Vectorize: Vectorize a Scalar Function
In robertzk/monadicbase: The R Base Package

Description Usage Arguments Details Value Examples

Vectorize creates a function wrapper that vectorizes the action of its argument FUN.

1 2	Vectorize(FUN, vectorize.args = arg.names, SIMPLIFY = TRUE, USE.NAMES = TRUE)

`FUN`	function to apply, found via `match.fun`.
`vectorize.args`	a character vector of arguments which should be vectorized. Defaults to all arguments of `FUN`.
`SIMPLIFY`	logical or character string; attempt to reduce the result to a vector, matrix or higher dimensional array; see the `simplify` argument of `sapply`.
`USE.NAMES`	logical; use names if the first ... argument has names, or if it is a character vector, use that character vector as the names.

The arguments named in the vectorize.args argument to Vectorize are the arguments passed in the ... list to mapply. Only those that are actually passed will be vectorized; default values will not. See the examples.

Vectorize cannot be used with primitive functions as they do not have a value for formals.

A function with the same arguments as FUN, wrapping a call to mapply.

# We use rep.int as rep is primitive
vrep <- Vectorize(rep.int)
vrep(1:4, 4:1)
vrep(times = 1:4, x = 4:1)

vrep <- Vectorize(rep.int, "times")
vrep(times = 1:4, x = 42)

f <- function(x = 1:3, y) c(x, y)
vf <- Vectorize(f, SIMPLIFY = FALSE)
f(1:3, 1:3)
vf(1:3, 1:3)
vf(y = 1:3) # Only vectorizes y, not x

# Nonlinear regression contour plot, based on nls() example
require(graphics)
SS <- function(Vm, K, resp, conc) {
    pred <- (Vm * conc)/(K + conc)
    sum((resp - pred)^2 / pred)
}
vSS <- Vectorize(SS, c("Vm", "K"))
Treated <- subset(Puromycin, state == "treated")

Vm <- seq(140, 310, length.out = 50)
K <- seq(0, 0.15, length.out = 40)
SSvals <- outer(Vm, K, vSS, Treated$rate, Treated$conc)
contour(Vm, K, SSvals, levels = (1:10)^2, xlab = "Vm", ylab = "K")