Compute distance matrix for lists of kanjimat objects

Apply kmatdist to every pair of kanjimat objects to compute the unbalanced or balanced Wasserstein distance.

Usage

kmatdistmat(
  klist,
  klist2 = NULL,
  p = 1,
  C = 0.2,
  type = c("unbalanced", "balanced")
)

Arguments

klist

a list of kanjimat objects.

klist2

an optional second list of kanjimat objects.

p, C, type

the same as for the function kmatdist.

Value

A matrix of dimension length(klist) x length(klist2) having as its \((i,j)\)-th entry the distance between klist[[i]] and klist2[[j]]. If klist2 is not provided it is assumed to be equal to klist, but the computation is more efficient as only the upper triangular part is computed and then symmetrized with diagonal zero.

See also

kmatdist, kanjidistmat

Examples

kmatdistmat(fivetrees1)
#>          [,1]     [,2]     [,3]     [,4]     [,5]
#> [1,]  0.00000 84.16072 57.59337 44.14622 44.49426
#> [2,] 84.16072  0.00000 69.80940 75.60980 86.55121
#> [3,] 57.59337 69.80940  0.00000 39.16901 66.16746
#> [4,] 44.14622 75.60980 39.16901  0.00000 44.66810
#> [5,] 44.49426 86.55121 66.16746 44.66810  0.00000
kmatdistmat(fivetrees1, fivetrees1)  # same result but slower
#>          [,1]     [,2]     [,3]     [,4]     [,5]
#> [1,]  0.00000 84.16072 57.59337 44.14622 44.49426
#> [2,] 84.16072  0.00000 69.80940 75.60980 86.55121
#> [3,] 57.59337 69.80940  0.00000 39.16901 66.16746
#> [4,] 44.14622 75.60980 39.16901  0.00000 44.66810
#> [5,] 44.49426 86.55121 66.16746 44.66810  0.00000
kmatdistmat(fivetrees1, fivetrees2)  # note the smaller values on the diagonal
#>           [,1]     [,2]     [,3]     [,4]      [,5]
#> [1,]  59.79662 84.09319 72.24528 76.97499  75.05534
#> [2,] 106.92515 58.29519 82.81458 93.28782 107.15642
#> [3,]  90.64552 90.41827 65.10304 82.02497  92.14198
#> [4,]  78.74045 88.73563 76.48978 67.54018  74.64072
#> [5,]  73.54473 88.44780 76.12515 72.28624  57.70252