2

I am currently trying to implement a SVD of a very large matrix using bigmemory and irlba. As far as I understand I have to adjust the mult command in the irlba package, which I have done like this: 

mult <- function(A, B, transpose=FALSE) {
  if(is.null(dim(B))) B <- cbind(B)
  if(transpose)
    return(cbind((t(B) %*% A)[]))
  cbind((A %*% B)[])
}

However, it does not work to run an SVD on a bigmatrix using irlba: 

irlbaObject <- irlba(big, nv = 10, mult = mult)

For replicability here is an example of a big matrix I want to do a SVD on: 

big <- file("big.txt", open = "a")
replicate(20, {
  x <- matrix(rnorm(100 * 100), nrow = 10)
  write.table(x, file  = 'big.txt', append = TRUE,
              row.names = FALSE, col.names = FALSE)
})

big <- read.big.matrix("big.txt", separated = FALSE,
                        type = "double",
                        backingfile = "big.bk",
                        backingpath = "/tmp",
                        descriptorfile = "big.desc")

This is the error message I get: 

Error in A %*% B : requires numeric/complex matrix/vector arguments
Called from: cbind((A %*% B)[])

Does anyone have an idea how to avoid this error?

4

1 回答 1

2

这应该有效：

library(bigalgebra)
library(irlba)

## --> CHANGES HERE <--
setMethod("%*%", signature(x = "big.matrix", y = "numeric"),
          function(x, y) x %*% as.matrix(y))
setMethod("%*%", signature(x = "numeric", y = "big.matrix"),
          function(x, y) t(x) %*% y)
mult <- function(A, B) (A %*% B)[]

# Repdata
x <- matrix(rnorm(20 * 100 * 100), nrow = 20 * 10)
big <- as.big.matrix(x)
# Computation
irlbaObject <- irlba(big, nv = 10, mult = mult)
# Verification
svd <- svd(x, nu = 10, nv = 10)
plot(irlbaObject$u, svd$u)
plot(irlbaObject$v, svd$v)

注 1：我认为 irlba 中的算法已经改变，现在只使用矩阵向量乘法。

注意 2：mult 是一个不推荐使用的参数（它将在下一个版本中消失）。

注3：我不确定这个解决方案会很快。如果您想要一个快速算法来计算部分 SVD，请尝试使用 bigstatsr包的函数 big_randomSVD（免责声明：我是作者）。

于 2018-05-03T07:09:40.940 回答