transform_if {tinycodet}

transform_if: Conditional Sub-set Transformation of Atomic objects

Description

The transform_if() function transforms an object x, based on the logical result (TRUE, FALSE, NA) of condition function cond(x) or logical vector cond, such that:

• For every value where cond(x)==TRUE / cond==TRUE, function yes(x) is run or scalar yes is returned.

• For every value where cond(x)==FALSE / cond==FALSE, function no(x) is run or scalar no is returned.

• For every value where cond(x)==NA / cond==NA, function other(x) is run or scalar other is returned.
  

For a more ifelse-like function where yes, no, and other are vectors, see kit::iif.

Usage

transform_if(x, cond, yes = function(x) x, no = function(x) x, other = NA)

Arguments

x

a vector, matrix, or array.

cond

either an object of class logical with the same length as x,
or a (possibly anonymous) function that returns an object of class logical with the same length as x.
For example: \(x)x>0.

yes

the (possibly anonymous) transformation function to use when function cond(x)==TRUE / logical cond==TRUE.
Alternatively, one can also supply an atomic scalar.
If argument yes is not specified, it defaults to \(x)x.

no

the (possibly anonymous) transformation function to use when function cond(x)==FALSE / logical cond==FALSE.
Alternatively, one can also supply an atomic scalar.
If argument no is not specified, it defaults to \(x)x.

other

the (possibly anonymous) transformation function to use when function cond(x) / logical cond returns NA.
Alternatively, one can also supply an atomic scalar.
If argument other is not specified, it defaults to NA.
Note that function other(x) is run or scalar other is returned when function cond(x) or logical cond is NA, not necessarily when x itself is NA.

Details

Be careful with coercion! For example the following code:

x <- c("a", "b")
transform_if(x, \(x) x == "a", as.numeric, as.logical)

returns:

[1] NA NA

due to the same character vector being given 2 incompatible classes.

Value

The transformed vector, matrix, or array (attributes are conserved).

See Also

tinycodet_dry

Examples

x <- c(-10:9, NA, NA)
object <- matrix(x, ncol = 2)
attr(object, "helloworld") <- "helloworld"
print(object)
y <- 0
z <- 1000

object |> transform_if(\(x) x > y, log, \(x) x^2, \(x) -z)
object |> transform_if(object > y, log, \(x) x^2, -z) # same as previous line