# image

##### Image Gridded Coordinates in Data Frame

Image gridded data, held in a data frame, keeping the right aspect ratio for axes, and the right cell shape

- Keywords
- dplot

##### Usage

```
# S3 method for data.frame
image(x, zcol = 3, xcol = 1, ycol = 2, asp = 1, ...)
xyz2img(xyz, zcol = 3, xcol = 1, ycol = 2, tolerance = 10 * .Machine$double.eps)
```

##### Arguments

- x
data frame (or matrix) with x-coordinate, y-coordinate, and z-coordinate in its columns

- zcol
column number or name of z-variable

- xcol
column number or name of x-coordinate

- ycol
column number or name of y-coordinate

- asp
aspect ratio for the x and y axes

- ...
arguments, passed to image.default

- xyz
data frame (same as

`x`

)- tolerance
maximum allowed deviation for coordinats from being exactly on a regularly spaced grid

##### Value

image.data.frame plots an image from gridded data, organized
in arbritrary order, in a data frame. It uses xyz2img and
image.default for this. In the S-Plus version, xyz2img
tries to make an image object with a size such that it will plot with
an equal aspect ratio; for the R version, image.data.frame uses the
`asp=1`

argument to guarantee this.

xyz2img returns a list with components: `z`

, a matrix
containing the z-values; `x`

, the increasing coordinates of the
rows of `z`

; `y`

, the increasing coordinates of the columns
of `z`

. This list is suitable input to image.default.

##### Note

I wrote this function before I found out about `levelplot`

,
a Lattice/Trellis function that lets you control the aspect ratio by
the `aspect`

argument, and that automatically draws a legend, and
therefore I now prefer levelplot over `image`

. Plotting points
on a levelplots is probably done with providing a panel function and
using `lpoints`

.

(for S-Plus only -- ) it is hard (if not impossible) to get exactly right
cell shapes (e.g., square for a square grid) without altering the size of
the plotting region, but this function tries hard to do so by extending
the image to plot in either x- or y-direction. The larger the grid, the
better the approximation. Geographically correct images can be obtained
by modifiying `par("pin")`

. Read the examples, image a 2 x 2 grid,
and play with `par("pin")`

if you want to learn more about this.

##### Examples

```
# NOT RUN {
library(sp)
data(meuse)
data(meuse.grid)
g <- gstat(formula=log(zinc)~1,locations=~x+y,data=meuse,model=vgm(1,"Exp",300))
x <- predict(g, meuse.grid)
image(x, 4, main="kriging variance and data points")
points(meuse$x, meuse$y, pch = "+")
# non-square cell test:
image(x[((x$y - 20) %% 80) == 0,], main = "40 x 80 cells")
image(x[((x$x - 20) %% 80) == 0,], main = "80 x 40 cells")
# the following works for square cells only:
oldpin <- par("pin")
ratio <- length(unique(x$x))/length(unique(x$y))
par(pin = c(oldpin[2]*ratio,oldpin[2]))
image(x, main="Exactly square cells, using par(pin)")
par(pin = oldpin)
library(lattice)
levelplot(var1.var~x+y, x, aspect = "iso", main = "kriging variance")
# }
```

*Documentation reproduced from package gstat, version 2.0-0, License: GPL (>= 2.0)*