R: Examples for 'base::Vectorize'

### ** Examples

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

[[1]]
[1] 1 1 1 1

[[2]]
[1] 2 2 2

[[3]]
[1] 3 3

[[4]]
[1] 4

vrep(times = 1:4, x = 4:1)

[[1]]
[1] 4

[[2]]
[1] 3 3

[[3]]
[1] 2 2 2

[[4]]
[1] 1 1 1 1

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

[[1]]
[1] 42

[[2]]
[1] 42 42

[[3]]
[1] 42 42 42

[[4]]
[1] 42 42 42 42

f <- function(x = 1:3, y) c(x, y)
vf <- Vectorize(f, SIMPLIFY = FALSE)
f(1:3, 1:3)

[1] 1 2 3 1 2 3

vf(1:3, 1:3)

[[1]]
[1] 1 1

[[2]]
[1] 2 2

[[3]]
[1] 3 3

vf(y = 1:3) # Only vectorizes y, not x

[[1]]
[1] 1 2 3 1

[[2]]
[1] 1 2 3 2

[[3]]
[1] 1 2 3 3

# 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")

# combn() has an argument named FUN
combnV <- Vectorize(function(x, m, FUNV = NULL) combn(x, m, FUN = FUNV),
                    vectorize.args = c("x", "m"))
combnV(4, 1:4)

[[1]]
     [,1] [,2] [,3] [,4]
[1,]    1    2    3    4

[[2]]
     [,1] [,2] [,3] [,4] [,5] [,6]
[1,]    1    1    1    2    2    3
[2,]    2    3    4    3    4    4

[[3]]
     [,1] [,2] [,3] [,4]
[1,]    1    1    1    2
[2,]    2    2    3    3
[3,]    3    4    4    4

[[4]]
     [,1]
[1,]    1
[2,]    2
[3,]    3
[4,]    4

combnV(4, 1:4, sum)

[[1]]
[1] 1 2 3 4

[[2]]
[1] 3 4 5 5 6 7

[[3]]
[1] 6 7 8 9

[[4]]
[1] 10

Examples for 'base::Vectorize'

Vectorize a Scalar Function