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|
optimx.run <- function(par, ufn, ugr=NULL, uhess=NULL, lower=-Inf, upper=Inf,
method=c("Nelder-Mead","BFGS"), itnmax=NULL, hessian=FALSE,
ctrl, ...) {
# Run methods
have.bounds<-ctrl$have.bounds
ctrl$have.bounds<-NULL ## or we get errors in optim()
npar<-length(par)
## 131027 modified for Inf 180412
if (length(lower) == 1 && is.finite(lower) ) lower<-rep(lower,npar)
if (length(upper) == 1 && is.finite(upper) ) upper<-rep(upper,npar)
## end 131027
nmeth<-length(method)
pstring<-names(par)
if (is.null(pstring)) {
pstring <- NULL
for (j in 1:npar) { pstring[[j]]<- paste("p",j,sep='')}
}
cnames <- c(pstring, "value", "fevals", "gevals", "niter", "convcode", "kkt1", "kkt2", "xtime")
ans.ret <- matrix(NA, nrow=nmeth, ncol=npar+8)
colnames(ans.ret)<-cnames
row.names(ans.ret)<-method
ans.details <- list()
ansout <- NULL # ensure NULL if we have no parameters or no successes
for (i in 1:nmeth) { # loop over the methods
meth <- method[i] # extract the method name
conv <- -1 # indicate that we have not yet converged
# cat("optimx.run with method ",meth," ctrl:")
# tmp <- readline("CONTINUE")
# print(ctrl)
# 20100608 - take care of polyalgorithms
if (! is.null(itnmax) ) {
if (length(itnmax) == 1) {ctrl$maxit <- itnmax} # Note we will execute this FIRST
else {if (length(itnmax) != nmeth) {
stop("Length of itnmax =",length(itnmax)," but should be ",nmeth) }
else { ctrl$maxit<-itnmax[i] }
}
if (ctrl$follow.on && (ctrl$trace>0)) cat("Do ",ctrl$maxit," steps of ")
}
if (ctrl$trace>0) cat("Method: ", meth, "\n") # display the method being used
# Extract control information e.g., trace
# 20100215: Note that maxit needs to be defined other than 0 e.g., for ucminf
# create local control list for a single method -- this is one of the key issues for optimx
mcontrol<-ctrl
mcontrol$follow.on<-NULL # And make sure that controls NOT in method are deleted (nulled)
mcontrol$usenumDeriv<-NULL # JN130207
mcontrol$save.failures<-NULL
## mcontrol$sort.result<-NULL
mcontrol$kkt<-NULL
mcontrol$starttests<-NULL
mcontrol$all.methods<-NULL
mcontrol$dowarn<-NULL
mcontrol$kkttol<-NULL
mcontrol$kkt2tol<-NULL
mcontrol$maximize<-NULL # Even if method DOES have it
mcontrol$badval<-NULL
mcontrol$scaletol<-NULL
# not used in any methods -- it is here for the scale check of parameters and bounds above
ans.ret[i, "value"] <- .Machine$double.xmax # to ensure value defined for sort
# Methods from optim()
if (meth=="Nelder-Mead" || meth == "BFGS" || meth == "L-BFGS-B" || meth == "CG" || meth == "SANN") {
# if (meth == "SANN") mcontrol$maxit<-10000 # !! arbitrary for now, though SANN NOT really included
# Take care of methods from optim(): Nelder-Mead, BFGS, L-BFGS-B, CG
if (have.bounds) { # 180417 to avoid issues with bounds
if (meth != "L-BFGS-B") stop("Bounds constraints for optim() require L-BFGS-B")
else { time <- system.time(ans <- try(optim(par=par, fn=ufn, gr=ugr,
lower=lower, upper=upper, method=meth,
control=mcontrol, ...), silent=TRUE))[1]
}
} else {time <- system.time(ans <- try(optim(par=par, fn=ufn, gr=ugr,
method=meth, control=mcontrol, ...), silent=TRUE))[1]
} # 180417
# The time is the index=1 element of the system.time for the process,
# which is a 'try()' of the regular optim() function
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
ans$convergence <- NULL
# convergence: An integer code. '0' indicates successful convergence.
# if (meth=="SANN") ans$convcode = 1 # always the case for SANN (but it reports 0!)
ans$fevals<-ans$counts[1] # save function and gradient count information
ans$gevals<-ans$counts[2]
ans$counts<-NULL # and erase the counts element now data is saved
} else { # bad result -- What to do?
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$convcode<-9999 # failed in run
if (ctrl$trace>0) cat("optim function evaluation failure\n")
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$fevals<-NA # save function and gradient count information
ans$gevals<-NA
}
ans$nitns<-NA # not used
} # end if using optim() methods
## --------------------------------------------
else if (meth == "nlminb") {
# Here we use portLib routine nlminb rather than optim as our minimizer
mcontrol$iter.max<-mcontrol$maxit # different name for iteration limit in this routine
mcontrol$maxit<-NULL
mcontrol$abs.tol<-0 # To fix issues when minimum is less than 0. 20100711
if ( is.null(mcontrol$trace) || is.na(mcontrol$trace) || mcontrol$trace == 0) {
mcontrol$trace = 0
} else {
mcontrol$trace = 1 # this is EVERY iteration. nlminb trace is freq of reporting.
}
time <- system.time(ans <- try(nlminb(start=par, objective=ufn, gradient=ugr, lower=lower,
upper=upper, control=mcontrol, ...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
# Translate output to common format and names
ans$value<-ans$objective
ans$objective<-NULL
ans$fevals<-ans$evaluations[1]
ans$gevals<-ans$evaluations[2]
ans$evaluations<-NULL # cleanup
ans$nitns<-ans$iterations
ans$iterations<-NULL
} else { # bad result -- What to do?
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$convcode<-9999 # failed in run
if (ctrl$trace>0) cat("nlminb function evaluation failure\n")
ans$value= ctrl$badval
ans$objective<-NULL
ans$par<-rep(NA,npar)
ans$nitns<-NA # not used
ans$gevals<-NA ## ?? missing 130929
ans$gevals<-NA ## 160826 added
ans$objective<-NULL
# ans$fevals<-ans$evaluations[1] ## 160826 removed
# ans$gevals<-ans$evaluations[2] ## 160826 removed
ans$evaluations<-NULL # cleanup
ans$iterations<-NULL
ans$message <- "nlminb failure" # 160826 added
}
ans$convergence<-NULL
## if (ctrl$maximize) {
## ans$value= -ans$value
## if (ctrl$trace) {
## cat("maximize using nlminb:\n")
## print(ans)
## }
## }
## ans.ret[meth, ] <- c(ans$par, ans$value, ans$fevals, ans$gevals, ans$nitns,
## ans$convcode, ans$kkt1, ans$kkt2, ans$xtimes)
} ## end if using nlminb
## --------------------------------------------
else if (meth == "nlm") { # Use stats package nlm routine
##?? tufn <- ufn # don't want to change user function object, so create copy
if (!is.null(ugr)) {
##?? attr(tufn, "gradient") <- ugr(par, ...) # seems to be evaluating it!
##?? attr(tufn, "gradient") <- ugr
##?? if (!is.null(uhess)) {
##?? attr(tufn, "hessian") <- uhess(par, ...)
##?? } else attr(tufn, "hessian") <- NULL
tufn <- function(x, ...) {
res <- ufn(x, ...)
attr(res,"gradient") <- ugr(x, ...)
return(res)
}
} else {
tufn <- ufn # use function without explicit gradient
}
# cat("ugr in nlm:\n")
# print(ugr)
# cat("tufn in nlm:\n")
# print(tufn)
## 091215 added control for iteration limit
if (! is.null(mcontrol$maxit)) {
iterlim<-mcontrol$maxit
mcontrol$maxit<-NULL # and remove it for this method- fix150120
} else { # null -- had wrong way round
iterlim = 100 # default
}
if (is.null(mcontrol$trace)) { print.level<-0 }
else { # fixed below in call which used to be to mcontrol$trace 150120
print.level<-mcontrol$trace
mcontrol$trace<-NULL
}
# 110121 -- need to put tufn NOT ufn in call
time <- system.time(ans <- try(nlm(f=tufn, p=par, ...,
iterlim=iterlim, print.level=print.level), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
if (ctrl$trace > 1) {
cat("nlm output ans:\n")
print(ans)
}
ans$convcode <- ans$code
if (ans$convcode == 1 || ans$convcode == 2 || ans$convcode == 3) ans$convcode <- 0
if (ans$convcode == 4) ans$convcode <- 1
# Translate output to common format
ans$value<-ans$minimum
ans$par<-ans$estimate
ans$estimate<-NULL
ans$minimum<-NULL
ans$fevals<-NA
ans$gevals<-NA # ?? need to fix this somehow in nlm code
ans$nitns<-ans$iterations
ans$iterations<-NULL
} else {
if (ctrl$trace > 0) cat("nlm failed for this problem\n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
} # end if using nlm
## --------------------------------------------
else if (meth == "spg") { # Use BB package routine spg as minimizer
mcontrol$maximize<-NULL # Use external maximization approach
time <- system.time(ans <- try(BB::spg(par=par, fn=ufn, gr=ugr, lower=lower, upper=upper,
control=mcontrol, ...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
ans$fevals<-ans$feval
ans$feval<-NULL # to erase conflicting name
ans$gevals<-NA # ??fixup needed
ans$nitns<-ans$iter
ans$iter<-NULL
} else { # spg failed
if (ctrl$trace > 0) cat("spg failed for this problem\n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
ans$convergence<-NULL
## if (ctrl$maximize) {
## ans$value= -ans$value
## }
} # end if using spg
## --------------------------------------------
else if (meth == "ucminf") {
## Use ucminf routine
if (is.null(ctrl$maxit)) mcontrol$maxit<-500 # ensure there is a default value
# Change 20100415 to avoid setting ctrl values when all.methods
mcontrol$maxeval<-mcontrol$maxit # Note it is just function evals for ucminf
mcontrol$maxit<-NULL
time <- system.time(ans <- try(ucminf::ucminf(par=par, fn=ufn, gr=ugr, control=mcontrol, ...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
# From ucminf documentation: convergence = 1 Stopped by small gradient (grtol).
# 2 Stopped by small step (xtol).
# 3 Stopped by function evaluation limit (maxeval).
# 4 Stopped by zero step from line search
# -2 Computation did not start: length(par) = 0.
# -4 Computation did not start: stepmax is too small.
# -5 Computation did not start: grtol or xtol <= 0.
# -6 Computation did not start: maxeval <= 0.
# -7 Computation did not start: given Hessian not pos. definite.
# message: String with reason of termination.
if (ans$convcode == 1 || ans$convcode == 2 || ans$convcode == 4) {
ans$convcode <- 0
} else {
ans$convcode <- ans$convergence
} # Termination criteria are tricky here! How to determine successful convergence?
ans$fevals<-ans$info[4]
ans$gevals<-ans$info[4] # calls fn and gr together
ans$info<-NULL # to erase conflicting name
ans$nitns<-NA
if (ctrl$trace > 0) cat("ucminf message:",ans$message,"\n")
} else { # ucminf failed
if (ctrl$trace > 0) cat("ucminf failed for this problem\n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
ans$convergence<-NULL
## if (ctrl$maximize) {
## ans$value= -ans$value
## }
} ## end if using ucminf
## --------------------------------------------
###### progress point #########
else if (meth == "Rcgmin") { # Use Rcgmin routine (ignoring masks)
bdmsk<-rep(1,npar)
mcontrol$trace<-NULL
if (ctrl$trace>0) mcontrol$trace<-1
tugr <- ugr
if (is.null(ugr)){
tugr <- "grfwd"
if (ctrl$trace>0) cat("Rcgmin using grfwd\n")
}
if (have.bounds) {
time <- system.time(ans <- try(Rcgminb(par=par, fn=ufn, gr=tugr, lower=lower, upper=upper,
bdmsk=bdmsk, control=mcontrol, ...), silent=TRUE))[1]
} else {
time <- system.time(ans <- try(Rcgminu(par=par, fn=ufn, gr=tugr,
control=mcontrol, ...), silent=TRUE))[1]
}
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
ans$fevals<-ans$counts[1]
ans$gevals<-ans$counts[2]
ans$counts<-NULL
# ans$value<-ans$value
} else {
if (ctrl$trace>0) cat("Rcgmin failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$fevals<-NA
ans$gevals<-NA
}
ans$nitns<-NA
ans$convergence<-NULL
} ## end if using Rcgmin
## --------------------------------------------
###### progress point #########
else if (meth == "Rvmmin") { # Use Rvmmin routine (ignoring masks)
bdmsk<-rep(1,npar)
mcontrol$trace<-NULL
if (ctrl$trace>0) mcontrol$trace <- ctrl$trace # 180414 was set to 1
tugr <- ugr
if (is.null(ugr)){
tugr <- "grfwd"
if (ctrl$trace>0) cat("Rvmmin using grfwd\n")
}
if (have.bounds) {
time <- system.time(ans <- try(Rvmminb(par=par, fn=ufn, gr=tugr, lower=lower, upper=upper,
bdmsk=bdmsk, control=mcontrol, ...), silent=TRUE))[1]
} else {
time <- system.time(ans <- try(Rvmminu(par=par, fn=ufn, gr=tugr,
control=mcontrol, ...), silent=TRUE))[1]
}
if (!inherits(ans, "try-error")) { # 150423 remove "&& (ans$convergence==0"
ans$convcode <- ans$convergence
ans$fevals<-ans$counts[1]
ans$gevals<-ans$counts[2]
## ans$value<-ans$fvalue
} else {
if (ctrl$trace>0) cat("Rvmmin failed for current problem \n")
# cat("Temporary answer:\n")
# print(ans)
# tmp <- readline()
ans<-list(fevals=NA) # ans not yet defined, so set as list
## ans$value<-ans$fvalue
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
}
ans$nitns<-NA # not used
ans$convergence<-NULL
} ## end if using Rvmmin
## --------------------------------------------
else if (meth == "lbfgsb3c") { # Use lbfgsb3c
mcontrol$maxit <- NULL
mcontrol$maxfeval <- NULL # changed from maxfevals 180321
mcontrol$trace<-NULL
mcontrol$iprint <- -1L
if (ctrl$trace>0) {
mcontrol$trace<-1
mcontrol$iprint <- 1
}
# cat("About to call lbfgsb3 in optimx.run\n")
# print(par)
# print(ufn)
# print(ugr)
time <- system.time(ans <- try(lbfgsb3c::lbfgsb3c(par=par, fn=ufn, gr=ugr,
lower=lower, upper=upper, control=mcontrol, ...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
# ans$fevals<-ans$info$isave[34]
ans$fevals<-ans$counts[1]
ans$gevals<-ans$counts[2]
# ans$value<-ans$f
# ans$par <- ans$prm
# ans$prm <- NULL
# ans$f <- NULL
# ans$info <- NULL
# Note: We don't use the returned gradient. Sigh.
} else {
if (ctrl$trace>0) cat("lbfgsb3c failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
## ans$value<-ans$fvalue
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$fevals<-NA
}
ans$nitns<-NA # not used
ans$convergence<-NULL
} ## end if using lbfgsb3c
## --------------------------------------------
else if (meth == "bobyqa") {# Use bobyqa routine from minqa package
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfun<-mcontrol$maxit
} else {
mcontrol$maxfun<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$iprint<-0
if (mcontrol$trace) mcontrol$iprint<-1
mcontrol$trace<-NULL
time <- system.time(ans <- try(minqa::bobyqa(par=par, fn=ufn, lower=lower, upper=upper, control=mcontrol,...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- 0
# cat("bobyqa - ans$feval = ans$feval\n")
if (ans$feval > mcontrol$maxfun) {
ans$convcode <- 1 # too many evaluations
}
ans$fevals<-ans$feval
ans$gevals<-NA
ans$value<-ans$fval
ans$nitns<-NA # not used
} else {
if (ctrl$trace>0) cat("bobyqa failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
## if (ctrl$maximize) {
## ans$value= -ans$value
## }
} ## end if using bobyqa
## --------------------------------------------
else if (meth == "uobyqa") {# Use uobyqa routine from minqa package
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfun<-mcontrol$maxit
} else {
mcontrol$maxfun<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$iprint<-0
if (mcontrol$trace) mcontrol$iprint<-1
mcontrol$trace<-NULL
time <- system.time(ans <- try(minqa::uobyqa(par=par, fn=ufn, control=mcontrol,...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- 0
if (ans$feval > mcontrol$maxfun) {
ans$convcode <- 1 # too many evaluations
}
ans$fevals<-ans$feval
ans$gevals<-NA
ans$value<-ans$fval
ans$nitns<-NA # not used
} else {
if (ctrl$trace>0) cat("uobyqa failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
## if (ctrl$maximize) {
## ans$value= -ans$value
## }
} ## end if using uobyqa
## --------------------------------------------
else if (meth == "newuoa") {# Use newuoa routine from minqa package
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfun<-mcontrol$maxit
} else {
mcontrol$maxfun<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$iprint<-0
if (mcontrol$trace) mcontrol$iprint<-1
mcontrol$trace<-NULL
time <- system.time(ans <- try(minqa::newuoa(par=par, fn=ufn, control=mcontrol,...), silent=TRUE))[1]
if (!inherits(ans, "try-error")) {
ans$convcode <- 0
if (ans$feval > mcontrol$maxfun) {
ans$convcode <- 1 # too many evaluations
}
ans$fevals<-ans$feval
ans$gevals<-NA
ans$value<-ans$fval
ans$nitns<-NA # not used
} else {
if (ctrl$trace>0) cat("newuoa failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
## if (ctrl$maximize) {
## ans$value= -ans$value
## }
} ## end if using newuoa
## --------------------------------------------
else
if (meth == "nmkb") {# Use nmkb routine from dfoptim package
if (any(par == lower) || any(par==upper)) {
if (ctrl$trace>0) cat("nmkb cannot start if on any bound \n")
warning("nmkb() cannot be started if any parameter on a bound")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run - ?? need special code for nmkb on bounds
ans$fevals<-NA
ans$gevals<-NA
ans$nitns<-NA
} else { # ok to proceed with nmkb()
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfeval<-mcontrol$maxit
} else {
mcontrol$maxfeval<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$maxit<-NULL # and null out control that is NOT used
if (mcontrol$trace > 0) {
mcontrol$trace<-TRUE # logical needed, not integer
} else { mcontrol$trace<-FALSE }
mcontrol$usenumDeriv<-NULL
mcontrol$maximize<-NULL
mcontrol$parscale<-NULL
mcontrol$fnscale<-NULL
# cat("nmkb mcontrol\n")
# print(mcontrol)
# cat("nmkb par:")
# print(par)
# if (have.bounds) {
# time <- system.time(ans <- try(dfoptim::nmkb(par=par, fn=ufn, lower = lower,
# upper = upper, control=mcontrol, ...), silent=TRUE))[1]
# } else {
# time <- system.time(ans <- try(dfoptim::nmk(par=par, fn=ufn,
# control=mcontrol, ...), silent=TRUE))[1]
# }
if (have.bounds) {
time <- system.time(ans <- try(dfoptim::nmkb(par=par, fn=ufn, lower = lower,
upper = upper, control=mcontrol, ...), silent=TRUE))[1]
} else {
## this worked when control=mcontrol did not
## time <- system.time(ans <- try(dfoptim::nmk(par=par, fn=ufn,
## control=list(trace=TRUE), ...)))[1]
## as.list did not work
# print(str(mcontrol))
# print(class(mcontrol))
time <- system.time(ans <- try(dfoptim::nmk(par=par, fn=ufn,
control=mcontrol, ...), silent=TRUE))[1]
}
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
ans$convergence<-NULL
ans$value<-as.numeric(ans$value)
ans$fevals<-ans$feval
ans$feval<-NULL
ans$gevals<-NA
if (ans$fevals > mcontrol$maxfeval) {
ans$convcode <- 1 # too many evaluations
}
ans$nitns<-NA # not used
# What about 'restarts' and 'message'??
# warning(ans$message," Restarts for stagnation =",ans$restarts)
ans$message<-NULL
ans$restarts<-NULL
} else {
if (ctrl$trace>0) cat("nmkb failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$fevals<-NA
ans$gevals<-NA
ans$nitns<-NA
}
} # end of check for parameter on bound
} ## end if using nmkb
## --------------------------------------------
else
if (meth == "hjkb") {# Use hjkb routine from dfoptim package
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfeval<-mcontrol$maxit
} else {
mcontrol$maxfeval<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$info<-FALSE # no trace printed
if (mcontrol$trace > 0) {
mcontrol$info<-TRUE # logical needed, not integer
} else { mcontrol$info<-FALSE }
mcontrol$trace=NULL
mcontrol$usenumDeriv<-NULL
mcontrol$maximize<-NULL
mcontrol$parscale<-NULL
mcontrol$fnscale<-NULL
if (! is.null(mcontrol$maxit)) {
mcontrol$maxfeval<-mcontrol$maxit
} else {
mcontrol$maxfeval<-5000*round(sqrt(npar+1)) # ?? default at 100215, but should it be changed?!!
}
mcontrol$maxit<-NULL # and null out control that is NOT used
if (have.bounds) {
time <- system.time(ans <- try(dfoptim::hjkb(par=par, fn=ufn, lower = lower,
upper = upper, control=mcontrol, ...), silent=TRUE))[1]
} else {
time <- system.time(ans <- try(dfoptim::hjk(par=par, fn=ufn,
control=mcontrol, ...), silent=TRUE))[1]
}
if (!inherits(ans, "try-error")) {
ans$convcode <- ans$convergence
if (ans$convcode == 1) ans$convcode=9999
ans$convergence<-NULL
ans$value<-as.numeric(ans$value)
ans$fevals<-ans$feval
ans$feval<-NULL
if (ans$fevals > mcontrol$maxfeval) {
ans$convcode <- 1 # too many evaluations
}
ans$gevals<-NA
ans$nitns<-ans$niter
ans$niter <- NULL
} else {
if (ctrl$trace>0) cat("hjkb failed for current problem \n")
ans<-list(fevals=NA) # ans not yet defined, so set as list
ans$value= ctrl$badval
ans$par<-rep(NA,npar)
ans$convcode<-9999 # failed in run
ans$gevals<-NA
ans$nitns<-NA
}
} ## end if using hjkb
## --------------------------------------------
# --- UNDEFINED METHOD ---
else { errmsg<-paste("UNDEFINED METHOD: ", meth, sep='')
stop(errmsg, call.=FALSE)
}
## --------------------------------------------
## Post-processing -- Kuhn Karush Tucker conditions
# Ref. pg 77, Gill, Murray and Wright (1981) Practical Optimization, Academic Press
if (ctrl$trace>0) { cat("Post processing for method ",meth,"\n") }
if (exists("ans$message")) {
amsg<-ans$message
ans$message <- NULL
} else { amsg <- "none" }
ngatend <- NA
nhatend <- NA
hev <- NA
if ( ctrl$save.failures || (ans$convcode < 1) ){# Save soln if converged or directed to save
if (ctrl$trace && ans$convcode==0) cat("Successful convergence! \n")
# Testing final soln. Use numDeriv for gradient & Hessian; compute Hessian eigenvalues
hessOK<-FALSE # indicator for later
gradOK<-FALSE
if ((ctrl$kkt || hessian) && (ans$convcode != 9999)) {
if (ctrl$trace>0) cat("Compute Hessian approximation at finish of ",method[i],"\n")
if (!is.null(uhess)){ # check if we have analytic hessian
nhatend<-try(uhess(ans$par, ...), silent=TRUE)
if (!inherits(nhatend, "try-error")) {
hessOK<-TRUE
}
} else {
if (is.null(ugr)) {
nhatend<-try(hessian(ufn, ans$par, ...), silent=TRUE) # change 20100711
} else {
nhatend<-try(jacobian(ugr,ans$par, ...), silent=TRUE) # change 20100711
} # numerical hessian at "solution"
if (!inherits(nhatend, "try-error")) { # no ! found 200127
hessOK<-TRUE
}
} # end hessian calculation
} # end test if hessian computed
ans$kkt1<-NA
ans$kkt2<-NA
if ((hessian || ctrl$kkt) && (ans$convcode != 9999)) {# avoid test when method failed
if (ctrl$trace>0) cat("Compute gradient approximation at finish of ",method[i],"\n")
if (is.null(ugr)) {
ngatend<-try(grad(ufn, ans$par, ...), silent=TRUE) # change 20100711
} else {
ngatend<-try(ugr(ans$par, ...), silent=TRUE) # Gradient at solution # change 20100711
}
if (!inherits(ngatend, "try-error")) gradOK<-TRUE # 100215 had == rather than != here
if ( (! gradOK) && (ctrl$trace>0)) cat("Gradient computation failure!\n")
if (gradOK) {
# test gradient
ans$kkt1<-(max(abs(ngatend)) <= ctrl$kkttol*(1.0+abs(ans$value)) ) # ?? sensible?
if (hessOK) {
# For bounds constraints, we need to "project" the gradient and Hessian
bset<-sort(unique(c(which(ans$par<=lower), which(ans$par>=upper))))
nbds<-length(bset) # number of elements nulled by bounds
# Note: we assume that we are ON, not over boundary,
# but use <= and >=. No tolerance is used.
ngatend[bset]<-0 # "project" the gradient
nhatend[bset,] <-0
nhatend[, bset] <-0 # and the Hessian
if (!isSymmetric(nhatend, tol=sqrt(.Machine$double.eps))) {
# hessOK<-FALSE ## Assume we will keep hessian after symmetrizing
asym <- sum(abs(t(nhatend) - nhatend))/sum(abs(nhatend))
asw <- paste("Hessian is reported non-symmetric with asymmetry ratio ",
asym, sep = "")
if (ctrl$trace > 1) cat(asw, "\n")
if (ctrl$dowarn) warning(asw)
### if (asym > ctrl$asymtol) stop("Hessian too asymmetric") ##??as yet don't stop
if (ctrl$trace > 1) cat("Force Hessian symmetric\n")
if (ctrl$dowarn) warning("Hessian forced symmetric", call. = FALSE)
nhatend <- 0.5 * (t(nhatend) + nhatend)
} # end symmetry test
hev<- try(eigen(nhatend)$values, silent=TRUE) # 091215 use try in case of trouble
if (ctrl$kkt){
if (! inherits(hev, "try-error")) {# 200127 missing !
# answers are OK, check Hessian properties
if (any(is.complex(hev))){
hessOK<-FALSE
cat("Complex eigenvalues found for method =",meth,"\n")
cat("coefficients for function value", ans$value," :\n")
print(ans$par)
dput(nhatend, file="badhess.txt")
warning("Complex eigenvalues found for method =",meth)
}
if (hessOK) {
negeig<-(hev[npar] <= (-1)*ctrl$kkt2tol*(1.0+abs(ans$value)))
evratio<-hev[npar-nbds]/hev[1]
# If non-positive definite, then there have zero evs (from the projection)
# in the place of the "last" eigenvalue and we'll have singularity.
# WARNING: Could have a weak minimum if semi-definite.
ans$kkt2<- (evratio > ctrl$kkt2tol) && (! negeig)
}
} else {
warnstr<-paste("Eigenvalue failure after method ",method[i],sep='')
if (ctrl$dowarn) warning(warnstr)
if (ctrl$trace>0) {
cat("Hessian eigenvalue calculation failure!\n")
print(nhatend)
}
}
} # kkt2 evaluation
} else { # computing Hessian has failed
warnstr<-paste("Hessian not computable after method ",method[i],sep='')
if (ctrl$dowarn) warning(warnstr)
if (ctrl$trace>0) cat(warnstr,"\n")
}
} else { # gradient failure
warnstr<-paste("Gradient not computable after method ",method[i],sep='')
if (ctrl$dowarn) warning(warnstr)
if (ctrl$trace>0) cat(warnstr,"\n")
}
} # end kkt test
ans$xtimes <- time
# Do we want more information saved?
if (ctrl$trace>0) {
cat("Save results from method ",meth,"\n")
print(ans)
}
if (ctrl$trace>0) { cat("Assemble the answers\n") }
ans.ret[meth, ] <- c(ans$par, ans$value, ans$fevals, ans$gevals, ans$nitns,
ans$convcode, ans$kkt1, ans$kkt2, ans$xtimes)
if (! gradOK) ngatend <- NA
if (! hessOK) {
nhatend <- NA
hev <- NA
}
} ## end post-processing of successful solution
ans.details<-rbind(ans.details, list(method=meth, ngatend=ngatend, nhatend=nhatend, hev=hev, message=amsg))
# 1303234 try list() not c()
row.names(ans.details)[[i]]>=meth
if (ctrl$follow.on) {
par <- ans$par # save parameters for next method
if (i < nmeth && (ctrl$trace>0)) cat("FOLLOW ON!\n") # NOT trace ??
}
} ## end loop over method (index i)
ansout <- NULL # default if no answers
if (length(ans$par) > 0) { # cannot save if no answers
ansout <- data.frame(ans.ret)# Don't seem to need drop=FALSE
attr(ansout, "details")<-ans.details
}
ansout # return(ansout)
} ## end of optimx.run
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