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plot_functions_BDC_model.R
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plot_functions_BDC_model.R
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# library(latex2exp)
library(HDInterval)
library(scales)
# functions to plot results of BDC model (Silvestro, Warnock et al. 2018 Nature Comm.)
### SKYLINE PLOTS
# PLOT SPECIATION MODE PREVALENCE
plot_polygon <- function(x,t1,t2,color="#3dab3c"){
for (lev in seq(0.95,0.10, length.out =30)){
hpd = hdi(x,lev)
polygon(x=-c(t1,t1,t2,t2), y = c(as.numeric(hpd[1:2]),rev(as.numeric(hpd[1:2]))),border=F,col=alpha(color,0.075))
}
}
plot_speciation_mode <- function(f,time_bins,Ymax=0,title=""){
tbl = read.table(f,h=T)
# tbl = tbl[50:dim(tbl)[1],]
indx_lambda_foss = grep("lambda_",colnames(tbl))
indx_lambda_tree = grep("tree_sp",colnames(tbl))
indx_mu_foss = grep("mu_",colnames(tbl))
indx_mu_tree = grep("tree_ex",colnames(tbl))
dL = tbl[indx_lambda_foss]- 2*tbl[indx_lambda_tree]
dL2= tbl[indx_lambda_foss]- tbl[indx_lambda_tree]
time_bins = sort(c(0,time_bins))[1:length(indx_lambda_foss)]
time_bins = rev(sort(time_bins))
x = c(1,2,3)
par(mfrow=c(3,2))
# speciation mode
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(-Ymax,Ymax),type="n",
ylab='Budding vs anagenetic speciation (lambda* - 2 lambda)',xlab="Time (Ma)",
main="Speciation mode")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),type="n",ylim=c(min(dL),max(dL)),
ylab='Budding vs anagenetic speciation (lambda* - 2 lambda)',xlab="Time (Ma)",
main="Speciation mode")
}
abline(h=0,lty=2)
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(dL[,t-1])
plot_polygon(x,t1,t2,color="#3dab3c")
}
# anagenetic + bifurcation mode
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,Ymax),type="n",
ylab='Bifurcation + anagenetic speciation (lambda* - lambda)',xlab="Time (Ma)")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),type="n",ylim=c(0,max(dL2)),
ylab='Bifurcation + anagenetic speciation (lambda* - lambda',xlab="Time (Ma)")
}
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(dL2[,t-1])
plot_polygon(x,t1,t2,color="#3dab3c")
}
# speciation rate
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,Ymax),type="n",
ylab='lambda*',xlab="Time (Ma)",main="Fossil estimates")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),type="n",ylim=c(0,max(tbl[indx_lambda_foss])),
ylab='lambda*',xlab="Time (Ma)",main="Fossil estimates")
}
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(tbl[indx_lambda_foss][,t-1])
plot_polygon(x,t1,t2,color="#084594")
}
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,Ymax),type="n",
ylab='lambda',xlab="Time (Ma)",main="Phylogenetic estimates")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,max(tbl[indx_lambda_foss])),type="n",
ylab='lambda',xlab="Time (Ma)",main="Phylogenetic estimates")
}
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(tbl[indx_lambda_tree][,t-1])
plot_polygon(x,t1,t2,color="#3182bd")
}
# extinction rate
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,Ymax),type="n",ylab='mu*',xlab="Time (Ma)")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),type="n",ylab='mu*',xlab="Time (Ma)",ylim=c(0,max(tbl[indx_mu_foss])))
}
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(tbl[indx_mu_foss][,t-1])
plot_polygon(x,t1,t2,color="#b30000")
}
if (Ymax){
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),ylim=c(0,Ymax),type="n",ylab='mu',xlab="Time (Ma)")
}else{
plot(mean(x),xlim=c(-max(time_bins),-min(time_bins)),type="n",ylab='mu',xlab="Time (Ma)",ylim=c(0,max(tbl[indx_mu_foss])))
}
for (t in 2:length(time_bins)){
t1=time_bins[t-1]
t2= time_bins[t]
x=as.numeric(tbl[indx_mu_tree][,t-1])
plot_polygon(x,t1,t2,color="#e34a33")
}
}
# pdf("your_path/PyRate_github/example_files/BDC_model/Ferns_BDCskyline_rates.pdf",width=8,height=12 )
# time_bins = rev(c(0,25,50,75,100,125,150,175))
# f="your_path/PyRate_github/example_files/BDC_model/Ferns_BDCskyline_mcmc.log"
# plot_speciation_mode(f,time_bins,0.03)
# dev.off()
# GET PLOTS AND P-VALUS FOR SKYLINE INDEPENDENT MODEL
plot_fossil_phylo_skyline <- function(mcmc_file,burnin=0.2,maxR_arg=0){
t = read.table(mcmc_file,h=T)
burnin=round(dim(t)[1]*0.25)
col_lambda = grep("lambda_",colnames(t))
col_mu = grep("mu_",colnames(t))
col_tree_sp = grep("tree_sp",colnames(t))
col_tree_ex = grep("tree_ex",colnames(t))
for (ind in 1:length(col_lambda)){
lambda_0 = t[burnin:dim(t)[1], col_lambda[ind] ]
mu_0 = t[burnin:dim(t)[1], col_mu[ind] ]
tree_sp = t[burnin:dim(t)[1], col_tree_sp[ind] ]
tree_ex = t[burnin:dim(t)[1], col_tree_ex[ind] ]
deltaSP = lambda_0-tree_sp
deltaEX = mu_0-tree_ex
treeDIV = tree_sp-tree_ex
fossDIV = lambda_0-mu_0
#hist(fossDIV-treeDIV)
comp = (fossDIV-treeDIV)
library(scales)
if (maxR_arg==0){
#maxR = max(c(lambda_0,mu_0,tree_sp ,tree_ex ))*1.2
maxR = sort(c(lambda_0,mu_0,tree_sp ,tree_ex ))[round(0.99*length(tree_ex)*4)] *1.2
}else{
maxR = maxR_arg
}
name_bin = paste("Time bin",ind)
plot(lambda_0~tree_sp,pch=19,col=alpha("blue",0.20), xlim=c(0,maxR),ylim=c(0,maxR),xlab="Phylogenetic estimates",
ylab="Fossil estimates",main= name_bin) #colnames(t)[col_lambda[ind]])
points(mu_0~tree_ex,pch=19,col=alpha("red",0.20))
abline(0,1, lty=2)
dSP = lambda_0-tree_sp
dEX = mu_0-tree_ex
minR = min(c(dSP,dEX,0))*1.2
maxR = max(c(dSP,dEX))*1.2
#hist(fossDIV-treeDIV)
comp = (dSP-dEX)
P = length(comp[comp> -1e-10])/length(comp)
plot(dSP~dEX,xlim=c(minR,maxR),ylim=c(minR,maxR),pch=19,col=alpha("black",0.20),xlab=TeX('$\\lambda^{*} - \\lambda$'),ylab=TeX('$\\mu^{*} - \\mu$'),main=paste("P =",round(min(P,1-P),3)) )
abline(0,1, lty=2)
}
}
# par(mfrow=c(4,4))
# f="your_path/PyRate_github/example_files/BDC_model/Ferns_Independent_skyline_mcmc.log"
# plot_fossil_phylo_skyline(f)
### CONSTANT RATE MODELS
# PLOT SPECIATION MODE PREVALENCE
plot_speciation_mode_const_rate <- function(f,title=""){
library(latex2exp)
tbl = read.table(f,h=T)
tbl = tbl[500:dim(tbl)[1],]
dL = tbl$lambda_0 - 2*tbl$tree_sp
#hist(dL)
library(easyGgplot2)
dL = data.frame(dL)
colnames(dL)="trait"
ggplot2.density( dL,xName="trait" ,xlim =c(-0.5,0.5),densityFill="#3dab3c",main=title,ylim=c(0,16))
}
plot_bifurcating_plus_anagenetic <- function(f,title=""){
library(latex2exp)
tbl = read.table(f,h=T)
tbl = tbl[500:dim(tbl)[1],]
dL = tbl$lambda_0 - tbl$tree_sp
#hist(dL)
library(easyGgplot2)
dL = data.frame(dL)
colnames(dL)="trait"
ggplot2.density( dL,xName="trait" ,xlim =c(0,0.7),densityFill="#3dab3c",main=title)
}
library(latex2exp)
TeX = function(x){return(x)}
plot_fossil_phylo <- function(mcmc_file){
print(mcmc_file)
t = read.table(mcmc_file,h=T)
burnin=round(dim(t)[1]*0.25)
lambda_0 = t$lambda_0[burnin:dim(t)[1]]
mu_0 = t$mu_0 [burnin:dim(t)[1]]
tree_sp = t$tree_sp [burnin:dim(t)[1]]
tree_ex = t$tree_ex [burnin:dim(t)[1]]
deltaSP = lambda_0-tree_sp
deltaEX = mu_0-tree_ex
par(mfrow=c(2,2))
treeDIV = tree_sp-tree_ex
fossDIV = lambda_0-mu_0
#hist(fossDIV-treeDIV)
comp = (fossDIV-treeDIV)
length(comp[comp>0])/length(comp)
library(scales)
maxR = max(c(lambda_0,mu_0,tree_sp ,tree_ex ))*1.2
plot(lambda_0~tree_sp,pch=19,col=alpha("blue",0.20), xlim=c(0,maxR),ylim=c(0,maxR),xlab="Phylogenetic estimates",ylab="Fossil estimates",main=strsplit(mcmc_file,"_")[[1]][1])
points(mu_0~tree_ex,pch=19,col=alpha("red",0.20))
abline(0,1, lty=2)
dSP = lambda_0-tree_sp
dEX = mu_0-tree_ex
minR = min(c(dSP,dEX,0))*1.2
maxR = max(c(dSP,dEX))*1.2
#hist(fossDIV-treeDIV)
comp = (dSP-dEX)
P = length(comp[comp>0])/length(comp)
plot(dSP~dEX,xlim=c(minR,maxR),ylim=c(minR,maxR),pch=19,col=alpha("black",0.20),xlab=TeX('$\\lambda^{*} - \\lambda$'),ylab=TeX('$\\mu^{*} - \\mu$'),main=paste("P =",round(P,3)) )
abline(0,1, lty=2)
d = sort(lambda_0-2*tree_sp)
P_neg = length(d[d<0])/length(d)
Sp_mean = mean(d)
Sp_min = d[round(length(d)*0.025)]
Sp_max = d[round(length(d)*0.975)]
hist((lambda_0-2*tree_sp),col=alpha("black",0.20),xlab=TeX('$\\lambda^{*} - 2\\lambda$'), main=paste("P_neg",round(c(P_neg,Sp_mean,Sp_min,Sp_max),2)))
d2 = mu_0-(tree_sp+tree_ex)
hist(d2,col=alpha("black",0.20),xlab=TeX('$\\lambda^{*} - 2\\lambda$'))
}