Compute cluster distance summaries

The returned tibble contains the id of the cluster pairs, with benchmark distance (d1), minimum (d2) and maximum (d3) distances between any points in the two clusters.

Usage

getClusterDists(dmat, groups, benchmarks)

Arguments

dmat

distance matrix

groups

groups resulting from clustering

benchmarks

data frame with benchmark id and group number

Value

data frame with distance information

Examples

dists <- getDists(Bikes$space1, "euclidean")
fit <- stats::hclust(dists, "ward.D2")
groups <- stats::cutree(fit, k = 4)
bm <- getBenchmarkInformation(as.matrix(dists), groups)
getClusterDists(as.matrix(dists), groups, bm)
#> # A tibble: 6 × 5
#>     grA   grB    d1     d2    d3
#>   <dbl> <dbl> <dbl>  <dbl> <dbl>
#> 1     1     2  2.69 0.397   5.76
#> 2     1     3  1.96 0.571   5.16
#> 3     1     4  2.72 0.422   6.00
#> 4     2     3  1.99 0.0643  3.82
#> 5     2     4  2.23 0.212   4.71
#> 6     3     4  1.56 0.793   3.81