[CppAD] Computung the sparsity pattern

[Philipp Bender]

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Dear list,

I have a problem understanding the sparsity methods CppAD provides and
following the example leaves me with some questions -- I hope someone
here can help me out.

I think rev_sparse_hess.cpp is what I need to learn, along with
Doc/forsparsejac.xml.

I have a function, for example R^6 --> R^2, and want to know where
first and second derivatives are known to be zero, no matter what the
input is like.

I have the tape called "f".

Now I begin to miss things. In my understanding, the sparsity pattern
for my R^6 -> R^2 problem should be of the shape (2x6) in the
Jacobian, and I should be able to directly obtain this from the tape.
So I wonder why in the example and the documentation there is this "r"
vector (shape nxn), and where it comes from?

Now for the Hessian. In the example h(nxn) should hold the result.
With vector s, the "output" is selected (in which of both output
variables of my range space am I interested in). Now I get an error if
I just leave the ForSparceJac part out. So obtaining the sparsity for
the Jacobian seems to have side effects needed by the Jacobian.

Are this practical issues I just have to live with or are there
serious AutoDiff issues I am missing here?

Is there some documentation for me to read about where this "R" comes
from which I need for the Jacobian? I think the identity matrix is
just an example, but I don't get the relation here.

Best regards,
Philipp



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