Matrix (version 1.7-1)

pMatrix-class: Permutation matrices

Description

The pMatrix class is the class of permutation matrices, stored as 1-based integer permutation vectors. A permutation matrix is a square matrix whose rows and columns are all standard unit vectors. It follows that permutation matrices are a special case of index matrices (hence pMatrix is defined as a direct subclass of indMatrix).

Multiplying a matrix on the left by a permutation matrix is equivalent to permuting its rows. Analogously, multiplying a matrix on the right by a permutation matrix is equivalent to permuting its columns. Indeed, such products are implemented in Matrix as indexing operations; see ‘Details’ below.

Objects from the Class

Objects can be created explicitly with calls of the form new("pMatrix", ...), but they are more commonly created by coercing 1-based integer index vectors, with calls of the form as(., "pMatrix"); see ‘Methods’ below.

Slots

margin,perm

inherited from superclass indMatrix. Here, perm is an integer vector of length Dim[1] and a permutation of 1:Dim[1].

Dim,Dimnames

inherited from virtual superclass Matrix.

Extends

Class "indMatrix", directly.

Methods

%*%

signature(x = "pMatrix", y = "Matrix") and others listed by showMethods("%*%", classes = "pMatrix"): matrix products implemented where appropriate as indexing operations.

coerce

signature(from = "numeric", to = "pMatrix"): supporting typical pMatrix construction from a vector of positive integers, specifically a permutation of 1:n. Row permutation is assumed.

t

signature(x = "pMatrix"): the transpose, which is a pMatrix with identical perm but opposite margin. Coincides with the inverse, as permutation matrices are orthogonal.

solve

signature(a = "pMatrix", b = "missing"): the inverse permutation matrix, which is a pMatrix with identical perm but opposite margin. Coincides with the transpose, as permutation matrices are orthogonal. See showMethods("solve", classes = "pMatrix") for more signatures.

determinant

signature(x = "pMatrix", logarithm = "logical"): always returning 1 or -1, as permutation matrices are orthogonal. In fact, the result is exactly the sign of the permutation.

Details

By definition, a permutation matrix is both a row index matrix and a column index matrix. However, the perm slot of a pMatrix cannot be used interchangeably as a row index vector and column index vector. If margin=1, then perm is a row index vector, and the corresponding column index vector can be computed as invPerm(perm), i.e., by inverting the permutation. Analogously, if margin=2, then perm and invPerm(perm) are column and row index vectors, respectively.

Given an n-by-n row permutation matrix P with perm slot p and a matrix M with conformable dimensions, we have

\(P M\)	=	P %*% M	=	M[p, ]
\(M P\)	=	M %*% P	=	M[, i(p)]
\(P'M\)	=	crossprod(P, M)	=	M[i(p), ]
\(MP'\)	=	tcrossprod(M, P)	=	M[, p]
\(P'P\)	=	crossprod(P)	=	Diagonal(n)
\(PP'\)	=	tcrossprod(P)	=	Diagonal(n)

where i := invPerm.

See Also

Superclass indMatrix of index matrices, for many inherited methods; invPerm, for computing inverse permutation vectors.

Examples

 
library(stats, pos = "package:base", verbose = FALSE)

(pm1 <- as(as.integer(c(2,3,1)), "pMatrix"))
t(pm1) # is the same as
solve(pm1)
pm1 %*% t(pm1) # check that the transpose is the inverse
stopifnot(all(diag(3) == as(pm1 %*% t(pm1), "matrix")),
          is.logical(as(pm1, "matrix")))

set.seed(11)
## random permutation matrix :
(p10 <- as(sample(10),"pMatrix"))

## Permute rows / columns of a numeric matrix :
(mm <- round(array(rnorm(3 * 3), c(3, 3)), 2))
mm %*% pm1
pm1 %*% mm
try(as(as.integer(c(3,3,1)), "pMatrix"))# Error: not a permutation

as(pm1, "TsparseMatrix")
p10[1:7, 1:4] # gives an "ngTMatrix" (most economic!)

## row-indexing of a  keeps it as an :
p10[1:3, ]