Hi everyone, First of all, thanks very much for GSLL. It's impressively comprehensive, and it's making my life a lot easier. 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: (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