R vapply和ddply的多核版本?
我有这样一个密码:R vapply和ddply的多核版本?,r,parallel-processing,multicore,plyr,R,Parallel Processing,Multicore,Plyr,我有这样一个密码: plot_cardinality <-function(data,name) { scT<-as(eclat(as(data.matrix(data)-1,"transactions"), parameter=list(support=0,minlen=1)),'data.frame') # count commas per data row in column items scT<-within(scT, size <- va
plot_cardinality <-function(data,name) {
scT<-as(eclat(as(data.matrix(data)-1,"transactions"), parameter=list(support=0,minlen=1)),'data.frame')
# count commas per data row in column items
scT<-within(scT, size <- vapply(items, count.commas, 1))
# use ddply to calculate min,mean,max support per size value
u<-ddply(scT, .(size), summarise, m=mean(support), min=min(support),max=max(support))
p <- ggplot(u) + geom_errorbar(data=u, aes(x=size, ymin=min, ymax=max)) + geom_point(aes(x=size,y=m), colour="red") +ggtitle(paste("Support for label occurence subsets\ndataset:",name))+xlab("Label subset cardinality")+ylab("Support of label subsets")
return(p)
}
plot\u基数并行化这不会让你走多远。您可能希望使用data.table
而不是ddply
。joran是正确的,但是,您可以在加载包doMC
后使用.parallel=TRUE
参数来设置ddply
。