我正在尝试计算单个数据集观测值之间的高尔距离。我在以下链接中找到了一个有用的函数:https://www.kaggle.com/olivermeyfarth/parallel-computation-of-gower-distance?scriptVersionId=46656,其中包含以下使用并行计算的代码。
代码如下:
computeDistance <- function(dt1, dt2, nThreads = 4) {
# Determine chunk-size to be processed by different threads
s <- floor(nrow(dt1) / nThreads)
# Setup multi-threading
modelRunner <- makeCluster(nThreads)
registerDoParallel(modelRunner)
# For numeric variables, build ranges (max-min) to be used in gower-distance.
# Ensure that the ranges is computed on the overall data and not on
# the chunks in the parallel threads. Also, note that function 'gower.dist()'
# seems to be buggy in regards to missing values (NA), which can be fixed by
# providing ranges for all numeric variables in the function-call
dt <- rbind(dt1, dt2)
rngs <- rep(NA, ncol(dt))
for (i in 1:ncol(dt)) {
col <- dt[[i]]
if (is.numeric(col)) {
rngs[i] <- max(col, na.rm = T) - min(col, na.rm = T)
}
}
# Compute distance in parallel threads; note that you have to include packages
# which must be available in the different threads
distanceMatrix <-
foreach(
i = 1:nThreads, .packages = c("StatMatch"), .combine = "rbind",
.export = "computeDistance", .inorder = TRUE
) %dopar% {
# Compute chunks
from <- (i - 1) * s + 1
to <- i * s
if (i == nThreads) {
to <- nrow(dt1)
}
# Compute distance-matrix for each chunk
# distanceMatrix <- daisy(dt1[from:to,],metric = "gower")
distanceMatrix <- gower.dist(dt1[from:to,], dt2, rngs = rngs)
}
# Clean-up
stopCluster(modelRunner)
return(distanceMatrix)
}
但是,当我尝试使用数据集运行代码时(以下数据只是一个简单的示例),如下所示:
Distance_data <- data.frame(cbind(c(4,234,6,1),c(4,1,6,4),c(3,75,23,1)))
distances <- computeDistance(Distance_data,Distance_data)
我在R中收到以下错误:
Error in e$fun(obj, substitute(ex), parent.frame(), e$data) :
worker initialization failed: package ‘clue’ could not be loaded
我尝试将线索包添加到foreach函数中的.packages参数,但这没有成功。任何帮助表示赞赏!
注意:您需要下载以下软件包才能运行功能
library(StatMatch)
library(doParallel)