Hi Nicholas, Thanks for the advice. I already tried (set! *warn-on-reflection* true), but it doesn't generate any warnings for any of these functions.
I tried adding ^doubles in gaussian-matrix1 as you suggested but that didn't really change the speed at all. And changing next-gaussian to a macro didn't make much difference to gaussian-matrix1, and it doesn't work with gaussian-matrix2 at all and I'm not quite sure yet how to fix it so it does. I would have thought gaussian-matrix1 would be faster than gaussian- matrix2, but it turns out it's the opposite. Then I thought that the reason using aset was slower must have something to do with reflection, but that doesn't seem to be the case. So I'm a bit confused now. More generally though, the main reason I wanted to use Java arrays was because I have to use FFT's in my simulation and I figured it would be better to do everything in Java arrays rather than copy a Clojure vector into a 2d array and back every time I needed to do an FFT. But am I wrong in thinking that? Thanks, Ranjit On Sep 19, 11:20 am, Nicolas Oury <nicolas.o...@gmail.com> wrote: > A first good start is to put > (set! *warn-on-relection* true) at the start of the file and removes > all reflective access. > > Before the 1.3 release, function cannot receive/returns primitive so > you might consider > (defmacro next-gaussian [] > `(.nextGaussian ^Random r)) > > (^Random is here to make sure r is seen with the right type) > > in both function, add ^doubles before arr at the binding point. > (defn ... [^doubles arr....]) > > then set will not be rflective and be as fast as a set in java. > > Ask other questions of you need more help. > The best reference on all that: clojure.org/java_interop > > > > On Sun, Sep 19, 2010 at 3:29 PM, Ranjit <rjcha...@gmail.com> wrote: > > Hi, > > > I'm trying learn Clojure to see if I can use it in my simulations, and > > one thing I need to do is generate arrays of normally distributed > > numbers. > > > I've been able to come up with the following two ways of doing this. > > gaussian-matrix2 is a lot faster than gaussian-matrix1, but I'm not > > sure why. And it's still slower than it should be I think. Is there > > anything I can do to speed this up still further? > > > Thanks, > > > -Ranjit > > > (import java.util.Random) > > (def r (Random. )) > > > (defn next-gaussian [] (.nextGaussian r)) > > > (defn gaussian-matrix1 [arr L] > > (doseq [x (range L) y (range L)] (aset arr x y (next-gaussian)))) > > > (defn gaussian-matrix2 [L] > > (into-array (map double-array (partition L (repeatedly (* L L) > > next-gaussian))))) > > > -- > > You received this message because you are subscribed to the Google > > Groups "Clojure" group. > > To post to this group, send email to clojure@googlegroups.com > > Note that posts from new members are moderated - please be patient with > > your first post. > > To unsubscribe from this group, send email to > > clojure+unsubscr...@googlegroups.com > > For more options, visit this group at > >http://groups.google.com/group/clojure?hl=en > > -- > Sent from an IBM Model M, 15 August 1989. -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en
