[Numpy-discussion] vectorized version of logsumexp? (from scipy.maxentropy)
Sat Oct 17 18:27:55 CDT 2009
On Sat, Oct 17, 2009 at 2:02 PM, Charles R Harris
> On Sat, Oct 17, 2009 at 11:54 AM, <email@example.com> wrote:
>> On Sat, Oct 17, 2009 at 1:20 PM, Charles R Harris
>> <firstname.lastname@example.org> wrote:
>> > On Sat, Oct 17, 2009 at 9:36 AM, per freem <email@example.com> wrote:
>> >> hi all,
>> >> in my code, i use the function 'logsumexp' from scipy.maxentropy a
>> >> lot. as far as i can tell, this function has no vectorized version
>> >> that works on an m-x-n matrix. i might be doing something wrong here,
>> >> but i found that this function can run extremely slowly if used as
>> >> follows: i have an array of log probability vectors, such that each
>> >> column sums to one. i want to simply iterate over each column and
>> >> renormalize it, using exp(col - logsumexp(col)). here is the code that
>> >> i used to profile this operation:
>> >> from scipy import *
>> >> from numpy import *
>> >> from numpy.random.mtrand import dirichlet
>> >> from scipy.maxentropy import logsumexp
>> >> import time
>> > Why aren't you using logaddexp ufunc from numpy?
>> Maybe because it is difficult to find, it doesn't have its own docs entry.
>> e.g. no link to logaddexp in
>> I have no idea, why it is different from the other ufuncs in the docs
>> (and help file).
>> It shows up correctly in the docs editor, but not in the numpy 1.3 and
>> online docs.
> That's curious, none of the five ufuncs added in 1.3 have links even though
> they all have documentation.
I found that they are missing from routines.math
I added logaddexp, logaddexp2 and exp2
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