PyMethodBase.h

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// @(#)root/tmva/pymva $Id$
// Authors: Omar Zapata, Lorenzo Moneta, Sergei Gleyzer 2015

/**********************************************************************************
 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis       *
 * Package: TMVA                                                                  *
 * Class  : PyMethodBase                                                          *
 * Web    : http://oproject.org                                                   *
 *                                                                                *
 * Description:                                                                   *
 *      Virtual base class for all MVA method based on Python                     *
 *                                                                                *
 **********************************************************************************/

#ifndef ROOT_TMVA_PyMethodBase
#define ROOT_TMVA_PyMethodBase

////////////////////////////////////////////////////////////////////////////////
//                                                                            //
// PyMethodBase                                                               //
//                                                                            //
// Virtual base class for all TMVA method based on Python/scikit-learn        //
//                                                                            //
////////////////////////////////////////////////////////////////////////////////

#include "TMVA/MethodBase.h"
#include "TMVA/Types.h"

#include "Rtypes.h"
#include "TString.h"

class TFile;
class TGraph;
class TTree;
class TDirectory;
class TSpline;
class TH1F;
class TH1D;

struct _object;
typedef _object PyObject;

// needed by NPY_API_VERSION
#include "numpy/numpyconfig.h"

#if (NPY_API_VERSION >= 0x00000007 )
struct tagPyArrayObject;
typedef tagPyArrayObject PyArrayObject;
#else
struct PyArrayObject;
#endif


namespace TMVA {

   class Ranking;
   class PDF;
   class TSpline1;
   class MethodCuts;
   class MethodBoost;
   class DataSetInfo;

   class PyMethodBase : public MethodBase {

      friend class Factory;
   public:

      // default constructur
      PyMethodBase(const TString &jobName,
                   Types::EMVA methodType,
                   const TString &methodTitle,
                   DataSetInfo &dsi,
                   const TString &theOption = "");

      // constructor used for Testing + Application of the MVA, only (no training),
      // using given weight file
      PyMethodBase(Types::EMVA methodType,
                   DataSetInfo &dsi,
                   const TString &weightFile);

      // default destructur
      virtual ~PyMethodBase();
      //basic python related function
      static void PyInitialize();
      static int  PyIsInitialized();
      static void PyFinalize();
      static void PySetProgramName(TString name);
      static TString Py_GetProgramName();

      static PyObject *Eval(TString code);//required to parse booking options from string to pyobjects
      static void Serialize(TString file,PyObject *classifier);
      static void UnSerialize(TString file,PyObject** obj);
      
      virtual void     Train() = 0;
      // options treatment
      virtual void     Init()           = 0;
      virtual void     DeclareOptions() = 0;
      virtual void     ProcessOptions() = 0;
      // create ranking
      virtual const Ranking *CreateRanking() = 0;

      virtual Double_t GetMvaValue(Double_t *errLower = 0, Double_t *errUpper = 0) = 0;

      Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets) = 0;
   protected:
      // the actual "weights"
      virtual void AddWeightsXMLTo(void *parent) const = 0;
      virtual void ReadWeightsFromXML(void *wghtnode) = 0;
      virtual void ReadWeightsFromStream(std::istream &) = 0;        // backward compatibility      
      virtual void ReadWeightsFromStream(TFile &) {}                 // backward compatibility


      virtual void ReadModelFromFile() = 0;

      // signal/background classification response for all current set of data 
      virtual std::vector<Double_t> GetMvaValues(Long64_t firstEvt = 0, Long64_t lastEvt = -1, Bool_t logProgress = false);

   protected:
      
      PyObject *fModule;//Module to load
      PyObject *fClassifier;//Classifier object

      PyArrayObject *fTrainData;
      PyArrayObject *fTrainDataWeights;//array of weights
      PyArrayObject *fTrainDataClasses;//array with sig/bgk class
   private:

      static PyObject *fModuleBuiltin;
      static PyObject *fEval;//eval funtion from python
      static PyObject *fOpen;//open function for files
   protected:
      static PyObject *fModulePickle;  //Module for model persistence
      static PyObject *fPickleDumps;  //Function to dumps PyObject information into string
      static PyObject *fPickleLoads;  //Function to load PyObject information from string

      static PyObject *fMain;//module __main__ to get namesapace local and global
      static PyObject *fGlobalNS;//global namesapace
      static PyObject *fLocalNS;//local namesapace

      
      ClassDef(PyMethodBase, 0) // Virtual base class for all TMVA method

   };
} // namespace TMVA

#endif