AbstractBestSubsets.hh

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#ifndef _BEST_SUBSETS_HH_
#define _BEST_SUBSETS_HH_

#include <string>
#include <openmodeller/om.hh>

#include "AlgorithmRun.hh"


/****************************************************************/
/************************* GARP Algorithm ***********************/

class AbstractBestSubsets : public AlgorithmImpl
{
public:
  AbstractBestSubsets( AlgMetadata const * );
  virtual ~AbstractBestSubsets() = 0;

  int needNormalization();
  
  int initialize();
  
  int iterate();
  
  int done() const;

  float getProgress() const;

  //
  // Methods used to project the model
  //
  
  Scalar getValue( const Sample& x ) const;
  
  int getConvergence( Scalar * const val ) const;

  /*
   */
protected:
  virtual void _getConfiguration( ConfigurationPtr& ) const;
  virtual void _setConfiguration( const ConstConfigurationPtr & );

  mutable std::string _subAlgorithm; //< mutable so it can be assigned in needNormalization if necessary

private:
  int numActiveThreads();
  int earlyTerminationConditionMet();
  int calculateBestSubset();
  void sortRuns(AlgorithmRun ** runList, int nelements, int errorType);

  //
  // best subsets parameters
  //
  double _trainProp;
  int _totalRuns;
  double _omissionThreshold;
  int _modelsUnderOmission;
  double _commissionThreshold;
  int _commissionSampleSize;
  int _maxThreads;

  bool _softOmissionThreshold;
  int _currentModelsUnderOmissionThreshold;

  //
  // Internal data structures for Best Subsets
  //
  AlgorithmRun ** _finishedRun;
  AlgorithmRun ** _activeRun;
  AlgorithmRun ** _bestRun;

  int _numFinishedRuns;
  int _numActiveRuns;
  int _numBestRuns;

  int _done;

  mutable float _maxProgress;

};


#endif