Cumulative Maximum

Running maximum, optionally along a single axis.

Usage

nv_cummax(x, axis = NULL, indices = FALSE, nan_rm = FALSE)

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 accumulate. 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::cummax().

indices

(logical(1))
If FALSE (default), returns the running-maximum array. If TRUE, returns list(values = ..., indices = ...) where indices is the index of the last occurrence of the running maximum at each position, of the default integer data type (see default_dtypes()). When axis = NULL, indices refer to the flattened input.

nan_rm

(logical(1))
How to handle NaN values in float inputs. If FALSE (default), NaN propagates forward from its first occurrence. If TRUE, NaN is treated as the identity element of the cumulative op (0 for sum, 1 for prod, -Inf / +Inf for max / min) and contributes nothing to the running value.

Value

(arrayish | named list of two arrayish)
One array when indices = FALSE, a named list of values and indices when indices = TRUE. The values have the input's data type and the indices the default integer data type; both have the input's shape when axis is given, and are 1-D of length prod(shape(x)) when axis is NULL.

See also

prim_cummax() for the underlying primitive.

Examples

# the running maximum keeps the data type; the indices are the default integer
x <- nv_matrix(c(3, 1, 4, 1, 5, 9), nrow = 2)
nv_cummax(x)
#> AnvlArray
#>  3
#>  3
#>  4
#>  4
#>  5
#>  9
#> [ CPUf32{6} ] 
nv_cummax(x, axis = 1L)
#> AnvlArray
#>  3 4 5
#>  3 4 9
#> [ CPUf32{2,3} ] 
nv_cummax(x, axis = 1L, indices = TRUE)
#> $values
#> AnvlArray
#>  3 4 5
#>  3 4 9
#> [ CPUf32{2,3} ] 
#> 
#> $indices
#> AnvlArray
#>  1 1 1
#>  1 1 2
#> [ CPUi32{2,3} ] 
#> 
nv_cummax(nv_array(c(1, NaN, 3)))                # NaN propagates
#> AnvlArray
#>    1
#>  nan
#>  nan
#> [ CPUf32{3} ] 
nv_cummax(nv_array(c(1, NaN, 3)), nan_rm = TRUE) # NaN skipped
#> AnvlArray
#>  1
#>  1
#>  3
#> [ CPUf32{3} ]