cluster.overplot: Shift overlying points into clusters

View source: R/cluster.overplot.R

cluster.overplotR Documentation

Shift overlying points into clusters

Description

⁠cluster.overplot⁠’ checks for overlying points in the x and y coordinates passed. Those points that are overlying are moved to form a small cluster of up to nine points. For large numbers of overlying points, see count.overplot or sizeplot. If you are unsure of the number of overplots in your data, run ‘⁠count.overplot⁠’ first to see if there are any potential clusters larger than nine.

Usage

 cluster.overplot(x,y,away=NULL,tol=NULL,...)

Arguments

x,y

Numeric data vectors or the first two columns of a matrix or data frame. Typically the x/y coordinates of points to be plotted.

away

How far to move overlying points in user units. Defaults to the width of a lower case "o" in the x direction and 5/8 of the height of a lower case "o" in the y direction. Must have both values.

tol

The largest distance between points that will be considered to be overlying. Defaults to 1/2 of the width of a lower case "o" in the x direction and 1/2 of the height of a lower case "o" in the y direction.

...

additional arguments returned as they are passed.

Value

A list with two components. For unique x-y pairs the elements will be the same as in the original. For overlying points up to eight additional points will be generated that will create a cluster of points instead of one.

Author(s)

Jim Lemon - thanks to Markus Elze for the test for a current graphics device

See Also

count.overplot,sizeplot

Examples

 xy.mat<-cbind(sample(1:10,200,TRUE),sample(1:10,200,TRUE))
 clusteredpoints<-
  cluster.overplot(xy.mat,col=rep(c("red","green"),each=100),
  away=rep(0.2,2))
 plot(clusteredpoints,col=clusteredpoints$col,
  main="Cluster overplot test")

plotrix documentation built on Nov. 10, 2023, 5:07 p.m.