Nothing
################################################################################
# "Working with dynamic models for agriculture"
# Daniel Wallach (INRA), David Makowski (INRA), James W. Jones (U.of Florida),
# Francois Brun (ACTA)
# version : 2013-03-25
############################### MAIN PROGRAM ###################################
# Chapter 10. Putting it all together in a case study
# Utilization on scenarios
library(ZeBook)
library(maps)
list_all=unique(maize.weather(weather_all=weather_EuropeEU)[,c("idsite","GPSlatitude","GPSlongitude","year")])
list_all_sy=paste(list_all$idsite,list_all$year,sep="-")
list_all_site=unique(list_all[,c("idsite","GPSlatitude","GPSlongitude")])
# From estimation step, We keep RUE=2.175675
best_param <- maize.define.param()["nominal",]
param_opti=c("RUE")
best_param[param_opti]=2.175675
# prediction of mean B at 240 and std at 240.
system.time(sim<-maize.multisy(best_param, list_all_sy,sdate=100,ldate=250))
#save(sim,file="output/maize.case_05_sim.rda")
sim240=subset(sim, day==240)
matsy=matrix(as.numeric(unlist(strsplit(paste(sim240$sy),"-"))),ncol=2,byrow=TRUE)
sim240$idsite=matsy[,1]
sim240$year=matsy[,2]
mean_by_idsite<-as.matrix(unlist(by(sim240$B, sim240$idsite, mean)))
sd_by_idsite<-as.matrix(unlist(by(sim240$B, sim240$idsite, sd)))
by_idsite=data.frame(idsite=rownames(mean_by_idsite),B240.mean=mean_by_idsite ,B240.sd=sd_by_idsite )
by_idsite$B240.coefvar=by_idsite$B240.sd / by_idsite$B240.mean
by_idsite=merge(list_all_site, by_idsite, by="idsite")
head(by_idsite)
################################################################################
# Mean B240
break.B240.mean= c(0 , 2250, 2750, 3000,3250,3750,+Inf)
class.m=cut(by_idsite$B240.mean, breaks=break.B240.mean, labels =c("<2250","2250-2750","2750-3000","3000-3250","3250-3750",">3750"))
col.m=paste(cut(by_idsite$B240.mean, breaks=break.B240.mean , labels =grey((seq(0.9,0.3,length=length(break.B240.mean)-1)))))
limits <- data.frame(limits = c('NO', 'NE', 'SO', 'SE'), lat = c(65, 65, 34, 34), long = c(-11, 30, -11, 30))
zone_select=list(x=c(-11,30,30,-11,-11), y=c(34,34,65,65,34))
# St/Cor B240
break.B240.coefvar= c(0 , 0.05, 0.1,0.25,0.5,1)
class.m.coefvar=cut(by_idsite$B240.coefvar, breaks=break.B240.coefvar, labels =c("<5%","5%-10%","10%-25%","25%-50%",">50%"))
col.m.coefvar=paste(cut(by_idsite$B240.coefvar, breaks=break.B240.coefvar , labels =grey((seq(0.9,0.3,length=length(break.B240.coefvar)-1)))))
limits <- data.frame(limits = c('NO', 'NE', 'SO', 'SE'), lat = c(65, 65, 34, 34), long = c(-11, 30, -11, 30))
zone_select=list(x=c(-11,30,30,-11,-11), y=c(34,34,65,65,34))
# Maps
# mean
par(mar=c(0.5,3,0.5,0.5))
EuropeEU <- map(database = 'world', xlim=c(limits$long[1],limits$long[2]), ylim=c(limits$lat[3],limits$lat[1]))
polygon(zone_select, col =rgb(0,0,0,0), border = rgb(0,0,0,0.2))
points(by_idsite$GPSlongitude,by_idsite$GPSlatitude, col= col.m,pch=16,cex=1)
legend("bottomright", legend=levels(class.m), col=grey((seq(0.9,0.3,length=length(break.B240.mean)-1))), pch=rep(19,5),cex=0.8, bg="white")
# coefficient of variation
dev.new()
par(mar=c(0.5,3,0.5,0.5))
EuropeEU <- map(database = 'world', xlim=c(limits$long[1],limits$long[2]), ylim=c(limits$lat[3],limits$lat[1]))
polygon(zone_select, col =rgb(0,0,0,0), border = rgb(0,0,0,0.2))
points(by_idsite$GPSlongitude,by_idsite$GPSlatitude, col= col.m.coefvar,pch=16,cex=1)
legend("bottomright", legend=levels(class.m.coefvar), col=grey((seq(0.9,0.3,length=length(break.B240.coefvar)-1))), pch=rep(19,5),cex=0.8, bg="white")
# end of file
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.