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reprosarefp.R
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reprosarefp.R
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library("devtools")
install_github("strucchange","mengluchu",build_vignettes = TRUE) # how to build on modified package
install_github("bfast2","mengluchu",build_vignettes = TRUE)
library("bfast")
library('rgdal')
library('raster')
library("spacetime")
library("scidb")
library("raster")
#scidbconnect("server_name", port, "user_name", "password")
data(prodespoints00) # mask forest
data(pdd) # validation
#data(fevi8) # array saved in Rdata
#output from SCIDB
sciref<-scidb("resarefpscidbf03")
tssarar1s<-array(as.double(sciref$spcu[]),c(150,150))[2:149,2:149]
tssarar2s<-array(as.double(sciref$spmo[]),c(150,150))[2:149,2:149]
tssarar3s<-array(as.double(sciref$cu[]),c(150,150))[2:149,2:149]
tssarar4s<-array(as.double(sciref$mo[]),c(150,150))[2:149,2:149]
tssarar5s<-array(as.double(sciref$arcu[]),c(150,150))[2:149,2:149]
tssarar6s<-array(as.double(sciref$armo[]),c(150,150))[2:149,2:149]
#generate confusion table
groundtruth<-pdd
ttssarar1<-generatecmpvalue(tssarar1s,pdd ,pv=0.05) #sarcu
ttssarar11<-generatecmpvalue(result.array=tssarar1s ,reference.sppoints=pdd ,pv=0.2)
ttssarar2<-generatecmpvalue(tssarar2s, pdd,pv=0.05) #sarmo
ttssarar22<-generatecmpvalue(tssarar2s, pdd,pv=0.1)
ttssarar3<-generatecmpvalue(tssarar3s, pdd,pv=0.05) #cu
ttssarar4<-generatecmpvalue(tssarar4s, pdd,pv=0.05) # mo
ttssarar5<-generatecmpvalue(tssarar5s, pdd,pv=0.05) #arcu
ttssarar6<-generatecmpvalue(tssarar6s, pdd,pv=0.05) #armo
cts<-rbind(ttssarar4,ttssarar6,ttssarar2,ttssarar22，ttssarar3，ttssarar5，ttssarar1，ttssarar11)
names1<-c("OLS-MOSUM p-value: 0.05","AR(1) OLS-MOSUM pvalue: 0.05","SAR OLS-MOSUM p-value: 0.05", "SAR OLS-MOSUM p-value: 0.1","OLS-CUSUM p-value: 0.05","AR(1) OLS-CUSUM p-value: 0.05","SAR OLS-CUSUM p-value: 0.05","SAR OLS-CUSUM p-value: 0.2")
barplotcm(cts, n=8,names1=names1)
# construct the validataion map
ptssarar1<-generateppvalue(tssarar1s,pv=0.05)
ptssarar11<-generateppvalue(tssarar1s,pv=0.005)
ptssarar2<-generateppvalue(tssarar2s, pv=0.05)
ptssarar22<-generateppvalue(tssarar2s,pv=0.2)
ptssarar3<-generateppvalue(tssarar3s,pv=0.05)
ptssarar4<-generateppvalue(tssarar4s,pv=0.05)
ptssarar5<-generateppvalue(tssarar5s,pv=0.05)
ptssarar6<-generateppvalue(tssarar6s,pv=0.05)
generatemapRAS1(ptssarar2,groundtruth,prodespoints00)
# with R or stored results
#stored results
#data(tssarar1) # corrected st model with original array sar cusum
#data(tssarar2)#sar mosum
#data(tssarar3)# cusum
#data(tssarar4)# mosum
#data(tssarar5)#ar cusum
#data(tssarar6)#ar mosum
#length(which(!is.na(match(tssarar4s,tssarar4))))
#tssarar4sp<-aperm(tssarar4s,c(2,1))
#spplot(raster(tssarar4s==0.01))
#length(which(tssarar2s<0.05,arr.ind=TRUE))
#reproduce with R
#takes a week to run
#tsall<-SARefpdents(inputarray=fevi8, le=636)
#tssarar1<-tsall[[1]]
#tssarar2<-tsall[[2]]
#tssarar3<-tsall[[3]]
#tssarar4<-tsall[[4]]
#tssarar5<-tsall[[5]]
#tssarar6<-tsall[[6]]