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Yes. Finally, the Voronoi diagrams with the use of x11() function. This diagram is presentation of a plane that is partitioned every time, a user clicks on the canvas of x11. This plane is partitioned into smaller regions that are close to given set of points.

Partitioning into smaller regions or convex polygons happens in such manner that each polygon contains only one generating point and every point in a given polygon is closer to its generating point than to any other.

This is certainly very useful for many fields of computer science and programming, graphics, geoanalysis, analysis of space, meteorology and so on. And also useful for this series of useless-useful functions

With R we have many packages available, but this function is focused on end-user and clicking on the canvas that partitions the plane into smaller convex regions or polygons.

The useless R code is in gist only ggplot2 function that generates the voronoi diagram and function to navigate mouse clicks on x11() interface

# packages
library(deldir)
library(ggplot2)

dff <- data.frame(NULL,NULL,NULL)

#### Graph
voronoiGraphBoard <- function(){
r <- ggplot(data=dff, aes(x=xl,y=yl)) +
geom_segment( aes(x = x1, y = y1, xend = x2, yend = y2), size = 1, data = voronoi$dirsgs, linetype = 1, color= "orange") + geom_point( shape=21, size = 3, color="red", fill="blue") + theme_void() return(r) } ### Clicking on canvas click <- function(DefaultGraph=voronoiGraphBoard(), steps=st){ DefaultGraph <- plot.new() for (n in 1:steps) { mouse.at <- locator(n = 1, type = "o") xl <- mouse.at$x
yl <- mouse.at$y distance <- sqrt((xl-100)^2 + (yl-100)^2) df <- data.frame(xl,yl, distance) dff <<- rbind(dff, df) if (nrow(dff)>=2){ voronoi <<- deldir(dff$xl, dff\$yl)
DefaultGraph <- voronoiGraphBoard()
print(DefaultGraph)
}
}
}

Draw_x11 <- function(st){
x11()
click(steps=st)
DefaultGraph <<- voronoiGraphBoard()
}


And the rest is just running the main function:

# Generate Voronoi with defined steps
Draw_x11(st=20)


As always, code is available in at the Github in same Useless_R_function repository.

Happy R-coding!