Hexagonal binning with classes

Description

Displays a hexagonally-binned scatterplot with coloured subtriangles to indicate number of observations in each class. With a single class, gives a base-graphics version of the ordinary hexbin plot.

Usage

hextri(x,...)
## Default S3 method:
hextri(x, y, class, colours, nbins = 10, border =
TRUE, diffuse=FALSE, style=c("alpha","size"), weights=NULL,
sorted=!diffuse,minfrac=0, ...)
## S3 method for class 'formula'
hextri(x, data=parent.frame(), class,colours,nbins=10,
border=TRUE, diffuse=FALSE, style=c("alpha","size"),weights=NULL, sorted=!diffuse,
 xlab=NULL, ylab=NULL,minfrac=0,...)

Arguments

Details

Uses the Sainte-Lague method to apportion counts to triangles, ensuring the counts round to exactly six triangles per hexagon.

The binning/aspect ratio are adjusted to give regular hexagons on the figure region set by plot(x,y). If you reshape the window you will need to redraw the plot.

Value

A list with components x, y, and col suitable as input to polygon()

Author(s)

Thomas Lumley

See Also

sainte_lague

Examples

xx<-rnorm(1000)
yy<-rnorm(1000)
cc<-cut(xx*yy,c(-Inf,-.4,0,.4,Inf))

plot(xx,yy,col=(1:4)[cc])
hextri(xx,yy,cc,1:4,nbins=20,border=TRUE,style="size")

##formula method
data(NHANES, package="hexbin")
hextri(Weight~Age, class=Smoke, col=c("red","orange","green","grey40"),
   data=NHANES, style="size",nbins=20, main="Smoking")
legend("topright",fill=c("red","orange","green","grey40"),
   legend=c("Current","Past","Never","unknown"),bty="n")

## minimum sizes

data(NHANES, package="hexbin")
hextri(Weight~Age, class=Smoke, col=c("red","orange","green","grey40"),
   data=NHANES, style="size",nbins=20, main="Smoking",minfrac=.2)
legend("topright",fill=c("red","orange","green","grey40"),
   legend=c("Current","Past","Never","unknown"),bty="n")


## using the return value of hextri
rval<-hextri(xx,yy,cc,1:4,nbins=20,border=TRUE,style="alpha")
plot(y~x,data=rval,type="n")
with(rval, polygon(x,y,col=col,border=NA))

## diffusion
xx<-runif(10000)
yy<-runif(10000)
cc<-rep(1:3,c(4750,4750,500))
hextri(xx,yy,cc,2:4,border=TRUE,diffuse=FALSE,style="size")
hextri(xx,yy,cc,2:4,border=TRUE,diffuse=TRUE,sorted=TRUE, style="size")

hextri(xx,yy,cc,2:4,border=TRUE,diffuse=TRUE,style="size",weights=cc)

A lattice panel function for hexagonal binning with classes

Description

Displays a hexagonally-binned scatterplot with coloured subtriangles to indicate number of observations in each class. Uses the Sainte-Lague method to apportion counts to triangles, ensuring the counts round to exactly six triangles per hexagon.

Usage

panel.hextri(x, y, groups, subscripts, colours, nbins = 10, border = TRUE,
   diffuse = FALSE, style = c("alpha", "size"), weights = NULL,
   sorted=!diffuse, shape = 1, ...)

Arguments

Value

A panel

Author(s)

Thomas Lumley

See Also

hextri is the base-graphics plot

Examples

library(lattice)
xx<-rnorm(1000)
yy<-rnorm(1000)
cc<-cut(xx*yy,c(-Inf,-.4,0,.4,Inf))
zz<-cut(xx+yy,c(-Inf,-1,0,1,Inf))

plot(xx,yy,col=(1:4)[cc])
xyplot(yy~xx|zz, panel=panel.hextri,groups=cc,colours=1:4,style="size",nbins=10)

data(airquality)
airquality$o3group<-with(airquality, cut(Ozone, c(0,18,60,Inf)))

xyplot(Temp~Solar.R|equal.count(Wind,4), groups=o3group, panel=panel.hextri,
  data=na.omit(airquality),colours=c("royalblue","grey60","goldenrod"),
  strip=strip.custom(var.name="Wind Speed"),xlab="Solar Radiation (langley)",
  ylab="Temperature (F)")

Proportional representation by Sainte-Lague method

Description

Originally an algorithm for proportional allocation of seats to parties in elections, used here to assign the six triangles in each hex to classes.

Usage

sainte_lague(votes, nseats)

Arguments

Value

Numeric vector of length nseats giving the class membership for each seat, with an error attribute giving the rounding errors for each party.

References

https://en.wikipedia.org/wiki/Sainte-Lagu%C3%AB_method

See Also

hextri

Examples

sainte_lague(c(100,200,300,50),6)