RandomHyperArray-class {DelayedRandomArray} | R Documentation |
A DelayedArray subclass that performs on-the-fly sampling of hypergeometric-distributed values.
RandomHyperArraySeed(dim, m, n, k, chunkdim = NULL, sparse = FALSE) ## S4 method for signature 'RandomHyperArraySeed' DelayedArray(seed) RandomHyperArray(dim, m, n, k, chunkdim = NULL, sparse = FALSE)
dim |
Integer vector of positive length, specifying the dimensions of the array. |
m, n, k |
Numeric vector used as the argument of the same name in |
chunkdim |
Integer vector of length equal to |
sparse |
Logical scalar indicating whether the sampled array should be treated as sparse. |
seed |
A RandomHyperArraySeed object. |
All constructors return an instance of a RandomHyperArray object, containing random draws from a hypergeometric distribution with the specified parameters.
Aaron Lun
The RandomArraySeed class, for details on chunking and the distributional parameters.
X <- RandomHyperArraySeed(c(1e5, 1e5), m=10, n=20, k=15) Y <- DelayedArray(X) Y # Fiddling with the distribution parameters: X2 <- RandomHyperArraySeed(c(1e5, 1e5), m=round(runif(1e5, 10, 20)), n=20, k=15, sparse=TRUE) Y2 <- DelayedArray(X2) Y2 # Using another array as input: library(Matrix) m <- round(RandomUnifArray(c(1e5, 1e5), 10, 20)) X3 <- RandomHyperArraySeed(c(1e5, 1e5), m=m, n=50, k=20) Y3 <- DelayedArray(X3) Y3