PndMvaVarPCATransform.h

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/* **********************************************
 * MVA variable transformation interface.       *
 * Principal Components Analysis (PCA).         *
 * Author: M.Babai@rug.nl                       *
 * LICENSE:                                     *
 * Version:                                     *
 * License:                                     *
 * **********************************************
 */
/*
 * This code is directly based on the Cern Root implementation of PCA.
 */
//#pragma once
#ifndef PND_MVA_VAR_PCA_TRANSFORM_H
#define PND_MVA_VAR_PCA_TRANSFORM_H

// C & C++ includes
#include <cassert>
#include <cstdlib>
#include <iostream>
#include <vector>
#include <utility>

// ROOT includes.
#include "TPrincipal.h"

class PndMvaVarPCATransform {
 public:
  explicit PndMvaVarPCATransform();

  virtual ~PndMvaVarPCATransform();

  bool InitPCATranformation(std::vector<std::pair<std::string, std::vector<float> *>> const &dat);

  std::vector<float> *Transform(std::vector<float> const &evd) const;

  inline TVectorD const &GetMeanValues() const;

  inline TMatrixD const &GetEigenVectors() const;

  void SetMeanVector(TVectorD const &vect);

  void SetEigenVectors(TMatrixD const &mat);

 private:
  PndMvaVarPCATransform(PndMvaVarPCATransform const &ot);
  PndMvaVarPCATransform &operator=(PndMvaVarPCATransform const &ot);

  /*
   * Given a list of n-dimensional data points, Computes PCA for the
   * current dataset.
   */
  void ComputePrincipalComponents(std::vector<std::pair<std::string, std::vector<float> *>> const &dat);

  // Mean values
  TVectorD *m_MeanValues;

  // Eigenvectors
  TMatrixD *m_EigenVectors;
};
//____________________ ENd of interface definition

inline TVectorD const &PndMvaVarPCATransform::GetMeanValues() const
{
  return (*m_MeanValues);
}

inline TMatrixD const &PndMvaVarPCATransform::GetEigenVectors() const
{
  return (*m_EigenVectors);
}
#endif