# invPerm: Inverse Permutation Vector In Matrix: Sparse and Dense Matrix Classes and Methods

## Description

From a permutation vector `p`, compute its inverse permutation vector.

## Usage

 `1` ```invPerm(p, zero.p = FALSE, zero.res = FALSE) ```

## Arguments

 `p` an integer vector of length, say, `n`. `zero.p` logical indicating if `p` contains values `0:(n-1)` or rather (by default, `zero.p = FALSE`) `1:n`. `zero.res` logical indicating if the result should contain values `0:(n-1)` or rather (by default, `zero.res = FALSE`) `1:n`.

## Value

an integer vector of the same length (`n`) as `p`. By default, (`zero.p = FALSE, zero.res = FALSE`), `invPerm(p)` is the same as `order(p)` or `sort.list(p)` and for that case, the function is equivalent to `invPerm. <- function(p) { p[p] <- seq_along(p) ; p }`.

## Author(s)

Martin Maechler

the class of permutation matrices, `pMatrix`.
 ```1 2 3 4 5 6 7 8 9``` ``` p <- sample(10) # a random permutation vector ip <- invPerm(p) p[ip] # == 1:10 ## they are indeed inverse of each other: stopifnot( identical(p[ip], 1:10), identical(ip[p], 1:10), identical(invPerm(ip), p) ) ```