r_matrix: Random transpose-identical dense/sparse matrix

In zdebruine/RcppML: Rcpp Machine Learning Library

Random transpose-identical dense/sparse matrix

Description

Generate a random sparse matrix, just like Matrix::rsparsematrix or (matrix(runif(nrow * ncol), nrow,)), but much faster. Generation of transpose-identical matrices is also supported without additional computational cost.

Usage

r_matrix(nrow, ncol, transpose_identical = FALSE)

r_sparsematrix(
  nrow,
  ncol,
  inv_density,
  transpose_identical = FALSE,
  pattern = FALSE
)

Arguments

nrow	number of rows
ncol	number of columns
transpose_identical	should the matrix be transpose-identical?
inv_density	an integer giving the inverse density of the matrix (i.e. 10 percent density corresponds to inv_density = 10). Density is probabilistic, not exact. See examples.
pattern	should a pattern matrix (Matrix::ngCMatrix) be returned? If not, a Matrix::dgCMatrix with random uniform values will be returned.

See Also

r_unif

r_matrix, r_unif, r_binom

Examples

# generate a simple random matrix
A <- r_matrix(10, 10)

# generate two matrices that are transpose identical
set.seed(123)
A1 <- r_matrix(10, 100, transpose_identical = TRUE)
set.seed(123)
A2 <- r_matrix(100, 10, transpose_identical = TRUE)
all.equal(t(A2), A1)

# generate a transpose-identical pair of speckled matrices
set.seed(123)
A <- r_sparsematrix(10, 100, inv_density = 10, transpose_identical = TRUE)
set.seed(123)
A <- r_sparsematrix(100, 10, inv_density = 10, transpose_identical = TRUE)
all.equal(t(A), A)
Matrix::isSymmetric(A[1:10, 1:10])
heatmap(as.matrix(A), scale = "none", Rowv = NA, Colv = NA)

# note that density is probabilistic, not absolute
A <- replicate(1000, r_sparsematrix(100, 100, 10))
densities <- sapply(A, function(x) length(x@i) / prod(dim(x)))
plot(density(densities)) # normal distribution centered at 0.100
range(densities)

zdebruine/RcppML documentation built on Sept. 13, 2023, 11:44 p.m.