[Numpy-discussion] Automatic differentiation (was Re: second-order gradient)

Rob Clewley rob.clewley@gmail....
Thu Oct 30 10:16:03 CDT 2008

> Maybe we should focus on writing a decent 'deriv' function then.  I
> know Konrad Hinsen's Scientific had a derivatives package
> (Scientific.Functions.Derivatives) that implemented automatic
> differentiation:
> http://en.wikipedia.org/wiki/Automatic_differentiation

That would be great, but wouldn't that be best suited as a utility
requiring Sympy? You'll want to take advantage of all sorts of
symbolic classes, especially for any source code transformation
approach. IMO Hinsen's implementation isn't a very efficient or
attractive solution to AD given the great existing C/C++ codes out
there. Maybe we should be looking to provide a python interface to an
existing open source package such as ADOL-C, but I'm all in favour of
a new pure python approach too. What would be perfect is to have a
single interface to a python AD package that would support a faster
implementation if the user wished to install a C/C++ package,
otherwise would default to a pure python equivalent.


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