Compute and Plot a 2-Dimensional Histogram
Compute and plot a 2-dimensional histogram.
hist2d(x,y=NULL, nbins=200, same.scale=FALSE, na.rm=TRUE, show=TRUE,
col=c("black", heat.colors(12)), FUN=base::length, xlab, ylab,
... )
## S3 method for class 'hist2d'
print(x, ...)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 the same 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
|
col |
Colors for the histogram. Defaults to "black" for bins containing no elements, a set of 16 heat colors for other bins. |
FUN |
Function used to summarize bin contents. Defaults to
|
xlab,ylab |
(Optional) x and y axis labels |
... |
Parameters passed to the image function. |
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.
A list containing 5 elements:
counts |
Matrix containing the number of points falling into each bin |
x.breaks, y.breaks |
Lower and upper limits of each bin |
x,y |
midpoints of each bin |
Gregory R. Warnes greg@warnes.net
## 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 an h2d object
h2d <- hist2d(x,y,show=FALSE, same.scale=TRUE, nbins=c(20,30))
## show object summary
h2d
## object contents
str(h2d)
## perspective plot
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) )Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.