gplots (version 2.7.4)

hist2d: Compute and Plot a 2-Dimensional Histogram

Description

Compute and plot a 2-dimensional histogram.

Usage

hist2d(x,y=NULL, nbins=200, same.scale=FALSE, na.rm=TRUE, show=TRUE,
       col=c("black", heat.colors(12)), ... )

Arguments

x

either a vector containing the x coordinates or a matrix with 2 columns.

y

a vector contianing the y coordinates, not required if `x' is matrix

nbins

number of bins in each dimension. May be a scalar or a 2 element vector. Defaults to 200.

same.scale

use a single range for x and y. Defaults to FALSE.

na.rm

Indicates whether missing values should be removed. Defaults to TRUE.

show

Indicates whether the histogram be displayed using image once it has been computed. Defaults to TRUE.

col

Colors for the histogram. Defaults to "black" for bins containing no elements, a set of 16 heat colors for other bins.

...

Parameters passed to the image function.

Value

• A list containing 3 elements:
• counts
  Matrix containing the number of points falling into each bin
• x
  lower x limit of each bin
• y
  lower y limit of each bin

Details

This fucntion creates a 2-dimensional histogram by cutting the x and y dimensions into nbins sections. A 2-dimensional matrix is then constucted which holds the counts of the number of observed (x,y) pairs that fall into each bin. If show=TRUE, this matrix is then then passed to image for display.

See Also

image, persp, hist

Examples

# example data, bivariate normal, no correlation
   x <- rnorm(2000, sd=4)
   y <- rnorm(2000, sd=1)

   # separate scales for each axis, this looks circular
   hist2d(x,y)

   # same scale for each axis, this looks oval
   hist2d(x,y, same.scale=TRUE)

   # use different # bins in each dimension
   hist2d(x,y, same.scale=TRUE, nbins=c(100,200) )

   # use the hist2d function to create inputs for a perspective plot ...
   h2d <- hist2d(x,y,show=FALSE, same.scale=TRUE, nbins=c(20,30))
   persp( h2d$x, h2d$y, h2d$counts,
          ticktype="detailed", theta=30, phi=30,
          expand=0.5, shade=0.5, col="cyan", ltheta=-30)

   # for contour (line) plot ...
   contour( h2d$x, h2d$y, h2d$counts, nlevels=4 )

   # for a filled contour plot ...
   filled.contour( h2d$x, h2d$y, h2d$counts, nlevels=4,
                   col=gray((4:0)/4) )