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## Plot of the densities
densitiesPlot <- function(matrix.x, matrix.y, quantiles,
sampleNames, bw, main, xlab, xlim,
ylim, lty = 1, lwd =1, mean = FALSE,
col, from, to, bty = "o"){
meanSample <- apply(matrix.x,1,mean)
plot(matrix.x[,1] , matrix.x[,2],
main = main,
ylab = "Density",
xlab = xlab,
col = "white",
xlim = xlim,
ylim = ylim, bty = bty
)
##rect(par("usr")[1], par("usr")[3], par("usr")[2], par("usr")[4], col = "black")
## Will plot individual densities
if (!mean){
##Wanna make sure colors are not randomly drawn
o <- order(col, decreasing=FALSE)
col <- col[o]
matrix.x <- matrix.x[,o]
matrix.y <- matrix.y[,o]
for (j in 1:ncol(matrix.x)){
lines(matrix.x[,j], matrix.y[,j],
col= col[j], lwd = lwd, lty=lty)
}
} else {
## Make sure to remove missing values
non.na.indices <- which(!is.na(col))
col <- col[non.na.indices]
quantiles <- quantiles[, non.na.indices]
unique.col <- unique(col)
n <- length(unique.col)
for (i in 1:n){
indices <- which(col==unique.col[[i]])
current.color <- col[indices][1]
if (length(indices==1)){
currentMean <- quantiles[,indices]
} else {
currentMean <- apply(quantiles[,indices],1,mean)
}
lines(density(currentMean, bw = bw, from= from, to = to),
lwd = lwd, lty=lty, col=current.color)
}
}
}
## To add selected density
addHoverDensity <- function(selectedSamples = c(), sampleNames,
matrix.x, matrix.y, col){
n <- length(selectedSamples)
if (n >= 1){
for (kk in 1:n){
lines(matrix.x[,selectedSamples[kk]],matrix.y[,selectedSamples[kk]],
col="black",lwd = 4, lty=3)
}
lines(matrix.x[,selectedSamples[n]],matrix.y[,selectedSamples[n]],
col="black",lwd = 3, lty=1)
}
}
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