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 reas
Chris Fonnesbeck 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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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 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
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
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 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
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
___
> 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
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, whic
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
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 f
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 ar
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)
>
>
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
___
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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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
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 o
William Reade wrote:
> Hi
>
> I hope this is the right place for this question... if not, I apologise,
> and ask only that you please direct me somewhere more appropriate.
>
> Line 532 of numerictypes.py reads "_unicodesize =
> array('u','U1').itemsize", but _unicodesize itself does not appear to
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
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 pr
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:
> --=_Part_25307_10322093.1219268954678
> Content-Type: text/plain; charset
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