Dear all, I want to derive from a data set that I have a set of 9 interpolation functions using approxfun() and store them in an R object. The data has some structure that I would like to reflect in the storage, so ideally I would store them in a data.frame. So far I failed. Here is what I tried: # My actual data has similar structure:> x <- 1:9 > y <- matrix(c(x*2, x*3, x*4), nr=3, nc=9) > f.df <- list() > cases <- c("case0", "case1", "case2") > for (i in 1:3) {f.df[[cases[i]]] <- y*i}# Prepare storage place> funcs <- data.frame(NA, NA, NA) > names(funcs) <- cases# Try to store interpolation functions> for (c in cases) {+ for (i in 1:3) { + funcs[i,c] <- approxfun(x, f.df[[c]][i,]) + } + } Error in "[<-"(`*tmp*`, iseq, value = vjj) : incompatible types # Failed to change the mode of a column:> mode(f.df[["case0"]]) <- "function"Error in as.function.default(x, envir) : list argument expected My attempts to initialize a data.frame into "function" mode using, as.function(), led to more failures. Is it possible to do? and how? Thank you for any suggestions or comments. Itay -------------------------------------------------------------- itayf at fhcrc.org Fred Hutchinson Cancer Research Center
Itay Furman wrote:> Dear all, > > I want to derive from a data set that I have a set of 9 > interpolation functions using approxfun() and store > them in an R object. The data has some structure that I would > like to reflect in the storage, so ideally I would store them in > a data.frame. So far I failed. > > Here is what I tried: > > # My actual data has similar structure: > >>x <- 1:9 >>y <- matrix(c(x*2, x*3, x*4), nr=3, nc=9) >>f.df <- list() >>cases <- c("case0", "case1", "case2") >>for (i in 1:3) {f.df[[cases[i]]] <- y*i} > > > # Prepare storage place > >>funcs <- data.frame(NA, NA, NA) >>names(funcs) <- cases > > > # Try to store interpolation functions > >>for (c in cases) { > > + for (i in 1:3) { > + funcs[i,c] <- approxfun(x, f.df[[c]][i,]) > + } > + } > Error in "[<-"(`*tmp*`, iseq, value = vjj) : > incompatible types > > # Failed to change the mode of a column: > >>mode(f.df[["case0"]]) <- "function" > > Error in as.function.default(x, envir) : list argument expected > > > My attempts to initialize a data.frame into "function" mode > using, as.function(), led to more failures. > > Is it possible to do? > and how? > > Thank you for any suggestions or comments. > Itay > > -------------------------------------------------------------- > itayf at fhcrc.org Fred Hutchinson Cancer Research Center >You cannot store a function that way. You might want to make "func" a list of lists as in: # Prepare storage place funcs <- vector(mode = "list", length = 3) names(funcs) <- cases # Try to store interpolation functions for (c in cases) { funcs[[c]] <- vector(mode = "list", length = 3) for (i in 1:3) { funcs[[c]][[i]] <- approxfun(x, f.df[[c]][i,]) } } Uwe Ligges
A column of a data frame is a vector, and all columns should have the same
length. You cannot meet those basic requirements if you make a column
class to be "function", but you can have a list of functions.
However, in your case you seem to want a 3x3 array of functions, so the
natural structure would be a matrix and not a data frame. As in
funcs <- matrix(vector("list", 9), 3, 3)
colnames(funcs) <- cases
for (c in cases)
for (i in 1:3)
funcs[[i,c]] <- approxfun(x, f.df[[c]][i,])
Since this is a list, you access elements as funcs[[i,j]].
On Wed, 3 Mar 2004, Itay Furman wrote:
>
> Dear all,
>
> I want to derive from a data set that I have a set of 9
> interpolation functions using approxfun() and store
> them in an R object. The data has some structure that I would
> like to reflect in the storage, so ideally I would store them in
> a data.frame. So far I failed.
>
> Here is what I tried:
>
> # My actual data has similar structure:
> > x <- 1:9
> > y <- matrix(c(x*2, x*3, x*4), nr=3, nc=9)
> > f.df <- list()
> > cases <- c("case0", "case1", "case2")
> > for (i in 1:3) {f.df[[cases[i]]] <- y*i}
>
> # Prepare storage place
> > funcs <- data.frame(NA, NA, NA)
> > names(funcs) <- cases
>
> # Try to store interpolation functions
> > for (c in cases) {
> + for (i in 1:3) {
> + funcs[i,c] <- approxfun(x, f.df[[c]][i,])
> + }
> + }
> Error in "[<-"(`*tmp*`, iseq, value = vjj) :
> incompatible types
>
> # Failed to change the mode of a column:
> > mode(f.df[["case0"]]) <- "function"
> Error in as.function.default(x, envir) : list argument expected
>
>
> My attempts to initialize a data.frame into "function" mode
> using, as.function(), led to more failures.
>
> Is it possible to do?
> and how?
>
> Thank you for any suggestions or comments.
> Itay
>
> --------------------------------------------------------------
> itayf at fhcrc.org Fred Hutchinson Cancer Research Center
>
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>
>
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
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