dist_betw_arrays: Distance between rows of two arrays
In lineup2: Lining Up Two Sets of Measurements

Description Usage Arguments Details Value See Also Examples

Calculate the distances between the rows of two multi-dimensional arrays.

1	dist_betw_arrays(x, y, distance = c("rmsd", "mad", "propdiff"), cores = 1)

`x`	A numeric array.
`y`	A second numeric array, with the same dimensions as `x`.
`distance`	Indicates whether to use Euclidean distance (`"rmsd"` for root mean square difference), the mean absolute difference (`"mad"`), or the proportion of differences (`"propdiff"`).
`cores`	Number of CPU cores to use, for parallel calculations. (If `0`, use `parallel::detectCores()`.) Alternatively, this can be links to a set of cluster sockets, as produced by `parallel::makeCluster()`.

The two arrays need to have the same dimensions, except for the leading dimension (rows). They are turned into matrices by merging all but the leading dimension, and then they're sent to dist_betw_matrices().

If x and y have m and n rows, respectively, the result is an m by n matrix whose (i,j)th element is the distance between the ith row of x and the jth row of y.

dist_betw_matrices(), corr_betw_matrices()

p <- 10
k <- 6
n <- 5
m <- 3
x <- array(stats::rnorm(n*k*p), dim=c(n,k,p))
rownames(x) <- LETTERS[1:n]
y <- array(stats::rnorm(m*k*p), dim=c(m,k,p))
rownames(y) <- letters[1:m]

d <- dist_betw_arrays(x, y)