Bin values into grid cells

Assign each point to the cell that contains it, and combine the values that land in the same cell.

Usage

grid_bin(x, value = NULL, grid = NULL, fun = mean, ...)

Arguments

x

coordinates, or coordinates carrying their value as z; see xyz_input()

value

one value per coordinate, or NULL to use the z of x

grid

a grid_spec() to interpolate onto, or NULL for a default one

fun

function used to combine the values in one cell

...

ignored

Value

A guerrilla_grid with values.

Details

This is the simplest thing that can be called interpolation, and it is not really interpolation at all: nothing is estimated between the points, cells with no point in them stay NA, and the answer depends entirely on how big the cells are. It is here because it is the honest baseline, and because the question it raises – what should happen when two points land in one cell – is a question every other method answers silently.

fun is that answer, made explicit. mean averages them, length counts them, function(x) x[1] keeps the first, and looking at grid_bin(fun = length) next to any other method is the quickest way to see where a surface is supported by data and where it is supported by the algorithm.

Points on the outer edge of the extent are outside the last cell and are dropped, which is one reason to pad a grid; see grid_spec().

The whole implementation is vaster::cell_from_xy() and tapply(). No raster class is involved, because none is needed.

Examples

xy <- cbind(runif(300), runif(300))
g <- grid_spec(xy, dimension = c(20, 20))
plot(grid_bin(xy, xy[, 1], g))


## how many points went into each cell
plot(grid_bin(xy, xy[, 1], g, fun = length))