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Copy pathN_ChooseBetweenM15andM13andM6.R
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N_ChooseBetweenM15andM13andM6.R
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#Only selecting between M15 and M13 AND gpp[[6]] (3-way)
#M13 is 14th in the list (i.e. gpp[[14]])
#M15 is last in the list (i.e. gpp[[16]])
#check the calls to be sure: gpp[[14]]$call
library(mgcv)
choosemod3<-function(lmods){ #list of models
modsummary<-AIC(lmods[[6]],lmods[[14]],lmods[[16]])
ord<-order(modsummary$AIC) #first is minimum
#if min AIC model has AIC at least 2 units lower than the next lowest,
#choose regardless of degrees of freedom
if(modsummary$AIC[ord[1]]-modsummary$AIC[ord[2]] < (-2)){
return(ord[1])
stop("Done. lowest AIC has no competition")
}
else {
#which models are within 2 AIC units, including self?
within2<-which(modsummary$AIC[ord[1]]-modsummary$AIC >=(-2))
#corresponding degrees of freedom:
theirDF<-modsummary$df[within2]
#pick the lowest degrees of freedom (aka fewest parameters)
bestmod<-within2[which(theirDF==min(theirDF))]
return(bestmod)
}
}
#AIR ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~####
setwd("/Users/doris/Documents/UIowa/GAMs_Jul7/Air_moreMods/") #DAILY outliers removed
gppmods<-list.files(pattern="GPP_D_*")
neemods<-list.files(pattern="NEE_D_*")
lemods<-list.files(pattern="LE_D_*")
airresults<-data.frame(matrix(NA,nrow=26,ncol=7))
names(airresults)<-c("site","GPPchoice","GPPdevexpl",
"NEEchoice","NEEdevexpl",
"LEchoice","LEdevexpl")
for(i in 1:length(gppmods)){
site<-substr(gppmods[i],nchar(gppmods[i])-6,nchar(gppmods[i])-4)
print(paste(site,i))
airresults[i,1]<-site
gpp<-readRDS(gppmods[i])
choose<-choosemod3(gpp)
airresults[i,2]<-choose
if(choose==1){ #3-way interaction
airresults[i,3]<-summary(gpp[[6]])$dev.expl
}
if(choose==2){ #no interaction
airresults[i,3]<-summary(gpp[[14]])$dev.expl
}
if(choose==3){ #2-way interaction
airresults[i,3]<-summary(gpp[[16]])$dev.expl
}
nee<-readRDS(neemods[i])
choose<-choosemod3(nee)
airresults[i,4]<-choose
if(choose==1){ #3-way interaction
airresults[i,5]<-summary(nee[[6]])$dev.expl
}
if(choose==2){
airresults[i,5]<-summary(nee[[14]])$dev.expl
}
if(choose==3){
airresults[i,5]<-summary(nee[[16]])$dev.expl
}
le<-readRDS(lemods[i])
choose<-choosemod3(le)
airresults[i,6]<-choose
if(choose==1){ #3-way interaction
airresults[i,7]<-summary(le[[6]])$dev.expl
}
if(choose==2){
airresults[i,7]<-summary(le[[14]])$dev.expl
}
if(choose==3){
airresults[i,7]<-summary(le[[16]])$dev.expl
}
}
table(airresults[,2])
table(airresults[,4])
table(airresults[,6])
write.csv(airresults,"/Users/doris/Documents/UIowa/GAMs_Jul7/Air_moreMods/airresults_ALL_modsummary_with3way.csv",row.names = FALSE)
#LEAF ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~####
setwd("/Users/doris/Documents/UIowa/GAMs_Jul7/Leaf_moreMods/") #DAILY outliers removed
gppmods<-list.files(pattern="GPP_D_*")
neemods<-list.files(pattern="NEE_D_*")
lemods<-list.files(pattern="LE_D_*")
leafresults<-data.frame(matrix(NA,nrow=26,ncol=7))
names(leafresults)<-c("site","GPPchoice","GPPdevexpl",
"NEEchoice","NEEdevexpl",
"LEchoice","LEdevexpl")
for(i in 1:length(gppmods)){
site<-substr(gppmods[i],nchar(gppmods[i])-6,nchar(gppmods[i])-4)
print(paste(site,i))
leafresults[i,1]<-site
gpp<-readRDS(gppmods[i])
choose<-choosemod3(gpp)
leafresults[i,2]<-choose #2 means more complicated model
if(choose==1){
leafresults[i,3]<-summary(gpp[[6]])$dev.expl
}
if(choose==2){
leafresults[i,3]<-summary(gpp[[14]])$dev.expl
}
if(choose==3){
leafresults[i,3]<-summary(gpp[[16]])$dev.expl
}
nee<-readRDS(neemods[i])
choose<-choosemod3(nee)
leafresults[i,4]<-choose
if(choose==1){
leafresults[i,5]<-summary(nee[[6]])$dev.expl
}
if(choose==2){
leafresults[i,5]<-summary(nee[[14]])$dev.expl
}
if(choose==3){
leafresults[i,5]<-summary(nee[[16]])$dev.expl
}
le<-readRDS(lemods[i])
choose<-choosemod3(le)
leafresults[i,6]<-choose
if(choose==1){
leafresults[i,7]<-summary(le[[6]])$dev.expl
}
if(choose==2){
leafresults[i,7]<-summary(le[[14]])$dev.expl
}
if(choose==3){
leafresults[i,7]<-summary(le[[16]])$dev.expl
}
}
write.csv(leafresults,"/Users/doris/Documents/UIowa/GAMs_Jul7/Leaf_moreMods/leafresults_ALL_modsummary_with3way.csv",row.names = FALSE)
table(leafresults[,2])
table(leafresults[,4])
table(leafresults[,6])
########### Alternative: significant or not:
#for(i in 1:length(gppmods)){
# gpp<-readRDS(gppmods[i])
# summary(gpp[[16]])
#}
############################## #gam.check plots for chosen models - FOR SUPP
leafresults<-read.csv("/Users/doris/Documents/UIowa/GAMs_Jul7/Leaf_moreMods/leafresults_ALL_modsummary_with3way.csv")
setwd("/Users/doris/Documents/UIowa/GAMs_Jul7/Leaf_moreMods/") #DAILY outliers removed
gppmods<-list.files(pattern="GPP_D_*")
neemods<-list.files(pattern="NEE_D_*")
lemods<-list.files(pattern="LE_D_*")
png("/Users/doris/Documents/UIowa/Figures/final/Leaf_GPPmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(gppmods)){
gpp<-readRDS(gppmods[u])
r<-which(leafresults$site==substr(gppmods[u],12,14))
if(leafresults$GPPchoice[r] ==1){
modchoice<-gpp[[6]]
inwords<-"3-way (Eqn.10)"
}
if(leafresults$GPPchoice[r] ==2){
modchoice<-gpp[[14]]
inwords<-"no int (Eqn.8)"
}
if(leafresults$GPPchoice[r] ==3){
modchoice<-gpp[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
#par("plt" = c(.15,.9,.15,.9))
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(leafresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted GPP"["s"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed GPP"["s"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()
png("/Users/doris/Documents/UIowa/Figures/final/Leaf_NEEmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(neemods)){
nee<-readRDS(neemods[u])
r<-which(leafresults$site==substr(neemods[u],12,14))
if(leafresults$NEEchoice[r] ==1){
modchoice<-nee[[6]]
inwords<-"3-way (Eqn.10)"
}
if(leafresults$NEEchoice[r] ==2){
modchoice<-nee[[14]]
inwords<-"no int (Eqn.8)"
}
if(leafresults$NEEchoice[r] ==3){
modchoice<-nee[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(leafresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted NEP"["s"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed NEP"["s"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()
png("/Users/doris/Documents/UIowa/Figures/final/Leaf_LEmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(lemods)){
le<-readRDS(lemods[u])
r<-which(leafresults$site==substr(lemods[u],11,13)) #hard coded numbers change bc LE has 2 letters, ugh
if(leafresults$LEchoice[r] ==1){
modchoice<-le[[6]]
inwords<-"3-way (Eqn.10)"
}
if(leafresults$LEchoice[r] ==2){
modchoice<-le[[14]]
inwords<-"no int (Eqn.8)"
}
if(leafresults$LEchoice[r] ==3){
modchoice<-le[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(leafresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted LE"["s"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed LE"["s"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()
#########################
airresults<-read.csv("/Users/doris/Documents/UIowa/GAMs_Jul7/Air_moreMods/airresults_ALL_modsummary_with3way.csv")
setwd("/Users/doris/Documents/UIowa/GAMs_Jul7/Air_moreMods/") #DAILY outliers removed
gppmods<-list.files(pattern="GPP_D_*")
neemods<-list.files(pattern="NEE_D_*")
lemods<-list.files(pattern="LE_D_*")
png("/Users/doris/Documents/UIowa/Figures/final/Air_GPPmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(gppmods)){
gpp<-readRDS(gppmods[u])
r<-which(airresults$site==substr(gppmods[u],11,13))
if(airresults$GPPchoice[r] ==1){
modchoice<-gpp[[6]]
inwords<-"3-way (Eqn.10)"
}
if(airresults$GPPchoice[r] ==2){
modchoice<-gpp[[14]]
inwords<-"no int (Eqn.8)"
}
if(airresults$GPPchoice[r] ==3){
modchoice<-gpp[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
#par("plt" = c(.15,.9,.15,.9))
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(airresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted GPP"["a"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed GPP"["a"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()
png("/Users/doris/Documents/UIowa/Figures/final/Air_NEEmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(neemods)){
nee<-readRDS(neemods[u])
r<-which(airresults$site==substr(neemods[u],11,13))
if(airresults$NEEchoice[r] ==1){
modchoice<-nee[[6]]
inwords<-"3-way (Eqn.10)"
}
if(airresults$NEEchoice[r] ==2){
modchoice<-nee[[14]]
inwords<-"no int (Eqn.8)"
}
if(airresults$NEEchoice[r] ==3){
modchoice<-nee[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(airresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted NEP"["a"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed NEP"["a"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()
png("/Users/doris/Documents/UIowa/Figures/final/Air_LEmod_eval.png",
width=1600,height=2000,units="px",res=200)
par(mfrow=c(7,4))
for (u in 1:length(lemods)){
le<-readRDS(lemods[u])
r<-which(airresults$site==substr(lemods[u],10,12)) #hard coded numbers change bc LE has 2 letters, ugh
if(airresults$LEchoice[r] ==1){
modchoice<-le[[6]]
inwords<-"3-way (Eqn.10)"
}
if(airresults$LEchoice[r] ==2){
modchoice<-le[[14]]
inwords<-"no int (Eqn.8)"
}
if(airresults$LEchoice[r] ==3){
modchoice<-le[[16]]
inwords<-"2-way (Eqn.9)"
}
res<-residuals(modchoice, type= "deviance")
observed.y <- napredict(modchoice$na.action, modchoice$y)
par("plt" = c(.25,.95,.3,.88))
plot(fitted(modchoice), observed.y, xlab = "",
ylab = "", main="",
pch=20,col=rgb(0,0,0,.3))
mtext(paste0(airresults$site[r],"; ",inwords),side=3,line=0.1,cex=0.8)
mtext(expression(paste("Fitted LE"["a"])),side =1,line=1.8,cex=0.6)
mtext(expression(paste("Observed LE"["a"])),side=2,line=1.8,cex=0.6)
abline(0,1,col="red")
par(new=TRUE)
par("plt" = c(0.25, 0.46, 0.65, 0.88))
hist(res, xlab = "", main = "",ylab="",yaxt='n',xaxt='n')
abline(v=0,col="red")
}
dev.off()