问题
I have the following code:
concept_vectors <- foreach(j = 1:2, .combine=rBind, .packages="Matrix") %do% {
Matrix::colMeans(sparseX[1:10,],sparseResult=TRUE)
}
which results in the following error message:
Error in { : no method for coercing this S4 class to a vector
However, if I either remove 'sparseResult=TRUE' option, or do not use colMeans at all, the code works, even if without colMeans, sparseX is still an S4 object.
If I replace rBind with rbind2 directly, then I still see the following error:
error calling combine function:
<simpleError in .__H__.rbind(deparse.level = 0, x, y): no method for coercing this S4 class to a vector>
Do you know any workaround for this?
回答1:
The problem was that colMeans returs sparseVector and not sparseMatrix. Therefore, rBind is not able to combine several sparseVector objects into sparseMatrix.
As mentioned at https://stackoverflow.com/a/8979207/1075993, the solution is to write a function, that will combine multiple sparseVector objects into sparseMatrix:
sameSizeVectorList2Matrix <- function(vectorList){
sm_i<-NULL
sm_j<-NULL
sm_x<-NULL
for (k in 1:length(vectorList)) {
sm_i <- c(sm_i,rep(k,length(vectorList[[k]]@i)))
sm_j <- c(sm_j,vectorList[[k]]@i)
sm_x <- c(sm_x,vectorList[[k]]@x)
}
return (sparseMatrix(i=sm_i,j=sm_j,x=sm_x,dims=c(length(vectorList),vectorList[[1]]@length)))
}
来源:https://stackoverflow.com/questions/32499520/r-rbind-from-matrix-package-does-not-work-for-sparse-matrices