Folks,
We are happy to announce the release of (long delayed) matplotlib 2.0!
This release completely overhauls the default style of the plots.
The source tarball and wheels for Mac, Win, and manylinux for python 2.7,
3.4-3.6 are available on pypi
pip install --upgrade matplotlib
and conda p
Folks,
Over at h5py we are trying to get a release out and have discovered (via
debian) that on ppc64el there is an apparent disagreement between the size
of a native long double according to hdf5 and numpy.
For all of the gorey details see: https://github.com/h5py/h5py/issues/817 .
In short, `n
Folks,
We are happy to announce matplotlib v2.0.0rc2 !
Please re-distribute this widely.
This is the final planned release candidate for the long awaited mpl v2.0
release.
For the full details of what is new please see
http://matplotlib.org/2.0.0rc2/users/whats_new.html
Some of the highlights:
Folks,
I am happy to announce the next release of Cycler.
This will become the minimal version for the upcoming mpl v2.0 release.
http://matplotlib.org/cycler/
Feature release for `cycler`. This release includes a number of new
features:
- `Cycler` objecst learned to generate an `itertools.c
The test data for mpl is available as a sperate conda package,
matplotlib-tests. The reason for splitting it is 40Mb of tests images.
Tom
On Thu, Feb 4, 2016, 09:09 Pauli Virtanen wrote:
> 04.02.2016, 07:56, Nathaniel Smith kirjoitti:
> [clip]
> > Whoops, got distracted talking about the resul
h attempt should remain something external to Numpy itself
and be released on my Github account without being
integrated to Numpy?
Best regards,
--
Thomas Baruchel
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On Fri, Dec 4, 2015 at 6:13 AM, David Cournapeau wrote:
>
>
> On Fri, Dec 4, 2015 at 11:06 AM, Nathaniel Smith wrote:
>
>> On Fri, Dec 4, 2015 at 1:27 AM, David Cournapeau
>> wrote:
>> > I would be in favour of dropping 3.3, but not 2.6 until it becomes too
>> > cumbersome to support.
>> >
>> >
I would also vote for leaving them up.
On Sat, Nov 14, 2015 at 4:21 AM Ralf Gommers wrote:
> On Fri, Nov 13, 2015 at 9:04 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Fri, Nov 13, 2015 at 12:50 PM, Nathaniel Smith wrote:
>>
>>> On Nov 13, 2015 10:06 AM, "Charles R Ha
+1 to posting it as part of the documentation.
I also like the idea of numfocus hosting the whole collection of them
locally so that we can just link to them.
On Sat, Oct 31, 2015, 19:01 Ralf Gommers wrote:
> Hi all,
>
> On Wed, Oct 28, 2015 at 11:48 PM, Ralf Gommers
> wrote:
>
>>
>> Hi all, t
Hey all,
We are pleased to finally announce the release of matplotlib 1.5.0! It has
been over a year since the last feature release and we have had over 230
people contribute to this cycle.
This release of matplotlib has several major new features including
- Auto-redraw using the object-orien
I would suggest
%matplotlib notebook
It will still have to a nice png, but you get an interactive figure when it
is live.
I agree that making the example code Python3 is critical.
Tom
On Thu, Oct 1, 2015 at 8:05 PM Jaime Fernández del Río
wrote:
> On Thu, Oct 1, 2015 at 11:46 AM, Alex Rogozh
Does anybody know what happened to the following links on the NumPy
homepage (http://www.numpy.org/):
- http://wiki.scipy.org/Wiki/NumPy_for_Matlab_Users
- http://www.numpy.org/
- http://wiki.scipy.org/Numpy_Functions_by_Category
They have not been available for some time now ...
__
To respond to the devils advocate:
Creating this organizational framework is a one time boot-strapping
event. You could use wording like "The initial council will include those
who have made significant contributions to numpy in the past and want to be
on it" or "The initial council will be cons
Hi Sylvain,
Sylvain Corlay wrote:
> Hi Thomas,
>
> This is great news!
>
> FYI, the traitlets module has been undergoing significant refactoring
> lately, improving the API to favor a broader usage in the community.
> One reason for this is that several projects o
gt; membership in practice.
>
> > Someone(s) that may not have worked on the core code, but is a major
> > player in the community, perhaps as the leader of a Numpy-dependent
> > project. This would provide representation for the broad community.
>
> Pointing out features of the
Hi everyone,
We have released a small experimental package called numtraits that
builds on top of the traitlets package and provides a NumericalTrait
class that can be used to validate properties such as:
* number of dimension (for arrays)
* shape (for arrays)
* domain (e.g. positive, negative, r
Please give it a try! (linux64 conda builds are available on the tacaswell
anaconda.org channel)
https://github.com/matplotlib/matplotlib/releases/tag/v1.5.0rc1
This release contains many new features. The highlights include:
- the object oriented API will now automatically re-draw the figure
On Sun, Feb 22, 2015 at 5:56 PM, Aldcroft, Thomas <
aldcr...@head.cfa.harvard.edu> wrote:
>
>
> On Sun, Feb 22, 2015 at 5:46 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Sun, Feb 22, 2015 at 3:40 PM, Aldcroft, Tho
On Sun, Feb 22, 2015 at 5:46 PM, Charles R Harris wrote:
>
>
> On Sun, Feb 22, 2015 at 3:40 PM, Aldcroft, Thomas <
> aldcr...@head.cfa.harvard.edu> wrote:
>
>>
>>
>> On Sun, Feb 22, 2015 at 2:52 PM, Nathaniel Smith wrote:
>>
>>> On Sun,
On Sun, Feb 22, 2015 at 2:52 PM, Nathaniel Smith wrote:
> On Sun, Feb 22, 2015 at 10:21 AM, Aldcroft, Thomas
> wrote:
> > The idea of a one-byte string dtype has been extensively discussed twice
> > before, with a lot of good input and ideas, but no action [1, 2].
> >
&
The idea of a one-byte string dtype has been extensively discussed twice
before, with a lot of good input and ideas, but no action [1, 2].
tl;dr: Perfect is the enemy of good. Can numpy just add a one-byte string
dtype named 's' that uses latin-1 encoding as a bridge to enable Python 3
usage in t
On Tue, Aug 12, 2014 at 12:17 PM, Eelco Hoogendoorn <
hoogendoorn.ee...@gmail.com> wrote:
> Thanks. Prompted by that stackoverflow question, and similar problems I
> had to deal with myself, I started working on a much more general extension
> to numpy's functionality in this space. Like you noted
Just to follow-on to my previous email, our labeling convention is
described in more detail here:
https://github.com/astropy/astropy/wiki/Issue-labeling-convention
Cheers,
Tom
Thomas Robitaille wrote:
> The issue with 'low hanging fruit' is that who is it low-hanging fruit
>
ot;. I think it is a better
> name than "newcomers".
>
> On Wed, Nov 26, 2014 at 1:19 PM, Aldcroft, Thomas
> mailto:aldcr...@head.cfa.harvard.edu>>
> wrote:
>
>
>
> On Wed, Nov 26, 2014 at 8:24 AM, Charles R Harris
> mailto:charlesr.har...@gma
On Wed, Nov 26, 2014 at 8:24 AM, Charles R Harris wrote:
>
>
> On Wed, Nov 26, 2014 at 2:36 AM, Sebastian Berg <
> sebast...@sipsolutions.net> wrote:
>
>> On Mi, 2014-11-26 at 08:44 +, David Cournapeau wrote:
>> > Hi,
>> >
>> >
>> > Would anybody mind if I create a label "newcomers" on GH, an
CE=2 -fPIC
^C
obviously, the flags aren't used in python 3. Did I overlook something
here? Do $OPT/$FOPT only work in Python 2.7 by design, is this a bug or
did I miss something?
Cheers
Thomas
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y execption than silently continue my calculations with
useless/wrong results.
Cheers
Thomas
On 2014-07-24 11:59, Eelco Hoogendoorn wrote:
Arguably, this isn't a problem of numpy, but of programmers being
trained to think of floating point numbers as 'real' numbers, rather
t
on why this has not
been done?
Cheers
Thomas
[1]
http://mail.scipy.org/pipermail/numpy-discussion/2010-November/053697.html
[2]
http://numpy-discussion.10968.n7.nabble.com/Bug-in-numpy-mean-revisited-td1293.html
___
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On Fri, Jul 18, 2014 at 11:10 AM, Julian Taylor <
jtaylor.deb...@googlemail.com> wrote:
> On Thu, Jul 17, 2014 at 5:48 PM, Nathaniel Smith wrote:
> > On Tue, Jul 15, 2014 at 4:29 PM, Charles R Harris
> > wrote:
> >> Thinking more about it, the easiest thing to do might be to make the S
> dtype
>
On Thu, Jul 17, 2014 at 11:52 AM, Nathaniel Smith wrote:
> On Tue, Jul 15, 2014 at 7:40 PM, Aldcroft, Thomas
> wrote:
> >
> > On Sat, Jul 12, 2014 at 8:02 PM, Nathaniel Smith wrote:
> >>
> >> OTOH, fixed length nul padded latin1 would be useful for va
On Tue, Jul 15, 2014 at 11:15 AM, Charles R Harris <
charlesr.har...@gmail.com> wrote:
>
>
>
> On Tue, Jul 15, 2014 at 5:26 AM, Sebastian Berg <
> sebast...@sipsolutions.net> wrote:
>
>> On Sa, 2014-07-12 at 12:17 -0500, Charles R Harris wrote:
>> > As previous posts have pointed out, Numpy's `S`
On Wed, Jul 16, 2014 at 6:48 AM, Todd wrote:
> On Jul 16, 2014 11:43 AM, "Chris Barker" wrote:
> > So numpy should have dtypes to match these. We're a bit stuck, however,
> because 'S' mapped to the py2 string type, which no longer exists in py3.
> Sorry not running py3 to see what 'S' does now,
On Sat, Jul 12, 2014 at 8:02 PM, Nathaniel Smith wrote:
> On 12 Jul 2014 23:06, "Charles R Harris"
> wrote:
> >
> > As previous posts have pointed out, Numpy's `S` type is currently
> treated as a byte string, which leads to more complicated code in python3.
> OTOH, the unicode type is stored as
", or if others would agree with my suggestion to change the default to
"ddof=1"?
Thomas
---
Prof. (FH) PD Dr. Thomas Haslwanter
School of Applied Health and Social Sciences
University of Applied Sciences Upper Austria
FH OÖ Studienbetriebs GmbH
Garnisonstraße 21
4020 Linz/Austria
Tel.: +43
failed with exit status 1
The problem went away (and matplotlib installed cleanly) when I re-did
the whole shebang using numpy 1.8.0, so I suspect this was caused by
something in the rc.
Cheers
Thomas
On 2014-03-03 17:23, Charles R Harris wrote:
Hi All,
Julian Taylor has put windows bin
the
Bulldozer/Piledriver code -- from
https://github.com/xianyi/OpenBLAS/releases/tag/v0.2.9.rc1
Cheers
Thomas
On 2014-02-24 20:58, Michael Hughes wrote:
Hello,
I'm trying to build numpy from source to use AMD's ACML for matrix
multiplication (specifically the multi-threade
hly surprised if OpenBLAS would be slower than Eigen,
given than the developers themselves say that Eigen is "nearly as fast
as GotoBLAS"[1], and that OpenBLAS was originally forked from GotoBLAS.
Cheers
Thomas
[1] http://eigen.tuxfami
On Tue, Jan 21, 2014 at 8:55 AM, Charles R Harris wrote:
>
>
>
> On Tue, Jan 21, 2014 at 5:54 AM, Aldcroft, Thomas <
> aldcr...@head.cfa.harvard.edu> wrote:
>
>>
>>
>>
>> On Mon, Jan 20, 2014 at 6:12 PM, Charles R Harris <
>> charlesr.h
On Mon, Jan 20, 2014 at 6:12 PM, Charles R Harris wrote:
>
>
>
> On Mon, Jan 20, 2014 at 3:58 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>>
>> On Mon, Jan 20, 2014 at 3:35 PM, Nathaniel Smith wrote:
>>
>>> On Mon, Jan 20, 2014 at 10:28 PM, Charles R Harris
>>> wrote:
>>>
On Mon, Jan 20, 2014 at 10:40 AM, Oscar Benjamin wrote:
> On Mon, Jan 20, 2014 at 10:00:55AM -0500, Aldcroft, Thomas wrote:
> > On Mon, Jan 20, 2014 at 5:11 AM, Oscar Benjamin
> > wrote:
> > > How significant are the performance issues? Does anyone really use
> numpy
&
On Mon, Jan 20, 2014 at 5:11 AM, Oscar Benjamin
wrote:
> On Fri, Jan 17, 2014 at 02:30:19PM -0800, Chris Barker wrote:
> > Folks,
> >
> > I've been blathering away on the related threads a lot -- sorry if it's
> too
> > much. It's gotten a bit tangled up, so I thought I'd start a new one to
> > ad
On Fri, Jan 17, 2014 at 5:30 PM, Chris Barker wrote:
> Folks,
>
> I've been blathering away on the related threads a lot -- sorry if it's
> too much. It's gotten a bit tangled up, so I thought I'd start a new one to
> address this one question (i.e. dont bring up genfromtext here):
>
> Would it b
On Fri, Jan 17, 2014 at 4:43 PM, wrote:
> On Fri, Jan 17, 2014 at 4:20 PM, Chris Barker
> wrote:
> > On Fri, Jan 17, 2014 at 12:36 PM, wrote:
> >>
> >> > ('S' ?) -- which is probably not what you want particularly if you
> >> > specify
> >> > an encoding. Though I can't figure out at the moment
On Fri, Jan 17, 2014 at 5:59 AM, Pauli Virtanen wrote:
> Julian Taylor googlemail.com> writes:
> [clip]
> > - inconvenience in dealing with strings in python 3.
> >
> > bytes are not strings in python3 which means ascii data is either a byte
> > array which can be inconvenient to deal with or 4
return None # dotblas needs ATLAS, Fortran compiled blas will not be sufficient.
return ext.depends[:1]
return None
#
All the best
Thomas
[1] http://numpy-discussion.10968.n7.nabble.com/Problems-when-using-ACML-with-numpy-td18135.html
___
Hi,
The behavior for ``np.median`` and array sub-classes has changed in
1.8.0rc, which breaks unit-handling code (such as the ``quantities``
package, or ``astropy.units``):
https://github.com/numpy/numpy/issues/3846
This previously worked from Numpy 1.5 (at least) to Numpy 1.7. Is
there a new (a
For the astropy Table class (which wraps numpy structured arrays), I
wrote functions that perform table joins and concatenate tables along
rows or columns. These are reasonably full-featured and handle most
of the common needs for these operations. The join function here
addresses some limitation
* On 13/08/2013 23:32, David Reed wrote:
> Hi Thomas,
>
> Your array is Nx6 do you want the nan values replace by the
> mean of the 2 adjacent elemets by row or by column?
Hi David,
i want it to be replaced by column.
I also found numpy.interp but this function replaces all nan
v
Hi,
i am trying to remove nan-values from an array of shape(40, 6).
These nan-values at point data[x] should be replaced by the mean
of data[x-1] and data[x+1] if both values at x-1 and x+1 are not
nan. The function nan_to_mean (see below) is working but i wonder
if i could optimize the code.
I t
Hi everyone,
The following example:
import numpy as np
class SimpleArray(np.ndarray):
__array_priority__ = 1
def __new__(cls, input_array, info=None):
return np.asarray(input_array).view(cls)
def __eq__(self, other):
return False
Hi list,
i want to calculate the least squares fit of some data with
missing values. So i masked all values using numpys masked array
module.
Unfortunately using linalg.lstsq i only get nan data back. Can
somebody help me solve this problem?
The output of np.linalg.lstsq ist:
(masked_array(data
On Thu, Jun 13, 2013 at 5:06 PM, wrote:
> On Thu, Jun 13, 2013 at 4:47 PM, Eric Firing wrote:
> > On 2013/06/13 10:36 AM, Benjamin Root wrote:
> >>
> >> On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas
> >> mailto:aldcr...@head.cfa.harvard.edu>>
>
On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing wrote:
> On 2013/06/12 8:13 AM, Warren Weckesser wrote:
> > That's why I suggested 'filledwith' (add the underscore if you like).
> > This also allows a corresponding masked implementation, 'ma.filledwith',
> > without clobbering the existing 'ma.fille
On Mon, Jun 10, 2013 at 3:47 PM, Nathaniel Smith wrote:
> Hi all,
>
> Is there anyone out there using numpy masked arrays, who has an
> opinion on how empty_like (and its friends ones_like, zeros_like)
> should handle the mask?
>
> Right now apparently if you call np.ma.empty_like on a masked arr
On Thu, May 30, 2013 at 4:58 PM, Aldcroft, Thomas <
aldcr...@head.cfa.harvard.edu> wrote:
>
>
>
> On Thu, May 30, 2013 at 4:27 PM, Robert Kern wrote:
>
>> On Thu, May 30, 2013 at 9:21 PM, Aldcroft, Thomas
>> wrote:
>> > I'm seeing some behavio
On Thu, May 30, 2013 at 4:27 PM, Robert Kern wrote:
> On Thu, May 30, 2013 at 9:21 PM, Aldcroft, Thomas
> wrote:
> > I'm seeing some behavior that I can't understand when creating a numpy
> array
> > of Python objects. Basically it seems that np.array() is calli
I'm seeing some behavior that I can't understand when creating a numpy
array of Python objects. Basically it seems that np.array() is calling the
object __getitem__ method for one object class but not another class, and I
can't understand the difference.
Here is an example, starting with a simple
sn't NPY_OBJECT when you implement
> __array__.
>
> dtypes is set with those line:
>
> retval = ufunc->type_resolver(ufunc, casting,
> op, type_tup, dtypes);
Thanks for looking into this - should this be considered a bug?
Tom
>
>
> HTH
&g
Hi everyone,
(this was posted as part of another topic, but since it was unrelated,
I'm reposting as a separate thread)
I've also been having issues with __array_priority__ - the following
code behaves differently for __mul__ and __rmul__:
"""
import numpy as np
class TestClass(object):
d
I've also been having issues with __array_priority__ - the following
code behaves differently for __mul__ and __rmul__:
"""
import numpy as np
class TestClass(object):
def __init__(self, input_array):
self.array = input_array
def __mul__(self, other):
print "Called __mu
Hi everyone,
I am currently trying to write a sub-class of Numpy ndarray, but am
running into issues for functions that return scalar results rather
than array results. For example, in the following case:
import numpy as np
class TestClass(np.ndarray):
def __new__(cls, input_arr
Adding to an old discussion thread (see below) ... an implementation
of the proposed functionality:
from numpy import rollaxis
def moveaxis(a, i, j = 0):
"""
move axis i of array a to position j
"""
n = a.ndim
i = i if i >= 0 else i + n
if j > i:
return rollaxis(a,
Hi everyone,
I'm currently having issues with installing Numpy 1.6.2 with Python
3.1 and 3.2 using pip in Travis builds - see for example:
https://travis-ci.org/astropy/astropy/jobs/3379866
The build aborts with a cryptic message:
ValueError: underlying buffer has been detached
Has anyone seen
I've recently opened a couple of pull requests that fix bugs with
MaskedArray - these are pretty straightforward, so would it be
possible to consider them in time for 1.7?
https://github.com/numpy/numpy/pull/2703
https://github.com/numpy/numpy/pull/2733
Thanks!
Tom
__
On 05/12/2012 05:34 PM, Pauli Virtanen wrote:
> 12.05.2012 17:30, Thomas Unterthiner kirjoitti:
> [clip]
>> However it didn't seem to work. The same 5000x5000 matrix-multiply is
>> still spinning at 100% CPU usage. I attached to the process after I let
>> it ru
ed since that message was written in
2006, or I did something wrong (I am absolutely unfamiliar with the
build-system used by numpy) or missed something :(
Thomas
2012/5/12 Thomas Unterthiner <mailto:thomas_unterthi...@web.de>>
On 05/12/2012 03:27 PM, numpy-discussion-r
On 05/12/2012 03:27 PM, numpy-discussion-requ...@scipy.org wrote:
> 12.05.2012 00:54, Thomas Unterthiner kirjoitti:
> [clip]
>> > The process will have 100% CPU usage and will not show any activity
>> > under strace. A gdb backtrace looks as follows:
>&g
to link by hand by adding the flag),
however the error persisted. The same with numpy-1.6.2rc1.
Fromt here I don't know how to proceed. Any help would be greatly
appreciated :)
Cheers
Thomas
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))] = x # works like put -> not what I want
a[array((0,2))] = x # same effect
print a # -> [1 None 2 None]
a[0],a[2] = x,x # set explicitly - works
print a # -> [[1, 2, 'f'] None [1, 2, 'f'] None]
thanks for your help!
cheers,
--
Thomas Tanner
can change the
Python default encoding (sys.getdefaultencoding()). That's never
normally changed, so Python 2 code can assume it's always ascii. I
guess pygtk sets the encoding from the system locale, so if it's set
to C, it will use ascii, and the
Hi,
I'm completely new to this list (and fairly new to numpy in general), but I
was wondering if you tried multiplying the bool array and the original
array.
Try:
x=array([[0,1,2],[3,4,5],[6,7,8]])
if rank(x) <= 1
dot(x>=1, x)
else
(x>=1)*x
This will give you a completely numerical array of
n ipython or by running the python script in a
> shell script?
Depending on what you want this for, you might look into IPython's demo
mode:
http://ipython.org/ipython-doc/stable/interactive/reference.html#interactive-demos-with-ipython
Thomas
_
On 1 March 2012 08:37, Pierre Haessig wrote:
> Just to start the new month on a light & happy topic :
> IPython 0.12 has entered Debian Testing !
>
Thanks to Julian Taylor for handling Debian packaging.
IPython 0.12 is also in the upcoming Ubuntu 1
he state now.
You may notice an ipython-mac job in the list - one of our
contributors kindly set up his Mac to run the test suite overnight,
and we have ShiningPanda download the zipped results. It's a neat
trick, but it's not really a solution if you're testing many OS
flavours
make the final call', through to
committees, voting systems, etc. So long as everything's going well,
it shouldn't restrict anyone, and it would reassure anyone who does
have concerns (justified or not) about conflicts of interest.
Thanks,
Thomas
__
, 2011 at 7:46 PM, Thomas Coffee wrote:
> Somewhat new to NumPy, but I've been investigating this for over an hour
> and found nothing helpful:
>
> Can anyone explain why this works ...
>
>
> >>> import numpy
> >>> numpy.fromfunction(lambda i, j: i*j,
ade explicit?
The motivation for the question is to be able to use fromfunction with a
function that can return infinity, which I only know how to create with the
explicit cast float('inf').
Thanks in advance for your help!
- Thomas
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x27;t find
libquadmath.so.0. Any ideas what might be wrong? Am I missing a dependent
package somewhere? How can I force the build to use the installed lapack
stuff? (installed via synaptic from the ubuntu debs) Numpy 1.5.1 builds and
installs with no problems.
--
Thomas K. Gamble
Research Te
Hello,
Is the following behavior normal?
In [1]: import numpy as np
In [2]: np.dtype([('a','http://mail.scipy.org/mailman/listinfo/numpy-discussion
ython along
with the scipy superpack.
Thomas
On Tue, Aug 2, 2011 at 12:06 PM, Ralf Gommers
wrote:
>
>
> On Tue, Aug 2, 2011 at 6:57 PM, Thomas Markovich <
> thomasmarkov...@gmail.com> wrote:
>
>> It appears that uninstalling python 2.7 and installing the scipy superpack
&
) ... Segmentation fault"
Thomas
On Tue, Aug 2, 2011 at 11:28 AM, Ralf Gommers
wrote:
>
>
> On Tue, Aug 2, 2011 at 6:14 PM, Thomas Markovich <
> thomasmarkov...@gmail.com> wrote:
>
>> I just have the default "apple" version of python that comes with Sno
ple
python?
On Tue, Aug 2, 2011 at 11:08 AM, Olivier Delalleau wrote:
> It's a wild guess, but in the past I've had seg faults issues on Mac due to
> conflicting versions of Python. Do you have multiple Python installs on your
> Mac?
>
> -=- Olivier
>
>
> 201
(dot 3)]
nose version 1.1.2
Segmentation
fault
thomasmarkovich:~ Thomas$
What is the best wa
> On Thu, Jun 30, 2011 at 11:32 AM, Thomas K Gamble
>
> wrote:
> > I'm trying to convert some IDL code to python/numpy and i'm having some
> > trouble understanding the rules for boradcasting during some operations.
> > example:
> >
> > giv
> On 30.06.2011, at 11:57PM, Thomas K Gamble wrote:
> >> np.add(b.reshape(2048,3136) * c, d, out=a[:,:3136])
> >>
> >> But to say whether this is really the equivalent result to what IDL
> >> does, one would have to study the IDL manual in detail or direc
Derek
>
>
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--
Thomas K. Gam
> On 30.06.2011, at 7:32PM, Thomas K Gamble wrote:
> > I'm trying to convert some IDL code to python/numpy and i'm having some
> > trouble understanding the rules for boradcasting during some operations.
> > example:
> >
> > given the following arr
lain this to me?
--
Thomas K. Gamble tkgam...@windstream.net
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Hello,
I am having trouble with performance when trying to create a cross
tabulation using numpy. Ideally, I would calculate each cell in the
cross tabulation separately because this gives me the greatest amount
of flexibility. I have included some sample code as a reference and
am really looki
there a way to do something like:
data = sum(dot(transpose(bipData), bipData))
with dot done on the desired axis of bipData?
This might give a fair speed increase. Or perhaps a different approach I'm not
seeing?
--
Thomas K. Gamble
Research Technologist, System/Network Administrator
Che
e fib1 subroutine is callable from Python.
Best regards,
Thomas
2011/2/16 Thomas Ingeman-Nielsen
> Hi,
>
> I'm trying to get started with f2py on a Windows 7 environment using the
> Python(x,y) v 2.6.5.6 distribution.
> I'm following the introductory example of the f2p
ot;fib" sources
f2py options: []
f2py:>
c:\users\thomas\appdata\local\temp\tmpamyxnx\src.win32-2.6\fibmodule.c
creating c:\users\thomas\appdata\local\temp\tmpamyxnx
creating c:\users\thomas\appdata\local\temp\tmpamyxnx\src.win32-2.6
Reading fortran codes...
Reading file 'fib1
outer.
Any help appriciated
Thomas
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all of these vectors at once?
Kind regards
Thomas
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e bruteForceSearch which is up
to 6 times faster.
But in case of a leaf in a kd-tree you end up with 50, 20, 10 or less points
where the speed-up is reversed. In this particular case 34000 runs take 90s
with your method and 50s with mine (not the bruteForce).
I see now the limits of the arrays but
y.ndarray compared
> toNumeric.array
>
> On Mon, Jan 10, 2011 at 6:04 PM, EMMEL Thomas
> wrote:
>
> >
> > Yes, of course and my real implementation uses exactly these methods,
> > but there are still issues with the arrays.
>
> Did you try kd-trees in scipy ?
>
> On Mon, Jan 10, 2011 at 5:09 PM, EMMEL Thomas
> wrote:
> > To John:
> >
> >> Did you try larger arrays/tuples? I would guess that makes a
> significant
> >> difference.
> >
> > No I didn't, due to the fact that these values are coordinat
array creation include the import process, which are going to be
> different for each module and are probably not indicative of the speed of
> array creation.
No, the timeit statements counts the time for the statement in the first
argument only,
the import-thing isn't included in the
2=x1[2]-x2[2];d0*d0+d1*d1+d2*d2','from
Numeric import array as a; x1=a((1.,2.,3.));x2=a((2.,4.,6.))').timeit()
#0.97426199913024902
Result: tuples are again the fastest variant, Numeric is faster than numpy and
both are faster than the variant above using the high-level functions
0
>
> will be used, but I'm not sure then how to "count" the number of "True"
> entries.
>
> TIA.
>
> Ian
one possibility:
len(where(a != 0)[0])
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Thomas K. Gamble
Research Technologist, System/Network Administrator
Chemical Diagnostics and Engi
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