overlap.vs.cor.R

library(entropy)
library(ggplot2)


olaps <- function(sp1, sp2){
  sp1 <- sp1/sum(sp1)
  sp2 <- sp2/sum(sp2)
  
  plot.table <- data.frame(species = c(rep("sp1", length(sp1)), rep("sp2", length(sp2))),
                           env = c(seq(1:length(sp1)), seq(1:length(sp2))),
                           suitability = c(sp1, sp2))
  
  return(list(
    D = 1 - sum(abs(sp1 - sp2))/2,
    I = 1 - sum((sqrt(sp1) - sqrt(sp2))^2)/2,
    cor = cor(sp1, sp2, method = "spearman"),
    suitplot = qplot(env, suitability, data = plot.table, col=species, geom = "line")
  ))
  
}

# Perfect positive correlation
sp1 <- seq(0.1, 1.0, 0.001)
sp2 <- seq(0.1, 1.0, 0.001)
olaps(sp1, sp2)

# Perfect negative correlation
sp1 <- seq(0.1, 1.0, 0.001)
sp2 <- seq(1.0, 0.1, -0.001)
olaps(sp1, sp2)

# Random
sp1 <- abs(rnorm(1000))
sp2 <- abs(rnorm(1000))
olaps(sp1, sp2)