Cut out a slice from an array. The resulting slice may be single- or multidimensional. The function is intended for arrays of class "power_array", and makes sure that the resulting array is of class power_array and keeps and, where needed, updates the object's attributes. These attributes are needed for various functions in the powergrid package to work well.
Arguments
- x
An array, in most common use cases an array of class
power_array, but may be any array with named dimensions.- slicer
A list whose named elements define at which dimension (the list element names), at which values (the list element values) a slice is taken from
power_array. Default NULL returns the unchanged array.
Value
An array with reduced dimensions as given by slicer. Note
that, relative to a standard array, some additional attributes are passed
to be used in the functions in package powergrid
Details
Internally, indexing ([) is used, but the implementation in
ArraySlicer is very flexible allowing for any number of dimensions in any
order in the slicer argument. The resulting slice is always an
array, also if only one dimension is left. dimnames are kept
intact.
See also
PowerGrid, [.power_array for reducing the dimensions of
an array of class power_array using [-indexing.
Examples
sse_pars = list(
n = seq(from = 20, to = 60, by = 5),
delta = seq(from = 0.5, to = 1.5, by = 0.2),
sd = seq(.1, .9, .2),
alpha = c(.05, .025, .1)) # a 4-dimensional grid
PowFun <- function(n, delta, sd, alpha){
ptt = power.t.test(n = n/2, delta = delta, sd = sd,
sig.level = alpha)
return(ptt$power)
}
power_array = PowerGrid(pars = sse_pars, fun = PowFun, n_iter = NA)
## cut out a 2-dimensional plane:
ArraySlicer(power_array,
slicer = list(alpha = .1, sd = .9))
#> delta
#> n 0.5 0.7 0.9 1.1 1.3 1.5
#> 20 0.3266194 0.5113619 0.6935575 0.8372357 0.9278669 0.9736115
#> 25 0.3832766 0.5955822 0.7824609 0.9064024 0.9683517 0.9916914
#> 30 0.4363362 0.6675901 0.8477025 0.9473643 0.9865455 0.9974895
#> 35 0.4859190 0.7284933 0.8946573 0.9709510 0.9944270 0.9992664
#> 40 0.5321084 0.7795046 0.9279025 0.9842242 0.9977416 0.9997915
#> 45 0.5749929 0.8218632 0.9511155 0.9915513 0.9991018 0.9999421
#> 50 0.6146775 0.8567685 0.9671303 0.9955305 0.9996486 0.9999843
#> 55 0.6512851 0.8853366 0.9780638 0.9976612 0.9998645 0.9999958
#> 60 0.6849538 0.9085756 0.9854597 0.9987880 0.9999484 0.9999989
#> Array of class `power_array` created using
#> PowerGrid.
#> Resulting dimensions:
#> n, delta.
#>
## Note that above, the dimension levels are called as numeric values, so the
## following works as well:
ArraySlicer(power_array,
slicer = list(alpha = 0.1, sd = 0.9))
#> delta
#> n 0.5 0.7 0.9 1.1 1.3 1.5
#> 20 0.3266194 0.5113619 0.6935575 0.8372357 0.9278669 0.9736115
#> 25 0.3832766 0.5955822 0.7824609 0.9064024 0.9683517 0.9916914
#> 30 0.4363362 0.6675901 0.8477025 0.9473643 0.9865455 0.9974895
#> 35 0.4859190 0.7284933 0.8946573 0.9709510 0.9944270 0.9992664
#> 40 0.5321084 0.7795046 0.9279025 0.9842242 0.9977416 0.9997915
#> 45 0.5749929 0.8218632 0.9511155 0.9915513 0.9991018 0.9999421
#> 50 0.6146775 0.8567685 0.9671303 0.9955305 0.9996486 0.9999843
#> 55 0.6512851 0.8853366 0.9780638 0.9976612 0.9998645 0.9999958
#> 60 0.6849538 0.9085756 0.9854597 0.9987880 0.9999484 0.9999989
#> Array of class `power_array` created using
#> PowerGrid.
#> Resulting dimensions:
#> n, delta.
#>
## They can be called by their actual character values as well:
ArraySlicer(power_array,
slicer = list(alpha = '0.1', sd = '0.9'))
#> delta
#> n 0.5 0.7 0.9 1.1 1.3 1.5
#> 20 0.3266194 0.5113619 0.6935575 0.8372357 0.9278669 0.9736115
#> 25 0.3832766 0.5955822 0.7824609 0.9064024 0.9683517 0.9916914
#> 30 0.4363362 0.6675901 0.8477025 0.9473643 0.9865455 0.9974895
#> 35 0.4859190 0.7284933 0.8946573 0.9709510 0.9944270 0.9992664
#> 40 0.5321084 0.7795046 0.9279025 0.9842242 0.9977416 0.9997915
#> 45 0.5749929 0.8218632 0.9511155 0.9915513 0.9991018 0.9999421
#> 50 0.6146775 0.8567685 0.9671303 0.9955305 0.9996486 0.9999843
#> 55 0.6512851 0.8853366 0.9780638 0.9976612 0.9998645 0.9999958
#> 60 0.6849538 0.9085756 0.9854597 0.9987880 0.9999484 0.9999989
#> Array of class `power_array` created using
#> PowerGrid.
#> Resulting dimensions:
#> n, delta.
#>
## (compare with dimnames(power_array))
## the following does not work:
if (FALSE) { # \dontrun{
ArraySlicer(power_array,
slicer = list(alpha = '.1', sd = '.9'))
} # }
##
## Cut out multiple levels from one dimension
ArraySlicer(power_array,
slicer = list(alpha = .1, sd = c(.9, .7)))
#> , , sd = 0.9
#>
#> delta
#> n 0.5 0.7 0.9 1.1 1.3 1.5
#> 20 0.3266194 0.5113619 0.6935575 0.8372357 0.9278669 0.9736115
#> 25 0.3832766 0.5955822 0.7824609 0.9064024 0.9683517 0.9916914
#> 30 0.4363362 0.6675901 0.8477025 0.9473643 0.9865455 0.9974895
#> 35 0.4859190 0.7284933 0.8946573 0.9709510 0.9944270 0.9992664
#> 40 0.5321084 0.7795046 0.9279025 0.9842242 0.9977416 0.9997915
#> 45 0.5749929 0.8218632 0.9511155 0.9915513 0.9991018 0.9999421
#> 50 0.6146775 0.8567685 0.9671303 0.9955305 0.9996486 0.9999843
#> 55 0.6512851 0.8853366 0.9780638 0.9976612 0.9998645 0.9999958
#> 60 0.6849538 0.9085756 0.9854597 0.9987880 0.9999484 0.9999989
#>
#> , , sd = 0.7
#>
#> delta
#> n 0.5 0.7 0.9 1.1 1.3 1.5
#> 20 0.4570025 0.6935575 0.8685265 0.9584072 0.9904886 0.9984479
#> 25 0.5350629 0.7824609 0.9295853 0.9847885 0.9978551 0.9998053
#> 30 0.6039964 0.8477025 0.9632142 0.9946389 0.9995396 0.9999770
#> 35 0.6643634 0.8946573 0.9811787 0.9981668 0.9999051 0.9999974
#> 40 0.7168148 0.9279025 0.9905394 0.9993888 0.9999811 0.9999997
#> 45 0.7620649 0.9511155 0.9953169 0.9998006 0.9999963 1.0000000
#> 50 0.8008528 0.9671303 0.9977127 0.9999361 0.9999993 1.0000000
#> 55 0.8339099 0.9780638 0.9988960 0.9999799 0.9999999 1.0000000
#> 60 0.8619365 0.9854597 0.9994728 0.9999937 1.0000000 1.0000000
#>
#> Array of class `power_array` created using
#> PowerGrid.
#> Resulting dimensions:
#> n, delta, sd.
#>