# directlabels - utility.function - Positioning Method - far.from.others.borders

Find the point on each curve which maximizes the distance to the plot border or to another curve.

```far.from.others.borders <- function(all.groups,...,debug=FALSE){
group.data <- split(all.groups, all.groups\$group)
group.list <- list()
for(groups in names(group.data)){
## Run linear interpolation to get a set of points on which we
## could place the label (this is useful for e.g. the lasso path
## where there are only a few points plotted).
approx.list <- with(group.data[[groups]], approx(x, y))
if(debug){
with(approx.list, grid.points(x, y, default.units="cm"))
}
group.list[[groups]] <- data.frame(approx.list, groups)
}
output <- data.frame()
for(group.i in seq_along(group.list)){
one.group <- group.list[[group.i]]
## From Mark Schmidt: "For the location of the boxes, I found the
## data point on the line that has the maximum distance (in the
## image coordinates) to the nearest data point on another line or
## to the image boundary."
dist.mat <- matrix(NA, length(one.group\$x), 3)
colnames(dist.mat) <- c("x","y","other")
## dist.mat has 3 columns: the first two are the shortest distance
## to the nearest x and y border, and the third is the shortest
## distance to another data point.
for(xy in c("x", "y")){
xy.vec <- one.group[,xy]
xy.mat <- rbind(xy.vec, xy.vec)
lim.fun <- get(sprintf("%slimits", xy))
diff.mat <- xy.mat - lim.fun()
dist.mat[,xy] <- apply(abs(diff.mat), 2, min)
}
other.groups <- group.list[-group.i]
other.df <- do.call(rbind, other.groups)
for(row.i in 1:nrow(dist.mat)){
r <- one.group[row.i,]
other.dist <- with(other.df, (x-r\$x)^2 + (y-r\$y)^2)
dist.mat[row.i,"other"] <- sqrt(min(other.dist))
}
shortest.dist <- apply(dist.mat, 1, min)
picked <- calc.boxes(one.group[which.max(shortest.dist),])
## Mark's label rotation: "For the angle, I computed the slope
## between neighboring data points (which isn't ideal for noisy
## data, it should probably be based on a smoothed estimate)."
left <- max(picked\$left, min(one.group\$x))
right <- min(picked\$right, max(one.group\$x))
neighbors <- approx(one.group\$x, one.group\$y, c(left, right))
slope <- with(neighbors, (y[2]-y[1])/(x[2]-x[1]))
picked\$rot <- 180*atan(slope)/pi
output <- rbind(output, picked)
}
output
}
```
 Please contact Toby Dylan Hocking if you are using directlabels or have ideas to contribute, thanks! Documentation website generated from source code version 2021.2.24 (git revision bb6db07 Mon, 14 Jun 2021 22:38:45 +0530) using inlinedocs. validate