index.csv

puranius.tre

(1,(2,((3,((4,5),(6,(7,(8,(9,10)))))),(11,(12,(13,((14,(15,16)),(17,(18,(19,20))))))))));

Vane_Wright_Index.R

library(ape)
library(phangorn)

##This is the tree who I'll want to calculate Vane-Wright index
##
tree <- read.tree("puranius.tre")
plot(tree)

##Now a read the table
##This table have terminal and the number of nodes who belong each terminal 
##Index I

data <- read.table("index.csv",header = T, sep=",")
data
##I values
data[,2]

##Summatory of all I values
total.I <- as.numeric(sum(data[,2]))

##Now the Q index is calculate
##Total I value / each I value

Q <- total.I/data$I
data$Q <- Q
data

##Foun the minimum Q value
min.Q <- min(data$Q)

##Whith the minimum Q value, the W index is calculate
## each Q value / minimum Q value

W <- data$Q/min.Q
data$W <- W
data

#Here, I create the basic function.

vane91 <- function(x){
  data <- x
  total.I <- as.numeric(sum(data[,2]))
  Q <- total.I/data[,2]
  data$Q <- Q
  min.Q <- min(data$Q)
  W <- data$Q/min.Q
  data$W <- W
  a <- 0
  l <- length(data[,1])
  
  #Find the highest W value and his terminal
  for (i in seq(1:l)){
    if (data[i,4]>a){
      a <- data[i,4]
      n <- i
    }
  }
  print(data)
  
  print("The terminal which highest W values is:")
  print(data[n,1])
  print("With W value =")
  print(a)
}

vane91(data)

##Remember vane91 use a data frame with just 2 columns (Terminals first and I index second)