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MImemory<-function(iicc,training.set){
require("Matrix")
Prob <-as.numeric(iicc$background)
q <- iicc$q
D <- iicc$D
prob_parella<-iicc$probparella
correction<-iicc$correction_1rOrdre
correction1rOrdreval<-iicc$correction_1rOrdre_val
Mperfil<-iicc$Mperfil
HXmax<-iicc$Hmax
H<-iicc$HX
llindar<-slot(correction1rOrdreval,"sderror")[nrow(training.set)]
matrixSel<-as(iicc$D>llindar,"sparseMatrix")
interA<-x<-summary(matrixSel)[[1]]
interB<-y<-summary(matrixSel)[[2]]
nucleotids<-c("A","T","C","G")
ErrorHX<-slot(correction1rOrdreval,"sderror")[nrow(training.set)+1]
VarD<-((4-1)^2)/(2*((nrow(training.set)+1)^2)*(log(2,base=exp(1)))^2)
ErrorMI<-(2*VarD)^(1/2)
Divergence<-lapply(seq(1, length(interA), 1), function(k){
mi<-matrix(0,length(nucleotids),length(nucleotids))
if (interA[k]==interB[k]){
diag(mi)<-sapply(c(1:length(nucleotids)),function(i){
w<-rbind(as.matrix(training.set[,interA[k]]),nucleotids[i])
ww<-rbind(as.matrix(training.set[,interB[k]]),nucleotids[i])
training.set.mes.val<-cbind(w,ww)
pmX<-probability(training.set.mes.val, Prob)
pmXY<-joint.probability(training.set.mes.val,Prob,prob_parella)
H<-switch(iicc$classentropy, "Shannon"=entropy.Shannon(pmX),"Renyi"=entropy.Renyi(pmX,q))
HXY<-entropy.joint(pmXY,q,iicc)
D<-switch(iicc$classentropy, "Shannon"=divergence.Shannon(training.set.mes.val,H,HXY,correction1rOrdreval),"Renyi"=divergence.Renyi(training.set.mes.val,pmX,pmXY,q,correction1rOrdreval))
zzmi<-D[1,1]
})
}else{
mi<-sapply(c(1:length(nucleotids)),function(i){
zmi<-sapply(c(1:length(nucleotids)),function(j){
w<-rbind(as.matrix(training.set[,interA[k]]),nucleotids[i])
ww<-rbind(as.matrix(training.set[,interB[k]]),nucleotids[j])
training.set.mes.val<-cbind(w,ww)
pmX<-probability(training.set.mes.val, Prob)
pmXY<-joint.probability(training.set.mes.val,Prob,prob_parella)
H<-switch(iicc$classentropy, "Shannon"=entropy.Shannon(pmX),"Renyi"=entropy.Renyi(pmX,q))
HXY<-entropy.joint(pmXY,q,iicc)
D<-switch(iicc$classentropy, "Shannon"=divergence.Shannon(training.set.mes.val,H,HXY,correction1rOrdreval),"Renyi"=divergence.Renyi(training.set.mes.val,pmX,pmXY,q,correction1rOrdreval))
zzmi<-D[1,2]
})
zmi
})
}
mi
})
list(Divergence=Divergence,interA=interB,interB=interA)
}
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