plotExtremeTrees: Plot the min/max distance trees from a target tree

In treenomial: Comparison of Trees using a Tree Defining Polynomial

Plot the min/max distance trees from a target tree

Description

Plot the min/max distance trees from a target tree

Usage

plotExtremeTrees(
  target,
  trees,
  n,
  comparison = "min",
  method = c("fraction", "logDiff", "wLogDiff", "pa", "ap"),
  type = c("default", "yEvaluated", "tipLabel"),
  y,
  numThreads = -1
)

Arguments

target	the phylo object of the tree to calculate the distances to
trees	a list of phylo objects to compare with the target
n	the number of trees to find and plot
comparison	whether to find the “min” or the “max” distance trees from the target
method	method to use when calculating coefficient distances: “fraction” for two coefficient matrices A and B returns sum(abs(A-B)/(A+B)), excluding elements where both A and B are zero “logDiff” for two coefficient matrices A and B returns sum(log(1+abs(A-B)) “wLogDiff” performs the “logDiff” method with weights on the rows “pa” total pairs where the coefficient is present in one matrix and absent in the other (presence-absence) “ap” opposite comparison of pa (absence-presence)
type	one of: “real” tree distinguishing polynomials in two variables x (columns) and y (rows) “yEvaluated” tree distinguishing polynomials with y evaluated at a specified argument “tipLabel” complex coefficient polynomial that utilize binary trait tip labels on the phylo objects
y	the y value to evaluate the polynomial at when type is “yEvaluated”, ignored otherwise
numThreads	number of threads to be used, the default (-1) will use the number of cores in the machine and numThreads = 0 will only use the main thread

Value

a list of lists containing the n min/max distance trees and their distances to target

Note

• the substituted y coefficient vector only supports the “logDiff” method and the “fraction” method

• “pa” and “ap” force symmetry in the output distance matrix

Examples

library(treenomial)
library(ape)
trees <- c(rmtree(1000, 50), rmtree(10, 9))
target <- rtree(50)
minTrees <- plotExtremeTrees(target, trees, 2, comparison = "min", numThreads = 0)

treenomial documentation built on June 7, 2022, 1:08 a.m.