image.SpatialGridDataFrame {sp} | R Documentation |
Convert gridded data in SpatialGridDataFrame to image format; call image on data in SpatialGridDataFrame format
image.SpatialGridDataFrame(x, attr = 1, xcol = 1, ycol = 2, asp = 1, axes = FALSE, ...) as.image.SpatialGridDataFrame(x, xcol = 1, ycol = 2)
x |
object of class SpatialGridDataFrame |
attr |
column number 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 |
asp |
aspect ratio of unit x and unit y axis |
axes |
logical; should coordinate axes be drawn? |
... |
arguments passed to image, see examples |
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.
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.
Edzer J. Pebesma
image.default, SpatialGridDataFrame-class,
levelplot in package lattice
data(meuse.grid) coordinates(meuse.grid) = c("x", "y") # promote to SpatialPointsDataFrame gridded(meuse.grid) = TRUE # promote to SpatialGridDataFrame image(meuse.grid["dist"], main = "Distance to river Meuse") data(meuse) coordinates(meuse) = c("x", "y") points(coordinates(meuse), pch = "+")