image.SpatialGridDataFrame {sp} | 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 = (!.isSDI() && 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` | default `!.isSDI()` as a workaround for a problem with repeated use in Windows SDI installations; if TRUE, use `rasterImage` to render the image if available; for legacy rendering set FALSE
`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

### See Also

image.default, SpatialGridDataFrame-class, levelplot in package `lattice`. Function `image.plot` in package `fields` can be used to make a legend for an image, see an example in https://stat.ethz.ch/pipermail/r-sig-geo/2007-June/002143.html

### 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)

[Package sp version 1.2-3 Index]