Class for spatial attributes that have spatial locations on a regular grid.
Objects can be created by calls of the form
x is of class
SpatialPointsDataFrame-class, or by importing through rgdal.
Ordered full grids are stored instead or unordered non-NA cells;
Object of class
"matrix"; bounding box
Object of class
see SpatialPoints; points slot
see GridTopology-class; grid parameters
integer; index of points in the list to points in the full (ordered) grid. x cycles fastest; all coordinates increase from low to hight except y, which decreases from high to low
Object of class data.frame, containing the attribute data
"Spatial", by class
signature(x = "SpatialPixelsDataFrame"): retrieves coordinates
signature(x = "SpatialPixelsDataFrame"): selects row(s) and/or attribute(s), and returns an
object of class
SpatialPixelsDataFrame; rows refer here to the pixel
numbers, not grid lines. For selecting a square block in a grid, coerce to
a SpatialGridDataFrame-class first, and use
[ on that object
signature(x = "SpatialPixelsDataFrame"): coerce to matrix
signature(x = "SpatialPixelsDataFrame"): rbind-like method
Edzer Pebesma, [email protected]
SpatialPixels-class, which does not contain the attribute data
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data(meuse.grid) # only the non-missing valued cells coordinates(meuse.grid) = c("x", "y") # promote to SpatialPointsDataFrame gridded(meuse.grid) <- TRUE # promote to SpatialPixelsDataFrame meuse.grid[["idist"]] = 1 - meuse.grid[["dist"]] # assigns new attribute image(meuse.grid["idist"]) # note the single [ # toy example: df = data.frame(z = c(1:6,NA,8,9), xc = c(1,1,1,2,2,2,3,3,3), yc = c(rep(c(0, 1.5, 3),3))) coordinates(df) = ~xc+yc gridded(df) = TRUE image(df["z"]) # draw labels to verify: cc = coordinates(df) z=df[["z"]] zc=as.character(z) zc[is.na(zc)]="NA" text(cc[,1],cc[,2],zc)
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