Cumulative Product

Cumulative product, optionally along a single axis.

Usage

nv_cumprod(x, axis = NULL, nan_rm = FALSE)

Arguments

x

(arrayish)
Input array.

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::cumprod().

nan_rm

(logical(1))
How to handle NaN values in floating-point 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
Has the same shape and data type as the input.

Relation to base R

Both nv_cumprod() (with axis = NULL) and base::cumprod() flatten a multi-dimensional input to 1-D before accumulating, but the flatten order differs: anvl arrays are row-major (C order), so the flattened sequence iterates the last axis fastest, whereas base R uses column-major (Fortran) order. The two agree on 1-D inputs.

See also

prim_cumprod() for the underlying primitive.

Examples

x <- nv_matrix(1:6, nrow = 2)
nv_cumprod(x)              # row-major flatten, then accumulate
#> AnvlArray
#>    1
#>    3
#>   15
#>   30
#>  120
#>  720
#> [ CPUi32{6} ] 
nv_cumprod(x, axis = 1L)    # accumulate along rows
#> AnvlArray
#>   1  3  5
#>   2 12 30
#> [ CPUi32{2,3} ] 
nv_cumprod(nv_array(c(2, NaN, 3)))                # NaN propagates
#> AnvlArray
#>    2
#>  nan
#>  nan
#> [ CPUf32{3} ] 
nv_cumprod(nv_array(c(2, NaN, 3)), nan_rm = TRUE) # NaN treated as 1
#> AnvlArray
#>  2
#>  2
#>  6
#> [ CPUf32{3} ]