spMatrix: Sparse Matrix Constructor From Triplet

Description

User friendly construction of a sparse matrix (inheriting from class '>TsparseMatrix) from the triplet representation.

This is much less flexible than sparseMatrix() and hence somewhat deprecated.

Usage

spMatrix(nrow, ncol, i = integer(), j = integer(), x = numeric())

Arguments

nrow, ncol

integers specifying the desired number of rows and columns.

i,j

integer vectors of the same length specifying the locations of the non-zero (or non-TRUE) entries of the matrix.

atomic vector of the same length as i and j, specifying the values of the non-zero entries.

Value

A sparse matrix in triplet form, as an R object inheriting from both '>TsparseMatrix and '>generalMatrix.

The matrix $M$ will have M[i[k], j[k]] == x[k], for $k = 1, 2, \dots, n$ , where n = length(i) and M[ i', j' ] == 0 for all other pairs $(i^{'}, j^{'})$ .

Examples

Run this code

# NOT RUN {
## simple example
A <- spMatrix(10,20, i = c(1,3:8),
                     j = c(2,9,6:10),
                     x = 7 * (1:7))
A # a "dgTMatrix"
summary(A)
str(A) # note that *internally* 0-based indices (i,j) are used

L <- spMatrix(9, 30, i = rep(1:9, 3), 1:27,
              (1:27) %% 4 != 1)
L # an "lgTMatrix"


## A simplified predecessor of  Matrix'  rsparsematrix() function :

 rSpMatrix <- function(nrow, ncol, nnz,
                       rand.x = function(n) round(rnorm(nnz), 2))
 {
     ## Purpose: random sparse matrix
     ## --------------------------------------------------------------
     ## Arguments: (nrow,ncol): dimension
     ##          nnz  :  number of non-zero entries
     ##         rand.x:  random number generator for 'x' slot
     ## --------------------------------------------------------------
     ## Author: Martin Maechler, Date: 14.-16. May 2007
     stopifnot((nnz <- as.integer(nnz)) >= 0,
               nrow >= 0, ncol >= 0, nnz <= nrow * ncol)
     spMatrix(nrow, ncol,
              i = sample(nrow, nnz, replace = TRUE),
              j = sample(ncol, nnz, replace = TRUE),
              x = rand.x(nnz))
 }

 M1 <- rSpMatrix(100000, 20, nnz = 200)
 summary(M1)
# }

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