你的程序大概是干嘛的？

internalWeights[internalWeights!=0]  想计算稀疏矩阵中的每一个非零元素减一个指定数值

There is a much more efficient way to get the NON-ZERO/missing elements out of a sparse matrix. See the program below.

library(Matrix)
rSparseMatrix <- function(nrow, ncol, nnz,
                          rand.x = function(n) runif(nnz, 0,1), ...)
{
  stopifnot((nnz <- as.integer(nnz)) >= 0,
            nrow >= 0, ncol >= 0, nnz <= nrow * ncol)
  sparseMatrix(i = sample(nrow, nnz, replace = TRUE),
               j = sample(ncol, nnz, replace = TRUE),
               x = rand.x(nnz), dims = c(nrow, ncol), ...)

}
set.seed(123)
nInternalUnits<-5000
connectivity<-100
nrow<-nInternalUnits
ncol<-nInternalUnits
nnz<-connectivity
maxVal<-0

internalWeights<-rSparseMatrix(nrow, ncol, nnz)
as.matrix(summary(internalWeights))
internalWeights[internalWeights!=0]


system.time(as.matrix(summary(internalWeights)))
system.time(internalWeights[internalWeights!=0])

运行后：
还是提示：<sparse>[ <logic> ] : .M.sub.i.logical() maybe inefficient
请问该提示可以忽略吗，会不会产生不良影响啊？

No. AFAIK.