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IDPmisc (version 0.9.3)

ixyplot: Image Scatter Plot for Large Datasets

Description

Produces an image scatter plot of large datasets where the colors encode the density of the points in the scatter plot. Works also with factors.

Usage

ixyplot(x, y = NULL,
        pixs = 1, zmax = NULL, ztransf = function(x){x},
        colramp = IDPcolorRamp, border = FALSE,
        xlab = NULL, ylab = NULL, nx.lab = 5, ny.lab = 5, minL.lab = 3,
        main = NULL, cex.main = par("cex.main"))

Arguments

x,y
Coordinates of points whose density is to be plotted. If x ist a matrix or a data.frame, the first two column are used as x and y respectively. y must be in this case NULL. x and y may b
pixs
Pixelsize in mm.
zmax
Maximum number of counts per pixel in the plot. When NULL, the density in the scatter plot is encoded from 0 to maximum number of counts per pixel observed. zmax must be equal or larger than maximum number of co
ztransf
Function to transform the number of counts per pixel, which will be mapped by the function in colramp to well defined colors. The user has to make sure that the transformed density lies in the range [0,zmax], where zma
colramp
Color ramp to encode the number of counts within a pixel.
border
Shall border be drawn between the colors in the legend: TRUE / FALSE.
xlab
Label for x-axis.
ylab
Label for y-axis.
nx.lab
Approximate number of labeled ticks on x-axis.
ny.lab
Approximate number of labeled ticks on y-axis.
minL.lab
The minimum length of the abbreviations of factor levels, used to label the axes.
main
Title.
cex.main
Size of title relative to par("cex")

Value

  • Maximum number of counts per Pixel found.

concept

  • large dataset
  • huge dataset

Details

The idea of this plot is similar to plot.hexbin. The hexagons are better suited to reflect the density of points in a plane than the squares used here. Nevertheless squares are, contrary to hexagons, invariant to reflexions at the x- and y-axis and therefore suited for scatter plot matrices and also for plotting factors. \crThisfunction is based on graphics

See Also

ilagplot, ipairs, Image

Examples

Run this code
x <-  rnorm(100000)
y <- atan(rnorm(100000,0))
ixyplot(x,y)
ixyplot(x,pixs=2)
ixyplot(iris[,1:2],pixs=4)
ixyplot(iris[,"Petal.Width"],iris[,"Species"],pixs=4)
ixyplot(x=iris[,"Species"],y=iris[,"Petal.Width"],pixs=4,border=TRUE,
        xlab="Species",
        ylab="Petal Width",
        main="Iris Species and Petal Width")

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