backtransform `scale()` for plotting

Question

I have a explanatory variable that is centered using scale() that is used to predict a response variable:

d <- data.frame(
  x=runif(100),
           


        

Answer 1

I am late to the party. But here is a useful tool to scale/unscale data in array format.

Example:

> (data <- array(1:8, c(2, 4)))            # create data
     [,1] [,2] [,3] [,4]
[1,]    1    3    5    7
[2,]    2    4    6    8
> obj <- Scale(data)                       # create object
> (data_scaled <- obj$scale(data))         # scale data
           [,1]       [,2]       [,3]       [,4]
[1,] -0.7071068 -0.7071068 -0.7071068 -0.7071068
[2,]  0.7071068  0.7071068  0.7071068  0.7071068
> (obj$unscale(data_scaled))               # unscale scaled data
     [,1] [,2] [,3] [,4]
[1,]    1    3    5    7
[2,]    2    4    6    8

## scale or unscale another dataset
## using the same mean/sd parameters
> (data2 <- array(seq(1, 24, 2), c(3, 4))) # create demo data
     [,1] [,2] [,3] [,4]
[1,]    1    7   13   19
[2,]    3    9   15   21
[3,]    5   11   17   23
> (data2_scaled <- obj$scale(data2))       # scale data
           [,1]      [,2]     [,3]     [,4]
[1,] -0.7071068  4.949747 10.60660 16.26346
[2,]  2.1213203  7.778175 13.43503 19.09188
[3,]  4.9497475 10.606602 16.26346 21.92031
> (obj$unscale(data2_scaled))              # unscale scaled data
     [,1] [,2] [,3] [,4]
[1,]    1    7   13   19
[2,]    3    9   15   21
[3,]    5   11   17   23

Function Scale():

Scale <- function(data, margin=2, center=TRUE, scale=TRUE){
    stopifnot(is.array(data), is.numeric(data),
              any(mode(margin) %in% c("integer", "numeric")),
              length(margin) < length(dim(data)),
              max(margin) <= length(dim(data)),
              min(margin) >= 1,
              !any(duplicated(margin)),
              is.logical(center), length(center)==1,
              is.logical(scale), length(scale)==1,
                  !(isFALSE(center) && isFALSE(scale)))
    margin <- as.integer(margin)

    m <- if(center) apply(data, 2, mean, na.rm=TRUE) else NULL
    s <- if(scale)  apply(data, 2, sd, na.rm=TRUE) else NULL
    ldim <- length(dim(data))
    cdim <- dim(data)[margin]
    data <- NULL # don't store the data

    Scale <- function(data){
        stopifnot(is.array(data), is.numeric(data),
                  length(dim(data)) == ldim,
                  dim(data)[margin] == cdim)
        if(center)
            data <- sweep(data, margin, m, `-`)
        if(scale)
            data <- sweep(data, margin, s, `/`)
        data
    }

    Unscale <- function(data){
        stopifnot(is.array(data), is.numeric(data),
                  length(dim(data)) == ldim,
                  dim(data)[margin] == cdim)
        if(scale)
            data <- sweep(data, margin, s, `*`)
        if(center)
            data <- sweep(data, margin, m, `+`)
        data
    }
    list(scale=Scale, unscale=Unscale, mean=m, sd=s)
}

Note: data.frames are not support yet.