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yap-6.3/packages/CLPBN/horus/Parfactor.cpp
2012-12-27 12:54:58 +00:00

942 lines
22 KiB
C++

#include "Parfactor.h"
#include "Histogram.h"
#include "Indexer.h"
#include "Util.h"
#include "Horus.h"
Parfactor::Parfactor (
const ProbFormulas& formulas,
const Params& params,
const Tuples& tuples,
unsigned distId)
{
args_ = formulas;
params_ = params;
distId_ = distId;
LogVars logVars;
for (size_t i = 0; i < args_.size(); i++) {
ranges_.push_back (args_[i].range());
const LogVars& lvs = args_[i].logVars();
for (size_t j = 0; j < lvs.size(); j++) {
if (Util::contains (logVars, lvs[j]) == false) {
logVars.push_back (lvs[j]);
}
}
}
LogVar newLv = logVars.size();
constr_ = new ConstraintTree (logVars, tuples);
// Change formulas like f(X,X), X in {(p1),(p2),...}
// to be like f(X,Y), (X,Y) in {(p1,p1),(p2,p2),...}.
// This will simplify shattering on the constraint tree.
for (size_t i = 0; i < args_.size(); i++) {
LogVarSet lvSet;
LogVars& lvs = args_[i].logVars();
for (size_t j = 0; j < lvs.size(); j++) {
if (lvSet.contains (lvs[j]) == false) {
lvSet |= lvs[j];
} else {
constr_->cloneLogVar (lvs[j], newLv);
lvs[j] = newLv;
++ newLv;
}
}
}
assert (params_.size() == Util::sizeExpected (ranges_));
}
Parfactor::Parfactor (const Parfactor* g, const Tuple& tuple)
{
args_ = g->arguments();
params_ = g->params();
ranges_ = g->ranges();
distId_ = g->distId();
constr_ = new ConstraintTree (g->logVars(), {tuple});
assert (params_.size() == Util::sizeExpected (ranges_));
}
Parfactor::Parfactor (const Parfactor* g, ConstraintTree* constr)
{
args_ = g->arguments();
params_ = g->params();
ranges_ = g->ranges();
distId_ = g->distId();
constr_ = constr;
assert (params_.size() == Util::sizeExpected (ranges_));
}
Parfactor::Parfactor (const Parfactor& g)
{
args_ = g.arguments();
params_ = g.params();
ranges_ = g.ranges();
distId_ = g.distId();
constr_ = new ConstraintTree (*g.constr());
assert (params_.size() == Util::sizeExpected (ranges_));
}
Parfactor::~Parfactor (void)
{
delete constr_;
}
LogVarSet
Parfactor::countedLogVars (void) const
{
LogVarSet set;
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].isCounting()) {
set.insert (args_[i].countedLogVar());
}
}
return set;
}
LogVarSet
Parfactor::uncountedLogVars (void) const
{
return constr_->logVarSet() - countedLogVars();
}
LogVarSet
Parfactor::elimLogVars (void) const
{
LogVarSet requiredToElim = constr_->logVarSet();
requiredToElim -= constr_->singletons();
requiredToElim -= countedLogVars();
return requiredToElim;
}
LogVarSet
Parfactor::exclusiveLogVars (size_t fIdx) const
{
assert (fIdx < args_.size());
LogVarSet remaining;
for (size_t i = 0; i < args_.size(); i++) {
if (i != fIdx) {
remaining |= args_[i].logVarSet();
}
}
return args_[fIdx].logVarSet() - remaining;
}
void
Parfactor::sumOutIndex (size_t fIdx)
{
assert (fIdx < args_.size());
assert (args_[fIdx].contains (elimLogVars()));
if (args_[fIdx].isCounting()) {
unsigned N = constr_->getConditionalCount (
args_[fIdx].countedLogVar());
unsigned R = args_[fIdx].range();
vector<double> numAssigns = HistogramSet::getNumAssigns (N, R);
Indexer indexer (ranges_, fIdx);
while (indexer.valid()) {
if (Globals::logDomain) {
params_[indexer] += numAssigns[ indexer[fIdx] ];
} else {
params_[indexer] *= numAssigns[ indexer[fIdx] ];
}
++ indexer;
}
}
LogVarSet excl = exclusiveLogVars (fIdx);
unsigned exp;
if (args_[fIdx].isCounting()) {
// counting log vars were already raised on counting conversion
exp = constr_->getConditionalCount (excl - args_[fIdx].countedLogVar());
} else {
exp = constr_->getConditionalCount (excl);
}
constr_->remove (excl);
TFactor<ProbFormula>::sumOutIndex (fIdx);
LogAware::pow (params_, exp);
}
void
Parfactor::multiply (Parfactor& g)
{
alignAndExponentiate (this, &g);
TFactor<ProbFormula>::multiply (g);
constr_->join (g.constr(), true);
simplifyGrounds();
assert (constr_->isCartesianProduct (countedLogVars()));
}
bool
Parfactor::canCountConvert (LogVar X)
{
if (nrFormulas (X) != 1) {
return false;
}
size_t fIdx = indexOfLogVar (X);
if (args_[fIdx].isCounting()) {
return false;
}
if (constr_->isCountNormalized (X) == false) {
return false;
}
if (constr_->getConditionalCount (X) == 1) {
return false;
}
if (constr_->isCartesianProduct (countedLogVars() | X) == false) {
return false;
}
return true;
}
void
Parfactor::countConvert (LogVar X)
{
size_t fIdx = indexOfLogVar (X);
assert (constr_->isCountNormalized (X));
assert (constr_->getConditionalCount (X) > 1);
assert (canCountConvert (X));
unsigned N = constr_->getConditionalCount (X);
unsigned R = ranges_[fIdx];
unsigned H = HistogramSet::nrHistograms (N, R);
vector<Histogram> histograms = HistogramSet::getHistograms (N, R);
Indexer indexer (ranges_);
vector<Params> sumout (params_.size() / R);
unsigned count = 0;
while (indexer.valid()) {
sumout[count].reserve (R);
for (unsigned r = 0; r < R; r++) {
sumout[count].push_back (params_[indexer]);
indexer.incrementDimension (fIdx);
}
count ++;
indexer.resetDimension (fIdx);
indexer.incrementExceptDimension (fIdx);
}
params_.clear();
params_.reserve (sumout.size() * H);
ranges_[fIdx] = H;
MapIndexer mapIndexer (ranges_, fIdx);
while (mapIndexer.valid()) {
double prod = LogAware::multIdenty();
size_t i = mapIndexer;
unsigned h = mapIndexer[fIdx];
for (unsigned r = 0; r < R; r++) {
if (Globals::logDomain) {
prod += LogAware::pow (sumout[i][r], histograms[h][r]);
} else {
prod *= LogAware::pow (sumout[i][r], histograms[h][r]);
}
}
params_.push_back (prod);
++ mapIndexer;
}
args_[fIdx].setCountedLogVar (X);
simplifyCountingFormulas (fIdx);
}
void
Parfactor::expand (LogVar X, LogVar X_new1, LogVar X_new2)
{
size_t fIdx = indexOfLogVar (X);
assert (fIdx != args_.size());
assert (args_[fIdx].isCounting());
unsigned N1 = constr_->getConditionalCount (X_new1);
unsigned N2 = constr_->getConditionalCount (X_new2);
unsigned N = N1 + N2;
unsigned R = args_[fIdx].range();
unsigned H1 = HistogramSet::nrHistograms (N1, R);
unsigned H2 = HistogramSet::nrHistograms (N2, R);
vector<Histogram> histograms = HistogramSet::getHistograms (N, R);
vector<Histogram> histograms1 = HistogramSet::getHistograms (N1, R);
vector<Histogram> histograms2 = HistogramSet::getHistograms (N2, R);
vector<unsigned> sumIndexes;
sumIndexes.reserve (H1 * H2);
for (unsigned i = 0; i < H1; i++) {
for (unsigned j = 0; j < H2; j++) {
Histogram hist = histograms1[i];
hist += histograms2[j];
sumIndexes.push_back (HistogramSet::findIndex (hist, histograms));
}
}
expandPotential (fIdx, H1 * H2, sumIndexes);
args_.insert (args_.begin() + fIdx + 1, args_[fIdx]);
args_[fIdx].rename (X, X_new1);
args_[fIdx + 1].rename (X, X_new2);
if (H1 == 2) {
args_[fIdx].clearCountedLogVar();
}
if (H2 == 2) {
args_[fIdx + 1].clearCountedLogVar();
}
ranges_.insert (ranges_.begin() + fIdx + 1, H2);
ranges_[fIdx] = H1;
}
void
Parfactor::fullExpand (LogVar X)
{
size_t fIdx = indexOfLogVar (X);
assert (fIdx != args_.size());
assert (args_[fIdx].isCounting());
unsigned N = constr_->getConditionalCount (X);
unsigned R = args_[fIdx].range();
vector<Histogram> originHists = HistogramSet::getHistograms (N, R);
vector<Histogram> expandHists = HistogramSet::getHistograms (1, R);
assert (ranges_[fIdx] == originHists.size());
vector<unsigned> sumIndexes;
sumIndexes.reserve (N * R);
Ranges expandRanges (N, R);
Indexer indexer (expandRanges);
while (indexer.valid()) {
vector<unsigned> hist (R, 0);
for (unsigned n = 0; n < N; n++) {
hist += expandHists[indexer[n]];
}
sumIndexes.push_back (HistogramSet::findIndex (hist, originHists));
++ indexer;
}
expandPotential (fIdx, std::pow (R, N), sumIndexes);
ProbFormula f = args_[fIdx];
args_.erase (args_.begin() + fIdx);
ranges_.erase (ranges_.begin() + fIdx);
LogVars newLvs = constr_->expand (X);
assert (newLvs.size() == N);
for (unsigned i = 0 ; i < N; i++) {
ProbFormula newFormula (f.functor(), f.logVars(), f.range());
newFormula.rename (X, newLvs[i]);
args_.insert (args_.begin() + fIdx + i, newFormula);
ranges_.insert (ranges_.begin() + fIdx + i, R);
}
}
void
Parfactor::reorderAccordingGrounds (const Grounds& grounds)
{
ProbFormulas newFormulas;
for (size_t i = 0; i < grounds.size(); i++) {
for (size_t j = 0; j < args_.size(); j++) {
if (grounds[i].functor() == args_[j].functor() &&
grounds[i].arity() == args_[j].arity()) {
constr_->moveToTop (args_[j].logVars());
if (constr_->containsTuple (grounds[i].args())) {
newFormulas.push_back (args_[j]);
break;
}
}
}
assert (newFormulas.size() == i + 1);
}
reorderArguments (newFormulas);
}
void
Parfactor::absorveEvidence (const ProbFormula& formula, unsigned evidence)
{
size_t fIdx = indexOf (formula);
assert (fIdx != args_.size());
LogVarSet excl = exclusiveLogVars (fIdx);
assert (args_[fIdx].isCounting() == false);
assert (constr_->isCountNormalized (excl));
LogAware::pow (params_, constr_->getConditionalCount (excl));
TFactor<ProbFormula>::absorveEvidence (formula, evidence);
constr_->remove (excl);
}
void
Parfactor::setNewGroups (void)
{
for (size_t i = 0; i < args_.size(); i++) {
args_[i].setGroup (ProbFormula::getNewGroup());
}
}
void
Parfactor::applySubstitution (const Substitution& theta)
{
for (size_t i = 0; i < args_.size(); i++) {
LogVars& lvs = args_[i].logVars();
for (size_t j = 0; j < lvs.size(); j++) {
lvs[j] = theta.newNameFor (lvs[j]);
}
if (args_[i].isCounting()) {
LogVar clv = args_[i].countedLogVar();
args_[i].setCountedLogVar (theta.newNameFor (clv));
}
}
constr_->applySubstitution (theta);
}
size_t
Parfactor::indexOfGround (const Ground& ground) const
{
size_t idx = args_.size();
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].functor() == ground.functor() &&
args_[i].arity() == ground.arity()) {
constr_->moveToTop (args_[i].logVars());
if (constr_->containsTuple (ground.args())) {
idx = i;
break;
}
}
}
return idx;
}
PrvGroup
Parfactor::findGroup (const Ground& ground) const
{
size_t idx = indexOfGround (ground);
return idx == args_.size()
? std::numeric_limits<PrvGroup>::max()
: args_[idx].group();
}
bool
Parfactor::containsGround (const Ground& ground) const
{
return findGroup (ground) != std::numeric_limits<PrvGroup>::max();
}
bool
Parfactor::containsGrounds (const Grounds& grounds) const
{
Tuple tuple;
LogVars tupleLvs;
for (size_t i = 0; i < grounds.size(); i++) {
size_t idx = indexOfGround (grounds[i]);
if (idx == args_.size()) {
return false;
}
LogVars lvs = args_[idx].logVars();
for (size_t j = 0; j < lvs.size(); j++) {
if (Util::contains (tupleLvs, lvs[j]) == false) {
tuple.push_back (grounds[i].args()[j]);
tupleLvs.push_back (lvs[j]);
}
}
}
constr_->moveToTop (tupleLvs);
return constr_->containsTuple (tuple);
}
bool
Parfactor::containsGroup (PrvGroup group) const
{
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].group() == group) {
return true;
}
}
return false;
}
bool
Parfactor::containsGroups (vector<PrvGroup> groups) const
{
for (size_t i = 0; i < groups.size(); i++) {
if (containsGroup (groups[i]) == false) {
return false;
}
}
return true;
}
unsigned
Parfactor::nrFormulas (LogVar X) const
{
unsigned count = 0;
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].contains (X)) {
count ++;
}
}
return count;
}
int
Parfactor::indexOfLogVar (LogVar X) const
{
size_t idx = args_.size();
assert (nrFormulas (X) == 1);
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].contains (X)) {
idx = i;
break;
}
}
return idx;
}
int
Parfactor::indexOfGroup (PrvGroup group) const
{
size_t pos = args_.size();
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].group() == group) {
pos = i;
break;
}
}
return pos;
}
unsigned
Parfactor::nrFormulasWithGroup (PrvGroup group) const
{
unsigned count = 0;
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].group() == group) {
count ++;
}
}
return count;
}
vector<PrvGroup>
Parfactor::getAllGroups (void) const
{
vector<PrvGroup> groups (args_.size());
for (size_t i = 0; i < args_.size(); i++) {
groups[i] = args_[i].group();
}
return groups;
}
string
Parfactor::getLabel (void) const
{
stringstream ss;
ss << "phi(" ;
for (size_t i = 0; i < args_.size(); i++) {
if (i != 0) ss << "," ;
ss << args_[i];
}
ss << ")" ;
ConstraintTree copy (*constr_);
copy.moveToTop (copy.logVarSet().elements());
ss << "|" << copy.tupleSet();
return ss.str();
}
void
Parfactor::print (bool printParams) const
{
cout << "Formulas: " ;
for (size_t i = 0; i < args_.size(); i++) {
if (i != 0) cout << ", " ;
cout << args_[i];
}
cout << endl;
if (args_[0].group() != Util::maxUnsigned()) {
vector<string> groups;
for (size_t i = 0; i < args_.size(); i++) {
groups.push_back (string ("g") + Util::toString (args_[i].group()));
}
cout << "Groups: " << groups << endl;
}
cout << "LogVars: " << constr_->logVarSet() << endl;
cout << "Ranges: " << ranges_ << endl;
if (printParams == false) {
cout << "Params: " ;
if (params_.size() <= 32) {
cout.precision(10);
cout << params_ << endl;
} else {
cout << "|" << params_.size() << "|" << endl;
}
}
ConstraintTree copy (*constr_);
copy.moveToTop (copy.logVarSet().elements());
cout << "Tuples: " << copy.tupleSet() << endl;
if (printParams) {
printParameters();
}
}
void
Parfactor::printParameters (void) const
{
vector<string> jointStrings;
Indexer indexer (ranges_);
while (indexer.valid()) {
stringstream ss;
for (size_t i = 0; i < args_.size(); i++) {
if (i != 0) ss << ", " ;
if (args_[i].isCounting()) {
unsigned N = constr_->getConditionalCount (
args_[i].countedLogVar());
HistogramSet hs (N, args_[i].range());
unsigned c = 0;
while (c < indexer[i]) {
hs.nextHistogram();
c ++;
}
ss << hs;
} else {
ss << indexer[i];
}
}
jointStrings.push_back (ss.str());
++ indexer;
}
for (size_t i = 0; i < params_.size(); i++) {
cout << "f(" << jointStrings[i] << ")" ;
cout << " = " << params_[i] << endl;
}
}
void
Parfactor::printProjections (void) const
{
ConstraintTree copy (*constr_);
LogVarSet Xs = copy.logVarSet();
for (size_t i = 0; i < Xs.size(); i++) {
cout << "-> projection of " << Xs[i] << ": " ;
cout << copy.tupleSet ({Xs[i]}) << endl;
}
}
void
Parfactor::expandPotential (
size_t fIdx,
unsigned newRange,
const vector<unsigned>& sumIndexes)
{
ullong newSize = (params_.size() / ranges_[fIdx]) * newRange;
if (newSize > params_.max_size()) {
cerr << "Error: an overflow occurred when performing expansion." ;
cerr << endl;
exit (EXIT_FAILURE);
}
Params backup = params_;
params_.clear();
params_.reserve (newSize);
size_t prod = 1;
vector<size_t> offsets (ranges_.size());
for (size_t i = ranges_.size(); i-- > 0; ) {
offsets[i] = prod;
prod *= ranges_[i];
}
size_t index = 0;
ranges_[fIdx] = newRange;
vector<unsigned> indices (ranges_.size(), 0);
for (size_t k = 0; k < newSize; k++) {
assert (index < backup.size());
params_.push_back (backup[index]);
for (size_t i = ranges_.size(); i-- > 0; ) {
indices[i] ++;
if (i == fIdx) {
if (indices[i] != ranges_[i]) {
int diff = sumIndexes[indices[i]] - sumIndexes[indices[i] - 1];
index += diff * offsets[i];
break;
} else {
// last index contains the old range minus 1
index -= sumIndexes.back() * offsets[i];
indices[i] = 0;
}
} else {
if (indices[i] != ranges_[i]) {
index += offsets[i];
break;
} else {
index -= (ranges_[i] - 1) * offsets[i];
indices[i] = 0;
}
}
}
}
}
void
Parfactor::simplifyCountingFormulas (size_t fIdx)
{
// check if we can simplify the parfactor
for (size_t i = 0; i < args_.size(); i++) {
if (i != fIdx &&
args_[i].isCounting() &&
args_[i].group() == args_[fIdx].group()) {
// if they only differ in the name of the counting log var
if ((args_[i].logVarSet() - args_[i].countedLogVar()) ==
(args_[fIdx].logVarSet()) - args_[fIdx].countedLogVar() &&
ranges_[i] == ranges_[fIdx]) {
simplifyParfactor (fIdx, i);
break;
}
}
}
}
void
Parfactor::simplifyGrounds (void)
{
if (args_.size() == 1) {
return;
}
LogVarSet singletons = constr_->singletons();
for (long i = 0; i < (long)args_.size() - 1; i++) {
for (size_t j = i + 1; j < args_.size(); j++) {
if (args_[i].group() == args_[j].group() &&
singletons.contains (args_[i].logVarSet()) &&
singletons.contains (args_[j].logVarSet())) {
simplifyParfactor (i, j);
i --;
break;
}
}
}
}
bool
Parfactor::canMultiply (Parfactor* g1, Parfactor* g2)
{
std::pair<LogVars, LogVars> res = getAlignLogVars (g1, g2);
LogVarSet Xs_1 (res.first);
LogVarSet Xs_2 (res.second);
LogVarSet Y_1 = g1->logVarSet() - Xs_1;
LogVarSet Y_2 = g2->logVarSet() - Xs_2;
Y_1 -= g1->countedLogVars();
Y_2 -= g2->countedLogVars();
return g1->constr()->isCountNormalized (Y_1) &&
g2->constr()->isCountNormalized (Y_2);
}
void
Parfactor::simplifyParfactor (size_t fIdx1, size_t fIdx2)
{
Params backup = params_;
params_.clear();
Indexer indexer (ranges_);
while (indexer.valid()) {
if (indexer[fIdx1] == indexer[fIdx2]) {
params_.push_back (backup[indexer]);
}
++ indexer;
}
for (size_t i = 0; i < args_[fIdx2].logVars().size(); i++) {
if (nrFormulas (args_[fIdx2].logVars()[i]) == 1) {
constr_->remove ({ args_[fIdx2].logVars()[i] });
}
}
args_.erase (args_.begin() + fIdx2);
ranges_.erase (ranges_.begin() + fIdx2);
}
std::pair<LogVars, LogVars>
Parfactor::getAlignLogVars (Parfactor* g1, Parfactor* g2)
{
g1->simplifyGrounds();
g2->simplifyGrounds();
LogVars Xs_1, Xs_2;
TinySet<size_t> matchedI;
TinySet<size_t> matchedJ;
ProbFormulas& formulas1 = g1->arguments();
ProbFormulas& formulas2 = g2->arguments();
for (size_t i = 0; i < formulas1.size(); i++) {
for (size_t j = 0; j < formulas2.size(); j++) {
if (formulas1[i].group() == formulas2[j].group() &&
g1->range (i) == g2->range (j) &&
matchedI.contains (i) == false &&
matchedJ.contains (j) == false) {
Util::addToVector (Xs_1, formulas1[i].logVars());
Util::addToVector (Xs_2, formulas2[j].logVars());
matchedI.insert (i);
matchedJ.insert (j);
}
}
}
return make_pair (Xs_1, Xs_2);
}
void
Parfactor::alignAndExponentiate (Parfactor* g1, Parfactor* g2)
{
alignLogicalVars (g1, g2);
LogVarSet comm = g1->logVarSet() & g2->logVarSet();
LogVarSet Y_1 = g1->logVarSet() - comm;
LogVarSet Y_2 = g2->logVarSet() - comm;
Y_1 -= g1->countedLogVars();
Y_2 -= g2->countedLogVars();
assert (g1->constr()->isCountNormalized (Y_1));
assert (g2->constr()->isCountNormalized (Y_2));
unsigned condCount1 = g1->constr()->getConditionalCount (Y_1);
unsigned condCount2 = g2->constr()->getConditionalCount (Y_2);
LogAware::pow (g1->params(), 1.0 / condCount2);
LogAware::pow (g2->params(), 1.0 / condCount1);
}
void
Parfactor::alignLogicalVars (Parfactor* g1, Parfactor* g2)
{
std::pair<LogVars, LogVars> res = getAlignLogVars (g1, g2);
const LogVars& alignLvs1 = res.first;
const LogVars& alignLvs2 = res.second;
// cout << "ALIGNING :::::::::::::::::" << endl;
// g1->print();
// cout << "AND" << endl;
// g2->print();
// cout << "-> align lvs1 = " << alignLvs1 << endl;
// cout << "-> align lvs2 = " << alignLvs2 << endl;
LogVar freeLogVar (0);
Substitution theta1, theta2;
for (size_t i = 0; i < alignLvs1.size(); i++) {
bool b1 = theta1.containsReplacementFor (alignLvs1[i]);
bool b2 = theta2.containsReplacementFor (alignLvs2[i]);
if (b1 == false && b2 == false) {
theta1.add (alignLvs1[i], freeLogVar);
theta2.add (alignLvs2[i], freeLogVar);
++ freeLogVar;
} else if (b1 == false && b2) {
theta1.add (alignLvs1[i], theta2.newNameFor (alignLvs2[i]));
} else if (b1 && b2 == false) {
theta2.add (alignLvs2[i], theta1.newNameFor (alignLvs1[i]));
}
}
const LogVarSet& allLvs1 = g1->logVarSet();
for (size_t i = 0; i < allLvs1.size(); i++) {
if (theta1.containsReplacementFor (allLvs1[i]) == false) {
theta1.add (allLvs1[i], freeLogVar);
++ freeLogVar;
}
}
const LogVarSet& allLvs2 = g2->logVarSet();
for (size_t i = 0; i < allLvs2.size(); i++) {
if (theta2.containsReplacementFor (allLvs2[i]) == false) {
theta2.add (allLvs2[i], freeLogVar);
++ freeLogVar;
}
}
// handle this type of situation:
// g1 = p(X), q(X) ; X in {(p1),(p2)}
// g2 = p(X), q(Y) ; (X,Y) in {(p1,p2),(p2,p1)}
LogVars discardedLvs1 = theta1.getDiscardedLogVars();
for (size_t i = 0; i < discardedLvs1.size(); i++) {
if (g1->constr()->isSingleton (discardedLvs1[i]) &&
g1->nrFormulas (discardedLvs1[i]) == 1) {
g1->constr()->remove (discardedLvs1[i]);
} else {
LogVar X_new = ++ g1->constr()->logVarSet().back();
theta1.rename (discardedLvs1[i], X_new);
}
}
LogVars discardedLvs2 = theta2.getDiscardedLogVars();
for (size_t i = 0; i < discardedLvs2.size(); i++) {
if (g2->constr()->isSingleton (discardedLvs2[i]) &&
g2->nrFormulas (discardedLvs2[i]) == 1) {
g2->constr()->remove (discardedLvs2[i]);
} else {
LogVar X_new = ++ g2->constr()->logVarSet().back();
theta2.rename (discardedLvs2[i], X_new);
}
}
// cout << "theta1: " << theta1 << endl;
// cout << "theta2: " << theta2 << endl;
g1->applySubstitution (theta1);
g2->applySubstitution (theta2);
}