filling some vectors with random and empty data and initializing a few
things.
It would kind of help, since it would make it clearer what's a scalar
and what's an array, and what
performance. It'd be nice,
but again I'm just trying to put together decent, fairly efficient
numpy code.
On Mon, May 19, 2008 at 3:53 PM, Christopher Barker
[EMAIL PROTECTED] wrote:
Anne Archibald wrote:
2008/5/19 James Snyder [EMAIL PROTECTED]:
I can provide the rest of the code if needed
in 1.784s
OK
Out[2]: unittest._TextTestResult run=996 errors=0 failures=0
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James Snyder
Biomedical Engineering
Northwestern University
[EMAIL PROTECTED]
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Numpy
a = fromiter(self.makegen(), int)
MemoryError: cannot allocate array memory
--
Ran 991 tests in 1.603s
FAILED (errors=3)
unittest._TextTestResult run=991 errors=3 failures=0
--
James Snyder
Biomedical Engineering
Northwestern
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