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Mean

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

Computes the arithmetic mean along the specified axes. You can also use mean().

Usage

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

# S3 method for class 'AnvlArray'
mean(x, trim = 0, na.rm = FALSE, ..., axes = NULL, drop = TRUE)

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.

trim

Currently not supported.

na.rm

Forwarded to nv_mean()'s nan_rm argument.

...

No additional arguments.

Value

(arrayish)
Has the input's data type where that is a float, and the default float data type (see default_dtypes()) otherwise. The shape is the input's with the reduced axes removed (drop = TRUE) or set to 1 (drop = FALSE).

See also

nv_reduce_sum()

Examples

x <- nv_matrix(1:6, nrow = 2)
# an integer input is averaged at the default float data type
nv_mean(x)
#> AnvlArray
#>  3.5000
#> [ CPUf32{} ] 

# a float input keeps its own, whatever the default float is
nv_mean(nv_array(c(1, 2), dtype = "f64"))
#> AnvlArray
#>  1.5000
#> [ CPUf64{} ] 

# reducing axis 1 removes it, drop = FALSE keeps it at size 1
nv_mean(x, axes = 1L)
#> AnvlArray
#>  1.5000
#>  3.5000
#>  5.5000
#> [ CPUf32{3} ] 
nv_mean(x, axes = 1L, drop = FALSE)
#> AnvlArray
#>  1.5000 3.5000 5.5000
#> [ CPUf32{1,3} ] 

# NaN propagates unless nan_rm = TRUE
nv_mean(nv_array(c(1, NaN, 3)))
#> AnvlArray
#>  nan
#> [ CPUf32{} ] 
nv_mean(nv_array(c(1, NaN, 3)), nan_rm = TRUE)
#> AnvlArray
#>  2
#> [ CPUf32{} ]