On Sat, Mar 24, 2012 at 08:04:49PM -0700, physicistintheory wrote:
> I'm relatively new to R and I'm stuck.
>
> I'm trying to construct a surface to optimize from a multivariate dataset.
> The dataset contains the response of a system to various stimuli. I am
> trying to optimize the mix of stimuli to maximize the response. To do so,
> I've interpolated the various datasets of type response vs. stimuli and I
> now have an array of functions "interps" whose length is the length of the
> array of the names of the various stimuli. I've also created a vector
> containing names for the stimuli, vars = x.1, x.2, x.3...
>
> Anyway, each of the functions in interps depends only on one variable
> (obviously). I would like to construct a function, call it, "surface" which
> is essentially: surface(vars) = interps[[1]]vars[[1]] +
> interps[[2]]vars[[2]]+...
>
> I've tried constructing surface recursively in a for loop:
> surface <- function(vars){0}
> for(i in 1:length(vars)){
> surface <- function(vars){surface(vars) + interps[[i]](vars[[i]])}
> }
Hi.
Is the following close to what you are asking for?
f1 <- function(x) 3*x^2 + x
f2 <- function(x) 2*x^2 + 2*x
f3 <- function(x) x^2 + 3*x
lstf <- list(f1, f2, f3)
args <- c("x2", "x4", "x5")
# input as a matrix or data frame
surface <- function(dat)
{
y <- rep(0, times=nrow(dat))
for (i in seq.int(along=lstf)) {
y <- y + lstf[[i]](dat[, args[i]])
}
y
}
dat <- matrix(1:35, ncol=5)
colnames(dat) <- paste("x", 1:5, sep="")
surface(dat)
[1] 2140 2346 2564 2794 3036 3290 3556
# compare with an explicit formula
f1(dat[, "x2"]) + f2(dat[, "x4"]) + f3(dat[, "x5"])
[1] 2140 2346 2564 2794 3036 3290 3556
# input as a named vector
surface1 <- function(x)
{
y <- 0
for (i in seq.int(along=lstf)) {
y <- y + lstf[[i]](x[args[i]])
}
unname(y)
}
vdat <- 1:5
names(vdat) <- paste("x", 1:5, sep="")
surface1(vdat)
[1] 94
# compare again
unname(f1(vdat["x2"]) + f2(vdat["x4"]) + f3(vdat["x5"]))
[1] 94
Hope this helps.
Petr Savicky.
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