Hi. That is really amazing.
I checked out that numexpr branch and saw some strange results when
evaluating expressions on a multi-core i7 processor.
Running the numexpr.test() yields a few 'F', which I suppose are failing
tests. I tried to let the tests finish but it takes more than 20 min, is
ther
Dear numpy developers,
The current implementation of numpy.interp(x,xp,fp) comes down to: first
calculating all the slopes of the linear interpolant (these are len(xp)-1),
then use a binary search to find where x is in xp (running time
log(len(xp)). So we obtain a running time of
O( len(xp) + len
On Fri, Jul 29, 2011 at 2:57 PM, Benjamin Root wrote:
>
>
> On Fri, Jul 29, 2011 at 2:52 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Fri, Jul 29, 2011 at 11:07 AM, Martin Ling wrote:
>>
>>> On Fri, Jul 29, 2011 at 09:14:00AM -0600, Charles R Harris wrote:
>>> >
>>> >
On Fri, Jul 29, 2011 at 1:57 PM, Benjamin Root wrote:
>
>
> On Fri, Jul 29, 2011 at 2:52 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Fri, Jul 29, 2011 at 11:07 AM, Martin Ling wrote:
>>
>>> On Fri, Jul 29, 2011 at 09:14:00AM -0600, Charles R Harris wrote:
>>> >
>>> >
On Fri, Jul 29, 2011 at 2:52 PM, Charles R Harris wrote:
>
>
> On Fri, Jul 29, 2011 at 11:07 AM, Martin Ling wrote:
>
>> On Fri, Jul 29, 2011 at 09:14:00AM -0600, Charles R Harris wrote:
>> >
>> >Well, if the shuttle used a different definition then it was out
>> there
>> >somewhere. The
On Fri, Jul 29, 2011 at 11:07 AM, Martin Ling wrote:
> On Fri, Jul 29, 2011 at 09:14:00AM -0600, Charles R Harris wrote:
> >
> >Well, if the shuttle used a different definition then it was out there
> >somewhere. The history of quaternions is rather involved and mixed up
> with
> >vec
+-- Pauli Virtanen ---+
> Fri, 29 Jul 2011 10:52:12 +0200, Yoshi Rokuko wrote:
> [clip]
> A, B = mod.meth(C, prob=.95)
> >
> > is it possible to return two arrays?
>
> The way to do this in Python is to build a tuple with
> Py_BuildValue("OO", A, B) and retur
On Jul 28, 2011 8:43 AM, "Matthew Brett" wrote:
> So, 1.6.0 is returning a zero-dimensional scalar of the given type,
> and 1.5.1 returns a python scalar.
>
> Zero dimensional scalars are designed to behave in a similar way to
> python scalars, so the change should be all but invisible in practice
On Fri, Jul 29, 2011 at 09:14:00AM -0600, Charles R Harris wrote:
>
>Well, if the shuttle used a different definition then it was out there
>somewhere. The history of quaternions is rather involved and mixed up with
>vectors, so it may be the case that there were different conventions.
On Fri, Jul 29, 2011 at 10:07 AM, Mark Wiebe wrote:
> On Thu, Jul 28, 2011 at 9:58 AM, Hans Meine <
> me...@informatik.uni-hamburg.de> wrote:
>
>> Hi again!
>>
>> Am Donnerstag, 21. Juli 2011, 16:56:21 schrieb Hans Meine:
>> > import numpy
>> >
>> > class Test(numpy.ndarray):
>> > pass
>> >
>
On 7/28/11 4:21 PM, Matthew Brett wrote:
> Hi,
>> Do you know if doctests supports any sort of manual intervention, like
>> a plugin system?
>
> Actually, I was going to ask you that question :)
>
> But yes, there's the NumpyDoctest nose plugin, for example. Using it
> does mean you have to custo
On Fri, Jul 29, 2011 at 9:03 AM, Martin Ling wrote:
> On Thu, Jul 28, 2011 at 09:48:29PM -0500, Robert Love wrote:
> >
> > Quaternions have a "handedness" or a sign convention. The recently
> > departed Space Shuttle used a Left versor convention while most
> > things, including Space Station, u
On Thu, Jul 28, 2011 at 9:58 AM, Hans Meine wrote:
> Hi again!
>
> Am Donnerstag, 21. Juli 2011, 16:56:21 schrieb Hans Meine:
> > import numpy
> >
> > class Test(numpy.ndarray):
> > pass
> >
> > a1 = numpy.ndarray((1,))
> > a2 = Test((1,))
> >
> > assert type(a1.min()) == type(a2.min()), \
>
On Thu, Jul 28, 2011 at 09:48:29PM -0500, Robert Love wrote:
>
> Quaternions have a "handedness" or a sign convention. The recently
> departed Space Shuttle used a Left versor convention while most
> things, including Space Station, use the right versor convention, in
> their flight software. Ma
Thanks Martins, that did the magic.
Thanks so much.
I'm on the tutorials now.
Regards.
On 29 Jul 2011 15:24, "Martin Ling" wrote:
> On Fri, Jul 29, 2011 at 02:55:15PM +0100, DIPO ELEGBEDE wrote:
>>
>> I have a 4 by 4 matrix filled with 0s, 1s and 2s.
>> I want to loop through the whole matrix to
On Jul 29, 2011, at 4:07 PM, Mark Wiebe wrote:
> As part of supporting the NA mask, I've rewritten boolean indexing. Here's a
> timing comparison of my version versus a previous version:
>
> In [2]: np.__version__
> Out[2]: '1.4.1'
> In [3]: a = np.zeros((1000,1000))
> In [4]: mask = np.random.
On Thu, Jul 28, 2011 at 8:54 AM, Martin Ling wrote:
> Hi,
>
> I'd like to kick off some discussion on general issues I've encountered
> while developing the quaternion dtype (see other thread, and the code
> at: https://github.com/martinling/numpy_quaternion)
>
> The basic issue is that the attri
On Fri, Jul 29, 2011 at 02:55:15PM +0100, DIPO ELEGBEDE wrote:
>
>I have a 4 by 4 matrix filled with 0s, 1s and 2s.
>I want to loop through the whole matrix to get the fields with 1s and 2s
>only and then count how many ones and how many twos.
Try this:
>>> m = matrix('1,2,0,2;2,2,1,
I've merged a pull request from Alok Singhal which implements Robert Kern's
idea for this.
Thanks,
Mark
On Wed, Jul 27, 2011 at 12:50 PM, Matthew Brett wrote:
> Hi,
>
> I see that (current trunk):
>
> In [9]: np.ones((1,), dtype=bool)
> Out[9]: array([ True], dtype='bool')
>
> - whereas (1.5.1):
As part of supporting the NA mask, I've rewritten boolean indexing. Here's a
timing comparison of my version versus a previous version:
In [2]: np.__version__
Out[2]: '1.4.1'
In [3]: a = np.zeros((1000,1000))
In [4]: mask = np.random.rand(1000,1000) > 0.5
In [5]: timeit a[mask] = 1.5
10 loops, bes
Hi All,
I am fresh on this list and would be looking forward to as much help as I
can get. I am hoping to develop ino helping others too after a short while.
Kindly help me with this task.
I would appreciate if you can point me to an example or brief explanation.
I have a 4 by 4 matrix filled w
On Thu, Jul 28, 2011 at 3:09 PM, Nathaniel Smith wrote:
> I have a different question about this than the rest of the thread. I'm
> confused at why there isn't a programmatic way to create a datetime dtype,
> other than by going through this special string-based mini-language. I guess
> I general
On Fri, Jul 29, 2011 at 4:12 AM, Hans Meine wrote:
> Am Freitag, 29. Juli 2011, 11:31:24 schrieb Hans Meine:
> > Am Donnerstag, 28. Juli 2011, 17:42:38 schrieb Matthew Brett:
> > > Was there a particular case you ran into where this was a problem?
> > [...]
> > Basically, the problem arose becaus
Fri, 29 Jul 2011 10:52:12 +0200, Yoshi Rokuko wrote:
[clip]
A, B = mod.meth(C, prob=.95)
>
> is ith possible to return two arrays?
The way to do this in Python is to build a tuple with
Py_BuildValue("OO", A, B) and return that.
___
NumPy-Discussi
+ Peter ---+
> On Fri, Jul 29, 2011 at 9:52 AM, Yoshi Rokuko wrote:
> >
> > hey, i have an algorithm that computes two matrices like that:
> >
> > A(i,k) = (x(i,k) + y(i,k))/norm
> > B(i,k) = (x(i,k) - y(i,k))/norm
> >
> > it would be convenient
Am Freitag, 29. Juli 2011, 11:31:24 schrieb Hans Meine:
> Am Donnerstag, 28. Juli 2011, 17:42:38 schrieb Matthew Brett:
> > Was there a particular case you ran into where this was a problem?
> [...]
> Basically, the problem arose because our ndarray subclass does not support
> zero-rank-instances f
On Fri, Jul 29, 2011 at 9:52 AM, Yoshi Rokuko wrote:
>
> hey, i have an algorithm that computes two matrices like that:
>
> A(i,k) = (x(i,k) + y(i,k))/norm
> B(i,k) = (x(i,k) - y(i,k))/norm
>
> it would be convenient to have the method like that:
>
A, B = mod.meth(C, prob=.95)
>
> is ith poss
Am Donnerstag, 28. Juli 2011, 17:42:38 schrieb Matthew Brett:
> If I understand you correctly, the problem is that, for 1.5.1:
> >>> class Test(np.ndarray): pass
> >>> type(np.min(Test((1,
>
>
>
> and for 1.6.0 (and current trunk):
> >>> class Test(np.ndarray): pass
> >>> type(np.min(Test((1
hey, i have an algorithm that computes two matrices like that:
A(i,k) = (x(i,k) + y(i,k))/norm
B(i,k) = (x(i,k) - y(i,k))/norm
it would be convenient to have the method like that:
>>> A, B = mod.meth(C, prob=.95)
is ith possible to return two arrays?
best regards
_
On 2011-07-28 07:50, Johan Råde wrote:
> How do I get the PyTypeObject* for a NumPy scalar type such as np.uint8?
>
> (The reason I'm asking is the following:
> I'm writing a C++ extension module. The Python interface to the module
> has a function f that takes a NumPy scalar type as an argument, f
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