R中的嵌套foreach循环，其中内循环返回矩阵

Question

theFrame <- data.frame(col1=rnorm(100), col2=rnorm(100))

theVector <- 2:30

regFor <- function(dataFrame, aVector, iterations)
{   
    #set up a blank results matrix to save into.
    results <- matrix(nrow=iterations, ncol=length(aVector))

    for(i in 1:iterations)
    {
        #set up a blank road map to fill with 1s according to desired parameters
        roadMap <- matrix(ncol=dim(dataFrame)[1], nrow=length(aVector), 0)
        row.names(roadMap) <- aVector
        colnames(roadMap) <- 1:dim(dataFrame)[1]

        for(j in 1:length(aVector))
        {
            #sample some of the 0s and convert to 1s according to desired number of sample
            roadMap[j,][sample(colnames(roadMap),aVector[j])] <- 1
        }

        temp <- apply(roadMap, 1, sum)

        results[i,] <- temp
    }

    results <- as.data.frame(results)
    names(results) <- aVector

    results
}

test <- regFor(theFrame, theVector, 2)

trying <- function(dataFrame, aVector, iterations, cores)
{   
    registerDoMC(cores)

    #set up a blank results list to save into. i doubt i need to do this
    results <- list()

    foreach(i = 1:iterations, .combine="rbind") %dopar%
    {
        #set up a blank road map to fill with 1s according to desired parameters
        roadMap <- matrix(ncol=dim(dataFrame)[1], nrow=length(aVector), 0)
        row.names(roadMap) <- aVector
        colnames(roadMap) <- 1:dim(dataFrame)[1]

        foreach(j = 1:length(aVector)) %do%
        {
            #sample some of the 0s and convert to 1s according to desired number of sample
            roadMap[j,][sample(colnames(roadMap),aVector[j])] <- 1
        }

        results[[i]] <- apply(roadMap, 1, sum)
    }
    results
}

test2 <- trying(theFrame, theVector, 2, 2)

我认为无论如何我都必须在内循环上使用foreach,对吗？

Answer 1

当使用foreach时，您不会像您所怀疑的那样“设置一个空白的结果列表来保存”。相反，您将计算foreach循环主体的结果合并，并返回合并结果。在这种情况下，我们希望外部foreach循环将向量（由内部foreach循环计算）按行组合成一个矩阵。该矩阵被分配给变量results，然后将其转换为数据帧。

以下是我第一次尝试转换您的示例：

library(doMC)

foreachVersion <- function(dataFrame, aVector, iterations, cores) {
  registerDoMC(cores) # unusual, but reasonable with doMC
  rows <- nrow(dataFrame)
  cols <- length(aVector)
  results <-
    foreach(i=1:iterations, .combine='rbind') %dopar% {
      # The value of the inner foreach loop is returned as
      # the value of the body of the outer foreach loop
      foreach(aElem=aVector, .combine='c') %do% {
        roadMapRow <- double(length=rows)
        roadMapRow[sample(rows,aElem)] <- 1
        sum(roadMapRow)
      }     
    }
  results <- as.data.frame(results)
  names(results) <- aVector
  results
}

内部循环不需要实现为foreach循环。您也可以使用sapply，但我会试着找出是否有更快的方法。但是对于这个答案，我想演示一个foreach方法。我使用的唯一真正的优化是通过在内部foreach循环中执行sum来消除对apply的调用。