image: Image or contour method for gridded spatial data; convert to...
In sp: Classes and Methods for Spatial Data

image.SpatialGridDataFrame

R Documentation

Image or contour method for gridded spatial data; convert to and from image data structure

Description

Create image for gridded data in SpatialGridDataFrame or SpatialPixelsDataFrame objects.

Usage

## S3 method for class 'SpatialGridDataFrame'
image(x, attr = 1, xcol = 1, ycol = 2, 
	col = heat.colors(12), red=NULL, green=NULL, blue=NULL,
        axes = FALSE, xlim = NULL,
	ylim = NULL, add = FALSE, ..., asp = NA, setParUsrBB=FALSE,
        interpolate = FALSE, angle = 0, 
	useRasterImage = !(.Platform$GUI[1] == "Rgui" &&
        getIdentification() == "R Console") && missing(breaks), breaks,
	zlim = range(as.numeric(x[[attr]])[is.finite(x[[attr]])]))
## S3 method for class 'SpatialPixelsDataFrame'
image(x, ...) 
## S3 method for class 'SpatialPixels'
image(x, ...) 
## S3 method for class 'SpatialGridDataFrame'
contour(x, attr = 1, xcol = 1, ycol = 2,
	col = 1, add = FALSE, xlim = NULL, ylim = NULL, axes = FALSE,
         ..., setParUsrBB = FALSE)
## S3 method for class 'SpatialPixelsDataFrame'
contour(x, ...) 
as.image.SpatialGridDataFrame(x, xcol = 1, ycol = 2, attr = 1)
image2Grid(im, p4 = as.character(NA), digits=10)

Arguments

`x`	object of class SpatialGridDataFrame
`attr`	column of attribute variable; this may be the column name in the data.frame of `data` (as.data.frame(data)), or a column number
`xcol`	column number of x-coordinate, in the coordinate matrix
`ycol`	column number of y-coordinate, in the coordinate matrix
`col`	a vector of colors
`red`, `green`, `blue`	columns names or numbers given instead of the `attr` argument when the data represent an image encoded in three colour bands on the 0-255 integer scale; all three columns must be given in this case, and the attribute values will be constructed using function `rgb`
`axes`	logical; should coordinate axes be drawn?
`xlim`	x-axis limits
`ylim`	y-axis limits
`zlim`	data limits for plotting the (raster, attribute) values
`add`	logical; if FALSE, the image is added to the plot layout setup by `plot(as(x, "Spatial"),axes=axes,xlim=xlim,ylim=ylim,asp=asp)` which sets up axes and plotting region; if TRUE, the image is added to the existing plot.
`...`	arguments passed to image, see examples
`asp`	aspect ratio to be used for plot
`setParUsrBB`	default FALSE, see `Spatial-class` for further details
`useRasterImage`	if TRUE, use `rasterImage` to render the image if available; for legacy rendering set FALSE; should be FALSE on Windows SDI installations
`breaks`	class breaks for coloured values
`interpolate`	default FALSE, a logical vector (or scalar) indicating whether to apply linear interpolation to the image when drawing, see `rasterImage`
`angle`	default 0, angle of rotation (in degrees, anti-clockwise from positive x-axis, about the bottom-left corner), see `rasterImage`
`im`	list with components named x, y, and z, as used for `image`
`p4`	CRS object, proj4 string
`digits`	default 10, number of significant digits to use for checking equal row/column spacing

Value

as.image.SpatialGridDataFrame returns the list with elements x and y, containing the coordinates of the cell centres of a matrix z, containing the attribute values in matrix form as needed by image.

Note

Providing xcol and ycol attributes seems obsolete, and it is for 2D data, but it may provide opportunities for plotting certain slices in 3D data. I haven't given this much thought yet.

filled.contour seems to misinterpret the coordinate values, if we take the image.default manual page as the reference.

Author(s)

Edzer Pebesma

Examples

data(meuse.grid)
coordinates(meuse.grid) = c("x", "y") # promote to SpatialPointsDataFrame
gridded(meuse.grid) = TRUE            # promote to SpatialGridDataFrame
data(meuse)
coordinates(meuse) = c("x", "y")
image(meuse.grid["dist"], main = "Distance to river Meuse")
points(coordinates(meuse), pch = "+")
image(meuse.grid["dist"], main = "Distance to river Meuse",
 useRasterImage=TRUE)
points(coordinates(meuse), pch = "+")

# color scale:
layout(cbind(1,2), c(4,1),1)
image(meuse.grid["dist"])
imageScale(meuse.grid$dist, axis.pos=4, add.axis=FALSE)
axis(4,at=c(0,.2,.4,.8), las=2)

data(Rlogo)
d = dim(Rlogo)
cellsize = abs(c(gt[2],gt[6]))
cells.dim = c(d[1], d[2]) # c(d[2],d[1])
cellcentre.offset = c(x = gt[1] + 0.5 * cellsize[1], y = gt[4] - (d[2] - 0.5) * abs(cellsize[2]))
grid = GridTopology(cellcentre.offset, cellsize, cells.dim)
df = as.vector(Rlogo[,,1])
for (band in 2:d[3]) df = cbind(df, as.vector(Rlogo[,,band]))
df = as.data.frame(df)
names(df) = paste("band", 1:d[3], sep="")
Rlogo <- SpatialGridDataFrame(grid = grid, data = df)
summary(Rlogo)
image(Rlogo, red="band1", green="band2", blue="band3")
image(Rlogo, red="band1", green="band2", blue="band3",
 useRasterImage=FALSE)
is.na(Rlogo$band1) <- Rlogo$band1 == 255
is.na(Rlogo$band2) <- Rlogo$band2 == 255
is.na(Rlogo$band3) <- Rlogo$band3 == 255
Rlogo$i7 <- 7
image(Rlogo, "i7")
image(Rlogo, red="band1", green="band2", blue="band3", add=TRUE)

sp documentation built on May 29, 2024, 5:33 a.m.