On Tue, Jun 9, 2009 at 6:34 PM, James Wrightjames@chumsley.org wrote:
Hi everyone,
First of all, thanks very much for GSLL. It's impressively comprehensive, and it's making my life a lot easier.
Thanks. Slowly, still more is coming, not complete yet...
I've been using `gsl:make-multi-dimensional-minimizer-f' in one of my projects for a while now, and I'm looking at switching to one of the gradient-based methods instead. However, I can't figure out how SCALARSP works with the f-and-gradient function.
As a very simple example, consider the function F(x1 x2) = x1^2 + x2^3:
You're trying to minimize a cubic? See below.
(defun f (x1 x2) (+ (* x1 x1) (* x2 x2 x2)))
For the function-and-gradient function, I need to return the value at [x1 x2], plus a vector of 2 partial derivatives. In total that's 3 items, so I had thought that the following function would work:
(defun h (x1 x2) (values (+ (* x1 x1) (* x2 x2 x2)) (* 2 x1) (* 3 x2 x2)))
However, when I try to use it like so:
(gsl:make-multi-dimensional-minimizer-fdf gsl:+vector-bfgs2+ 2 '(f g h) #m(9.0 9.0) 0.1d0 0.1d0 t)
I get a TYPE-ERROR: The value NIL is not of type DOUBLE-FLOAT. I'm fairly sure that my definition of H is the problem here, because when I trace F, G, and H, H is the only function that gets called.
I've also tried having H return F(X) as the first value and the gradient vector as the second value, but no dice. (SBCL complains that a double-float vector is not a double-float, which is true. :)
I'm running SBCL and the most recent version of GSLL (I pulled from the master branch about an hour ago). Could anyone give me a hint as to what I'm doing wrong here? I could always implement using non-scalarsp functions, but if that's the only fix, then it seems pointless for make-multi-dimensional-minimizer-fdf to take a scalarsp argument in the first place.
Thanks very much! James
There was definitely a bug in the multidimensional minimizer code, which I've now fixed, so do a fresh pull of master. Thanks for the alert. However, you are giving it a function which has no minimum, because the cubic is unbounded negative. I was kind of hoping GSL would alert you to this fact, but in fact it gets a "solution" which is a bit hard to explain (and definitely not a minimum).
I have created a scalar example which is the same as the vector case, the parabaloid, at the end of the file minimization-multi.lisp. It gets an answer identical to the vector result. It has been added to the examples/tests 'minimization-multi.
Liam