Question

我正在尝试使用foreach在并行代码中转换我的嵌套循环。我不明白该怎么做。按照我的代码：提前谢谢!!

setwd("simul")
IntervalTime <- c(10,15,20)
ThinIntesity <- c(10,15,20,25)
MINSTOCKGROW <- c(200,250,300)
meteoScen <- c("rcp4p5", "rcp8p5")
Co2mod <- c("CO2_rcp4p5", "CO2_rcp8p5")
fileSettings <- c("set_co2_on_man_off.txt", "set_co2_on_man_on.txt")
mapUnc <- data.frame()
uncerOut <- data.frame()
mapUncNoMan <- data.frame()
validation <- list()

Sample <- getSample(resDE,thin=700,start=0.3*niter,coda=F)
nSample <- nrow(Sample)
ValidationOutput <- "./output/"
#FOR MANAGEMENT CASES

这里是并行化的代码，但我尝试了不同的方法但只有一个核心工作

for (i in 1:length(IntervalTime)){
  for(p in 1:length(MINSTOCKGROW)){
    for (j in 1:length(ThinIntesity)){
      for(z in 1:length(meteoScen)){
        for (k in 1:nSample){
          # MAP BAYESIAN REFERENCE
          ps <- createMixWithDefaults(pars = Sample[k, ],defaults = paramDefault, parind)
          if (meteoScen[z]=="M45"){
            #running the model
            unlink(list.files("./output/Validation",full.names = TRUE),recursive=TRUE)
            validation <- run3DCMCC(modelrun)
            validation$annual$MINSTOCKGROW <- MINSTOCKGROW[p]
            validation$annual$Management <- paste0(meteoScen[z],"_","IV_",IntervalTime[i],"_","IT_",ThinIntesity[j])
            validation$annual$CODE <- paste0(meteoScen[z],"_","IV_",IntervalTime[i],"_","IT_",ThinIntesity[j],"_",MINSTOCKGROW[p],"_",validation$annual$YEAR)
            validation$annual$Thinintensity <- ThinIntesity[j]
            validation$annual$intervTime <- IntervalTime[i]

            validation$annual$Meteo <- meteoScen[z]
            validation$annual$Manage <- "MANAGEMENT"
            validation$annual$Harv_Wood <- cumsum(validation$annual$C_HW)
            validation$annual$StockCarbon <- validation$annual$Harv_Wood+validation$annual$STANDING_WOOD

            # validation$monthly$Date <- as.yearmon(paste0(validation$monthly$YEAR, "-", validation$monthly$MONTH))
            # validation$monthly$Management <- paste0("METEO_",meteoScenario[z],"INTERVAL_",IntervalTime[i],"INTENSITY_",ThinIntesity[j])
            validationDF <- data.frame(validation$annual)
            write.table(validationDF, paste0("./dataOut/",meteoScen[z],"_IV_",IntervalTime[i],"_IT_",ThinIntesity[j],"_MINSTCK_",MINSTOCKGROW[p],"_MAN_ON",".txt"),quote = F, sep = "\t",row.names = F,col.names = T)
            mapUnc <- rbind(mapUnc, validation$annual)

          } else {

嵌套循环中的条件

            ps <- createMixWithDefaults(pars = Sample[k, ],defaults = paramDefault,parind)
            #running the model
            unlink(list.files("./output/",full.names = TRUE),recursive=TRUE)
            validation <- run3DCMCC(modelrun)
            validation$annual$MINSTOCKGROW <- MINSTOCKGROW[p]
            validation$annual$Management <- paste0(meteoScen[z],"_","IV_",IntervalTime[i],"_","IT_",ThinIntesity[j])
            validation$annual$CODE <- paste0(meteoScen[z],"_","IV_",IntervalTime[i],"_","IT_",ThinIntesity[j],"_",validation$annual$YEAR)
            validation$annual$Thinintensity <- ThinIntesity[j]
            validation$annual$intervTime <- IntervalTime[i]
            validation$annual$Meteo <- meteoScen[z]
            validation$annual$Manage <- "MANAGEMENT"
            validation$annual$Harv_Wood <- cumsum(validation$annual$C_HW)
            validation$annual$StockCarbon <- validation$annual$Harv_Wood+validation$annual$STANDING_WOOD

            validationDF <- data.frame(validation$annual)
            write.table(validationDF, paste0("./dataOut/",meteoScen[z],"_","IV_",IntervalTime[i],"_","IT_",ThinIntesity[j],"_MAN_ON",".txt"),quote = F, sep = "\t",row.names = F,col.names = T)

所有运行模型的rbind

mapUnc <- rbind(mapUnc, validation$annual)

          }
        }
      }
    }
  }
}

Answer 1

实际上，您可能不需要任何for循环。考虑输入向量上的expand.grid，它返回所有可能组合的data.frame。然后，运行Map（mapply的变体）通过构建 vaildationDF 的函数迭代地和逐个元素地传递列值。然后Map()将返回一个等于展开网格df行的数据帧列表（即所有组合）。

当然，由于您没有提供可重现的示例，未知库和函数调用，因此下面只是该过程的草图。此外，if/else条件看起来几乎相同，但下面是if条款的重写。此外，某些行似乎是多余的，因为从未使用 ps 对象（因此 Sample 未在下面合并）。可能 ps 与 modelrun 相关联？并且unlink()不会影响循环中的项目：

IntervalTime <- c(10,15,20)          # passed as i variable in fct. via Map()
ThinIntesity <- c(10,15,20,25)       # passed as t variable in fct. via Map() 
MINSTOCKGROW <- c(200,250,300)       # passed as g variable in fct. via Map()
meteoScen <- c("rcp4p5", "rcp8p5")   # passed as m variable in fct. via Map()

loopdf <- expand.grid(IntervalTime=IntervalTime, 
                      ThinIntensity=ThinIntesity, 
                      MINSTOCKGROW=MINSTOCKGROW, 
                      meteoScen=meteoScen)

createValidationDF <- function (i, t, g, m) {

  validation <- run3DCMCC(modelrun)
  validation$annual$MINSTOCKGROW <- g
  validation$annual$Management <- paste0(m,"_","IV_", i,"_","IT_", t)
  validation$annual$CODE <- paste0(m,"_","IV_",i,"_","IT_", t,"_",g,"_",
                                   validation$annual$YEAR)
  validation$annual$Thinintensity <- t
  validation$annual$intervTime <- i

  validation$annual$Meteo <- m
  validation$annual$Manage <- "MANAGEMENT"
  validation$annual$Harv_Wood <- cumsum(validation$annual$C_HW)
  validation$annual$StockCarbon <- validation$annual$Harv_Wood+validation$annual$STANDING_WOOD

  validationDF <- data.frame(validation$annual)

  write.table(validationDF, paste0("./dataOut/", m ,"_IV_", i,"_IT_", t,"_MINSTCK_",  g,"_MAN_ON",".txt"),
              quote = F, sep = "\t",row.names = F,col.names = T)

  return(validationDF)
}

df_List <- Map(createValidationDF, loopdf$IntervalTime, loopdf$ThinIntensity,
                                   loopdf$MINSTOCKGROW, loopdf$meteoScen)

mapUnc <- do.call(rbind, df_List)

R：循环嵌套，与foreach并行更改

1 个答案: