On Thu, Sep 25, 2008 at 9:36 AM, frank wang <[EMAIL PROTECTED]> wrote:
> Hi, All,
>
> I am using ipython with --pylab flag. ipython loads the numpy into the
> workspace, so I do not know abs is from python or numpy. The weird thing is
> if I execute the code line by line, I do not have any speed pr
In creating an array of type numpy.complex128, I'm having problems
passing in Sage types that should be considered complex numbers since
they implement the standard __complex__ method. However, numpy doesn't
recognize that. Here's a minimal example:
In [1]: class MyNum:
...: def __comp
> >From my understanding, using the modulename.functionname will slow down the
> python performance. For a big simulation, it may not be a good idear.
The slowdown is very small (I'd say inferior to a ms), it's nothing
compared to the way you're doing your computations.
Matthieu
--
French PhD st
On Wed, Sep 24, 2008 at 9:25 PM, <[EMAIL PROTECTED]> wrote:
> I'm working on getting the Sage matrices for real/complex doubles to use
> numpy as a backend. In this, I'm using the PyArray_SETITEM macro from
> within Cython. However, Cython wraps the macro in a function call to
> convert the outp
I'm working on getting the Sage matrices for real/complex doubles to use
numpy as a backend. In this, I'm using the PyArray_SETITEM macro from
within Cython. However, Cython wraps the macro in a function call to
convert the output to a Python value:
__pyx_1 = PyInt_FromLong(PyArray_SETITEM(
On Wed, Sep 24, 2008 at 21:29, Dinesh B Vadhia
<[EMAIL PROTECTED]> wrote:
> I'm using numpy take() to pickout elements from a (1xM) array A indicated by
> the index numbers in indices ie.
>
> B = A.take(indices = list_indexes)
>
> It work perfectly but as A is large the performance isn't great and
I'm using numpy take() to pickout elements from a (1xM) array A indicated by
the index numbers in indices ie.
B = A.take(indices = list_indexes)
It work perfectly but as A is large the performance isn't great and was
wondering if there are faster methods available or ways to improve the use of
Hi, All,
I am using ipython with --pylab flag. ipython loads the numpy into the
workspace, so I do not know abs is from python or numpy. The weird thing is if
I execute the code line by line, I do not have any speed problem. But when I
combine them together into one command, it slowdonws the
Nadav Horesh wrote:
> You should use absolute (a ufunc) and not abs (internal python function):
>
plot(absolute(fft(b)))
another reason why "import *" is a bad idea:
import numpy as np
import pylab as plot #(what is the convention for this now?)
pylab.plot(np.absolute(np.fft(b)))
yes, it
Michel Dupront wrote:
> I have a c++ function that take as argument a std::vector.
>>From python I want to call the c++ function with an array
> object. For that purpose I want to write a typemap.
Have you seen the SWIG typemaps that come with numpy?:
...\site-packages\numpy\doc\swig
They are de
Ups! Since I´ve started to use Cython, it seems I´m starting to forget
things about SWIG. Mi comments about a typecheck typemaps were a
nonsese (they have another pourpose). Look at the SWIG docs, you need
to use something like SWIG_arg_fail macro.
On Wed, Sep 24, 2008 at 6:48 PM, Lisandro Dalcin
I believe you should look at the SWIG docs and then write a typecheck
typemap. Checking foir the type of and array and returning NULL is not
fair play for SWIG, nor for Python. Before returning NULL, and
exception should be set. For this, SWIG provides some 'SWIG_xxx_fail'
macros. Typemaps and frag
Thank you very much for all of you. I have downloaded the binary version 1.2rc
and it fixed the problem.
My special thanks to the person who created the window binary version for users
who do not know or do not have the capacity to build the numpy from source.
Frank> Date: Wed, 24 Sep 200
On Wed, Sep 24, 2008 at 11:13 AM, Bruce Southey <[EMAIL PROTECTED]> wrote:
> What is the status of NumPy 1.2 and when can we expect the final version?
I hope to announce it on Friday or Saturday. The only thing I am
looking into now is whether we should back port the fix to lookfor or
not:
http:/
Hi,
What is the status of NumPy 1.2 and when can we expect the final version?
Thanks
Bruce
Jarrod Millman wrote:
> Hello,
>
> The 1.2.0rc2 is now available:
> http://svn.scipy.org/svn/numpy/tags/1.2.0rc2
>
> The source tarball is here:
> https://cirl.berkeley.edu/numpy/numpy-1.2.0rc2.tar.gz
>
> H
Vincent,
You should really consider putting an example next time. I must admit that I'm
not sure what you're trying to do, and where/why it fails.
Yes, by default, the mask of a new MaskedArray is set to the value 'nomask',
which is the boolean False. Directly setting an element of the mask in
You could try something like:
In [15]: arr = numpy.array([100,200,300])
In [16]: arr2 = numpy.empty((len(arr)*2,))
In [17]: arr2[::2]=arr
In [18]: arr2[1::2]=numpy.arange(len(arr))
In [20]: arr2
Out[20]: array([ 100.,0., 200.,1., 300.,2.])
2008/9/24 Nadav Horesh <[EMAIL PROTECTE
2008/9/24 Joshua Lippai <[EMAIL PROTECTED]>:
> And the version would be displayed on screen. Bear in mind that unlike
> the release, which installs via an installer file you double click,
> you will have to compile numpy from the downloaded source code
> yourself. Detailed instructions for doing th
Note that the fix was also backported to 1.2, for which binary builds are
available:
David
[ copied from a recent thread ]
The 1.2.0rc2 is now available:
http://svn.scipy.org/svn/numpy/tags/1.2.0rc2
The source tarball is here:
https://cirl.berkeley.edu/numpy/numpy-1.2.0rc2.tar.gz
Here is the u
Hello,
I am trying to use Numeric and swig but it seems that
there are few points that I don't understand.
The only excuse I have is that I am new to these tools.
I have a simple example that I cannot make work the
way I would like.
I have a c++ function that take as argument a std::vecto
Wed, 24 Sep 2008 11:18:43 +, Pauli Virtanen wrote:
> Tue, 23 Sep 2008 15:48:22 -0700, joep wrote:
>> A possible solution would be in
>>
>> http://bazaar.launchpad.net/~pauli-virtanen/scipy/pydocweb/revision/386
>>
>> It seems to be possible to be used in the same way when iter_modules
>> is
Hi,
Tue, 23 Sep 2008 15:48:22 -0700, joep wrote:
> A possible solution would be in
>
> http://bazaar.launchpad.net/~pauli-virtanen/scipy/pydocweb/revision/386
>
> It seems to be possible to be used in the same way when iter_modules is
> not available.
> The usage in ``_lookfor_generate_cache``
On Wed, Sep 24, 2008 at 09:57:13AM +0200, David Kaplan wrote:
> > > X = asarray( mgrid[ 0:4, 0:4, 0:4 ] )
> > Doesn't this force a data copy?
> I am not sure if this forces a copy (asarray shouldn't for arrays,
> unlike array, but I am not sure what it does for lists that can
> trivially become
Probably I'm just overlooking something obvious, but I'm having problems
with maskedarrays (numpy.ma from svn: '1.3.0.dev5861'), the mask by
default being a single bool value ('False') instead of a properly sized
bool array. If I then try to mask one value by assigning values to
certain mask po
Possibilities:
column_stack((arange(len(ar)),ar))
or
transpose((arange(len(ar)),ar)).ravel()
Nadav.
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Thomas Heller
נשלח: ד 24-ספטמבר-08 11:30
אל: numpy-discussion@scipy.org
נושא: [Numpy-discussion] inserting indexes into an array
I have a n
I have a numpy array comtaining numbers (a, b, ...), like this:
array([a, b, c, d, e, f])
What is the fastest way to create another array that has the index
of the element before each element of the original array?
The result should look like this:
array([0, a, 1, b, 2, c, 3, d, 4, e, 5, f])
-
On Wed, Sep 24, 2008 at 02:57, David Kaplan <[EMAIL PROTECTED]> wrote:
> Hi,
>
> On Tue, 2008-09-23 at 20:54 -0500, [EMAIL PROTECTED]
> wrote:
>> On Tue, Sep 23, 2008 at 09:39:53AM +0200, David Kaplan wrote:
>> > I would note that there is nothing in the API breakage that prevents
>> > doing what G
Hi,
On Tue, 2008-09-23 at 20:54 -0500, [EMAIL PROTECTED]
wrote:
> On Tue, Sep 23, 2008 at 09:39:53AM +0200, David Kaplan wrote:
> > I would note that there is nothing in the API breakage that prevents
> > doing what Gael mentions. The only change is that:
>
> > > > X = mgrid[0:4, 0:4, 0:4]
>
>
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