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Min Reduction

Source: R/api.R, R/api-generics.R
nv_reduce_min.Rd

Finds the minimum of array elements along the specified axes.

Usage

nv_reduce_min(x, axes = NULL, drop = TRUE, nan_rm = FALSE)

Arguments

x

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

axes

(integer() | NULL)
Axes to reduce over. Negative values count from the end, i.e. -1 refers to the last axis. If NULL (default), reduces over all axes.

drop

(logical(1))
Whether to drop the reduced axes: removed from the output shape if TRUE, set to 1 if FALSE.

nan_rm

(logical(1))
How to handle NaN values in float inputs. If FALSE (default), NaN propagates. If TRUE, NaN values are skipped.

Value

(arrayish)
Has the input's data type. The shape is the input's with the reduced axes removed (drop = TRUE) or set to 1 (drop = FALSE).

The min() generic

min() reduces over all axes and, like base::min(), takes several data arguments: min(x, y) is the smallest element of both arrays. na.rm becomes nan_rm. Beyond base R, named arguments are passed on, so min(x, axes = 1L) reduces a single axis – but only when x is the only data argument.

See also

prim_reduce_min() for the underlying primitive.

Examples

x <- nv_matrix(1:6, nrow = 2)
# no axes given: reduce over all of them
nv_reduce_min(x)
#> AnvlArray
#>  1
#> [ CPUi32{} ] 

# reducing axis 1 removes it, drop = FALSE keeps it at size 1
nv_reduce_min(x, axes = 1L)
#> AnvlArray
#>  1
#>  3
#>  5
#> [ CPUi32{3} ] 
nv_reduce_min(x, axes = 1L, drop = FALSE)
#> AnvlArray
#>  1 3 5
#> [ CPUi32{1,3} ] 

# negative axes count from the end
nv_reduce_min(x, axes = -1L)
#> AnvlArray
#>  1
#>  2
#> [ CPUi32{2} ] 

# NaN propagates unless nan_rm = TRUE
nv_reduce_min(nv_array(c(1, NaN, 3)))
#> AnvlArray
#>  nan
#> [ CPUf32{} ] 
nv_reduce_min(nv_array(c(1, NaN, 3)), nan_rm = TRUE)
#> AnvlArray
#>  1
#> [ CPUf32{} ]