I'm considering giving it another try using Stream Processors or some form of Arrows instead of lists. I think this strategy might allow me to do several transformations of the same input list in pseudo-parallel, which would allow the GC to collect old data as soon as its not needed by the computation that decides when to buy and sell. The Stream Processor library I was looking at uses Continuation Passing Style, which I don't know too much about, and I'm not sure Arrows will work out.
Generalizing the problem, how does one express: "given multiple transformations of an infinite numeric list, perform some IO at the first instance some predicate is met"?
I feel that Arrows might somehow trivially allow me to compute on huge lists without leaking, but don't understand them well enough to apply them.
If one could write an arrow that applies the transformations to the input list in parallel, then I'd think you could solve the above example something like this:
(f &&& g) >>> dropWhile (\(x,y) -> x > 0 && y > 0) >>> performSomeIO
Maybe <+> is the arrow operator I'm looking for, not &&&, but to be honest, the documentation for Arrows blows my mind. I think a few examples would go a long way.
Thanks,
Greg
On 7/6/06, Joel Reymont <[EMAIL PROTECTED]> wrote:
Is anyone using Haskell for heavy numerical computations? Could you
share your experience?
My app will be mostly about running computations over huge amounts of
stock data (time series) so I'm thinking I might be better of with
OCaml.
Thanks, Joel
--
http://wagerlabs.com/
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