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posterior_feasibility_domains_woody.R
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# packages used for parallelization
library(doMC)
registerDoMC(cores = 7)
# define functions used below
require(here)
source(here("code/lib/feasibility_utils.R"))
source(here("code/lib/posterior_utils.R"))
# general code that finds and loads all candidate model fits
source(here("code/lib/load_models.R"))
# parameters not estimated via inference
source(here("data/germination/extra_params.R"))
# tuning parameters that mostly control speed of these calculations
set.seed(123454)
subsample <- 50
desired_feasible <- 5000
max_samples <- 50000
# extract derived posteriors of pop dyn model parameter values
# replace those posteriors with the medians
posteriors <- list(vero=list(),trcy=list())
for(model in c('ricker','beverton_holt')){
vero_model <- focal_models[["vero"]][[model]]
posteriors[["vero"]][[model]] <- posterior_parameters(
vero_model,
s=seed_survival["vero"],
g=germination["vero"],
model_name=vero_model$name
)
trcy_model <- focal_models[["trcy"]][[model]]
posteriors[["trcy"]][[model]] <- posterior_parameters(
trcy_model,
s=seed_survival["trcy"],
g=germination["trcy"],
model_name=trcy_model$name
)
}
only.median <- FALSE
for(model in c('ricker','beverton_holt')){
# attach the median to the front of the posteriors
posteriors[["vero"]][[model]] <- rbind(
apply(posteriors[["vero"]][[model]], 2, median),
posteriors[["vero"]][[model]]
)
posteriors[["trcy"]][[model]] <- rbind(
apply(posteriors[["trcy"]][[model]], 2, median),
posteriors[["trcy"]][[model]]
)
if(only.median){
posteriors[["vero"]][[model]] <- posteriors[["vero"]][[model]][1,,drop=FALSE]
posteriors[["trcy"]][[model]] <- posteriors[["trcy"]][[model]][1,,drop=FALSE]
}else{
sub_samp <- sample.int(nrow(posteriors[["vero"]][[model]])-1, subsample) + 1
posteriors[["vero"]][[model]] <- posteriors[["vero"]][[model]][c(1,sub_samp),]
posteriors[["trcy"]][[model]] <- posteriors[["trcy"]][[model]][c(1,sub_samp),]
}
}
for(woody in c(1)){
filename <- paste0(
"figures/posterior_feasibility_domains_",
ifelse(woody,"woody","open"),
".pdf"
)
pdf(
file=here(filename),
width=7,
height=7
)
layout.matrix <- matrix(
c(1,2,3,4),
nrow = 2,
ncol = 2,
byrow = T
)
layout(mat = layout.matrix, heights=c(1,1), widths = c(1,1))
par(oma = c(2, 2, 0, 0))
par(mar = c(2, 3, 2, 1.5))
xlim <- ylim <- c(0,500)
xmin <- list()
ymin <- list()
xminr <- list()
yminr <- list()
xmax <- list()
ymax <- list()
xmaxr <- list()
ymaxr <- list()
cntr <- 0
for(tmodel in c('beverton_holt','ricker')){
for(vmodel in c('beverton_holt','ricker')){
model_combo <- paste('v',vmodel, 't',tmodel, woody, sep="_")
# xmin[[vmodel]] <- Inf
# ymin[[tmodel]] <- Inf
# xmax[[vmodel]] <- 0
# ymax[[tmodel]] <- 0
# manually tweaked limits based on previously collected xmax, ymax data
min_inv <- Inf
if(vmodel=="beverton_holt"){
xlim <- c(1/min_inv,140)
}else if(vmodel=="ricker"){
xlim <- c(1/min_inv,70)
}
if(tmodel=="beverton_holt"){
ylim <- c(1/min_inv,125)
}else if(tmodel=="ricker"){
ylim <- c(1/min_inv,50)
}
# message(model_combo)
# plot scaffold
plot(
x=NA,
y=NA,
xlim=xlim,
ylim=ylim,
type='n',
xlab="",
ylab="",
# log='xy',
# main=model_combo,
cex.lab=1.5
)
# dashed lines to guide the eyes
abline(h=0,lty='dashed',lwd=1.5)
abline(v=0,lty='dashed',lwd=1.5)
# to store whether or not the posterior of r is inside or outside the hull
r_in_hull <- numeric(nrow(posteriors[["vero"]][[vmodel]]))
for(i in rev(seq.int(nrow(posteriors[["vero"]][[vmodel]])))){
alpha <- alpha_matrix(
vero_row = posteriors[["vero"]][[vmodel]][i,],
trcy_row = posteriors[["trcy"]][[tmodel]][i,],
woody = woody
)
R_max <- maximum_radius(
alpha = alpha,
gN_max = gN_max
)
# growth rate constraints
# TODO: convert this to a function?
rconstraints <- list(
lower = c(vero=focal_models[["vero"]][[vmodel]]$constraints[1], trcy=focal_models[["trcy"]][[tmodel]]$constraints[1]),
upper = c(vero=focal_models[["vero"]][[vmodel]]$constraints[2], trcy=focal_models[["trcy"]][[tmodel]]$constraints[2])
)
results <- integrate_area(
alpha = alpha,
gN_max = gN_max,
rconstraints = rconstraints,
npts = max_samples
)$coords
# model_combo <- paste(vmodel,tmodel,woody,sep='_')
bcfd_hull <- grDevices::chull(results)
bcfd_hull <- c(bcfd_hull, bcfd_hull[1])
bcfd_hull <- results[bcfd_hull,]
xmin[[vmodel]] <- min(xmin[[vmodel]], min(bcfd_hull[,1]))
ymin[[tmodel]] <- min(ymin[[tmodel]], min(bcfd_hull[,2]))
xmax[[vmodel]] <- max(xmax[[vmodel]], max(bcfd_hull[,1]))
ymax[[tmodel]] <- max(ymax[[tmodel]], max(bcfd_hull[,2]))
r <- growth_rates(
vero_row = posteriors[["vero"]][[vmodel]][i,],
trcy_row = posteriors[["trcy"]][[tmodel]][i,],
woody = woody
)
xminr[[vmodel]] <- min(xminr[[vmodel]],r[1])
yminr[[tmodel]] <- min(yminr[[tmodel]],r[2])
xmaxr[[vmodel]] <- max(xmaxr[[vmodel]],r[1])
ymaxr[[tmodel]] <- max(ymaxr[[tmodel]],r[2])
if(i>1){
polygon(
bcfd_hull,
border = NA,
lty = 0,
col = scales::alpha("mediumseagreen", alpha = 0.1)
)
}else{
polygon(
bcfd_hull,
border = "black",
lty=1
# col = scales::alpha("mediumseagreen", alpha = 0.1)
)
}
r_in_hull_test <- sp::point.in.polygon(
r[1],
r[2],
bcfd_hull$ri,
bcfd_hull$rj
)
r_in_hull[i] <- (r_in_hull_test>0)
}
# to plot the vital rates r
for(i in rev(seq.int(nrow(posteriors[["vero"]][[vmodel]])))){
r <- growth_rates(
vero_row = posteriors[["vero"]][[vmodel]][i,],
trcy_row = posteriors[["trcy"]][[tmodel]][i,],
woody = woody
)
pch <- ifelse(r_in_hull[i],21,23)
if(i==1){
points(
r[1],
r[2],
pch=pch,
col='black',
bg='mediumseagreen'
)
}else{
pcol <- ifelse(r_in_hull[i],'white','grey')
points(
r[1],
r[2],
pch=pch,
col='black', #scales::alpha("black", alpha = 0.1),
bg=pcol #scales::alpha("white", alpha = 0.1)
)
}
}
vtext <- switch(
vmodel,
ricker="Ricker",
beverton_holt="Beverton-Holt"
)
ttext <- switch(
tmodel,
ricker="Ricker",
beverton_holt="Beverton-Holt"
)
# label the axes
if(cntr %in% c(2,3)){
mtext(
bquote(.(vtext) ~ "vital rate," ~ italic(nu)["G. rosea"]),
side = 1,
# outer = TRUE,
line=2.75,
cex=1.2
)
}
if(cntr %in% c(0,2)){
mtext(
bquote(.(ttext) ~ "vital rate," ~ italic(nu)["T. cyanopetala"]),
side = 2,
line=2.25,
# outer = TRUE,
cex=1.2
) #, adj = 1)
}
cntr <- cntr + 1
}
}
dev.off()
}