# create image collection from example Landsat data only
# if not already done in other examples
if (!file.exists(file.path(tempdir(), "L8.db"))) {
L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
".TIF", recursive = TRUE, full.names = TRUE)
create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db"), quiet = TRUE)
}
L8.col = image_collection(file.path(tempdir(), "L8.db"))
v = cube_view(extent=list(left=388941.2, right=766552.4,
bottom=4345299, top=4744931, t0="2018-01", t1="2018-12"),
srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
L8.cube = raster_cube(L8.col, v)
L8.cube = select_bands(L8.cube, c("B04", "B05"))
f <- function() {
x <- read_chunk_as_array()
out <- reduce_time(x, function(x) {
cor(x[1,], x[2,], use="na.or.complete", method = "kendall")
})
write_chunk_from_array(out)
}
L8.cor = chunk_apply(L8.cube, f)chunk_apply
Apply an R function on chunks of a data cube
Description
Apply an R function on chunks of a data cube
Usage
Arguments
| Argument | Description |
|---|---|
| cube | source data cube |
| f | R function to apply over all chunks |
Details
This function internally creates a gdalcubes stream data cube, which streams data of a chunk to a new R process. For reading data, the function typically calls x <- read_chunk_as_array() which then results in a 4 dimensional (band, time, y, x) array. Similarly write_chunk_from_array(x) will write a result array as a chunk in the resulting data cube. The chunk size of the input cube is important to control how the function will be exposed to the data cube. For example, if you want to apply an R function over complete pixel time series, you must define the chunk size argument in raster_cube to make sure that chunk contain the correct parts of the data.
Value
a proxy data cube object
Note
This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.