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我正在寻求有关此示例的帮助。它可能与pbapply包无关，而是与mclapply(). 但是，也许有人知道这里发生了什么。

问题

唯一的区别是使用pblapply()/mclapply()而不是lapply()（我在 macOS 上）。在此示例中，该pblapply()方法返回NULL，而lapply()尝试工作正常。

有趣的一点是，它的行为只与我使用lda(). glm()其他使用或其他建模方法的示例工作正常。

似乎并行应用调用甚至没有从这里开始（基于它完成的速度）。

sperrorest()是一个通用框架（因此这里不应该是问题），我很困惑为什么该示例使用顺序方法（lapply()）而不是并行方法（pblapply()）。

此外，foreach()使用 apply* 函数而不是使用相同的方法可以正常工作。因此，我假设它与lda()并行 apply* 调用无关且相关。

笔记：

该示例在两个内核上运行，因此它应该在任何机器上运行。

首先，请做devtools::install_github("pat-s/sperrorest@mclapply-vs-lapply")。

代码（可重现）

library(MASS)
library(sperrorest)
library(parallel)
library(pbapply)

currentSample <- partition.cv(maipo, nfold = 4)
currentSample[[2]] <- partition.cv(maipo, nfold = 4)[[1]]
currentRes <- currentSample

lda.predfun <- function(object, newdata, fac = NULL) {
  library(nnet)
  majority <- function(x) {
    levels(x)[which.is.max(table(x))]
  }

  majority.filter <- function(x, fac) {
    for (lev in levels(fac)) {
      x[ fac == lev ] <- majority(x[ fac == lev ])
    }
    x
  }

  pred <- predict(object, newdata = newdata)$class
  if (!is.null(fac)) pred <- majority.filter(pred, newdata[,fac])
  return(pred)
}

data("maipo", package = "sperrorest")
predictors <- colnames(maipo)[5:ncol(maipo)]
fo <- as.formula(paste("croptype ~", paste(predictors, collapse = "+")))


# pblapply attempt (not working)
runreps_res <- pblapply(cl = 2, currentSample, function(X) 
  runreps(currentSample = X, data = maipo,
          formula = fo, par.mode = 1, pred.fun = lda.predfun,
          do.try = FALSE, model.fun = lda,
          error.fold = TRUE, error.rep = TRUE, do.gc = 1,
          err.train = TRUE, importance = FALSE, currentRes = currentRes, 
          pred.args = list(fac = "field"), response = "croptype", par.cl = 2, 
          coords = c("x", "y"), progress = 1, pooled.obs.train = c(), 
          pooled.obs.test = c(), err.fun = err.default))

# mclapply attempt (not working)
runreps_res <- mclapply(mc.cores = 2, currentSample, function(X) 
  runreps(currentSample = X, data = maipo,
          formula = fo, par.mode = 1, pred.fun = lda.predfun,
          do.try = FALSE, model.fun = lda,
          error.fold = TRUE, error.rep = TRUE, do.gc = 1,
          err.train = TRUE, importance = FALSE, currentRes = currentRes, 
          pred.args = list(fac = "field"), response = "croptype", par.cl = 2, 
          coords = c("x", "y"), progress = 1, pooled.obs.train = c(), 
          pooled.obs.test = c(), err.fun = err.default))

# lapply attempt (working)
runreps_res <- lapply(currentSample, function(X) 
  runreps(currentSample = X, data = maipo,
          formula = fo, par.mode = 1, pred.fun = lda.predfun,
          do.try = FALSE, model.fun = lda,
          error.fold = TRUE, error.rep = TRUE, do.gc = 1,
          err.train = TRUE, importance = FALSE, currentRes = currentRes, 
          pred.args = list(fac = "field"), response = "croptype", par.cl = 2, 
          coords = c("x", "y"), progress = 1, pooled.obs.train = c(), 
          pooled.obs.test = c(), err.fun = err.default))
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