void Restaurant::initializeAdmixtureProportions(void) {
// set up vectors for admixture
if (assumingAdmixture == true && assumingDpp == false)
{
// what type of prior are we placing on the mixing proportions?
if (settingsPtr->getAdmixtureDist() == "fixed")
admixtureVarianceParm = settingsPtr->getAdmixtureParm1();
else if (settingsPtr->getAdmixtureDist() == "exponential")
admixtureVarianceParm = ranPtr->exponentialRv( settingsPtr->getAdmixtureParm1() );
else if (settingsPtr->getAdmixtureDist() == "uniform")
admixtureVarianceParm = ranPtr->uniformRv( settingsPtr->getAdmixtureParm1(), settingsPtr->getAdmixtureParm2() );
else if (settingsPtr->getAdmixtureDist() == "gamma")
admixtureVarianceParm = ranPtr->gammaRv( settingsPtr->getAdmixtureParm1(), settingsPtr->getAdmixtureParm2() );
// get the upper and lower limits for the admixture variance parameter
if (settingsPtr->getAdmixtureDist() == "uniform")
{
admixtureLowerLimit = settingsPtr->getAdmixtureParm1();
admixtureUpperLimit = settingsPtr->getAdmixtureParm2();
}
else if (settingsPtr->getAdmixtureDist() == "exponential")
{
admixtureLowerLimit = 0.001;
admixtureUpperLimit = ( 1.0 / settingsPtr->getAdmixtureParm1() ) * 100.0;
}
else if (settingsPtr->getAdmixtureDist() == "gamma")
{
admixtureLowerLimit = 0.001;
admixtureUpperLimit = ( settingsPtr->getAdmixtureParm1() / settingsPtr->getAdmixtureParm2() ) * 100.0;
}
// initialize the counts and probabilities for the mixing proportions
popCounts = new MbVector<int>[observationsPtr->getNumIndividuals()];
popProbs = new MbVector<double>[observationsPtr->getNumIndividuals()];
for (int i=0; i<observationsPtr->getNumIndividuals(); i++)
{
popCounts[i] = MbVector<int>(modelPtr->getNumPopulations());
popProbs[i] = MbVector<double>(modelPtr->getNumPopulations());
MbVector<double> alp( modelPtr->getNumPopulations() );
for (int j=0; j<modelPtr->getNumPopulations(); j++)
alp[j] = admixtureVarianceParm / modelPtr->getNumPopulations();
ranPtr->dirichletRv(alp, popProbs[i]);
for (int j=0; j<modelPtr->getNumPopulations(); j++)
popCounts[i][j] = 0;
}
for (int i=0; i<getNumTables(); i++)
{
Table *tp = getTable(i);
for (int j=0; j<tp->getNumPatrons(); j++)
{
Patron *p = tp->getPatron(j);
popCounts[ p->getIndividual() ][ i ]++;
}
}
}
}
void Restaurant::updateSeatingForFixedTables(void) {
// allocate memory for reassignment probabilities
vector<double> probs;
// loop over all patrons, attempting to reseat each
for (int idx=0; idx<numPatrons; idx++)
{
// get a pointer to the element and its current table
Patron *p = patrons[idx];
Table *tablePtr = p->getTable();
// remove the element from the table
tablePtr->removePatronFromTable(p);
if (assumingAdmixture == true)
popCounts[ p->getIndividual() ][ getIndexForTable(tablePtr) ]--;
// calculate the likelihood when the element is seated at all possible tables
for (int i=0; i<getNumTables(); i++)
{
Table *tp = getTable(i);
double lnC = 0.0;
if (assumingAdmixture == true)
lnC = log( popProbs[ p->getIndividual() ][ i ] );
probs.push_back( tp->lnLikelihood(p) + lnC );
}
normalizeVector( probs );
// pick a table for reassignment
tablePtr = getTable( multinomialRv(probs) );
// add the element to that table
tablePtr->addPatronToTable(p);
if (assumingAdmixture == true)
popCounts[ p->getIndividual() ][ getIndexForTable(tablePtr) ]++;
// clear the probs vector
probs.clear();
}
}
double Restaurant::lnPriorProbability(void) {
if (assumingAdmixture == false && assumingDpp == false)
{
// fixed number of populations with no admixture
return -numPatrons * log(getNumTables());
}
else if (assumingAdmixture == true && assumingDpp == false)
{
// fixed number of poulations with admixture
double lnP = 0.0;
for (int idx=0; idx<numPatrons; idx++)
{
Patron *p = patrons[idx];
Table *tablePtr = p->getTable();
lnP += log(popProbs[ p->getIndividual() ][ getIndexForTable(tablePtr) ]);
}
return lnP;
}
else if (assumingAdmixture == false && assumingDpp == true)
{
// number of populations is a random variable, but no admixture
/* f({\mathbf z}, k | \alpha, c) = \alpha^k {\prod_{i=1}^k(\eta_i - 1)! \over \prod_{i=1}^c(\alpha + i - 1)} */
double lnSum1 = 0.0;
for (vector<Table *>::iterator p=tables.begin(); p != tables.end(); p++)
{
lnSum1 += lnFactorial[ (*p)->getNumPatrons() - 1 ];
}
double lnSum2 = 0.0;
for (int i=1; i<=numPatrons; i++)
lnSum2 += log(concentrationParm + i - 1.0);
double lnP = getNumTables() * log(concentrationParm) + lnSum1 - lnSum2;
return lnP;
}
return 0.0;
}
void Restaurant::initializePatrons(void) {
// how many patrons?
if (assumingAdmixture == false)
numPatrons = observationsPtr->getNumIndividuals();
else if (assumingAdmixture == true && individualsInRestaurant == -1)
numPatrons = observationsPtr->getNumIndividuals() * observationsPtr->getTotalNumAlleleCopies();
else if (assumingAdmixture == true && individualsInRestaurant >= 0)
numPatrons = observationsPtr->getTotalNumAlleleCopies();
// allocate the patrons
patrons = new Patron*[numPatrons];
// set the index information for each patron
if (assumingAdmixture == false)
{
for (int i=0; i<numPatrons; i++)
{
patrons[i] = new PatronIndividual( observationsPtr, i, observationsPtr->getNumLoci(), observationsPtr->getNumUniqueAlleles() );
patrons[i]->setIndex(i);
patrons[i]->setIndividual(i);
}
}
else if (assumingAdmixture == true && individualsInRestaurant == -1)
{
for (int i=0, m=0; i<observationsPtr->getNumIndividuals(); i++)
{
for (int j=0; j<observationsPtr->getNumLoci(); j++)
{
int ploidy = 1;
if (observationsPtr->getIsDiploid(j) == true)
ploidy = 2;
for (int k=0; k<ploidy; k++)
{
patrons[m] = new PatronAllele( observationsPtr, m, i, j, k, observationsPtr->getNumUniqueAllelesAtLocus(j) );
m++;
}
}
}
}
else if (assumingAdmixture == true && individualsInRestaurant >= 0)
{
for (int j=0, m=0; j<observationsPtr->getNumLoci(); j++)
{
int ploidy = 1;
if (observationsPtr->getIsDiploid(j) == true)
ploidy = 2;
for (int k=0; k<ploidy; k++)
{
patrons[m] = new PatronAllele( observationsPtr, m, individualsInRestaurant, j, k, observationsPtr->getNumUniqueAllelesAtLocus(j) );
m++;
}
}
}
// set the data for each patron
for (int i=0; i<numPatrons; i++)
{
Patron *p = patrons[i];
int elemIdx = p->getIndividual();
p->setData( observationsPtr->getPtrToIndividual(elemIdx) );
}
// set the ln likelihood for each data element when placed in a population by itself
for (int i=0; i<numPatrons; i++)
{
Patron *p = patrons[i];
double x = lnLikelihoodNewTable(p);
p->setLnLikelihoodAlone(x);
}
}
