## ----main_benchmark------------------------------------------------------ library(netbenchmark) top20.aupr <- netbenchmark(methods="all",datasources.names = "Toy", local.noise=20,global.noise=10, noiseType=c("normal","lognormal"), datasets.num = 2,experiments = 40, seed=1422976420,verbose=FALSE) ## ----print--------------------------------------------------------------- print(top20.aupr[[1]]) ## ----wrapper_examples---------------------------------------------------- Spearmancor <- function(data){ cor(data,method="spearman") } Pearsoncor <- function(data){ cor(data,method="pearson") } ## ----evaluate_grn-------------------------------------------------------- res <- netbenchmark(datasources.names="syntren300", methods=c("Spearmancor","Pearsoncor"),verbose=FALSE) aupr <- res[[1]][,-(1:2)] ## ----fig.width=7, fig.height=6------------------------------------------- boxplot(aupr, main="Syntren300",ylab=expression('AUPR'[20])) ## ----fig.width=7, fig.height=6------------------------------------------- PR <- res[[5]][[1]] col <- rainbow(3) plot(PR$rec[,1],PR$pre[,1],type="l",lwd=3,col=col[1],xlab="Recall", ylab="Precision",main="Syntren300",xlim=c(0,1),ylim=c(0,1)) lines(PR$rec[,2],PR$pre[,2],type="l",lwd=3,col=col[2]) lines(PR$rec[,3],PR$pre[,3],type="l",lwd=3,col=col[3]) legend("topright", inset=.05,title="Method",colnames(PR$rec),fill=col) ## ----compare_grn--------------------------------------------------------- comp <- netbenchmark(datasources.names="syntren300", methods=c("all.fast","Spearmancor","Pearsoncor"),verbose=FALSE) aupr <- comp[[1]][,-(1:2)] ## ----fig.width=7, fig.height=6------------------------------------------- #make the name look prety library("tools") colnames(aupr) <- sapply(colnames(aupr),file_path_sans_ext) boxplot(aupr, main="Syntren300", ylab=expression('AUPR'[20]))