Hi Ajo, Le 19/09/2013 16:26, Ajo Fod a écrit : > Created: https://issues.apache.org/jira/browse/MATH-1036#comment-13771933
This looks promising. Would it be possible to have this class implement RealFieldElement<GradStructure> and to have some unit tests? best regards, Luc > > > > On Thu, Sep 19, 2013 at 12:29 AM, luc <l...@spaceroots.org> wrote: > >> Le 2013-09-19 08:26, Ajo Fod a écrit : >> >>> Hello, >>> >> >> Hi Ajo, >> >> >> >>> Ran into problems with DerivativeStructure today. It requires a lot of >>> memory with 6000 or so independent variables. I poked around and found >>> it the problem starts with the number of DSCompiler objects >>> instantiated. >>> >> >> Yes, this is a know side effect of the ability to handle both several >> variables >> and several derivative orders. It is even worse when you combine medium >> numbers >> but along both axes (say 20 derivatives and 20 variables, I guess it is >> almost >> impossible to fir in memory of regular desktop computers). >> >> >> >>> Given this and my earlier observation that in sparse derivative trees, >>> the existing structure allocates space for all independent variables >>> and hence is computationally inefficient, I designed a >>> faster/leaner(less memory) structure. >>> >>> One shortcomming of DS is that it computes only up to the first >>> derivative. This may not be a problem in many cases such as the >>> minimization of a multivariate function where optimization can be much >>> quicker with a gradient. Going as far as the hessian may be >>> fundamentally too memory or time intensive. So, it is useful to have >>> an easier method to computing just the first derivative. >>> >> >> This sound interesting, I hope it could be added as a more specialized >> alternative. The name should probably be adapted to reflect it is designed >> for order 1 and many variables (perhaps DerivativeStructure1N or something >> like that). >> >> >> >>> The design of DS is that all DS instances created either as a results >>> of calling: >>> >>> DS.getConst(value); // for constants >>> >>> DS.getVariable(idx, value); // for independent variables >>> >>> ... OR as a rest of some computation. >>> >>> I felt it appropriate to add an addInPlace and multInPlace for >>> aggregation processes so that objects are not copied over too often. >>> >> >> If you handle a really large number of variables at the same time, it >> makes sense (same discussion as why general matrices and vectors are often >> not immutable). >> >> >>> Attached is the code. >>> >> >> Attachments are automatically stripped from messages sent to the list. >> Small >> code snippets can be written directly in the mail, but larger >> contributions can >> only be attached to JIRA issues (but still discussion occurs on the list, >> yes, >> its cumbersome, we are sorry for that). >> >> Thank you very much for you interest in this field of differentiation. >> >> best regards, >> Luc >> >> >>> Cheers, >>> Ajo >>> >>> >>> ------------------------------**------------------------------**--------- >>> To unsubscribe, e-mail: >>> dev-unsubscribe@commons.**apache.org<dev-unsubscr...@commons.apache.org> >>> For additional commands, e-mail: dev-h...@commons.apache.org >>> >> >> ------------------------------**------------------------------**--------- >> To unsubscribe, e-mail: >> dev-unsubscribe@commons.**apache.org<dev-unsubscr...@commons.apache.org> >> For additional commands, e-mail: dev-h...@commons.apache.org >> >> > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
