R/qqthin.R

"qqthin" <-
function(x, y, ends=c(.01,.99), eps=0.001,
           xlab = deparse(substitute(x)), adj.xlab=NULL,
           ylab = deparse(substitute(y)), show.line=TRUE,
           print.thinning.details=TRUE, centerline=TRUE, ...){
    ## qqthin() is a substitute for qqplot(), that thins
    ## out plotted points from the region where they are
    ## dense.  Apart from the overlaid curve that shows
    ## the region where points have been thinned, it may
    ## be hard to distinguish the result of qqthin()
    ## from that of qqplot()
    xlab <- xlab
    ylab <- ylab
    x <- sort(x)
    y <- sort(y)
    dx<-diff(x)
    epsdist <- sqrt(diff(range(x))^2+diff(range(y))^2)*eps
    dx<-0.5*(c(dx[1],dx)+c(dx,dx[length(dx)]))
    dy<-diff(y)
    dy<-0.5*(c(dy[1],dy)+c(dy,dy[length(dy)]))
    dpoints <- epsdist/sqrt(dx^2+dy^2)
    ## dpoints is a local measure of the number of points
    ## per unit distance along the diagonal, with the unit
    ## set to approximately eps*(length of diagonal)
    dig<-floor(dpoints)+1
    ## dig is, roughly, the number of points per unit distance.
    ## We wish to retain one point per unit distance.  For this
    ## retain points where cdig rounds to an integer. For such
    ## points, cdig has increased by approx 1, relative to the
    ## previous point that is retained.
    cdig<-round(cumsum(1/dig))
    subs<-match(unique(cdig), cdig)
    if(is.null(adj.xlab))
      plot(x[subs], y[subs], xlab=xlab, ylab=ylab)
    else {
      plot(x[subs], y[subs], xlab="", ylab=ylab)
      mtext(side=1, xlab, adj=adj.xlab, line=par()$mgp[1])
    }
    if(any(diff(subs)>1)){
    n1 <- min(subs[c(diff(subs),0)>1])
    n2 <- max(subs[c(0,diff(subs))>1])
    ns1 <- match(n1, subs)
    ns2 <- match(n2, subs)
    if(print.thinning.details)
        print(paste("Graph retains", length(subs), "points."))
    if(centerline)
      lines(smooth.spline(x[subs[ns1:ns2]], y[subs[ns1:ns2]]),
            col="grey", lwd=2)
  }
    if(show.line)abline(0, 1, col="red")
    invisible(length(subs))
  }

Try the hddplot package in your browser

Any scripts or data that you put into this service are public.

hddplot documentation built on Sept. 14, 2023, 5:07 p.m.