Sort

Sorts an array along an axis.

You can also use sort() directly.

Usage

nv_sort(x, axis = NULL, decreasing = FALSE, stable = FALSE)

# S3 method for class 'AnvlArray'
sort(x, decreasing = FALSE, ..., axis = NULL)

Arguments

x

(arrayish)
One input. Can be any data type. An R value materializes at its default data type.

axis

(integer(1) | NULL)
Axis along which to sort. Negative values count from the end, i.e. -1 refers to the last axis. If NULL (default), the input is first flattened to a 1-D array, like base::sort().

decreasing

(logical(1))
If TRUE, sort in decreasing order.

stable

(logical(1))
If TRUE, the sort is stable: equal values keep their original relative order along axis. Default FALSE. Stability is only observable for floats when -0 / +0 or -NaN / +NaN are mixed (they compare equal under the total order used here); for distinct values the result is identical either way.

...

Passed on to nv_sort(), e.g. stable.

Value

(arrayish)
Has the input's shape and data type.

NaN handling

NaN values sort to the end (ascending) or beginning (descending), regardless of sign. +0 and -0 compare equal.

The sort() generic

Like base::sort(), nv_sort() with axis = NULL flattens a multi-axis array into one sorted vector, so sort() on an anvl array agrees with base R (the flatten order does not matter once the elements are sorted). It differs in one respect: base R drops NA by default, whereas NaN is kept and sorted to the end. Pass axis to sort each slice along one axis instead, which keeps the shape.

See also

prim_sort() for the underlying primitive, nv_order(), nv_top_k(), nv_median(), nv_which_max(), nv_which_min().

Examples

# sorting moves elements, so the data type and shape stay
x <- nv_array(c(3, 1, 4, 1, 5, 9, 2, 6))
nv_sort(x)
#> AnvlArray
#>  1
#>  1
#>  2
#>  3
#>  4
#>  5
#>  6
#>  9
#> [ CPUf32{8} ] 
sort(x) # via the S3 generic
#> AnvlArray
#>  1
#>  1
#>  2
#>  3
#>  4
#>  5
#>  6
#>  9
#> [ CPUf32{8} ] 
nv_sort(x, decreasing = TRUE)
#> AnvlArray
#>  9
#>  6
#>  5
#>  4
#>  3
#>  2
#>  1
#>  1
#> [ CPUf32{8} ] 

m <- nv_matrix(c(3, 1, 5, 2, 4, 0), nrow = 2, byrow = TRUE)
nv_sort(m) # one sorted vector, like base R
#> AnvlArray
#>  0
#>  1
#>  2
#>  3
#>  4
#>  5
#> [ CPUf32{6} ] 
nv_sort(m, axis = 2L) # each row sorted, shape kept
#> AnvlArray
#>  1 3 5
#>  0 2 4
#> [ CPUf32{2,3} ]