生成随机稀疏矩阵 [英] Generating random sparse matrix

查看:351
本文介绍了生成随机稀疏矩阵的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在处理大型矩阵-按10^8列和10^3-10^4行的顺序.由于这些矩阵仅是一和零(超过99%的零),因此我认为Matrix包中的稀疏构造是适当的.但是,我没有像下面的示例那样看到一种生成随机矩阵的方法.请注意,非零条目由概率col_prob定义.

I am dealing with large matrices - on the order of 10^8 columns and 10^3-10^4 rows. Since these matrices are only ones and zeros (over 99% zeros), I think the sparse construction in the Matrix package is appropriate. However, I don't see a way to generate a random matrix like in the example below. Note that non-zero entries are defined by the column probabilities col_prob.

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转换为稀疏矩阵:

Certainly I can convert rmat into a sparse matrix:

rmat_sparse <- Matrix(rmat, sparse=TRUE)

但是,我想一步生成稀疏矩阵.我不确定函数Matrix::rsparsematrix是否可以完成此操作.

However, I would like to generate the sparse matrix in one step. I'm not sure that the function Matrix::rsparsematrix can accomplish this.

推荐答案

以下函数将通过操纵空白dgCMatrix对象的值来生成您要查找的类型的稀疏矩阵.它基本上一次创建一个rbinom行,并相应地填充@i@p值.

The following function will generate a sparse matrix of the type you are looking for, by manipulating the values of a blank dgCMatrix object. It basically creates the rbinom rows one at a time and populates the @i and @p values accordingly.

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 .

这篇关于生成随机稀疏矩阵的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆