# Run tests, where possible, on user objective function `fnchk` checks a user-provided R function, `ffn`. ```r 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 ## Examples ```r # 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) ```

fnchk function