Hey Dag,
On Wed, Aug 20, 2008 at 1:18 PM, Dag Sverre Seljebotn
[EMAIL PROTECTED] wrote:
Cython just had a release, and amongst the new features are efficient
NumPy array indexing for integers, real floats and Python objects.
You can get it at http://cython.org
For those new to Cython, I've
Hi Stefan,
yes, indeed, that's what I thought. This result is odd. Has correlate
been changed since version 1.0.4, or should I submit this as a bug?
Best regards,
Hanno
Stéfan van der Walt [EMAIL PROTECTED] said:
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Content-Type: text/plain;
Hi Hanno
2008/8/22 Hanno Klemm [EMAIL PROTECTED]:
yes, indeed, that's what I thought. This result is odd. Has correlate
been changed since version 1.0.4, or should I submit this as a bug?
Is there any way that you could try out the latest release on your
machine and see if it solves your
Hi all,
This is my personal recollection of the documentation BoF. Feel free to
comment or correct the text below.
Regards
Stéfan
Summary of the Documentation Birds-of-a-Feather Session
===
Topics proposed for discussion
Travis E. Oliphant wrote:
I don't know the answer to these questions.
Thanks for your response -- can anyone suggest a better forum for these
sorts of issues?
I would say that unicode arrays are rare and I would definitely work on
floating-point first.Any chance we can see some of
Hi Stefan,
I checked it with numpy version 1.1.1 just now and the result is the same:
x = N.array([0.,0,1,0,0])
y1 = N.array([1.,0,0,0,0])
N.correlate(x,y1, mode='full')
array([ 0., 0., 0., 0., 0., 0., 1., 0., 0.])
y2 = N.array([1.,0,0,0,0,0,0])
N.correlate(x,y2, mode='full')
Hi list,
are there any plans to implement a routine to solve the generalized
eigenvector problem as is done in matlab ?
see http://www.mathworks.com/access/helpdesk/help/techdoc/ref/eig.html
manuel
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Manuel Metz wrote:
are there any plans to implement a routine to solve the generalized
eigenvector problem as is done in matlab ?
see http://www.mathworks.com/access/helpdesk/help/techdoc/ref/eig.html
import numpy
help(numpy.linalg.eig)
Is it what you wanted?
HTH,
Jon
Jonathan Wright wrote:
Manuel Metz wrote:
are there any plans to implement a routine to solve the generalized
eigenvector problem as is done in matlab ?
see http://www.mathworks.com/access/helpdesk/help/techdoc/ref/eig.html
import numpy
help(numpy.linalg.eig)
Is it what you
I've been experimenting with both a non-framework, non-universal 64-bit
build and a 4-way universal build of the python (2.6) trunk with numpy
1.1.1. The non-framework 64 build appears to give me exactly the same
results from numpy.test() as the standard 32-bit version (as well as
allowing large
On Fri, Aug 22, 2008 at 07:00, Chris Kees
[EMAIL PROTECTED] wrote:
I've been experimenting with both a non-framework, non-universal 64-bit
build and a 4-way universal build of the python (2.6) trunk with numpy
1.1.1. The non-framework 64 build appears to give me exactly the same
results from
Robert Kern wrote:
On Fri, Aug 22, 2008 at 07:00, Chris Kees
[EMAIL PROTECTED] wrote:
Hi,
I've been experimenting with both a non-framework, non-universal 64-bit
build and a 4-way universal build of the python (2.6) trunk with numpy
1.1.1. The non-framework 64 build appears to give me
I'm looking for a way to acccomplish the following task without lots
of loops involved, which are really slowing down my code.
I have a 128x512 array which I want to break down into 2x2 squares.
Then, for each 2x2 square I want to do some simple calculations
such as finding the maximum value,
I'm looking for a way to acccomplish the following task without lots
of loops involved, which are really slowing down my code.
I have a 128x512 array which I want to break down into 2x2 squares.
Then, for each 2x2 square I want to do some simple calculations
such as finding the maximum
2008/8/21 William Reade [EMAIL PROTECTED]:
Line 532 of numerictypes.py reads _unicodesize =
array('u','U1').itemsize, but _unicodesize itself does not appear to be
referenced anywhere else. My questions are:
I removed this in r5674.
Regards
Stéfan
On 8/22/08 11:34 AM, Michael Abshoff [EMAIL PROTECTED]
wrote:
Robert Kern wrote:
On Fri, Aug 22, 2008 at 07:00, Chris Kees
[EMAIL PROTECTED] wrote:
Hi,
I've been experimenting with both a non-framework, non-universal 64-bit
build and a 4-way universal build of the python (2.6) trunk
Is there any prospect for easily getting ranges of floats in numpy, rather than
just integers? In R, for example, you can specify a decimal value for the step
size. It would be great to be able to do the following:
arange(0, 100, 0.1)
for a sequence from 0 to 100 in steps of 0.1. It seems rather
On Fri, Aug 22, 2008 at 9:35 PM, Chris Fonnesbeck [EMAIL PROTECTED] wrote:
Is there any prospect for easily getting ranges of floats in numpy, rather
than
just integers? In R, for example, you can specify a decimal value for the step
size. It would be great to be able to do the following:
Chris Fonnesbeck wrote:
Is there any prospect for easily getting ranges of floats
in numpy, rather than just integers?
help(np.linspace)
Help on function linspace in module numpy.lib.function_base:
linspace(start, stop, num=50, endpoint=True, retstep=False)
Return
Nathan Bell wrote:
arange(0, 100, 0.1) does exactly what you want.
Hmmm; maybe.
I thought Chris wanted the endpoint...
Cheers,
Alan Isaac
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Chris Fonnesbeck listservs at mac.com writes:
It would be great to be able to do the following:
arange(0, 100, 0.1)
As it turns out, I am an idiot.
Apologies.
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I'm trying to generate negative binomial random numbers where the n parameter
is non integer (1 in fact). This should be possible, as n only needs to be
real. However, I get the following message:
ValueError: n = 0
I assume this is because some rounding is going on behind the scenes.
The
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