Revision 75151566
Added by Benoit Parmentier over 12 years ago
| climate/research/oregon/interpolation/GAM_LST_reg.R | ||
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####################Interpolation of Tmax for 10 dates.##################### |
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#This script interpolates station values for the Oregon case study. This program loads the station data from a csv file
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#and perform two types of regression: multiple linear model and general additive model (GAM). Note that this program:
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#1)assumes that the csv file is in the current working
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#This script interpolates station values for the Oregon case study. This program loads the station data from a shapefile
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#and perform 8 regressions using the general additive model (GAM). Note that this program:
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#1)assumes that the shapefile in the current working
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#2)extract relevant variables from raster images before performing the regressions. |
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#This scripts predicts tmas xsing GAM and LST derived from MOD11A1. |
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#Interactions terms are also included and assessed using the RMSE from validation dataset. |
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results_table_RMSE<-as.data.frame(results_RMSEnum) |
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results_table_AIC<-as.data.frame(results_AICnum) |
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colnames(results_table_RMSE)<-c("dates","ns","mod1", "mod2","mod3", "mod4", "mod5", "mod6", "mod7")
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colnames(results_table_AIC)<-c("dates","ns","mod1", "mod2","mod3", "mod4", "mod5", "mod6", "mod7")
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colnames(results_table_RMSE)<-c("dates","ns","mod1", "mod2","mod3", "mod4", "mod5", "mod6", "mod7", "mod8")
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colnames(results_table_AIC)<-c("dates","ns","mod1", "mod2","mod3", "mod4", "mod5", "mod6", "mod7", "mod8")
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#results_table_RMSE |
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#write.csv(results_table_RMSE, file= paste(path,"/","results_GAM_Assessment",out_prefix,".txt",sep="")) |
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#write.csv(results_table_AIC, file= paste(path,"/","results_GAM_Assessment",out_prefix,".txt",sep=""),append=TRUE) |
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write.table(results_table_RMSE, file= paste(path,"/","results_GAM_Assessment",out_prefix,".txt",sep=""), sep=",") |
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write.table(results_table_AIC, file= paste(path,"/","results_GAM_Assessment",out_prefix,".txt",sep=""),sep=",", append=TRUE) |
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#Can also use file connection |
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f<-file(paste(path,"/","results_GAM_Assessment",out_prefix,"2.txt",sep=""),"w") |
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write(results_table_RMSE, file=f) |
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close(f) |
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# End of script########## |
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###Analysing the results from the 365 days run: Summarize by month |
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for(i in 1:nrow(results_table_RMSE)){
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date<-results_table_RMSE$dates[i] |
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date<-strptime(date, "%Y%m%d") |
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results_table_RMSE$month[i]<-as.integer(strftime(date, "%m")) |
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} |
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average<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE,mean, na.rm=TRUE) |
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average<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE, FUN=mean) |
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#average on all the data.frame |
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averaget<-aggregate(results_table_RMSE, by=list(results_table_RMSE$month),FUN=mean, na.rm=TRUE) |
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#mediant<-aggregate(results_table_RMSE, by=list(results_table_RMSE$month),FUN=median, na.rm=TRUE) |
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#average_lowt<-aggregate(results_table_RMSE, by=list(results_table_RMSE$month), FUN=function(v) t.test(v)$conf.int[1]) |
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#average_up<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE, function(v) t.test(v)$conf.int[2]) |
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median<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE, median, na.rm=TRUE) |
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average_low<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE, function(v) t.test(v)$conf.int[1]) |
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average_up<-aggregate(cbind(mod1,mod2,mod3,mod4,mod5,mod6,mod7,mod8)~month,data=results_table_RMSE, function(v) t.test(v)$conf.int[2]) |
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#Selecting dates and files based on names |
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#cor_LST_LC<-matrix(1,10,1) |
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# for(i in 1:length(dates)){
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# cor_LST_LC1[i]<-cor(ghcn.subsets[[i]]$LST,ghcn.subsets[[i]]$LC1) |
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# } |
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# for(i in 1:length(dates)){
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# cor_LST_LC3[i]<-cor(ghcn.subsets[[i]]$LST,ghcn.subsets[[i]]$LC3) |
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# } |
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mod<-names(averaget) |
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mod<-mod[4:11] |
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#Saving graphic plots |
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for(i in 1:length(mod)){
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X11(width=14,height=10) |
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name<-mod[i] |
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barplot2(average[[name]],plot.ci=TRUE, ci.l=average_low[[name]], ci.u=average_up[[name]],main="Mean RMSE per month", names.arg=c("Jan", "Feb", "Mar", "Apr", "May", "Jun","Jul", "Aug", "Sep","Oct", "Nov", "Dec"),ylim=c(20,30),ylab="RMSE in tenth deg C",xlab=name)
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#title(paste("Sampling RMSE for mod",i,sep=""))
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savePlot(paste("barplot_results_RMSE_month_",name,out_prefix,".png", sep=""), type="png")
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dev.off() |
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} |
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for(i in 1:length(mod)){
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X11(width=14,height=10) |
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name<-mod[i] |
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barplot2(average[[name]],plot.ci=TRUE, ci.l=average_low[[name]], ci.u=average_up[[name]],main=paste(" Mean RMSE per month ",name, sep=""), names.arg=c("Jan", "Feb", "Mar", "Apr", "May", "Jun","Jul", "Aug", "Sep","Oct", "Nov", "Dec"),ylim=c(20,30),ylab="RMSE in tenth deg C",xlab=name)
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#title(paste("Sampling RMSE for mod",i,sep=""))
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savePlot(paste("barplot_results_RMSE_month_",name,out_prefix,".png", sep=""), type="png")
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dev.off() |
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X11(width=14,height=10) |
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name<-mod[i] |
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hist(results_table_RMSE[[name]],breaks=15, main=paste(" Histogram RMSE_",name, sep=""),xlab=paste("RMSE ",name, sep=""))
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savePlot(paste("Hist_results_RMSE_365_",name,out_prefix,".png", sep=""), type="png")
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dev.off() |
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} |
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for(i in 1:length(mod)){
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X11(width=14,height=10) |
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name<-mod[i] |
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hist(results_table_RMSE[[name]],breaks=15, main=paste(" Histogram RMSE_",name, sep=""),xlab=paste("RMSE ",name, sep=""))
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savePlot(paste("Hist_results_RMSE_365_",name,out_prefix,".png", sep=""), type="png")
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dev.off() |
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} |
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r<-(results_table_RMSE[,3:10]) #selecting only the columns related to models... |
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mean_r<-mean(r) |
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median_r<-sapply(r, median) |
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sd_r<-sapply(r, sd) |
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barplot(mean_r,ylim=c(23,26),ylab="RMSE in tenth deg C") |
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barplot(median_r,ylim=c(23,26),ylab="RMSE in tenth deg C",add=TRUE,inside=FALSE,beside=TRUE) # put both on the same plot |
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barplot(sd_r,ylim=c(6,8),ylab="RMSE in tenth deg C") # put both on the same plot |
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height<-rbind(mean_r,median_r) |
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barplot(height,ylim=c(23,26),ylab="RMSE in tenth deg C",beside=TRUE,legend=rownames(height)) |
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barplot(height,ylim=c(23,26),ylab="RMSE in tenth deg C",beside=TRUE, col=c("darkblue","red"),legend=rownames(height)) # put both on the same plot
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barplot2(mean_r,median_r,ylim=c(23,26),ylab="RMSE in tenth deg C") # put both on the same plot |
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#Collect var explained and p values for each var... |
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# End of script########## |
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#mod9<- gam(tmax~ te(lat,lon,ELEV_SRTM), data=ghcn_s_20101031) |
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names(results_table_RMSE) |
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Also available in: Unified diff
GAM LST, adding lines to assess RMSE per month over 365 dates, task #406