chunk_apply: Apply an R function on chunks of a data cube

View source: R/chunk_apply.R

chunk_applyR Documentation

Apply an R function on chunks of a data cube


Apply an R function on chunks of a data cube


chunk_apply(cube, f)



source data cube


R function to apply over all chunks


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.


a proxy data cube object


This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.


# 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")
L8.cor = chunk_apply(L8.cube, f)

gdalcubes documentation built on April 14, 2023, 5:08 p.m.