Produce a Sunflower Scatter Plot

Description

Multiple points are plotted as ‘sunflowers’ with multiple leaves (‘petals’) such that overplotting is visualized instead of accidental and invisible.

Usage

sunflowerplot(x, ...)

## Default S3 method:
sunflowerplot(x, y = NULL, number, log = "", digits = 6,
              xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL,
              add = FALSE, rotate = FALSE,
              pch = 16, cex = 0.8, cex.fact = 1.5,
              col = par("col"), bg = NA, size = 1/8, seg.col = 2,
              seg.lwd = 1.5, ...)

## S3 method for class 'formula'
sunflowerplot(formula, data = NULL, xlab = NULL, ylab = NULL, ...,
             subset, na.action = NULL)

Arguments

Details

This is a generic function with default and formula methods.

For number[i] == 1, a (slightly enlarged) usual plotting symbol (pch) is drawn. For number[i] > 1, a small plotting symbol is drawn and number[i] equi-angular ‘rays’ emanate from it.

If rotate = TRUE and number[i] >= 2, a random direction is chosen (instead of the y-axis) for the first ray. The goal is to jitter the orientations of the sunflowers in order to prevent artefactual visual impressions.

Value

A list with three components of same length,

Use xyTable() (from package grDevices) if you are only interested in this return value.

Side Effects

A scatter plot is drawn with ‘sunflowers’ as symbols.

Author(s)

Andreas Ruckstuhl, Werner Stahel, Martin Maechler, Tim Hesterberg, 1989–1993. Port to R by Martin Maechler maechler@stat.math.ethz.ch.

References

Chambers, J. M., Cleveland, W. S., Kleiner, B. and Tukey, P. A. (1983) Graphical Methods for Data Analysis. Wadsworth.

Schilling, M. F. and Watkins, A. E. (1994) A suggestion for sunflower plots. The American Statistician, 48, 303–305.

Murrell, P. (2005) R Graphics. Chapman & Hall/CRC Press.

See Also

density, xyTable

Examples

require(stats) # for rnorm
require(grDevices)

## 'number' is computed automatically:
sunflowerplot(iris[, 3:4])
## Imitating Chambers et al, p.109, closely:
sunflowerplot(iris[, 3:4], cex = .2, cex.fact = 1, size = .035, seg.lwd = .8)
## or
sunflowerplot(Petal.Width ~ Petal.Length, data = iris,
              cex = .2, cex.fact = 1, size = .035, seg.lwd = .8)


sunflowerplot(x = sort(2*round(rnorm(100))), y = round(rnorm(100), 0),
              main = "Sunflower Plot of Rounded N(0,1)")
## Similarly using a "xyTable" argument:
xyT <- xyTable(x = sort(2*round(rnorm(100))), y = round(rnorm(100), 0),
               digits = 3)
utils::str(xyT, vec.len = 20)
sunflowerplot(xyT, main = "2nd Sunflower Plot of Rounded N(0,1)")

## A 'marked point process' {explicit 'number' argument}:
sunflowerplot(rnorm(100), rnorm(100), number = rpois(n = 100, lambda = 2),
              main = "Sunflower plot (marked point process)",
              rotate = TRUE, col = "blue4")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(graphics)
> png(filename="/home/ddbj/snapshot/RGM3/R_rel/result/graphics/sunflowerplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: sunflowerplot
> ### Title: Produce a Sunflower Scatter Plot
> ### Aliases: sunflowerplot sunflowerplot.default sunflowerplot.formula
> ### Keywords: hplot smooth nonparametric
> 
> ### ** Examples
> 
> require(stats) # for rnorm
> require(grDevices)
> 
> ## 'number' is computed automatically:
> sunflowerplot(iris[, 3:4])
> ## Imitating Chambers et al, p.109, closely:
> sunflowerplot(iris[, 3:4], cex = .2, cex.fact = 1, size = .035, seg.lwd = .8)
> ## or
> sunflowerplot(Petal.Width ~ Petal.Length, data = iris,
+               cex = .2, cex.fact = 1, size = .035, seg.lwd = .8)
> 
> 
> sunflowerplot(x = sort(2*round(rnorm(100))), y = round(rnorm(100), 0),
+               main = "Sunflower Plot of Rounded N(0,1)")
> ## Similarly using a "xyTable" argument:
> xyT <- xyTable(x = sort(2*round(rnorm(100))), y = round(rnorm(100), 0),
+                digits = 3)
> utils::str(xyT, vec.len = 20)
List of 3
 $ x     : num [1:24] -4 -4 -4 -4 -2 -2 -2 -2 -2 -2 0 0 0 0 0 2 2 2 2 2 4 4 4 4
 $ y     : num [1:24] -2 -1 0 1 -3 -2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1
 $ number: int [1:24] 1 1 2 2 1 2 5 11 5 1 5 5 16 3 3 4 7 11 8 1 1 2 1 2
> sunflowerplot(xyT, main = "2nd Sunflower Plot of Rounded N(0,1)")
> 
> ## A 'marked point process' {explicit 'number' argument}:
> sunflowerplot(rnorm(100), rnorm(100), number = rpois(n = 100, lambda = 2),
+               main = "Sunflower plot (marked point process)",
+               rotate = TRUE, col = "blue4")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>