This function runs ape::dist.nodes() with some additional filtering and sorting. By default,
it returns distances between every pair of non-nested clades, i.e. every pair of collateral (non-lineal) nodes
including terminals and internal nodes.
Arguments
- tree
A phylogeny of class
"phylo".- lineal
Logical indicating whether to retain distances for pairs of nodes that are lineal ancestors/descendants. If
FALSE(the default), these are set toNA, retaining values only for node pairs that are collateral kin.- edges
Logical indicating whether to return a distance matrix with a row for every edge in
tree. IfTRUE(the default), rows/columns of the result correspond totree$edge. IfFALSE, rows/columns correspond to nodes as inape::dist.nodes().
Examples
clade_dist(ape::rtree(10))
#> 12 13 14 1 15 2 3 4
#> 12 NA NA NA NA NA NA NA NA
#> 13 NA NA NA NA NA NA NA NA
#> 14 NA NA NA NA NA NA NA 1.6690957
#> 1 NA NA NA NA 0.7929678 1.323180 1.488792 2.4106172
#> 15 NA NA NA 0.7929678 NA NA NA 1.7205420
#> 2 NA NA NA 1.3231803 NA NA 1.226036 2.2507544
#> 3 NA NA NA 1.4887917 NA 1.226036 NA 2.4163658
#> 4 NA NA 1.669096 2.4106172 1.7205420 2.250754 2.416366 NA
#> 16 NA 0.2271871 1.207727 1.9492483 1.2591730 1.789385 1.954997 0.9157431
#> 17 NA 0.4527496 1.433289 2.1748108 1.4847355 2.014948 2.180559 1.1413056
#> 5 NA 0.7535804 1.734120 2.4756416 1.7855663 2.315779 2.481390 1.4421364
#> 6 NA 1.0892152 2.069755 2.8112764 2.1212012 2.651414 2.817025 1.7777712
#> 7 NA 0.7062116 1.686751 2.4282728 1.7381976 2.268410 2.434021 1.3947676
#> 18 1.167491 1.3634476 2.343987 3.0855088 2.3954335 2.925646 3.091257 2.0520036
#> 8 1.873925 2.0698814 3.050421 3.7919426 3.1018674 3.632080 3.797691 2.7584374
#> 19 2.116067 2.3120242 3.292564 4.0340854 3.3440101 3.874223 4.039834 3.0005802
#> 9 2.296406 2.4923629 3.472903 4.2144241 3.5243489 4.054561 4.220173 3.1809189
#> 10 2.332967 2.5289240 3.509464 4.2509852 3.5609100 4.091122 4.256734 3.2174800
#> 16 17 5 6 7 18 8 19
#> 12 NA NA NA NA NA 1.167491 1.873925 2.116067
#> 13 0.2271871 0.4527496 0.7535804 1.0892152 0.7062116 1.363448 2.069881 2.312024
#> 14 1.2077267 1.4332893 1.7341201 2.0697549 1.6867513 2.343987 3.050421 3.292564
#> 1 1.9492483 2.1748108 2.4756416 2.8112764 2.4282728 3.085509 3.791943 4.034085
#> 15 1.2591730 1.4847355 1.7855663 2.1212012 1.7381976 2.395434 3.101867 3.344010
#> 2 1.7893855 2.0149480 2.3157788 2.6514136 2.2684100 2.925646 3.632080 3.874223
#> 3 1.9549969 2.1805594 2.4813902 2.8170250 2.4340214 3.091257 3.797691 4.039834
#> 4 0.9157431 1.1413056 1.4421364 1.7777712 1.3947676 2.052004 2.758437 3.000580
#> 16 NA NA NA NA NA 1.198721 1.905155 2.147298
#> 17 NA NA NA NA 0.7045871 1.424284 2.130718 2.372860
#> 5 NA NA NA 0.9372964 1.0054179 1.725115 2.431548 2.673691
#> 6 NA NA 0.9372964 NA 1.3410527 2.060749 2.767183 3.009326
#> 7 NA 0.7045871 1.0054179 1.3410527 NA 1.677746 2.384180 2.626322
#> 18 1.1987212 1.4242837 1.7251145 2.0607493 1.6777457 NA NA NA
#> 8 1.9051550 2.1307176 2.4315484 2.7671832 2.3841796 NA NA 1.655010
#> 19 2.1472978 2.3728603 2.6736911 3.0093259 2.6263223 NA 1.655010 NA
#> 9 2.3276365 2.5531991 2.8540299 3.1896647 2.8066611 NA 1.835349 NA
#> 10 2.3641976 2.5897602 2.8905910 3.2262258 2.8432222 NA 1.871910 NA
#> 9 10
#> 12 2.2964062 2.3329673
#> 13 2.4923629 2.5289240
#> 14 3.4729026 3.5094637
#> 1 4.2144241 4.2509852
#> 15 3.5243489 3.5609100
#> 2 4.0545613 4.0911225
#> 3 4.2201728 4.2567339
#> 4 3.1809189 3.2174800
#> 16 2.3276365 2.3641976
#> 17 2.5531991 2.5897602
#> 5 2.8540299 2.8905910
#> 6 3.1896647 3.2262258
#> 7 2.8066611 2.8432222
#> 18 NA NA
#> 8 1.8353492 1.8719103
#> 19 NA NA
#> 9 NA 0.3972386
#> 10 0.3972386 NA