Nothing
threshOpt <- function(distobj, sppVector, threshold = 0.01){
distobj <- as.matrix(distobj)
#individual (diag) values excluded
diag(distobj) <- NA
#indices of singletons
singletons <- rmSingletons(sppVector, exclude=FALSE)
#gets vector of column rows of all non-singletons
ZZ <- rmSingletons(sppVector, exclude=TRUE)
#run the sensitivity loop - singleton species (MU) excluded from iteration - only uses ZZ for query
#False positive - no matches within x% of query --- as the "NA" value
#Positive - only 1 sp. within x% of query --- as the "TRUE" value;
#False negative - more than 1 spp. within x% of query --- as the "FALSE" value
#remember for 0, we need to say ==0 rather than <0
OUT <- NULL
for(i in 1:dim(distobj)[1]) {
inThresh <- sppVector[which(distobj[,i] < threshold)]
if(length(inThresh) == 0 && i %in% singletons) OUT[i] <- "True neg" else {
if(length(inThresh) == 0 && !i %in% singletons) OUT[i] <- "False pos" else{
if(length(unique(inThresh)) == 1 && unique(inThresh) == sppVector[i]) OUT[i] <- "True pos" else{
if(length(unique(inThresh)) == 1 && !unique(inThresh) == sppVector[i]) OUT[i] <- "False neg" else OUT[i] <- "False neg"}
}}}
OUT <- factor(OUT, levels=c("True neg", "True pos", "False neg", "False pos"))
tab <- table(OUT)
tab <- c(threshold, tab, sum(tab[3], tab[4]))
names(tab)[c(1,6)] <- c("Threshold", "Cumulative error")
tab
}
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