[Numpy-discussion] vectorized version of logsumexp? (from scipy.maxentropy)
Charles R Harris
Sat Oct 17 13:02:37 CDT 2009
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.
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