[Rd] nlminb with constraints failing on some platforms
ProfJCNash
pro|jcn@@h @end|ng |rom gm@||@com
Thu Jan 31 19:32:31 CET 2019
I'm not entirely sure what you are asking. However, optimx is really NOT
meant as a production tool. I intend it as a way to
1) try out a lot of optimizers quickly on a user's problem or problem
class to select a method or methods that suit well;
2) to provide (in the source code of optimr()) an example of how to
call the particular optimizers. They all have a lot of different syntax
elements, which in fact are the biggest headache in building and
extending optimx.
Best, JN
On 2019-01-31 9:26 a.m., Amit Mittal wrote:
> Prof Nash, Prof Galanos
>
> Is it possible to use a generic code stub in front of packages that use
> optimx to improve optimx use or curtail it according to the requirements?
>
>
> Best Regards
>
> Amit
>
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> On Thu, Jan 31, 2019 at 7:22 PM ProfJCNash <profjcnash using gmail.com
> <mailto:profjcnash using gmail.com>> wrote:
>
> This is not about the failure on some platforms, which is an important
> issue. However, what is below may provide a temporary workaround until
> the source of the problem is uncovered.
>
> FWIW, the problem seems fairly straightforward for most optimizers at my
> disposal in the R-forge (developmental) version of the optimx package at
> https://r-forge.r-project.org/projects/optimizer/
>
> I used the code
>
> ## KKristensen19nlminb.R
> f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 )
> opt <- nlminb(rep(0, 10), f, lower=-1, upper=3)
> xhat <- rep(1, 10)
> abs( opt$objective - f(xhat) ) < 1e-4 ## Must be TRUE
> opt
> library(optimx)
> optx <- opm(rep(0,10), f, lower=-1, upper=3, method="ALL")
> summary(optx, order=value)
> optxc <- opm(rep(0,10), f, gr="grcentral", lower=-1, upper=3,
> method="ALL")
> summary(optxc, order=value)
> optxn <- opm(rep(0,10), f, gr="grnd", lower=-1, upper=3, method="ALL")
> summary(optxn, order=value)
>
> It should not be too difficult to actually supply the gradient, which
> would give speedier and more reliable outcomes.
>
>
> JN
>
>
>
> On 2019-01-28 3:56 a.m., Kasper Kristensen via R-devel wrote:
> > I've noticed unstable behavior of nlminb on some Linux systems.
> The problem can be reproduced by compiling R-3.5.2 using gcc-8.2 and
> running the following snippet:
> >
> > f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 )
> > opt <- nlminb(rep(0, 10), f, lower=-1, upper=3)
> > xhat <- rep(1, 10)
> > abs( opt$objective - f(xhat) ) < 1e-4 ## Must be TRUE
> >
> > The example works perfectly when removing the bounds. However,
> when bounds are added the snippet returns 'FALSE'.
> >
> > An older R version (3.4.4), compiled using the same gcc-8.2, did
> not have the problem. Between the two versions R has changed the
> flags to compile Fortran sources:
> >
> > < SAFE_FFLAGS = -O2 -fomit-frame-pointer -ffloat-store
> > ---
> >> SAFE_FFLAGS = -O2 -fomit-frame-pointer -msse2 -mfpmath=sse
> >
> > Reverting to the old SAFE_FFLAGS 'solves' the problem.
> >
> >> sessionInfo()
> > R version 3.5.2 (2018-12-20)
> > Platform: x86_64-pc-linux-gnu (64-bit)
> > Running under: Scientific Linux release 6.4 (Carbon)
> >
> > Matrix products: default
> > BLAS/LAPACK:
> /zdata/groups/nfsopt/intel/2018update3/compilers_and_libraries_2018.3.222/linux/mkl/lib/intel64_lin/libmkl_gf_lp64.so
> >
> > locale:
> > [1] C
> >
> > attached base packages:
> > [1] stats graphics grDevices utils datasets methods base
> >
> > loaded via a namespace (and not attached):
> > [1] compiler_3.5.2
> >
> >
> >
> > [[alternative HTML version deleted]]
> >
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