Get the distance matrices from objects fitted with the function
clustering()
. This is especially useful to get distance matrices
from several objects to be further analyzed using pairs_mantel()
.
Arguments
- ...
Object(s) of class
clustering
.]- digits
The number of significant figures. Defaults to
2
.
Author
Tiago Olivoto tiagoolivoto@gmail.com
Examples
# \donttest{
library(metan)
d <- data_ge2 %>%
mean_by(GEN) %>%
column_to_rownames("GEN") %>%
clustering()
get_dist(d)
#> $d
#> H1 H10 H11 H12 H13 H2 H3 H4 H5 H6 H7 H8
#> H1 0.00 49.24 36.63 55.94 39.76 22.00 28.60 34.48 42.49 10.77 24.96 50.59
#> H10 49.24 0.00 13.73 8.30 42.95 48.85 29.18 46.05 48.06 51.34 26.89 8.77
#> H11 36.63 13.73 0.00 20.00 40.07 40.23 16.18 41.01 45.28 40.25 13.59 14.45
#> H12 55.94 8.30 20.00 0.00 49.06 56.01 33.96 52.93 54.39 58.52 32.68 8.59
#> H13 39.76 42.95 40.07 49.06 0.00 20.76 48.04 9.11 6.78 32.52 40.82 49.88
#> H2 22.00 48.85 40.23 56.01 20.76 0.00 40.93 14.18 22.03 12.71 34.51 53.61
#> H3 28.60 29.18 16.18 33.96 48.04 40.93 0.00 46.77 52.96 36.07 7.93 26.52
#> H4 34.48 46.05 41.01 52.93 9.11 14.18 46.77 0.00 8.67 26.16 39.70 52.51
#> H5 42.49 48.06 45.28 54.39 6.78 22.03 52.96 8.67 0.00 34.14 45.65 55.21
#> H6 10.77 51.34 40.25 58.52 32.52 12.71 36.07 26.16 34.14 0.00 30.85 54.36
#> H7 24.96 26.89 13.59 32.68 40.82 34.51 7.93 39.70 45.65 30.85 0.00 26.25
#> H8 50.59 8.77 14.45 8.59 49.88 53.61 26.52 52.51 55.21 54.36 26.25 0.00
#> H9 63.45 16.57 27.13 9.65 58.17 64.91 39.28 61.89 63.28 66.73 39.22 13.19
#> H9
#> H1 63.45
#> H10 16.57
#> H11 27.13
#> H12 9.65
#> H13 58.17
#> H2 64.91
#> H3 39.28
#> H4 61.89
#> H5 63.28
#> H6 66.73
#> H7 39.22
#> H8 13.19
#> H9 0.00
#>
#> attr(,"class")
#> [1] "clustering"
# }