In jr-packages/jrAdvGgplot2: The jrAdvGgplot2 package

setClass("Cohort",
         representation(
           details = "data.frame",
           centre = "character"
         )
)
w = c(32, 39, 33, 66, 24)
h = c(1.4, 1.47, 1.47, 1.58, 1.25)
coh_s4 = new("Cohort",
             details = data.frame(weight = w, height = h),
             centre = "NCL"
)

S4 objects ^[I've intentionally mirrored the functions from previous practical to highlight the differences.]

1. Following the Cohort example in the notes, suppose we want to make a generic for the mean function.

2. Using the isGeneric function, determine if the mean function is an S4 generic. If not, use setGeneric to create an S4 generic.

isGeneric("mean")
setGeneric("mean")

1. Using setMethod, create a mean method for the Cohort class.^[Be careful to match the arguments.]

setMethod("mean", signature = c("Cohort"), 
          definition = function(x, ...) {
            m1 = mean(x@details[, 1], ...)
            m2 = mean(x@details[, 2], ...)
            return(c(m1, m2))
          }
)

1. Repeat the above steps for the sd function.

isGeneric("sd")
setGeneric("sd")
setMethod("sd", signature = c("Cohort"), 
          definition = function(x, na.rm = FALSE) {
            m1 = sd(x@details[, 1], na.rm = na.rm)
            m2 = sd(x@details[, 2], na.rm = na.rm)
            return(c(m1, m2))
          }
)

1. Create a summary method for the cohort class

2. Use isGeneric to determine if an S4 generic exists.

3. Use setGeneric to set the generic method (if necessary).
4. Create an S4 summary method.

isGeneric("summary")
setGeneric("summary")
setMethod("summary", signature = c("Cohort"), 
                    definition = function(object, ...) {
            summary(object@details)
          }
)

1. Create a hist method for the cohort class. When the hist function is called on a cohort, it should produce a single plot showing two histograms - one for height and another for weight.

isGeneric("hist")
setGeneric("hist")
setMethod("hist", signature = c("Cohort"), 
          definition = function(x, ...) {
            op = par(mfrow = c(1, 2))
            hist(x@details[, 1], main = "Weight", ...)
            hist(x@details[, 2], main = "Height", ...)
            par(op)
          }
)

1. Create a [ method for the cohort class. This method should return a cohort object, but with the relevant rows sub setted.

isGeneric("[")
getGeneric("[")
## Can you determine what drop does?
setMethod("[", signature = c("Cohort"), 
          definition = function(x, i, j, ..., drop = TRUE) {
            x@details = x@details[i, j, ..., drop = drop]
            x
          }
)

1. Create a <- method for the cohort class. This method should allow us to replace values in the details data frame.

isGeneric("[<-")
setGeneric("[<-")

setMethod("[<-", signature = c("Cohort"), 
          definition = function(x, i, j, value) {
            x@details[i, j] = value
            x
          }
)
coh_s4[1, ] =  5

Solutions

Solutions are contained within the course package

library("jrAdvGgplot2")
vignette("solutions3", package = "jrAdvGgplot2")

jr-packages/jrAdvGgplot2 documentation built on Dec. 27, 2019, 2:23 p.m.