[Numpy-discussion] vectorized version of logsumexp? (from scipy.maxentropy)
Charles R Harris
charlesr.harris@gmail....
Sat Oct 17 14:02:09 CDT 2009
On Sat, Oct 17, 2009 at 12:59 PM, Charles R Harris <
charlesr.harris@gmail.com> wrote:
>
>
> On Sat, Oct 17, 2009 at 12:40 PM, Neal Becker <ndbecker2@gmail.com> wrote:
>
>> Somewhat offtopic, but is there a generalization of the logsumexp shortcut
>> to more than 2 variables?
>>
>> IIRC, it's this for 2 variables:
>> log (exp (a) + exp (b)) = max (a,b) + log (1 + exp (-abs (a-b)))
>>
>>
> logaddexp.reduce will apply it along array rows. The reduce loop could
> probably be optimized a bit using the methods that Dale used to optimize the
> reduce case for add. Hmm, the reduce loop would need to be implemented for
> the generic loops. The logaddexp case could possibly be optimized further by
> writing a specialized loop for the reduce case.
>
>
Example:
In [1]: x = arange(9).reshape(3,3)
In [2]: logaddexp.reduce(x, axis=1)
Out[2]: array([ 2.40760596, 5.40760596, 8.40760596])
In [3]: logaddexp.reduce(x, axis=0)
Out[3]: array([ 6.05094576, 7.05094576, 8.05094576])
Chuck
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