reduce_time: Reduce multidimensional data over time

In gdalcubes: Earth Observation Data Cubes from Satellite Image Collections

Reduce multidimensional data over time

Description

This generic function applies a reducer function over a data cube, an R array, or other classes if implemented.

Usage

reduce_time(x, ...)

Arguments

x	object to be reduced
...	further arguments passed to specific implementations

Value

return value and type depend on the class of x

See Also

reduce_time.cube

reduce_time.array

Examples

# 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="2018-06"),
              srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
reduce_time(raster_cube(L8.col, v) , "median(B02)", "median(B03)", "median(B04)")  
 
d <- c(4,16,32,32)
x <- array(rnorm(prod(d)), d)
y <- reduce_time(x, function(v) {
  apply(v, 1, mean)
})
 

gdalcubes documentation built on May 29, 2024, 5:11 a.m.