date:20061005

Re: [Numpy-discussion] On loop and broadcasting (again)

2006-10-05 Thread David Cournapeau

Travis Oliphant wrote:
> David Cournapeau wrote:
>
>> Hi,
>>
>>   The email from Albert made me look again on some surprising results I 
>> got a few months ago when starting my first "serious" numpy project. I 
>> noticed that when computing multivariate gaussian densities, centering 
>> the data was more expensive than everything else, including 
>> exponentiation. Now that I have some experience with numpy, and 
>> following the previous discussion, I tried the following script:
>>  
>>
>
> Try it again with the new code in SVN.
>
It looks like your modification solved this particular issue !:

 100.6450.0650.6450.065 
storage_email.py:8(center_broadcast)
 100.6250.0620.6250.062 
storage_email.py:26(center_manual)
  10.3330.3330.3330.333 
/usr/lib/python2.4/site-packages/numpy/lib/shape_base.py:530(repmat)

Now, using broadcast is as fast as doing the substraction itself (which 
does not include the necessary repmat). I tried it on my laptop, where I 
can safely use beta code (python 2.4 + SVN numpy), which  explains the 
timing differences compared to my previous email; as the memory is 
limited on the laptop, I only benchmarked the brodcasting. For smaller 
arrays, I couldn't see major differences in relative timing for the 
other implementations.

Thank you very much !

David

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Re: [Numpy-discussion] repmat

2006-10-05 Thread David Cournapeau

Bill Baxter wrote:
>
>> I'm not completely sold on the whole reparray thing: does repmat have
>> any use outside of the linear algebra convention of squashing a 3D array
>> into a 2D matrix (or however that goes)? If not, perhaps it should just
>> get left alone and exciled to matrix specific functions namespace. So:
>> 
>
> Well, I'm not sure about N-d, but I've definitely had a need for 1-d
> version of it.  That's what prompted me to look into this.  Also I
> think I read a comment in the other thread about pyEM that repmat()
> turned out to be one of the faster ways to implement
> something-or-other (?). 
It was in a very specific case, and it could have been replaced by an 
other function in this case without any loss of performance. The 
following is my experience with matlab/repmat: generally, repmat was 
necessary in many cases in matlab either for efficiency (big scalar 
matrix were slow to generate using ones and zeros, for example) and 
because matlab had almost no broadcasting rules, repmat was almost 
mandatory for matlab. In numpy, the syntax at least does not require 
repmat (at least, I never *had* to use it in numpy, and I used it a lot 
with matlab).

Moreoever, the slowness of some broadcasting seem solved in recent 
subversion (see my answer on the specific thread),

David
>  At the very least you could think of tiling
> 3D image data as one application, in fact 'tile()' is probably a
> better name for the function than 'reparray'.
>
> I was initially suprised that 'repeat()' featured so prominently in
> numpy.  I initially assumed it meant "repmat", and was surprised when
> it didn't do that.  I thought "why on earth would you want to do
> that?".  But it does turn out to have lots of uses (like implementing
> "repmat" ;-))
>
>   
>> +1 on deprecating, moving or otherwise getting rid of repmat.
>> Neutral on whether to replace it with something else, but if it is
>> replaced #3 looks like the correct route, but not with a different
>> argument name than 'shape'. Perhaps 'reps'.
>> 
>
> Hey!  Looks like we agree on the name of the argument, apparently.  :-)
> I do think there is a strong connection with "shape" though, that
> 'reps' hides. Maybe 'repshape' or 'tileshape'?  I'd be happy with
> reps, though.  Agreed that 'shape' is bad.  Makes it sound like you
> should specify the actual .shape of the output.
>
> --bb
>
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>   


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Re: [Numpy-discussion] contribution about history of Numeric

2006-10-05 Thread Fernando Perez

On 10/5/06, Paul Dubois <[EMAIL PROTECTED]> wrote:
> I was reading the 'History of SciPy' page and noticed the discussion about
> Numeric. Here's the true story about why the various names for the original:
> numpy, Numeric, Numerical.

I added this to the wiki page (http://www.scipy.org/History_of_SciPy),
though I don't know how to make a block quote in wiki markup, so I
left it without any visual clue.

Thanks for the info!

Best,

f

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[Numpy-discussion] contribution about history of Numeric

2006-10-05 Thread Paul Dubois

I was reading the 'History of SciPy' page and noticed the discussion about Numeric. Here's the true story about why the various names for the original: numpy, Numeric, Numerical.At the time Source Forge was pretty young, and I decided to put the project there. We all said 'numpy' informally not Numerical Python but the module name was Numeric. I created the project as numpy. I have no memory of why I didn't call it Numeric, but if it wasn't a conflict, probably I was focused on making it clear it was for Python and/or easy to type. (the FTP's etc. all had to go through a long directory path that involved the name). The documentation for the CVS stuff was confusing, and I made a mistake with my first submit of 'Numeric' (I think it was ending up with everything in Numeric/Numeric) and then discovered I could not delete it; you had to ask the Source Forge staff. Impatient, I did a second submit as Numerical.
In short, all my fault, but then again, SF was so security-minded that it was hard to do anything. That's why I soon gave up on their website and hosted it at my own site for so long.
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