【发布时间】：2023-02-12 00:08:30
【问题描述】：
我正在尝试将嵌套的 foreach 循环应用于列表。使用嵌套 for 循环时，我的代码有效。但是当我尝试使用 foreach 循环时，我没有得到完整的结果（在列表中），而只是几个值。
这是我的嵌套 for 循环代码：
library(sn)
library(mnormt)
library(mokken)
library(polycor)
library(foreach)
library(parallel)
data("DS14")
data<-DS14[,3:5] # for testing I only use 3 variables
source("C:/Users/.../code to apply function fit_skewnorm (Kolbe et al., 2021).R")
# Kolbe et al. for reference: https://doi.org/10.3390/psych3040037
# see Appendix B
allresults_skew <- replicate(ncol(data)-1, matrix(NA,ncol(data),9), simplify = FALSE)
for(p in 1:ncol(data)){
for(q in 2:ncol(data)){
if(q<=p){
next}
tryCatch({ # a function to continue with loop in case of errors
obsn = table(data[,p], data[,q])
ncats1 = nrow(obsn)
ncats2 = ncol(obsn)
ntot = sum(obsn)
obsp = obsn/ntot
proportions2 = matrix(colSums(obsp), 1, ncats2)
proportions1 = matrix(rowSums(obsp), ncats1 , 1)
premultiplier = matrix(0, ncats1, ncats1)
for(l in 1:ncats1)for(m in 1:l)premultiplier[l,m] = 1
postmultiplier = matrix(0, ncats2, ncats2)
for(l in 1:ncats2)for(m in l:ncats2)postmultiplier[l,m] = 1
cumulprops2 = proportions2 %*% postmultiplier
cumulprops1 = premultiplier %*% proportions1
nthresholds1 = ncats1 - 1
nthresholds2 = ncats2 - 1
thresholds1 = matrix(0, 1, nthresholds1)
for(l in 1:nthresholds1)thresholds1[l] = qnorm(cumulprops1[l])
thresholds2 = matrix(0, 1, nthresholds2)
for(l in 1:nthresholds2)thresholds2[l] = qnorm(cumulprops2[l])
pcorr = polycor::polychor(obsn)
results_fit = fit_skewnorm(c("th1" = thresholds1, "th2" = thresholds2, "corr" = pcorr, "alpha" = c(2 ,2)))
allresults_skew[[p]][q,1] <- p
allresults_skew[[p]][q,2] <- q
allresults_skew[[p]][q,3] <- results_fit[,1]
allresults_skew[[p]][q,4] <- results_fit[,2]
allresults_skew[[p]][q,5] <- results_fit[,3]
allresults_skew[[p]][q,6] <- results_fit[,4]
allresults_skew[[p]][q,7] <- results_fit[,5]
allresults_skew[[p]][q,8] <- results_fit[,6]
allresults_skew[[p]][q,9] <- results_fit[,7]
}, error=function(e){cat("ERROR :",conditionMessage(e), "\n")}) # part of tryCatch
}
}
然后，allresults_skew 是：
[[1]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] NA NA NA NA NA NA NA NA NA
[2,] 1 2 19.97874 13 0.095741675130554 0.2705112 0 1.4656923 0.7528304
[3,] 1 3 65.49704 13 0.000000005354567 0.8426818 0 0.2512463 2.2963329
[[2]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] NA NA NA NA NA NA NA NA NA
[2,] NA NA NA NA NA NA NA NA NA
[3,] 2 3 31.14632 13 0.003209404 0.2753952 0 0.7247398 0.5957852
我当前的嵌套 foreach 循环如下所示：
allresults_skew <- replicate(ncol(data)-1, matrix(NA,ncol(data),9), simplify = FALSE)
no_cores <- detectCores(logical = TRUE)
cl <- makeCluster(no_cores-1)
registerDoParallel(cl)
getDoParWorkers()
foreach(i = 1:ncol(data),.combine = 'cbind') %:%
foreach(j = 2:ncol(data), .combine = 'rbind') %dopar% {
if(j<=i){
return(NA)}
tryCatch({ # a function to continue with loop in case of errors
#progress(i, ncol(data)-1)
obsn = table(data[,i], data[,j])
ncats1 = nrow(obsn)
ncats2 = ncol(obsn)
ntot = sum(obsn)
obsp = obsn/ntot
proportions2 = matrix(colSums(obsp), 1, ncats2)
proportions1 = matrix(rowSums(obsp), ncats1 , 1)
premultiplier = matrix(0, ncats1, ncats1)
for(l in 1:ncats1)for(m in 1:l)premultiplier[l,m] = 1
postmultiplier = matrix(0, ncats2, ncats2)
for(l in 1:ncats2)for(m in l:ncats2)postmultiplier[l,m] = 1
cumulprops2 = proportions2 %*% postmultiplier
cumulprops1 = premultiplier %*% proportions1
nthresholds1 = ncats1 - 1
nthresholds2 = ncats2 - 1
thresholds1 = matrix(0, 1, nthresholds1)
for(l in 1:nthresholds1)thresholds1[l] = qnorm(cumulprops1[l])
thresholds2 = matrix(0, 1, nthresholds2)
for(l in 1:nthresholds2)thresholds2[l] = qnorm(cumulprops2[l])
pcorr = polycor::polychor(obsn)
results_fit = fit_skewnorm(c("th1" = thresholds1, "th2" = thresholds2, "corr" = pcorr, "alpha" = c(2 ,2)))
allresults_skew[[i]][j,1] <- i
allresults_skew[[i]][j,2] <- j
allresults_skew[[i]][j,3] <- results_fit[,1]
allresults_skew[[i]][j,4] <- results_fit[,2]
allresults_skew[[i]][j,5] <- results_fit[,3]
allresults_skew[[i]][j,6] <- results_fit[,4]
allresults_skew[[i]][j,7] <- results_fit[,5]
allresults_skew[[i]][j,8] <- results_fit[,6]
allresults_skew[[i]][j,9] <- results_fit[,7]
}, error=function(e){cat("ERROR :",conditionMessage(e), "\n")}) # part of tryCatch
NULL
}
stopCluster(cl)
这些 foreach 循环运行后，我得到这个矩阵：
[,1] [,2] [,3]
result.1 0.7528304 NA NA
result.2 2.2963329 0.5957852 NA
并询问 allresults_skew，给我：
[[1]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] NA NA NA NA NA NA NA NA NA
[2,] NA NA NA NA NA NA NA NA NA
[3,] NA NA NA NA NA NA NA NA NA
[[2]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,] NA NA NA NA NA NA NA NA NA
[2,] NA NA NA NA NA NA NA NA NA
[3,] NA NA NA NA NA NA NA NA NA
因此，foreach 循环只是给出 for 循环最后一列的值，但只是在代码运行之后。使用 allresults_skew 矩阵仍然完全不适用。 如果有人可以帮助我并告诉我要更改什么，我将不胜感激。
我也不确定是否在两个 foreach 循环中选择 .combine = 'c'、'rbind' 或 'cbind'。但我认为这并不能解释为什么代码没有生成包含 3 x 9 矩阵的列表。
【问题讨论】：
-
我找到了适合我的解决方案：
标签： list for-loop parallel-foreach