plotExtremeTrees {treenomial}

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)