[SciPy-user] [ANN][Automatic Differentiation] Beta Version of PYADOLC

Sebastian Walter sebastian.walter@gmail....
Tue May 12 09:07:38 CDT 2009

I am  pleased to announce the release of PYADOLC (beta version).

Homepage: http://github.com/b45ch1/pyadolc/
For download and instructions check the homepage.

About the package
PYADOLC is a wrapper of the C++ software ADOL-C.
It computes derivatives of arbitrarily complex algorithms  (with loops
and if then else) efficiently on the C++ side.

0) easy and pythonic user interface
1) efficient computation of _gradients_ g, _Hessians_ H and _higher_
order tensors T
2) efficient computation of products   dot(u.T, H), dot(H,v) as they
are needed in optimization algorithms
3) well documented by docstrings. For more information one can read
the C++ documentation.
4) extensive unit test and many examples, including constrained
optimization by projected gradients, etc ...
5) should be suitable for derivative generation of rather large scale
optimization problems.
   E.g. optimal control problems, inverse problems,  This is not tested though.
6) Sparse Jacobian support.

Suggestions and Bugs:
Please report any bugs or inconveniences that you encounter!
E.g. just write me if you have troubles with the installation.

Everything *should* work as you expect.
Sparse Jacobian support is experimental and the build process needs a
little user assistance but should work.

The API is not completely fixed. However, changes to the API will be
backward compatible.

Hope someone can make use of it.


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