R functions evaluate arguments lazily; the arguments are evaluated as they are needed. Thus, lazy evaluation reduces the time needed for computation. In the following recipe, we will demonstrate how lazy evaluation works.
Ensure that you completed the previous recipes by installing R on your operating system.
Perform the following steps to see how lazy evaluation works:
First, we create a
lazyfuncfunction withxandyas the argument, but only returnx:>lazyfunc<- function(x, y){ + x + } >lazyfunc(3) [1] 3
On the other hand, if the function returns the summation of
xandybut we do not passyinto the function, an error occurs:>lazyfunc2<- function(x, y){ + x + y + } >lazyfunc2(3) Error in lazyfunc2(3) : argument "y" is missing, with no default
We can also specify a default value to the
yargument in the function but pass thexargument only to the function:>lazyfunc4<- function(x, y=2){ + x + y + } >lazyfunc4(3) [1] 5
In addition to this, we can use lazy evaluation to perform Fibonacci computation in a function:
>fibonacci<- function(n){ + if (n==0) + return(0) + if (n==1) + return(1) + return(fibonacci(n-1) + fibonacci(n-2)) + } >fibonacci(10) [1] 55
R performs a lazy evaluation to evaluate an expression if its value is needed. This type of evaluation strategy has the following three advantages:
It increases performance due to the avoidance of repeated evaluation
It recursively constructs an infinite data structure
It inherently includes iteration in its data structure
In this recipe, we demonstrate some lazy evaluation examples in the R code. In our first example, we create a function with two arguments, x and y, but return only x. Due to the characteristics of lazy evaluation, we can successfully obtain function returns even though we pass the value of x to the function. However, if the function return includes both x and y, as step 2 shows, we will get an error message because we only passed one value to the function. If we set a default value to y, then we do not necessarily need to pass both x and y to the function.
As lazy evaluation has the advantage of creating an infinite data structure without an infinite loop, we use a Fibonacci number generator as the example. Here, this function first creates an infinite list of Fibonacci numbers and then extracts the nth element from the list.