def __init__(self, counts, locPrior, alpha, dag):
likelihoodCalc.__init__(self, counts, locPrior, alpha, dag)
(lks, lksTot, junk) = deterministic(self.counts, locPrior, self.dag)
self.lksTot = lksTot
self.lksDat = {False: lks, True: powList(lks, alpha)}
self.calc()
def __init__(self, counts, locPrior, alpha, dag):
likelihoodCalc.__init__(self, counts, locPrior, alpha, dag)
(lks, lksTot, (betas, betasFound, betasNFound)) = multiRate(self.counts, locPrior, self.dag)
self.lksTot = lksTot
self.betasDat = switchDat(betas, betasFound, betasNFound, alpha)
self.likelihoodDat = {False: lks, True: powList(lks, alpha)}
s = listAdd(lks, dag.sumUpto(lks))
s = listDiv(s, betas) # sumUpto with the beta contribution from [i] cancelled
renyiLks = powList(lks, alpha)
r = listAdd(renyiLks, dag.sumUpto(renyiLks))
r = listDiv(r, self.betasDat[True][cOrig])
self.uptoBetas = {False: s, True: r} #
self.calc()
def __init__(self,counts,locPrior,alpha,dag):
likelihoodCalc.__init__(self,counts,locPrior,alpha,dag)
(lks,lksTot,junk)=deterministic(self.counts,locPrior,self.dag)
self.lksTot=lksTot
self.lksDat={False:lks,True:powList(lks,alpha)}
self.calc()
def __init__(self,counts,locPrior,alpha,dag):
likelihoodCalc.__init__(self,counts,locPrior,alpha,dag)
(lks,lksTot,(betas,betasFound,betasNFound))=multiRate(self.counts,locPrior,self.dag)
self.lksTot=lksTot
self.betasDat=switchDat(betas,betasFound,betasNFound,alpha)
self.likelihoodDat={False: lks, True: powList(lks,alpha)}
s= listAdd(lks,dag.sumUpto(lks))
s=listDiv(s,betas) # sumUpto with the beta contribution from [i] cancelled
renyiLks=powList(lks,alpha)
r=listAdd(renyiLks, dag.sumUpto(renyiLks))
r=listDiv(r,self.betasDat[True][cOrig])
self.uptoBetas = {False: s, True: r} #
self.calc()
def switchDat(orig, found, Nfound, alpha):
r = {}
r[False] = [orig, found, Nfound]
r[True] = [powList(orig, alpha), powList(found, alpha), powList(Nfound, alpha)]
return r
def switchDat(orig,found,Nfound,alpha):
r={}
r[False]=[orig,found,Nfound]
r[True]=[powList(orig,alpha),powList(found,alpha),powList(Nfound,alpha)]
return r