extmat: External matrices operations.

In svd: Interfaces to Various State-of-Art SVD and Eigensolvers

External matrices operations.

Description

A set of routines to operate on "external" matrices.

Usage

is.extmat(X)
extmat.ncol(X)
extmat.nrow(X)
extmat(mul, tmul, nrow, ncol, env = parent.frame())
ematmul(emat, v, transposed = FALSE)

Arguments

X, emat	matrix to operate on
mul	function performing the multiplication of matrix to vector
tmul	function performing the multiplication of transposed matrix to vector
nrow	number of rows of the matrix
ncol	number of columns of the matrix
env	environment, where matrix-vector multiplication function call is evaluated in
transposed	logical, if 'TRUE' the multiplication is performed with the transposed matrix.
v	vector to multiply with.

Details

These routines checks whether the given external pointer actually points to "external matrix" structure and allow to extract the number of columns and rows respectively.

'extmat' is a convenient wrapper which allows one provide just the routines which will multiply with matrix and the transposed one (e.g. if the matrix is sparse or structured) and allow to use the SVD routines of the package

Value

Object 'extmat' class

See Also

extmat

Examples

## Not run: 
library(Matrix)
f <- function(v) as.numeric(A %*% v) # Convert Matrix object back to vector
tf <- function(v) as.numeric(tA %*% v) # Convert Matrix object back to vector

e <- new.env()
assign("A", USCounties, e)
assign("tA", t(USCounties), e)
environment(f) <- e
environment(tf) <- e

m <-extmat(f, tf, nrow(USCounties), ncol(USCounties))
system.time(v1 <- propack.svd(m, neig = 10))
#   user  system elapsed 
#  0.252   0.007   0.259 
system.time(v2 <- propack.svd(as.matrix(USCounties), neig = 10))
#   user  system elapsed 
#  8.563   0.027   8.590 

## End(Not run)

# The largest eigenvalue and the corresponding eigenvector of a Hilbert matrix
h <- outer(1:5000, 1:5000, function(i, j) 1 / (i + j - 1))
v1 <- trlan.eigen(h, neig = 1)
print(v1$d)

svd documentation built on July 26, 2023, 5:36 p.m.