refactoring, cleaning up

1 files changed, 79 insertions, 54 deletions

diff --git a/dtrain/learner.h b/dtrain/learner.h
index a953284d..038749e2 100644
--- a/dtrain/learner.h
+++ b/dtrain/learner.h
@@ -1,71 +1,96 @@
-/*class Learnerx
+#ifndef _DTRAIN_LEARNER_H_
+#define _DTRAIN_LEARNER_H_
+
+#include <string>
+#include <vector>
+#include <map>
+
+#include "sparse_vector.h"
+#include "score.h"
+
+
+namespace dtrain
+{
+
+
+class Learner
 {
   public:
-    virtual void Init(const vector<SparseVector<double> >& kbest, const Scores& scores) {};
-    virtual void Update(SparseVector<double>& lambdas);
-};*/
+    virtual void Init( const vector<SparseVector<double> >& kbest, const Scores& scores,
+                       const bool invert_score = false ) {};
+    virtual void Update( SparseVector<double>& lambdas ) {};
+};
 
-class SofiaLearner //: public Learnerx FIXME
+
+class SofiaLearner : public Learner
 {
-  // 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;
+    void
+    Init( const size_t sid, const vector<SparseVector<double> >& kbest, /*const FIXME*/ Scores& scores,
+          const bool invert_score = false )
+    {
+      assert( kbest.size() == scores.size() );
+      ofstream o;
+      unlink( "/tmp/sofia_ml_training" );
+      o.open( "/tmp/sofia_ml_training", 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++;
+      double score;
+      for ( size_t k = 0; k < kbest.size(); ++k ) {
+        map<int,double> m;
+        SparseVector<double>::const_iterator it = kbest[k].begin();
+        score = scores[k].GetScore();
+        if ( invert_score ) score = -score;
+        o << score;
+        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) );
         }
-        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;
+        map<int,double>::iterator ti = m.begin();
+        for ( ; ti != m.end(); ++ti ) {
+          o << " " << ti->first << ":" << ti->second;
+        }
+        o << endl;
       }
-      o << endl;
+      o.close();
     }
-    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++;
+    void
+    Update(SparseVector<double>& lambdas)
+    {
+      string call = "./sofia-ml --training_file /tmp/sofia_ml_training --model_out /tmp/sofia_ml_model --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" );
+      i.open( "/tmp/sofia_ml_model", 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;
 };
 
+
+} // namespace
+
+#endif
+