Collapse array
Usage
collapse(x, keep, ...)
# S3 method for class 'array'
collapse(
x,
keep,
average = TRUE,
transform = c("asis", "10log10", "square", "sqrt"),
...
)Arguments
- x
A numeric multi-mode tensor (array), without
NA- keep
Which dimension to keep
- ...
passed to other methods
- average
collapse to sum or mean
- transform
transform on the data before applying collapsing; choices are
'asis'(no change),'10log10'(used to calculate decibel),'square'(sum-squared),'sqrt'(square-root and collapse)
Examples
# Set ncores = 2 to comply to CRAN policy. Please don't run this line
ravetools_threads(n_threads = 2L)
# Example 1
x = matrix(1:16, 4)
# Keep the first dimension and calculate sums along the rest
collapse(x, keep = 1)
#> [1] 7 8 9 10
rowMeans(x) # Should yield the same result
#> [1] 7 8 9 10
# Example 2
x = array(1:120, dim = c(2,3,4,5))
result = collapse(x, keep = c(3,2))
compare = apply(x, c(3,2), mean)
sum(abs(result - compare)) # The same, yield 0 or very small number (1e-10)
#> [1] 5.684342e-14
# \donttest{
ravetools_threads(n_threads = -1)
# Example 3 (performance)
# Small data, no big difference
x = array(rnorm(240), dim = c(4,5,6,2))
microbenchmark::microbenchmark(
result = collapse(x, keep = c(3,2)),
compare = apply(x, c(3,2), mean),
times = 1L, check = function(v){
max(abs(range(do.call('-', v)))) < 1e-10
}
)
#> Unit: microseconds
#> expr min lq mean median uq max neval
#> result 402.680 402.680 402.680 402.680 402.680 402.680 1
#> compare 626.738 626.738 626.738 626.738 626.738 626.738 1
# large data big difference
x = array(rnorm(prod(300,200,105)), c(300,200,105,1))
microbenchmark::microbenchmark(
result = collapse(x, keep = c(3,2)),
compare = apply(x, c(3,2), mean),
times = 1L , check = function(v){
max(abs(range(do.call('-', v)))) < 1e-10
})
#> Unit: milliseconds
#> expr min lq mean median uq max neval
#> result 19.78243 19.78243 19.78243 19.78243 19.78243 19.78243 1
#> compare 196.17184 196.17184 196.17184 196.17184 196.17184 196.17184 1
# }