BinnedScatter {aroma.core} | R Documentation |
The BinnedScatter class
Description
Package: aroma.core
Class BinnedScatter
list
~~|
~~+--
BinnedScatter
Directly known subclasses:
public class BinnedScatter
extends list
Usage
BinnedScatter(data=NULL, density=NULL, map=NULL, params=NULL)
Arguments
data |
|
density |
... |
map |
... |
params |
A |
Fields and Methods
Methods:
plot | - | |
points | - | |
reorder | - | |
subsample | - | |
subset | - | |
Methods inherited from list:
Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, all.equal, as.CopyNumberDataSetTuple, as.data.frame, attachLocally, callHooks, coerce,ANY,list-method, exportAromaUnitPscnBinarySet, listToXml, mergeBoxplotStats, relist, type.convert, within
Author(s)
Henrik Bengtsson
See Also
The spatial density is estimated by internal functions of the smoothScatter package.
Examples
# Sample scatter data
n <- 10e3
x <- rnorm(n=n)
y <- rnorm(n=n)
xy <- cbind(x=x, y=sin(x)+y/5)
# Bin data and estimate densities
xyd <- binScatter(xy)
layout(matrix(1:4, nrow=2))
par(mar=c(5,4,2,1))
# Plot data
plot(xyd, pch=1)
# Thin scatter data by subsampling
rhos <- c(1/3, 1/4, 1/6)
for (kk in seq_along(rhos)) {
xyd2 <- subsample(xyd, size=rhos[kk])
points(xyd2, pch=1, col=kk+1)
}
for (kk in seq_along(rhos)) {
xyd2 <- subsample(xyd, size=rhos[kk])
plot(xyd2, pch=1, col=kk+1)
mtext(side=3, line=0, sprintf("Density: %.1f%%", 100*rhos[kk]))
}
[Package aroma.core version 3.3.1 Index]