### This is for simulation only, ploting correlation aganst true values.
rm(list = ls())
suppressMessages(library(cubfits, quietly = TRUE))
source("00-set_env.r")
source(paste(prefix$code.plot.ps, "u0-get_case_main.r", sep = ""))
source(paste(prefix$code.plot.ps, "u2-plot_b_corr.r", sep = ""))
### Load true Phi.
fn.in <- paste(prefix$data, "simu_true_", model, ".rda", sep = "")
if(file.exists(fn.in)){
load(fn.in)
} else{
stop(paste(fn.in, " is not found.", sep = ""))
}
b.Init <- convert.b.to.bVec(Eb)
### Load data.
fn.in <- paste(prefix$data, "pre_process.rda", sep = "")
load(fn.in)
### Get AA and synonymous codons.
aa.names <- names(reu13.df.obs)
coef.names <- cubfits:::get.my.coefnames(model)
b.names <- NULL
for(i.aa in aa.names){
tmp <- sort(unique(reu13.df.obs[[i.aa]]$Codon))
tmp <- tmp[-length(tmp)]
b.names <- c(b.names, rep(coef.names, each = length(tmp)))
}
### Get true values.
all.names <- b.names
id.slop <- grep("Delta.t", all.names)
scale.EPhi <- mean(EPhi)
b.Init[id.slop] <- b.Init[id.slop] * scale.EPhi
for(i.case in case.names){
title <- paste(workflow.name, ", ", get.case.main(i.case, model), sep = "")
### Subset of mcmc output.
fn.in <- paste(prefix$subset, i.case, "_PM.rda", sep = "")
if(!file.exists(fn.in)){
cat("File not found: ", fn.in, "\n", sep = "")
next
}
load(fn.in)
### Subset of mcmc output with scaling.
fn.in <- paste(prefix$subset, i.case, "_PM_scaling.rda", sep = "")
if(!file.exists(fn.in)){
cat("File not found: ", fn.in, "\n", sep = "")
next
}
load(fn.in)
### Plot log(mu)
id.intercept <- grep("log.mu", all.names)
x <- b.Init[id.intercept]
y <- b.PM[id.intercept]
xlim <- my.range(x)
ylim <- my.range(y)
y.ci <- b.ci.PM[id.intercept,]
fn.out <- paste(prefix$plot.ps.single, "corr_true_logmu_", i.case,
".pdf", sep = "")
pdf(fn.out, width = 5, height = 5)
plot.b.corr(x, y, b.label,
y.ci = y.ci,
xlim = xlim, ylim = ylim,
xlab = "True", ylab = "Estimated",
main = "log(mu)", workflow.name = title)
mtext(date(), line = 2.5, cex = 0.4)
dev.off()
### Plot Delta.t.
id.slop <- grep("Delta.t", all.names)
x <- b.Init[id.slop]
y <- b.PM[id.slop]
xlim <- my.range(x)
ylim <- my.range(y)
y.ci <- b.ci.PM[id.slop,]
fn.out <- paste(prefix$plot.ps.single, "corr_true_deltat_", i.case,
".pdf", sep = "")
pdf(fn.out, width = 5, height = 5)
plot.b.corr(x, y, b.label,
y.ci = y.ci,
xlim = xlim, ylim = ylim,
xlab = "True", ylab = "Estimated",
main = "Delta.t", workflow.name = title)
mtext(date(), line = 2.5, cex = 0.4)
dev.off()
}
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