# grid.hexagons

##### Add Hexagon Cells to Plot

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.

- Keywords
- aplot

##### 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.

##### 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]

##### SIDE EFFECTS

Adds hexagons to the plot.

##### 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()
```

*Documentation reproduced from package hexbin, version 1.29.0, License: GPL-2*