downsample a stars or stars_proxy object either by skipping rows, columns and bands, or by computing a single value (e.g. the mean) from the sub-tiles involved
Usage
st_downsample(x, n, ...)
# S3 method for class 'stars'
st_downsample(x, n, ..., offset = 0, FUN)
# S3 method for class 'stars_proxy'
st_downsample(x, n, ...)Arguments
- x
object of class stars or stars_proxy
- n
integer; for each dimension the number of pixels/lines/bands etc that will be skipped; see Details.
- ...
arguments passed on to
FUN(e.g.,na.rm = TRUEto ignore missing values if FUN ismean)- offset
integer; offset(s) for downsampling, in pixels, starting at the offset of each dimension; should be smaller or equal to
n- FUN
function; if given, downsampling will apply FUN to each of the the subtiles
Details
If all n == 0, no downsampling takes place; if it is 1, every second row/column/band is skipped, if it is 2, every second+third row/column/band are skipped, etc.
Downsampling a stars_proxy object returns a stars object, is
equivalent to calling st_as_stars(x, downsample = 2), and only downsamples
the first two (x and y) dimensions.
Downsampled regular rasters keep their dimension offsets, have a cell size (delta) that is n[i]+1 times larger, and may result in a (slightly) different extent.
Note that terra's aggregate with fact=2 corresponds to
st_downsample(x, n = 1, FUN = mean): fact is one larger than n.
Examples
(m = matrix(1:121, 11, 11))
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
#> [1,] 1 12 23 34 45 56 67 78 89 100 111
#> [2,] 2 13 24 35 46 57 68 79 90 101 112
#> [3,] 3 14 25 36 47 58 69 80 91 102 113
#> [4,] 4 15 26 37 48 59 70 81 92 103 114
#> [5,] 5 16 27 38 49 60 71 82 93 104 115
#> [6,] 6 17 28 39 50 61 72 83 94 105 116
#> [7,] 7 18 29 40 51 62 73 84 95 106 117
#> [8,] 8 19 30 41 52 63 74 85 96 107 118
#> [9,] 9 20 31 42 53 64 75 86 97 108 119
#> [10,] 10 21 32 43 54 65 76 87 98 109 120
#> [11,] 11 22 33 44 55 66 77 88 99 110 121
(s = st_as_stars(m))
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 1 31 61 61 91 121
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 11 0 1 FALSE [x]
#> X2 1 11 0 1 FALSE [y]
st_downsample(s, 1)
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 1 28.5 61 61 93.5 121
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 6 0 2 FALSE [x]
#> X2 1 6 0 2 FALSE [y]
st_downsample(s, 1)[[1]]
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 1 23 45 67 89 111
#> [2,] 3 25 47 69 91 113
#> [3,] 5 27 49 71 93 115
#> [4,] 7 29 51 73 95 117
#> [5,] 9 31 53 75 97 119
#> [6,] 11 33 55 77 99 121
st_downsample(s, 1, offset = 1)
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 13 37 61 61 85 109
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 5 1 2 FALSE [x]
#> X2 1 5 1 2 FALSE [y]
st_downsample(s, 1, offset = 1)[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 13 35 57 79 101
#> [2,] 15 37 59 81 103
#> [3,] 17 39 61 83 105
#> [4,] 19 41 63 85 107
#> [5,] 21 43 65 87 109
st_downsample(s, 1, offset = c(0,1))
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 12 36.5 61 61 85.5 110
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 6 0 2 FALSE [x]
#> X2 1 5 1 2 FALSE [y]
st_downsample(s, 1, offset = c(0,1))[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 12 34 56 78 100
#> [2,] 14 36 58 80 102
#> [3,] 16 38 60 82 104
#> [4,] 18 40 62 84 106
#> [5,] 20 42 64 86 108
#> [6,] 22 44 66 88 110
st_downsample(s, 1, FUN = mean)
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 7 31 55 55 79 103
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 5 0 2 FALSE [x]
#> X2 1 5 0 2 FALSE [y]
st_downsample(s, 1, FUN = mean)[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 7 29 51 73 95
#> [2,] 9 31 53 75 97
#> [3,] 11 33 55 77 99
#> [4,] 13 35 57 79 101
#> [5,] 15 37 59 81 103
st_downsample(s, 1, offset = 1, FUN = mean)
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> A1 19 43 67 67 91 115
#> dimension(s):
#> from to offset delta point x/y
#> X1 1 5 1 2 FALSE [x]
#> X2 1 5 1 2 FALSE [y]
st_downsample(s, 1, offset = c(0,1), FUN = mean)[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 18 40 62 84 106
#> [2,] 20 42 64 86 108
#> [3,] 22 44 66 88 110
#> [4,] 24 46 68 90 112
#> [5,] 26 48 70 92 114