我处理的是大型矩阵--按
set.seed(1) #For reproducibility
ncols <- 20
nrows <- 10
col_prob <- runif(ncols,0.1,0.2)
rmat <- matrix(rbinom(nrows*ncols,1,col_prob),
ncol=ncols,byrow=T)
当然，我可以将
rmat_sparse <- Matrix(rmat, sparse=TRUE)
但是，我想一步生成稀疏矩阵。我不确定函数
下面的函数将通过操作空白的
library(Matrix)
randsparse <- function(nrows, ncols, col_prob) {
mat <- Matrix(0, nrows, ncols, sparse = TRUE) #blank matrix for template
i <- vector(mode = "list", length = ncols) #each element of i contains the '1' rows
p <- rep(0, ncols) #p will be cumsum no of 1s by column
for(r in 1:nrows){
row <- rbinom(ncols, 1, col_prob) #random row
p <- p + row #add to column identifier
if(any(row == 1)){
for (j in which(row == 1)){
i[[j]] <- c(i[[j]], r-1) #append row identifier
}
}
}
p <- c(0, cumsum(p)) #this is the format required
i <- unlist(i)
x <- rep(1, length(i))
mat@i <- as.integer(i)
mat@p <- as.integer(p)
mat@x <- x
return(mat)
}
set.seed(1)
randsparse(10, 20, runif(20, 0.1, 0.2))
10 x 20 sparse Matrix of class "dgCMatrix"
[1,] 1 . . . . . . . 1 . . . . . 1 . . . . .
[2,] . . . . . . . . . . . . . . . . . . . .
[3,] 1 . . . . . . . . . . . . . . 1 1 . . 1
[4,] . . . . . . . . . . . . . 1 . . . . . .
[5,] . . . 1 . . . . 1 . 1 . . . . . . . . .
[6,] 1 . . . . . . . . . . . . . 1 . . . 1 .
[7,] . . . . . . . . . . . . . . . . . . . .
[8,] . 1 . . 1 . . . . . . . 1 . . 1 . . . 1
[9,] . . 1 . . . . . 1 . . . . 1 . . . 1 . .
[10,] . . . . . . . . . . 1 . . 1 . . . 1 1 .
