optimx (version 2023-10.21)

fnchk: Run tests, where possible, on user objective function

Description

fnchk checks a user-provided R function, ffn.

Usage

fnchk(xpar, ffn, trace=0, ... )

Value

The output is a list consisting of list(fval=fval, infeasible=infeasible, excode=excode, msg=msg)

fval

The calculated value of the function at parameters xpar if the function can be evaluated.

infeasible

FALSE if the function can be evaluated, TRUE if not.

excode

An exit code, which has a relationship to

msg

A text string giving information about the result of the function check: Messages and the corresponding values of excode are:

fnchk OK;

excode = 0; infeasible = FALSE

Function returns INADMISSIBLE;

excode = -1; infeasible = TRUE

Function returns a vector not a scalar;

excode = -4; infeasible = TRUE

Function returns a list not a scalar;

excode = -4; infeasible = TRUE

Function returns a matrix list not a scalar;

excode = -4; infeasible = TRUE

Function returns an array not a scalar;

excode = -4; infeasible = TRUE

Function returned not length 1, despite not vector, matrix or array;

excode = -4; infeasible = TRUE

Function returned non-numeric value; excode = 0;

excode = -1; infeasible = TRUE

Function returned Inf or NA (non-computable);

excode = -1; infeasible = TRUE

Arguments

xpar

the (double) vector of parameters to the objective funcion

ffn

a user-provided function to compute the objective function

trace

set >0 to provide output from fnchk to the console, 0 otherwise

...

optional arguments passed to the objective function.

Author

John C. Nash <[e-mail]>

Details

fnchk attempts to discover various errors in function setup in user-supplied functions primarily intended for use in optimization calculations. There are always more conditions that could be tested!

Examples

# Want to illustrate each case.
# Ben Bolker idea for a function that is NOT scalar
# rm(list=ls())
# library(optimx)
sessionInfo()
benbad<-function(x, y){
  # y may be provided with different structures
  f<-(x-y)^2
} # very simple, but ...

y<-1:10
x<-c(1)
cat("fc01: test benbad() with y=1:10, x=c(1)\n")
fc01<-fnchk(x, benbad, trace=4, y)
print(fc01)

y<-as.vector(y)
cat("fc02: test benbad() with y=as.vector(1:10), x=c(1)\n")
fc02<-fnchk(x, benbad, trace=1, y)
print(fc02)

y<-as.matrix(y)
cat("fc03: test benbad() with y=as.matrix(1:10), x=c(1)\n")
fc03<-fnchk(x, benbad, trace=1, y)
print(fc03)

y<-as.array(y)
cat("fc04: test benbad() with y=as.array(1:10), x=c(1)\n")
fc04<-fnchk(x, benbad, trace=1, y)
print(fc04)

y<-"This is a string"
cat("test benbad() with y a string, x=c(1)\n")
fc05<-fnchk(x, benbad, trace=1, y)
print(fc05)

cat("fnchk with Rosenbrock\n")
fr <- function(x) {   ## Rosenbrock Banana function
  x1 <- x[1]
  x2 <- x[2]
  100 * (x2 - x1 * x1)^2 + (1 - x1)^2
}
xtrad<-c(-1.2,1)
ros1<-fnchk(xtrad, fr, trace=1)
print(ros1)
npar<-2
opros<-list2env(list(fn=fr, gr=NULL, hess=NULL, MAXIMIZE=FALSE, PARSCALE=rep(1,npar), FNSCALE=1,
                     KFN=0, KGR=0, KHESS=0, dots=NULL))
uros1<-fnchk(xtrad, fr, trace=1)
print(uros1)