Hey Mani,
I've included Rick Ratzel on this since he is the author of elmer and
may have more guidance.
eric
mani sabri wrote:
> Hi
> Sorry for irrelevant subject.
> I found elmer when I was googling for something to wrap my python/numpy code
> to C/C++ automatically because I want a dll for
's related to matrix multiplication and devision, either point or
>> matrix (i.e. like A\B, A*B, dot(A,B)).
>>
>
> Eric Jones has made an attempt.
>
>http://svn.scipy.org/svn/numpy/branches/multicore/
>
> Unfortunately, the overhead of starting the
Just looked at this... Now that is just cool.
I'd say it should be part of Numpy.
eric
Bill Baxter wrote:
> On 3/19/07, Bill Baxter <[EMAIL PROTECTED]> wrote:
>
>> I wrote a little python module to go fetch the Numpy examples from the
>> scipy wiki page, parse them, and print out entries.
>
I recently noticed that we can't pickle ufuncs (like sin, ...). Is
there any technical reason this doesn't work, or is it in the category
of 'just needs to be done...'
FYI, I noticed that it didn't work on the old Numeric either.
thanks,
eric
Python 2.4.3 - Enthought Edition 1.0.0 (#69, Aug
Thanks for the update. For now, I'll try doing what I need to by
sub-classing float. But, I'm gonna miss __array_finalize__ :-).
eric
Travis Oliphant wrote:
> eric jones wrote:
>
>
>> Hey all,
>>
>> I am playing around with sub-classing the new-fangle
Hey all,
I am playing around with sub-classing the new-fangled float64 objects
and friends. I really like the new ndarray subclassing features
(__array_finalize__, etc.), and was exploring whether or not the scalars
worked the same way. I've stubbed my toe right out of the blocks
though. I
I just noticed a bug in this code. "PyArray_ITER_NEXT(iter);" should be moved
out of the if statement.
eric
eric jones wrote:
>
>
> Rick White wrote:
>> Just so we don't get too smug about the speed, if I do this in IDL
>> on the same machine it is 10 t
Rick White wrote:
Just so we don't get too smug about the speed, if I do this in IDL on
the same machine it is 10 times faster (0.28 seconds instead of 4
seconds). I'm sure the IDL version uses the much faster approach of
just sweeping through the array once, incrementing counts in the
Looks to me like Rick's version is simpler and faster.It looks like it
offers a speed-up of about 1.6 on my machine over the weave version. I
believe this is because the sorting approach results in quite a few less
compares than the algorithm I used.
Very cool. I vote that his version go int
r options I've tried. On my laptop it took 30 seconds
> to generate a histogram from 500 million numbers, which is fine.
>
> Thanks and best regards,
>
> Cameron.
>
>
> On 14/12/06, eric jones <[EMAIL PROTECTED]> wrote:
>
>> Hmmm.
>>
>> ?
Hmmm.
? Not sure. ?
Change that line to this instead which should work as well.
code = array_converter.declaration_code(self, templatize, inline)
Both work for me.
eric
Cameron Walsh wrote:
> On 13/12/06, Cameron Walsh <[EMAIL PROTECTED]> wrote:
>
>> On 13
Hey Cameron,
I wrote a simple weave based histogram function that should work for
your problem. It should work for any array input data type. The needed
files (and a few tests and examples) are attached.
Below is the output from the histogram_speed.py file attached. The test
takes about 1
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