C++
C#
RC – reference class
6.1. Base Types
The base types are build upon the “structures” from the language C that underlies R.2 Knowing this inheritance, the possibilities and limitations of the base types should not be a mystery. A struct is basically a collection of variables that are gathered under one name. In our example (the bank account) it could hold the name of the account holder, the balance as a number, but not the balance as a function. The following works:
struct
# Define a string: acc <- “Philippe” # Force an attribute, balance, on it: acc$balance <- 100 ## Warning in acc$balance <- 100: Coercing LHS to a list # Inspect the result: acc ## [[1]] ## [1] “Philippe” ## ## $balance ## [1] 100
This means that the base type holds information on how the object is stored in memory (and hence how much bytes it occupies), what variables it has, etc. The base types are part of R's code and compiled, so it is only possible to create new ones by modifying R's source code and recompiling. When thinking about the base types, one readily recalls all the types that we studied in the previous sections such as integers, vectors, matrices are base types. However, there are more exotic ones such as environments, functions, calls.
Some conventions are not straightforward but deeply embedded in R and many people's code, some things might be somewhat surprising. Consider the following code:
# a function build in core R typeof(mean) ## [1] “closure” is.primitive(mean) ## [1] FALSE # user defined function are “closures: add1 <- function(x) {x+1} typeof(add1) ## [1] “closure” is.function(add1) ## [1] TRUE is.object(add1) ## [1] FALSE
is.primitive()
typeof()
is.function()
is.object()
As mentioned before, the mainstream OO implementation in R is a generic-function implementation. That means that functions that display different behaviour for different objects will dispatch the action to a more specialized function.3
The importance of these struct-based base type is that all other object types are built upon these: S3 objects are directly build on top of the base types, S4 objects use a special-purpose base type, and RC objects are a combination of S4 and environments (which is also a base type).
6.2. S3 Objects
S3 is probably the most simple implementation of an OO system that is still useful. In its simplicity, it is extremely versatile and user friendly (once you get your old C and C++ reflexes under control).
The function is.object() returns true both for S3 and S4 objects. There is no base function that allows directly to test if an object is S3, but there is a to test to check if an object is S4. So we can test if something is S3 as follows.
# is.S3 # Determines if an object is S3 # Arguments: # x -- an object # Returns: # boolean -- TRUE if x is S3, FALSE otherwise is.S3 <- function(x){is.object(x) & !isS4(x)} # Create two test objects: M <- matrix(1:16, nrow=4) df <- data.frame(M) # Test our new function: is.S3(M) ## [1] FALSE is.S3(df) ## [1] TRUE
However, it is not really necessary to create such function by ourselves. We can leverage the library pryr, which provides a function otype() that returns the type of object.
pryr
otype()
library(pryr) otype(M) ## [1] “base” otype(df) ## [1] “S3” otype(df$X1) # a vector is not S3 ## [1] “base” df$fac <-factor(df$X4) otype(df$fac) # a factor is S3 ## [1] “S3”
The methods are provided by the generic function.4 Those functions will do different things for different S3 objects.
If you would like to determine if a function is S3 generic, then you can check the source code for the use of the function useMethod(). This function will take care of the dispatching and hence decide which method to call for the given object.
useMethod()
However, this method is not foolproof because some primitive functions have this switch statement embedded in their C-code. For example, [, sum(), rbind(), and cbind() are generic functions, but this is not visible in their code in R.
Alternatively, it is possible to use the function ftype from the package pryr:
mean ## function (x, …) ## UseMethod(“mean”) ## <bytecode: 0x563423e48908> ## <environment: namespace:base> ftype(mean) ## [1] “s3” “generic” sum ## function (…, na.rm = FALSE) .Primitive(“sum”) ftype(sum) ## [1] “primitive” “generic”
R calls the functions that have this switch in their C-code “internal” “generic”.
The S3 generic function basically decides to what other function to dispatch its task. For example, the function print can be called with any base or S3 object and print will decide what to do based on its class. Try the function apropos() to find out what different methods exist (or type print. in RStudio.
apropos(“print.”) ## [1] “print.AsIs” ## [2] “print.by” ## [3] “print.condition” ## [4] “print.connection” ## [5] “print.data.frame” ## [6] “print.Date” ## [7] “print.default” ## [8] “print.difftime” ## [9] “print.Dlist” ## [10] “print.DLLInfo” ## [11] “print.DLLInfoList” ## [12] “print.DLLRegisteredRoutines” ## [13] “print.eigen” ## [14] “print.factor” ## [15] “print.function” ## [16] “print.hexmode” ## [17] “print.libraryIQR” ## [18] “print.listof” ## [19] “print.NativeRoutineList” ## [20] “print.noquote” ## [21] “print.numeric_version” ## [22] “print.octmode” ## [23] “print.packageInfo” ## [24] “print.POSIXct” ## [25] “print.POSIXlt” ## [26] “print.proc_time” ## [27] “print.restart” ## [28] “print.rle” ## [29] “print.simple.list” ## [30] “print.srcfile” ## [31] “print.srcref” ## [32] “print.summary.table” ## [33] “print.summaryDefault” ## [34] “print.table” ## [35] “print.warnings” ## [36] “printCoefmat” ## [37] “sprintf” apropos(“mean.”) ## [1] “.colMeans” “.rowMeans” “colMeans” ## [4] “kmeans” “mean.Date”