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/*class Learnerx
{
public:
virtual void Init(const vector<SparseVector<double> >& kbest, const Scores& scores) {};
virtual void Update(SparseVector<double>& lambdas);
};*/
class SofiaLearner //: public Learnerx FIXME
{
// TODO bool invert_score
public:
void
Init( const size_t sid, const vector<SparseVector<double> >& kbest, /*const*/ Scores& scores )
{
assert( kbest.size() == scores.size() );
ofstream o;
//unlink( "/tmp/sofia_ml_training_stupid" );
o.open( "/tmp/sofia_ml_training_normalx", ios::trunc ); // TODO randomize, filename exists
int fid = 0;
map<int,int>::iterator ff;
for ( size_t k = 0; k < kbest.size(); ++k ) {
map<int,double> m;
SparseVector<double>::const_iterator it = kbest[k].begin();
o << scores[k].GetScore();
for ( ; it != kbest[k].end(); ++it) {
ff = fmap.find( it->first );
if ( ff == fmap.end() ) {
fmap.insert( pair<int,int>(it->first, fid) );
fmap1.insert( pair<int,int>(fid, it->first) );
fid++;
}
m.insert(pair<int,double>(fmap[it->first], it->second));
}
map<int,double>::iterator ti = m.begin();
for ( ; ti != m.end(); ++ti ) {
o << " " << ti->first << ":" << ti->second;
}
o << endl;
}
o.close();
}
void
Update(SparseVector<double>& lambdas)
{
string call = "./sofia-ml --training_file /tmp/sofia_ml_training_normalx --model_out /tmp/sofia_ml_model_normalx --loop_type stochastic --lambda 100 --dimensionality ";
std::stringstream out;
out << fmap.size();
call += out.str();
call += " &>/dev/null";
system ( call.c_str() );
ifstream i;
//unlink( "/tmp/sofia_ml_model_stupid" );
i.open( "/tmp/sofia_ml_model_normalx", ios::in );
string model;
getline( i, model );
vector<string> strs;
boost::split( strs, model, boost::is_any_of(" ") );
int j = 0;
for ( vector<string>::iterator it = strs.begin(); it != strs.end(); ++it ) {
lambdas.set_value(fmap1[j], atof( it->c_str() ) );
j++;
}
}
private:
map<int,int> fmap;
map<int,int> fmap1;
};
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