hexbin (version 1.29.0)

grid.hexagons: Add Hexagon Cells to Plot

Description

Plots cells in an hexbin object. The function distinquishes among counts using 5 different styles. This function is the hexagon plotting engine from the plot method for hexbin objects.

Usage

grid.hexagons(dat, style = c("colorscale", "centroids", "lattice",
	      "nested.lattice", "nested.centroids", "constant.col"),
         use.count=TRUE, cell.at=NULL,
	 minarea = 0.05, maxarea = 0.8, check.erosion = TRUE,
	 mincnt = 1, maxcnt = max(dat@count), trans = NULL,
	 colorcut = seq(0, 1, length = 17),
	 density = NULL, border = NULL, pen = NULL,
	 colramp = function(n){ LinGray(n,beg = 90, end = 15) },
	 def.unit=  "native",
	 verbose = getOption("verbose"))

Arguments

dat

an object of class hexbin, see hexbin.

style

character string specifying the type of plotting; must be (a unique abbrevation) of the values given in Usage above.

use.count

logical specifying if counts should be used.

cell.at

numeric vector to be plotted instead of counts, must besame length as the number of cells.

minarea

numeric, the fraction of cell area for the lowest count.

maxarea

the fraction of the cell area for the largest count.

check.erosion

logical indicating only eroded points should be used for "erodebin" objects; simply passed to hcell2xy, see its documentation.

mincnt

numeric; cells with counts smaller than mincnt are not shown.

maxcnt

cells with counts larger than this are not shown.

trans

a transformation function (or NULL) for the counts, e.g., sqrt.

colorcut

a vector of values covering [0, 1] which determine hexagon color class boundaries or hexagon size boundaries -- for style = "colorscale" only.

density

grid.polygon argument for shading. 0 causes the polygon not to be filled. This is not implemented (for grid.polygon) yet.

border

grid.polygon() argument. Draw the border for each hexagon.

pen

colors for grid.polygon(). Determines the color with which the polygon will be filled.

colramp

function of an integer argument n returning n colors. n is determined

def.unit

default unit to be used.

verbose

logical indicating if some diagnostic output should happen.

SIDE EFFECTS

Adds hexagons to the plot.

Details

The six plotting styles have the following effect: [object Object],[object Object],[object Object],[object Object]

Hexagon size encoding minarea and maxarea determine the area of the smallest and largest hexagons plotted. Both are expressed fractions of the bin cell size. Typical values might be .04 and 1. When both values are 1, all plotted hexagons are bin cell size, if maxarea is greater than 1 than hexagons will overlap. This is sometimes interesting with the lattice and centroid styles.

Count scaling

relcnt <- (trans(cnt)-trans(mincnt)) / (trans(maxcnt)-trans(mincnt)) area <- minarea + relcnt*maxarea

By default the transformation trans() is the identity function. The legend routine requires the transformation inverse for some options.

Count windowing mincnt and maxcnt Only routine only plots cells with cnts in [mincnts, maxcnts]

References

Carr, D. B. (1991) Looking at Large Data Sets Using Binned Data Plots, pp. 7--39 in Computing and Graphics in Statistics; Eds. A. Buja and P. Tukey, Springer-Verlag, New York.

See Also

hexbin, smooth.hexbin, erode.hexbin, hcell2xy, gplot.hexbin, hboxplot, hdiffplot, grid.hexlegend

Examples

set.seed(506)
x <- rnorm(10000)
y <- rnorm(10000)

# bin the points
bin <- hexbin(x,y)

# Typical approach uses plot( <hexbin> ) which controls the plot shape :
plot(bin, main = "Bivariate rnorm(10000)")

## but we can have more manual control:

# A mixture distribution
x <- c(rnorm(5000),rnorm(5000,4,1.5))
y <- c(rnorm(5000),rnorm(5000,2,3))
hb2 <- hexbin(x,y)

# Show color control and overplotting of hexagons
## 1) setup coordinate system:
P <- plot(hb2, type="n", main = "Bivariate mixture (10000)")# asp=1

## 2) add hexagons (in the proper viewport):
pushHexport(P$plot.vp)
grid.hexagons(hb2, style= "lattice", border = gray(.1), pen = gray(.6),
              minarea = .1, maxarea = 1.5)
popViewport()

## How to treat 'singletons' specially:
P <- plot(hb2, type="n", main = "Bivariate mixture (10000)")# asp=1
pushHexport(P$plot.vp)
grid.hexagons(hb2, style= "nested.centroids", mincnt = 2)# not the single ones
grid.hexagons(hb2, style= "centroids", maxcnt = 1, maxarea=0.04)# single points
popViewport()