library(iNEXT)
library(SpadeR)
library(knitr)
library(dplyr)
library(ggplot2)
library(bipartite)

knitr::kable(matrix)
t <- seq (1,1000)

interp-extrap <- iNEXT(matrix, q = 0, datatype = "abundance", size = t)
interp-extra

par(mar=c(10,10,10,10), las = 1, xpd=TRUE)

plotweb(matrix, method = "normal", empty = TRUE, labsize = 1.5, ybig =3,  y.width.low = 0.1, 
        y.width.high = 0.1, low.spacing = NULL, high.spacing = NULL,
        arrow="no",  col.interaction="grey80", col.high = "orange1", 
        col.low="darkgreen",  bor.col.interaction ="black", bor.col.high="black", 
        bor.col.low="black", high.lablength = NULL, low.lablength = NULL,
        sequence=NULL, low.abun=NULL, low.abun.col="green", 
        bor.low.abun.col ="black", high.abun=NULL, high.abun.col="red", 
        bor.high.abun.col="black", text.rot=90, text.high.col="black", 
        text.low.col="black", adj.high=NULL, adj.low=NULL, plot.axes =FALSE,
        low.y=-1.2, high.y=2.3, add=FALSE, y.lim=c(-2,3.4), x.lim=c(0,3.5), low.plot=TRUE, 
        high.plot=TRUE, high.xoff = 0, low.xoff = 0, high.lab.dis = NULL, 
        low.lab.dis = NULL, abuns.type="additional")

visweb(matrix, prednames = T, preynames = T, labsize =1)

all_indices<-networklevel(matrix)
all_indices

indices_sps_aves<-specieslevel(matrix)[[1]] 
indices_sps_animals
indices_sps_plantas<-specieslevel(matrix)[[2]]
indices_sps_plants

mod.Red.1<-computeModules(web=matrix,steps=1E8)
mod.Red.2<-computeModules(web=matrix,steps=1E8)
mod.Red.3<-computeModules(web=matrix,steps=1E8)
mod.Red.4<-computeModules(web=matrix,steps=1E8)
mod.Red.5<-computeModules(web=matrix,steps=1E8)
mod.Red.6<-computeModules(web=matrix,steps=1E8)
mod.Red.7<-computeModules(web=matrix,steps=1E8)
mod.Red.8<-computeModules(web=matrix,steps=1E8)
mod.Red.9<-computeModules(web=matrix,steps=1E8)
mod.Red.10<-computeModules(web=matrix,steps=1E8)
mod.Red.11<-computeModules(web=matrix,steps=1E8)
mod.Red.12<-computeModules(web=matrix,steps=1E8)
mod.Red.13<-computeModules(web=matrix,steps=1E8)
mod.Red.14<-computeModules(web=matrix,steps=1E8)
mod.Red.15<-computeModules(web=matrix,steps=1E8)
mod.Red.16<-computeModules(web=matrix,steps=1E8)
mod.Red.17<-computeModules(web=matrix,steps=1E8)
mod.Red.18<-computeModules(web=matrix,steps=1E8)
mod.Red.19<-computeModules(web=matrix,steps=1E8)
mod.Red.20<-computeModules(web=matrix,steps=1E8)

mod.Red.1@likelihood
mod.Red.2@likelihood
mod.Red.3@likelihood
mod.Red.4@likelihood
mod.Red.5@likelihood
mod.Red.6@likelihood
mod.Red.7@likelihood
mod.Red.8@likelihood
mod.Red.9@likelihood
mod.Red.10@likelihood
mod.Red.11@likelihood
mod.Red.12@likelihood
mod.Red.13@likelihood
mod.Red.14@likelihood
mod.Red.15@likelihood
mod.Red.16@likelihood
mod.Red.17@likelihood
mod.Red.18@likelihood
mod.Red.19@likelihood
mod.Red.20@likelihood

printoutModuleInformation(mod.Red.19)

plotModuleWeb(mod.Red.19,rank=TRUE, labsize = 0.9)

nulos <- nullmodel(matrix, N=10, method=1)
indice.nulos <- unlist(sapply(nulos, networklevel, index="connectance")) 
indice.nulos

obs 
mean(indice.nulos) 
sd(indice.nulos) 
(z <- (obs - mean(index.nulls))/sd(index.nulls)) 

plot(density(indice.nulos), xlim=c(min(obs, min(indice.nulos)), max(obs, max(indice.nulos))), 
     main="CObserved and Expected values", xlab = "connectance", ylab = "Density")
abline(v=obs, col="red", lwd=3)