Compute and plot a 2dimensional histogram.
1 2 3 4 5 
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 2dimensional histogram by cutting the x and
y dimensions into nbins
sections. A 2dimensional 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
image
, persp
, hist
,
freq2d
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33  ## 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) )

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