demo/pub_code/plot.fig7.GCB.R
In USGS-R/mda.lakes: Tools for combining models, data, and processing for lakes
plot.fig7.GCB <- function(years){
cex.box = 0.8
cex.ttl = 0.8
tck <- 0.02
plt.rng.x <- c(.25,1.75)
plt.rng.y <- data.frame("Kw"=c(-6,6),"RT"=c(-1.2,1.2),"hc"=c(-1.2,1.2))
tick.x <- c(-20,0.5,1,1.5,50)
tick.y <- data.frame("Kw"=c(-10,-5,NA,0,NA,5,10),"RT"=c(-10,-1,NA,0,NA,1,10),"hc"=c(-10,NA,-1,0,NA,1,10))
tick.x.lab <- c(NA,"-50%","0","+50%",NA)
plot_colors <<- c("black", 'grey65', "grey80","grey40")
lab.perc <<- 14 # label (e.g., (a) spacing percent from corner)
par.mgp <<- data.frame(x=c(.9,.1,0),y=c(.66,-.06,0),y.s=c(.83,-.06,0))
small.thresh <<- 1000000 # 100 ha
large.thresh <<- 1e20 # effectively no upper limit
plot.order <<- c("medium","small","large")
line.wd <<- 1.1 # plot line width
fig.w <- 3.14961
v.spc <- 0.05 # inches of vertical space to separate panels (top only)
h.spc <- 0.05 # inches of horizontal space to separate panels (right only)
l.mar <- 0.0
r.mar <- 0#v.spc
t.mar <- 0.01
b.mar <- 0.22
left.spc <- 0.25 #0.1
pan.size <- (fig.w-3*(h.spc+left.spc)-r.mar-l.mar)/3
fig.h <- pan.size+v.spc+b.mar+t.mar
print(fig.h)
print(fig.w)
pdf(file = "../Figure_08.pdf",title='Read et al. figure',
width=fig.w, height=fig.h)
#png(filename = "../Figure_07.png",
# width = fig.w, height = fig.h, units = "in", res=450)
panels = matrix(c(1,2,3),1,3)
layout(panels)
par(mai=c(b.mar,left.spc, v.spc, h.spc),mgp=par.mgp$x,omi=c(0,l.mar,t.mar,r.mar),ps=13)
plot.kw(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
plot.RT(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
plot.hc(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
dev.off()
}
plot.kw <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'Kw'
write.param <- expression(paste("Change in K"["d"]," (%)"))
#par(mgp=c(.9,.06,0))
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
ylim=plt.rng.y$Kw, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xlab=" ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y.s)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$Kw,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$Kw,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(a)')
}
plot.RT <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'RT'
#par(mgp=c(.9,.06,0))
write.param = paste("Change in ",param," (%)",sep='')
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
ylim=plt.rng.y$RT, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xlab=" ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$RT,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$Kw,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.ave.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
# -----
sens.x = rev(sens.x) # because RT is the reverse of param increase (flow is being increased, RT goes down!!)
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
# -- other file
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.air.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
sens.vals <- sens.table[,-1]
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd,lty=3)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd,lty=3)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(b)')
}
plot.hc <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'hc'
write.param <- expression(paste("Change in h"["s"]," (%)"))
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
xlab=" ",
ylim=plt.rng.y$hc, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y.s)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$hc,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$hc,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(c)')
}
get.text.location <- function(par,perc=10){
x.lim <- par$usr[1:2] # limits
y.lim <- par$usr[3:4]
# upper right hand
y.range <- y.lim[2]-y.lim[1]
x.range <- x.lim[2]-x.lim[1]
y <- y.lim[2]-y.range*perc/100
x <- x.lim[1]+x.range*perc/100
return(c(x,y))
}
plot.fig7.GCB(years=c(1998,1996))
USGS-R/mda.lakes documentation built on Nov. 13, 2020, 8:28 p.m.
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plot.fig7.GCB <- function(years){
cex.box = 0.8
cex.ttl = 0.8
tck <- 0.02
plt.rng.x <- c(.25,1.75)
plt.rng.y <- data.frame("Kw"=c(-6,6),"RT"=c(-1.2,1.2),"hc"=c(-1.2,1.2))
tick.x <- c(-20,0.5,1,1.5,50)
tick.y <- data.frame("Kw"=c(-10,-5,NA,0,NA,5,10),"RT"=c(-10,-1,NA,0,NA,1,10),"hc"=c(-10,NA,-1,0,NA,1,10))
tick.x.lab <- c(NA,"-50%","0","+50%",NA)
plot_colors <<- c("black", 'grey65', "grey80","grey40")
lab.perc <<- 14 # label (e.g., (a) spacing percent from corner)
par.mgp <<- data.frame(x=c(.9,.1,0),y=c(.66,-.06,0),y.s=c(.83,-.06,0))
small.thresh <<- 1000000 # 100 ha
large.thresh <<- 1e20 # effectively no upper limit
plot.order <<- c("medium","small","large")
line.wd <<- 1.1 # plot line width
fig.w <- 3.14961
v.spc <- 0.05 # inches of vertical space to separate panels (top only)
h.spc <- 0.05 # inches of horizontal space to separate panels (right only)
l.mar <- 0.0
r.mar <- 0#v.spc
t.mar <- 0.01
b.mar <- 0.22
left.spc <- 0.25 #0.1
pan.size <- (fig.w-3*(h.spc+left.spc)-r.mar-l.mar)/3
fig.h <- pan.size+v.spc+b.mar+t.mar
print(fig.h)
print(fig.w)
pdf(file = "../Figure_08.pdf",title='Read et al. figure',
width=fig.w, height=fig.h)
#png(filename = "../Figure_07.png",
# width = fig.w, height = fig.h, units = "in", res=450)
panels = matrix(c(1,2,3),1,3)
layout(panels)
par(mai=c(b.mar,left.spc, v.spc, h.spc),mgp=par.mgp$x,omi=c(0,l.mar,t.mar,r.mar),ps=13)
plot.kw(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
plot.RT(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
plot.hc(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab)
dev.off()
}
plot.kw <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'Kw'
write.param <- expression(paste("Change in K"["d"]," (%)"))
#par(mgp=c(.9,.06,0))
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
ylim=plt.rng.y$Kw, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xlab=" ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y.s)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$Kw,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$Kw,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(a)')
}
plot.RT <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'RT'
#par(mgp=c(.9,.06,0))
write.param = paste("Change in ",param," (%)",sep='')
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
ylim=plt.rng.y$RT, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xlab=" ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$RT,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$Kw,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.ave.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
# -----
sens.x = rev(sens.x) # because RT is the reverse of param increase (flow is being increased, RT goes down!!)
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
# -- other file
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.air.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
sens.vals <- sens.table[,-1]
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd,lty=3)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd,lty=3)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(b)')
}
plot.hc <- function(year,col,plt.rng.x,plt.rng.y,cex.ttl,cex.box,tick.x,tick.y,label,tck,tick.x.lab){
source('Libraries/GLM.functions.R')
param <- 'hc'
write.param <- expression(paste("Change in h"["s"]," (%)"))
plot(c(0,1),c(0,1), type="l", col=NA,
axes=F,
xlab=" ",
ylim=plt.rng.y$hc, xlim=plt.rng.x,
ylab="Temp. difference (°C) ",
xaxs="i", yaxs="i",cex.lab=cex.ttl)
par(mgp=par.mgp$y.s)
title(xlab=write.param,cex.lab=cex.ttl)
axis(1,las=1, at=tick.x,cex.axis=cex.box, tck=tck,labels=tick.x.lab)
axis(3,at=tick.x,las=1, cex.axis=cex.box, tck=tck,labels=NA)
par(mgp=par.mgp$x)
axis(2,las=1, at=tick.y$hc,cex.axis=cex.box, tck=tck)
axis(4,at=tick.y$hc,las=1, cex.axis=cex.box, tck=tck,labels=NA)
sens.file <- paste("../supporting files/sensitivity_relative_",param,'.tsv',sep='')
sens.table <- read.delim(sens.file,sep='\t')
WBICs <- as.character(sens.table$WBICs)
sens.vals <- sens.table[,-1]
sizes <- vector(length=length(WBICs))
# do size categories too!
for (j in 1:length(WBICs)){
sizes[j] <- getArea(WBICs[j])
}
num.sims <- length(names(sens.vals))
sens.x <- vector(length=num.sims)
head.length <- nchar(paste(param,"_relative_",sep=''))
paste(param,"_relative_",sep='')
for (k in 1:num.sims){
sens.x[k] <- as.numeric(substring(names(sens.vals)[k],head.length+1))
}
comp.idx <- which(sens.x==1)
diffs <- data.frame("small"=vector(length=length(sens.x)),
"medium"=vector(length=length(sens.x)),
"large"=vector(length=length(sens.x)))
small.i <- (sizes<=small.thresh)
med.i <- (sizes>small.thresh & sizes<large.thresh)
large.i <- (sizes>=large.thresh)
for (k in 1:length(sens.x)){
sim.norm <- sens.vals[,comp.idx]
sim.comp <- sens.vals[,k]
diffs$small[k] <- median(sim.comp[small.i]-sim.norm[small.i],na.rm=TRUE)
diffs$medium[k] <- median(sim.comp[med.i]-sim.norm[med.i],na.rm=TRUE)
diffs$large[k] <- median(sim.comp[large.i]-sim.norm[large.i],na.rm=TRUE)
}
lines(sens.x,diffs[[plot.order[1]]],col=plot_colors[1],type='l',lwd=line.wd)
lines(sens.x,diffs[[plot.order[2]]],col=plot_colors[2],type='l',lwd=line.wd)
label.loc <- get.text.location(par(),perc=lab.perc)
text(label.loc[1],label.loc[2],label='(c)')
}
get.text.location <- function(par,perc=10){
x.lim <- par$usr[1:2] # limits
y.lim <- par$usr[3:4]
# upper right hand
y.range <- y.lim[2]-y.lim[1]
x.range <- x.lim[2]-x.lim[1]
y <- y.lim[2]-y.range*perc/100
x <- x.lim[1]+x.range*perc/100
return(c(x,y))
}
plot.fig7.GCB(years=c(1998,1996))
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