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

Create image for gridded data in SpatialGridDataFrame or SpatialPixelsDataFrame objects.

# S3 method for 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 SpatialPixelsDataFrame
image(x, ...)
# S3 method for SpatialPixels
image(x, ...)
# S3 method for SpatialGridDataFrame
contour(x, attr = 1, xcol = 1, ycol = 2,
        col = 1, add = FALSE, xlim = NULL, ylim = NULL, axes = FALSE,
         ..., setParUsrBB = FALSE)
# S3 method for 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.

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)
#> Object of class SpatialGridDataFrame
#> Coordinates:
#>   min max
#> x   0 101
#> y -77   0
#> Is projected: NA 
#> proj4string : [NA]
#> Grid attributes:
#>   cellcentre.offset cellsize cells.dim
#> x               0.5        1       101
#> y             -76.5        1        77
#> Data attributes:
#>      band1           band2           band3      
#>  Min.   :  0.0   Min.   :  0.0   Min.   :  0.0  
#>  1st Qu.:131.0   1st Qu.:138.0   1st Qu.:151.0  
#>  Median :196.0   Median :199.0   Median :215.0  
#>  Mean   :182.3   Mean   :185.4   Mean   :192.8  
#>  3rd Qu.:254.0   3rd Qu.:255.0   3rd Qu.:254.0  
#>  Max.   :255.0   Max.   :255.0   Max.   :255.0  
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)

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

Arguments

Value

Note

See also

Examples