Nothing
initial_h_guess <-
function(TS,S,beta,meta)
#TS: Time series data.
#S: The slope of one certain metabolite.
#beta: The beta value for initial guess of h.
#meta: The serial number of metabolites included in the calculation. e.g. meta=c(1,3) means only 1st and 3rd metabolites affect this function.
{
thres=0.09 # The threshold for initial h. In this version. This threshold is a const.
L=log(TS[which(S<0),meta]) #select the time points that the metabolite is down regulated.
# Global guess of h.
# To see whether the metabolite is mainly up regulated
if(length(which(S<0))==0) # The betabolite keeps being up regulated.
{
L=log(TS[,meta])
Vt=solve(t(L)%*%L,tol=1e-18)%*%t(L)%*%log(S+0.1/beta)
}
else if(length(which(S<0))==length(meta)) # The number down regulated time points is equal to the number of metabolites we concern.
{
L=log(TS[which(S<0),meta])
Vt=solve(L,tol=1e-18)%*%log(2-S[which(S<0)]/beta)
}
else if(length(which(S<0))<length(meta))
{
Vt=c(rep(0.01,length(meta)))
}
else
{
L=log(TS[which(S<0),meta])
Vt=solve(t(L)%*%L,tol=1e-18)%*%t(L)%*%log(2-S[which(S<0)]/beta)
}
#Local guess of h.
#To calculate whether the down regulation is too steep.
LL=matrix(data=0,nrow=nrow(TS),ncol=1+length(meta))
LL[,1]=1
LL[,2:(1+length(meta))]=log(TS[,meta])
if(length(which((S+exp(beta))<0))==0) #If there is no time point that is too steep.
{
vt=solve(t(LL)%*%LL,tol=1e-18)%*%t(LL)%*%log(S+exp(beta))
}
else # If there are still some steep points.
{
vt=solve(t(LL)%*%LL,tol=1e-18)%*%t(LL)%*%log(S+exp(beta))
con=which(abs(vt[2:length(vt)])<thres) # To see whether vt is under the requirement
flag=0
while(((length(which((S+exp(beta))<0))!=0)|(!vt[1]>0)|(length(con)==0))&&flag<20)# Set beta until there is no steep time point.
{
beta=beta+1
vt=solve(t(LL)%*%LL,tol=1e-18)%*%t(LL)%*%log(S+exp(beta))
con=which(abs(vt[2:length(vt)])<thres)
flag=flag+1
}
}
con=which(abs(vt[2:length(vt)])<thres)
flag=0
while(((!vt[1]>0)|length(con)!=length(meta))&&flag<20)# Let all the value in h get under the theshold
{
beta=beta+1
vt=solve(t(LL)%*%LL,tol=1e-18)%*%t(LL)%*%log(S+exp(beta))
con=which(abs(vt[2:length(vt)])<thres)
flag=flag+1
}
Vt=c(beta,Vt)
vt=as.vector(vt)
return(list(Vt=Vt,vt=vt))
}
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