Does anyone know of any Haskell code for numeric minimization? I was thinking conjugate gradient would be good, but at this point I'd be happy with anything. I've found some code written by Tomasz Cholewo at http://ci.uofl.edu/tom/software/Haskell/ but it requires importing his "Arr.lhs" library, which is not publicly available. The only other thing I've been able to dig up is this www.st.cs.ru.nl/papers/1997/serp97-cgfunctional.ps.gz which suggests Haskell is slow for such problems. I suspect this was an implementation issue, so I don't think their code would be very helpful (though it would be nice to tidy it up and demonstrate the improvement - could it beat the Clean implementation they give?) The other possibility I was considering was using Alberto Ruiz's wrapper for the GSL library http://dis.um.es/~alberto/GSLHaskell/ The only problems with this are (1) requires having GSL available, so it's not as portable, and (2) does everything in terms of lists, which requires a lot of translations to and from lists (I'm using mutable arrays). If there's nothing already written that works together, one of these should give me a start, but I'd like to avoid reinventing the wheel if possible. Thanks! -- Chad Scherrer "Time flies like an arrow; fruit flies like a banana" -- Groucho Marx