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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 hist2d
print(x, ...)
either a vector containing the x coordinates or a matrix with 2 columns.
a vector contianing the y coordinates, not required if `x' is matrix
number of bins in each dimension. May be a scalar or a 2 element vector. Defaults to 200.
use the same range for x and y. Defaults to FALSE.
Indicates whether missing values should be removed. Defaults to TRUE.
Indicates whether the histogram be displayed using
image
once it has
been computed. Defaults to TRUE.
Colors for the histogram. Defaults to "black" for bins containing no elements, a set of 16 heat colors for other bins.
Function used to summarize bin contents. Defaults to
base::length
. Use, e.g., mean
to calculate means for each bin
instead of counts.
(Optional) x and y axis labels
Parameters passed to the image function.
A list containing 5 elements:
Matrix containing the number of points falling into each bin
Lower and upper limits of each bin
midpoints of each bin
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.
# NOT RUN {
## 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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