R: Reduce multidimensional data over time

reduce_time {gdalcubes} | R Documentation

## 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"))
    }

    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)
    })

[Package gdalcubes version 0.6.0 Index]