# Vectorize

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##### Vectorize a Scalar Function

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

Keywords
manip, utilities
##### Usage
Vectorize(FUN, vectorize.args = arg.names, SIMPLIFY = TRUE, USE.NAMES = TRUE)
##### Arguments
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.
##### Details

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.

##### Value

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

• Vectorize
##### Examples
library(base) # 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") 
Documentation reproduced from package base, version 3.1.3, License: Part of R 3.1.3

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