fnchk function

Run tests, where possible, on user objective function

fnchk checks a user-provided R function, ffn.

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

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.

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!

Returns

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

Author(s)

John C. Nash profjcnash@gmail.com

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)