statscore_t RandomDirectionOptimizer::TrueRun(Point& P) const
{
statscore_t prevscore = P.GetScore();
// do specified number of random direction optimizations
unsigned int nrun = 0;
unsigned int nrun_no_change = 0;
for (; nrun_no_change < m_num_random_directions; nrun++, nrun_no_change++)
{
// choose a random direction in which to optimize
Point direction;
direction.Randomize();
//find the minimum on the line
statscore_t score = LineOptimize(P, direction, P);
if (verboselevel() > 4) {
cerr << "direction: " << direction << " => " << score;
cerr << " (" << (score-prevscore) << ")" << endl;
cerr << "\tending point: " << P << " => " << score << endl;
}
if (score-prevscore > kEPS)
nrun_no_change = 0;
prevscore = score;
}
if (verboselevel() > 2) {
cerr << "end Powell Algo, nrun=" << nrun << endl;
}
return prevscore;
}
statscore_t Optimizer::Run(Point& P) const
{
if (!m_feature_data) {
cerr << "error trying to optimize without Features loaded" << endl;
exit(2);
}
if (!m_scorer) {
cerr << "error trying to optimize without a Scorer loaded" << endl;
exit(2);
}
if (m_scorer->getReferenceSize() != m_feature_data->size()) {
cerr << "error length mismatch between feature file and score file" << endl;
exit(2);
}
P.SetScore(GetStatScore(P));
if (verboselevel () > 2) {
cerr << "Starting point: " << P << " => " << P.GetScore() << endl;
}
statscore_t score = TrueRun(P);
// just in case its not done in TrueRun
P.SetScore(score);
if (verboselevel() > 2) {
cerr << "Ending point: " << P << " => " << score << endl;
}
return score;
}
statscore_t SimpleOptimizer::TrueRun(Point& P) const
{
statscore_t prevscore = 0;
statscore_t bestscore = MIN_FLOAT;
Point best;
// If P is already defined and provides a score,
// We must improve over this score.
if (P.GetScore() > bestscore) {
bestscore = P.GetScore();
best = P;
}
int nrun = 0;
do {
++nrun;
if (verboselevel() > 2 && nrun > 1)
cerr << "last diff=" << bestscore-prevscore << " nrun " << nrun << endl;
prevscore = bestscore;
Point linebest;
for (unsigned int d = 0; d < Point::getdim() + m_num_random_directions; d++) {
if (verboselevel() > 4) {
// cerr<<"minimizing along direction "<<d<<endl;
cerr << "starting point: " << P << " => " << prevscore << endl;
}
Point direction;
if (d < Point::getdim()) { // regular updates along one dimension
for (unsigned int i = 0; i < Point::getdim(); i++)
direction[i]=0.0;
direction[d]=1.0;
}
else { // random direction update
direction.Randomize();
}
statscore_t curscore = LineOptimize(P, direction, linebest);//find the minimum on the line
if (verboselevel() > 5) {
cerr << "direction: " << d << " => " << curscore << endl;
cerr << "\tending point: "<< linebest << " => " << curscore << endl;
}
if (curscore > bestscore) {
bestscore = curscore;
best = linebest;
if (verboselevel() > 3) {
cerr << "new best dir:" << d << " (" << nrun << ")" << endl;
cerr << "new best Point " << best << " => " << curscore << endl;
}
}
}
P = best; //update the current vector with the best point on all line tested
if (verboselevel() > 3)
cerr << nrun << "\t" << P << endl;
} while (bestscore-prevscore > kEPS);
if (verboselevel() > 2) {
cerr << "end Powell Algo, nrun=" << nrun << endl;
cerr << "last diff=" << bestscore-prevscore << endl;
cerr << "\t" << P << endl;
}
return bestscore;
}