// Class: ReadElectron_Upstream_TMVA
// Automatically generated by MethodBase::MakeClass
//

/* configuration options =====================================================

#GEN -*-*-*-*-*-*-*-*-*-*-*- general info -*-*-*-*-*-*-*-*-*-*-*-

Method         : MLP::Electron_Upstream_TMVA
TMVA Release   : 4.2.0         [262656]
ROOT Release   : 5.34/18       [336402]
Creator        : jonesc
Date           : Wed Jun 18 01:06:56 2014
Host           : ec-slc6-x86-64-spi-9
Dir            : /var/pcfst/r03/lhcb/jonesc/ANNPID/results/MC12/TrainHeavy/TrainPhysTksNoGhosts-EvalPhysTks-ReweightRICH2/TMVA-NoPreSels-NoGECs/MLP/Norm/ScaleF1.2/BP/NCycles750/CE/tanh/CVTest15/CVImp1e-16/NotUseRegulator/Electron/Upstream
Training events: 1200000
Analysis type  : [Classification]


#OPT -*-*-*-*-*-*-*-*-*-*-*-*- options -*-*-*-*-*-*-*-*-*-*-*-*-

# Set by User:
NCycles: "750" [Number of training cycles]
HiddenLayers: "24" [Specification of hidden layer architecture]
NeuronType: "tanh" [Neuron activation function type]
EstimatorType: "CE" [MSE (Mean Square Estimator) for Gaussian Likelihood or CE(Cross-Entropy) for Bernoulli Likelihood]
V: "True" [Verbose output (short form of "VerbosityLevel" below - overrides the latter one)]
VarTransform: "Norm" [List of variable transformations performed before training, e.g., "D_Background,P_Signal,G,N_AllClasses" for: "Decorrelation, PCA-transformation, Gaussianisation, Normalisation, each for the given class of events ('AllClasses' denotes all events of all classes, if no class indication is given, 'All' is assumed)"]
H: "True" [Print method-specific help message]
TrainingMethod: "BP" [Train with Back-Propagation (BP), BFGS Algorithm (BFGS), or Genetic Algorithm (GA - slower and worse)]
EpochMonitoring: "True" [Provide epoch-wise monitoring plots according to TestRate (caution: causes big ROOT output file!)]
ConvergenceImprove: "1.000000e-16" [Minimum improvement which counts as improvement (<0 means automatic convergence check is turned off)]
ConvergenceTests: "15" [Number of steps (without improvement) required for convergence (<0 means automatic convergence check is turned off)]
UseRegulator: "False" [Use regulator to avoid over-training]
# Default:
RandomSeed: "1" [Random seed for initial synapse weights (0 means unique seed for each run; default value '1')]
NeuronInputType: "sum" [Neuron input function type]
VerbosityLevel: "Verbose" [Verbosity level]
CreateMVAPdfs: "False" [Create PDFs for classifier outputs (signal and background)]
IgnoreNegWeightsInTraining: "False" [Events with negative weights are ignored in the training (but are included for testing and performance evaluation)]
LearningRate: "2.000000e-02" [ANN learning rate parameter]
DecayRate: "1.000000e-02" [Decay rate for learning parameter]
TestRate: "10" [Test for overtraining performed at each #th epochs]
Sampling: "1.000000e+00" [Only 'Sampling' (randomly selected) events are trained each epoch]
SamplingEpoch: "1.000000e+00" [Sampling is used for the first 'SamplingEpoch' epochs, afterwards, all events are taken for training]
SamplingImportance: "1.000000e+00" [ The sampling weights of events in epochs which successful (worse estimator than before) are multiplied with SamplingImportance, else they are divided.]
SamplingTraining: "True" [The training sample is sampled]
SamplingTesting: "False" [The testing sample is sampled]
ResetStep: "50" [How often BFGS should reset history]
Tau: "3.000000e+00" [LineSearch "size step"]
BPMode: "sequential" [Back-propagation learning mode: sequential or batch]
BatchSize: "-1" [Batch size: number of events/batch, only set if in Batch Mode, -1 for BatchSize=number_of_events]
UpdateLimit: "10000" [Maximum times of regulator update]
CalculateErrors: "False" [Calculates inverse Hessian matrix at the end of the training to be able to calculate the uncertainties of an MVA value]
WeightRange: "1.000000e+00" [Take the events for the estimator calculations from small deviations from the desired value to large deviations only over the weight range]
##


#VAR -*-*-*-*-*-*-*-*-*-*-*-* variables *-*-*-*-*-*-*-*-*-*-*-*-

NVar 20
TrackP                        TrackP                        TrackP                        TrackP                                                          'F'    [256.920013428,4793400]
TrackPt                       TrackPt                       TrackPt                       TrackPt                                                         'F'    [6.0154671669,882678.1875]
TrackChi2PerDof               TrackChi2PerDof               TrackChi2PerDof               TrackChi2PerDof                                                 'F'    [0.00387042481452,2.99801039696]
TrackNumDof                   TrackNumDof                   TrackNumDof                   TrackNumDof                                                     'I'    [4,28]
TrackLikelihood               TrackLikelihood               TrackLikelihood               TrackLikelihood                                                 'F'    [-49.2771110535,-0.336537152529]
TrackGhostProbability         TrackGhostProbability         TrackGhostProbability         TrackGhostProbability                                           'F'    [0.0309826973826,1]
TrackFitVeloChi2              TrackFitVeloChi2              TrackFitVeloChi2              TrackFitVeloChi2                                                'F'    [5.73693614569e-06,54.0769615173]
TrackFitVeloNDoF              TrackFitVeloNDoF              TrackFitVeloNDoF              TrackFitVeloNDoF                                                'I'    [1,23]
RichUsedAero                  RichUsedAero                  RichUsedAero                  RichUsedAero                                                    'I'    [0,1]
RichUsedR1Gas                 RichUsedR1Gas                 RichUsedR1Gas                 RichUsedR1Gas                                                   'I'    [0,1]
RichAboveMuThres              RichAboveMuThres              RichAboveMuThres              RichAboveMuThres                                                'I'    [0,1]
RichAboveKaThres              RichAboveKaThres              RichAboveKaThres              RichAboveKaThres                                                'I'    [0,1]
RichDLLe                      RichDLLe                      RichDLLe                      RichDLLe                                                        'F'    [-999,116.291496277]
RichDLLmu                     RichDLLmu                     RichDLLmu                     RichDLLmu                                                       'F'    [-999,86.09349823]
RichDLLk                      RichDLLk                      RichDLLk                      RichDLLk                                                        'F'    [-999,79.6075973511]
RichDLLp                      RichDLLp                      RichDLLp                      RichDLLp                                                        'F'    [-999,78.3151016235]
RichDLLbt                     RichDLLbt                     RichDLLbt                     RichDLLbt                                                       'F'    [-999,47.5948982239]
InAccBrem                     InAccBrem                     InAccBrem                     InAccBrem                                                       'I'    [0,1]
BremPIDe                      BremPIDe                      BremPIDe                      BremPIDe                                                        'F'    [-999,4.79148387909]
VeloCharge                    VeloCharge                    VeloCharge                    VeloCharge                                                      'F'    [0.498595505953,3.5272872448]
NSpec 0


============================================================================ */

#include <vector>
#include <cmath>
#include <string>
#include <iostream>

#ifndef IClassifierReader__def
#define IClassifierReader__def

class IClassifierReader {

 public:

   // constructor
   IClassifierReader() : fStatusIsClean( true ) {}
   virtual ~IClassifierReader() {}

   // return classifier response
   virtual double GetMvaValue( const std::vector<double>& inputValues ) const = 0;

   // returns classifier status
   bool IsStatusClean() const { return fStatusIsClean; }

 protected:

   bool fStatusIsClean;
};

#endif

class ReadElectron_Upstream_TMVA : public IClassifierReader {

 public:

   // constructor
   ReadElectron_Upstream_TMVA( std::vector<std::string>& theInputVars ) 
      : IClassifierReader(),
        fClassName( "ReadElectron_Upstream_TMVA" ),
        fNvars( 20 ),
        fIsNormalised( false )
   {      
      // the training input variables
      const char* inputVars[] = { "TrackP", "TrackPt", "TrackChi2PerDof", "TrackNumDof", "TrackLikelihood", "TrackGhostProbability", "TrackFitVeloChi2", "TrackFitVeloNDoF", "RichUsedAero", "RichUsedR1Gas", "RichAboveMuThres", "RichAboveKaThres", "RichDLLe", "RichDLLmu", "RichDLLk", "RichDLLp", "RichDLLbt", "InAccBrem", "BremPIDe", "VeloCharge" };

      // sanity checks
      if (theInputVars.size() <= 0) {
         std::cout << "Problem in class \"" << fClassName << "\": empty input vector" << std::endl;
         fStatusIsClean = false;
      }

      if (theInputVars.size() != fNvars) {
         std::cout << "Problem in class \"" << fClassName << "\": mismatch in number of input values: "
                   << theInputVars.size() << " != " << fNvars << std::endl;
         fStatusIsClean = false;
      }

      // validate input variables
      for (size_t ivar = 0; ivar < theInputVars.size(); ivar++) {
         if (theInputVars[ivar] != inputVars[ivar]) {
            std::cout << "Problem in class \"" << fClassName << "\": mismatch in input variable names" << std::endl
                      << " for variable [" << ivar << "]: " << theInputVars[ivar].c_str() << " != " << inputVars[ivar] << std::endl;
            fStatusIsClean = false;
         }
      }

      // initialize min and max vectors (for normalisation)
      fVmin[0] = -1;
      fVmax[0] = 1;
      fVmin[1] = -1;
      fVmax[1] = 1;
      fVmin[2] = -1;
      fVmax[2] = 0.99999988079071;
      fVmin[3] = -1;
      fVmax[3] = 1;
      fVmin[4] = -1;
      fVmax[4] = 1;
      fVmin[5] = -1;
      fVmax[5] = 0.99999988079071;
      fVmin[6] = -1;
      fVmax[6] = 1;
      fVmin[7] = -1;
      fVmax[7] = 1;
      fVmin[8] = -1;
      fVmax[8] = 1;
      fVmin[9] = -1;
      fVmax[9] = 1;
      fVmin[10] = -1;
      fVmax[10] = 1;
      fVmin[11] = -1;
      fVmax[11] = 1;
      fVmin[12] = -1;
      fVmax[12] = 1;
      fVmin[13] = -1;
      fVmax[13] = 1;
      fVmin[14] = -1;
      fVmax[14] = 1;
      fVmin[15] = -1;
      fVmax[15] = 1;
      fVmin[16] = -1;
      fVmax[16] = 1;
      fVmin[17] = -1;
      fVmax[17] = 1;
      fVmin[18] = -1;
      fVmax[18] = 1;
      fVmin[19] = -1;
      fVmax[19] = 0.99999988079071;

      // initialize input variable types
      fType[0] = 'F';
      fType[1] = 'F';
      fType[2] = 'F';
      fType[3] = 'I';
      fType[4] = 'F';
      fType[5] = 'F';
      fType[6] = 'F';
      fType[7] = 'I';
      fType[8] = 'I';
      fType[9] = 'I';
      fType[10] = 'I';
      fType[11] = 'I';
      fType[12] = 'F';
      fType[13] = 'F';
      fType[14] = 'F';
      fType[15] = 'F';
      fType[16] = 'F';
      fType[17] = 'I';
      fType[18] = 'F';
      fType[19] = 'F';

      // initialize constants
      Initialize();

      // initialize transformation
      InitTransform();
   }

   // destructor
   virtual ~ReadElectron_Upstream_TMVA() {
      Clear(); // method-specific
   }

   // the classifier response
   // "inputValues" is a vector of input values in the same order as the 
   // variables given to the constructor
   double GetMvaValue( const std::vector<double>& inputValues ) const;

 private:

   // method-specific destructor
   void Clear();

   // input variable transformation

   double fMin_1[3][20];
   double fMax_1[3][20];
   void InitTransform_1();
   void Transform_1( std::vector<double> & iv, int sigOrBgd ) const;
   void InitTransform();
   void Transform( std::vector<double> & iv, int sigOrBgd ) const;

   // common member variables
   const char* fClassName;

   const size_t fNvars;
   size_t GetNvar()           const { return fNvars; }
   char   GetType( int ivar ) const { return fType[ivar]; }

   // normalisation of input variables
   const bool fIsNormalised;
   bool IsNormalised() const { return fIsNormalised; }
   double fVmin[20];
   double fVmax[20];
   double NormVariable( double x, double xmin, double xmax ) const {
      // normalise to output range: [-1, 1]
      return 2*(x - xmin)/(xmax - xmin) - 1.0;
   }

   // type of input variable: 'F' or 'I'
   char   fType[20];

   // initialize internal variables
   void Initialize();
   double GetMvaValue__( const std::vector<double>& inputValues ) const;

   // private members (method specific)

   double ActivationFnc(double x) const;
   double OutputActivationFnc(double x) const;

   int fLayers;
   int fLayerSize[3];
   double fWeightMatrix0to1[25][21];   // weight matrix from layer 0 to 1
   double fWeightMatrix1to2[1][25];   // weight matrix from layer 1 to 2

   double * fWeights[3];
};

inline void ReadElectron_Upstream_TMVA::Initialize()
{
   // build network structure
   fLayers = 3;
   fLayerSize[0] = 21; fWeights[0] = new double[21]; 
   fLayerSize[1] = 25; fWeights[1] = new double[25]; 
   fLayerSize[2] = 1; fWeights[2] = new double[1]; 
   // weight matrix from layer 0 to 1
   fWeightMatrix0to1[0][0] = -0.176655533434592;
   fWeightMatrix0to1[1][0] = 2.26719555087425;
   fWeightMatrix0to1[2][0] = 1.67288186800258;
   fWeightMatrix0to1[3][0] = 4.62436566790025;
   fWeightMatrix0to1[4][0] = -3.3314273537763;
   fWeightMatrix0to1[5][0] = -1.58426450751333;
   fWeightMatrix0to1[6][0] = 0.277116451605021;
   fWeightMatrix0to1[7][0] = 4.43364378309398;
   fWeightMatrix0to1[8][0] = -2.22409813422623;
   fWeightMatrix0to1[9][0] = -5.55248558419964;
   fWeightMatrix0to1[10][0] = -5.66298348898587;
   fWeightMatrix0to1[11][0] = -0.0790580806021106;
   fWeightMatrix0to1[12][0] = -0.487418248143332;
   fWeightMatrix0to1[13][0] = -0.204231063904716;
   fWeightMatrix0to1[14][0] = -0.415803823133102;
   fWeightMatrix0to1[15][0] = 0.484001655107196;
   fWeightMatrix0to1[16][0] = -0.676106766942763;
   fWeightMatrix0to1[17][0] = 2.66528946470487;
   fWeightMatrix0to1[18][0] = 0.103461684336847;
   fWeightMatrix0to1[19][0] = 1.97732271184466;
   fWeightMatrix0to1[20][0] = -0.0725358251437275;
   fWeightMatrix0to1[21][0] = -1.06972135953844;
   fWeightMatrix0to1[22][0] = -0.849003417500399;
   fWeightMatrix0to1[23][0] = -0.375444001367165;
   fWeightMatrix0to1[0][1] = -1.79842495011568;
   fWeightMatrix0to1[1][1] = 1.73921038707666;
   fWeightMatrix0to1[2][1] = 2.32313315175333;
   fWeightMatrix0to1[3][1] = -0.288114126060364;
   fWeightMatrix0to1[4][1] = -4.27826994445124;
   fWeightMatrix0to1[5][1] = 0.0533164804516156;
   fWeightMatrix0to1[6][1] = 1.9936277031931;
   fWeightMatrix0to1[7][1] = 3.02611582860134;
   fWeightMatrix0to1[8][1] = -0.607039625520579;
   fWeightMatrix0to1[9][1] = -3.37901772744709;
   fWeightMatrix0to1[10][1] = -4.72128648490947;
   fWeightMatrix0to1[11][1] = -0.349577718032416;
   fWeightMatrix0to1[12][1] = -0.700615651412231;
   fWeightMatrix0to1[13][1] = 2.07049694670722;
   fWeightMatrix0to1[14][1] = -1.08643113105619;
   fWeightMatrix0to1[15][1] = 0.848924212668649;
   fWeightMatrix0to1[16][1] = 1.29703785805299;
   fWeightMatrix0to1[17][1] = 0.554995735179043;
   fWeightMatrix0to1[18][1] = 1.89416125765019;
   fWeightMatrix0to1[19][1] = 1.72610966609655;
   fWeightMatrix0to1[20][1] = -0.492244765012982;
   fWeightMatrix0to1[21][1] = -1.82512383818754;
   fWeightMatrix0to1[22][1] = -0.0052716770132683;
   fWeightMatrix0to1[23][1] = 0.122425945982224;
   fWeightMatrix0to1[0][2] = -0.812212453615799;
   fWeightMatrix0to1[1][2] = 0.539673182300233;
   fWeightMatrix0to1[2][2] = 1.40283935072312;
   fWeightMatrix0to1[3][2] = 0.141840426743402;
   fWeightMatrix0to1[4][2] = -0.67972835945279;
   fWeightMatrix0to1[5][2] = 0.353093007991435;
   fWeightMatrix0to1[6][2] = -3.22410023793932;
   fWeightMatrix0to1[7][2] = -0.414322482425541;
   fWeightMatrix0to1[8][2] = -0.628547434369076;
   fWeightMatrix0to1[9][2] = -0.0900031542627206;
   fWeightMatrix0to1[10][2] = 0.0442777332561691;
   fWeightMatrix0to1[11][2] = 2.65489832825396;
   fWeightMatrix0to1[12][2] = -0.267926041673084;
   fWeightMatrix0to1[13][2] = -0.567549885577638;
   fWeightMatrix0to1[14][2] = -0.544902684196129;
   fWeightMatrix0to1[15][2] = 1.35187173321979;
   fWeightMatrix0to1[16][2] = 1.24420140363115;
   fWeightMatrix0to1[17][2] = 0.0175603524794594;
   fWeightMatrix0to1[18][2] = -0.383334268586652;
   fWeightMatrix0to1[19][2] = -2.2660764952879;
   fWeightMatrix0to1[20][2] = 0.951472238342079;
   fWeightMatrix0to1[21][2] = -1.40266411550791;
   fWeightMatrix0to1[22][2] = 0.483730495492385;
   fWeightMatrix0to1[23][2] = -1.17160505614803;
   fWeightMatrix0to1[0][3] = 0.762985692550852;
   fWeightMatrix0to1[1][3] = -0.549462924841542;
   fWeightMatrix0to1[2][3] = 1.31173686783468;
   fWeightMatrix0to1[3][3] = -0.149728178499739;
   fWeightMatrix0to1[4][3] = -2.20751722068559;
   fWeightMatrix0to1[5][3] = -1.73822993798106;
   fWeightMatrix0to1[6][3] = 2.48229123281282;
   fWeightMatrix0to1[7][3] = 0.37490543660146;
   fWeightMatrix0to1[8][3] = 1.51474557328303;
   fWeightMatrix0to1[9][3] = 0.723529601053879;
   fWeightMatrix0to1[10][3] = 0.949769785346942;
   fWeightMatrix0to1[11][3] = 0.403694546536886;
   fWeightMatrix0to1[12][3] = 1.24191925945527;
   fWeightMatrix0to1[13][3] = -1.3164329438666;
   fWeightMatrix0to1[14][3] = 1.53287190595546;
   fWeightMatrix0to1[15][3] = -1.19195698233932;
   fWeightMatrix0to1[16][3] = -0.886680216988079;
   fWeightMatrix0to1[17][3] = -1.10768271071133;
   fWeightMatrix0to1[18][3] = 0.186140982587055;
   fWeightMatrix0to1[19][3] = -1.43245753371038;
   fWeightMatrix0to1[20][3] = 1.02959004796092;
   fWeightMatrix0to1[21][3] = -1.25122196476653;
   fWeightMatrix0to1[22][3] = -0.197177257124284;
   fWeightMatrix0to1[23][3] = 1.20881709434098;
   fWeightMatrix0to1[0][4] = -1.23204256502087;
   fWeightMatrix0to1[1][4] = 0.874469930261493;
   fWeightMatrix0to1[2][4] = -1.94061446490993;
   fWeightMatrix0to1[3][4] = 0.735454535806224;
   fWeightMatrix0to1[4][4] = -2.91575292385859;
   fWeightMatrix0to1[5][4] = -0.682466408063019;
   fWeightMatrix0to1[6][4] = 0.172816822026314;
   fWeightMatrix0to1[7][4] = 0.557059032136189;
   fWeightMatrix0to1[8][4] = -1.43668243617486;
   fWeightMatrix0to1[9][4] = -0.584698194947664;
   fWeightMatrix0to1[10][4] = -0.288384733296859;
   fWeightMatrix0to1[11][4] = 0.591955984198826;
   fWeightMatrix0to1[12][4] = 1.58937649834169;
   fWeightMatrix0to1[13][4] = 0.473810949056702;
   fWeightMatrix0to1[14][4] = -1.87694126652109;
   fWeightMatrix0to1[15][4] = 0.412323097688199;
   fWeightMatrix0to1[16][4] = 1.05395413995833;
   fWeightMatrix0to1[17][4] = 2.92642802198242;
   fWeightMatrix0to1[18][4] = -0.662437327344508;
   fWeightMatrix0to1[19][4] = 2.91898753576433;
   fWeightMatrix0to1[20][4] = -0.0928604025848666;
   fWeightMatrix0to1[21][4] = -2.19045817853122;
   fWeightMatrix0to1[22][4] = 1.54202981246027;
   fWeightMatrix0to1[23][4] = -2.07854494563094;
   fWeightMatrix0to1[0][5] = 1.41350592104878;
   fWeightMatrix0to1[1][5] = -0.558679874359393;
   fWeightMatrix0to1[2][5] = -0.204295849445855;
   fWeightMatrix0to1[3][5] = 0.499783369462805;
   fWeightMatrix0to1[4][5] = 1.89810600075655;
   fWeightMatrix0to1[5][5] = -0.294618533473144;
   fWeightMatrix0to1[6][5] = -2.50965824900887;
   fWeightMatrix0to1[7][5] = 1.90185195428741;
   fWeightMatrix0to1[8][5] = -0.027319228334368;
   fWeightMatrix0to1[9][5] = 0.0257450663343018;
   fWeightMatrix0to1[10][5] = 0.263520276875534;
   fWeightMatrix0to1[11][5] = -5.05165964753999;
   fWeightMatrix0to1[12][5] = -0.0696656341292729;
   fWeightMatrix0to1[13][5] = 1.10908977778435;
   fWeightMatrix0to1[14][5] = -0.19327434917795;
   fWeightMatrix0to1[15][5] = 1.54250139477803;
   fWeightMatrix0to1[16][5] = 0.287883208856613;
   fWeightMatrix0to1[17][5] = -1.17975220711322;
   fWeightMatrix0to1[18][5] = -0.781068264471168;
   fWeightMatrix0to1[19][5] = 2.22808988802148;
   fWeightMatrix0to1[20][5] = 1.6675874359327;
   fWeightMatrix0to1[21][5] = 0.380033627386721;
   fWeightMatrix0to1[22][5] = 0.761480816849636;
   fWeightMatrix0to1[23][5] = 0.199832161290844;
   fWeightMatrix0to1[0][6] = -0.500151295924953;
   fWeightMatrix0to1[1][6] = 0.789252059690949;
   fWeightMatrix0to1[2][6] = 1.46004319284768;
   fWeightMatrix0to1[3][6] = -0.780746564496383;
   fWeightMatrix0to1[4][6] = -1.03681269173024;
   fWeightMatrix0to1[5][6] = 0.00980530785948058;
   fWeightMatrix0to1[6][6] = -3.73310335712271;
   fWeightMatrix0to1[7][6] = 2.66518456337504;
   fWeightMatrix0to1[8][6] = 1.37632728885112;
   fWeightMatrix0to1[9][6] = -0.2856071169161;
   fWeightMatrix0to1[10][6] = -0.672012450768827;
   fWeightMatrix0to1[11][6] = -0.882571539223797;
   fWeightMatrix0to1[12][6] = 2.47581423690974;
   fWeightMatrix0to1[13][6] = 0.458131095252133;
   fWeightMatrix0to1[14][6] = 1.16457732760007;
   fWeightMatrix0to1[15][6] = -1.25746867880218;
   fWeightMatrix0to1[16][6] = 1.68012793599097;
   fWeightMatrix0to1[17][6] = 0.909040477703171;
   fWeightMatrix0to1[18][6] = -0.441843319941709;
   fWeightMatrix0to1[19][6] = 1.83654493247489;
   fWeightMatrix0to1[20][6] = 1.37544643122166;
   fWeightMatrix0to1[21][6] = -0.194045111360392;
   fWeightMatrix0to1[22][6] = 0.0786909300348264;
   fWeightMatrix0to1[23][6] = 0.629716849586969;
   fWeightMatrix0to1[0][7] = -0.468888901972641;
   fWeightMatrix0to1[1][7] = 1.79059121791456;
   fWeightMatrix0to1[2][7] = 1.52395372575732;
   fWeightMatrix0to1[3][7] = 1.33874971672306;
   fWeightMatrix0to1[4][7] = 2.76114240065806;
   fWeightMatrix0to1[5][7] = 1.72148141364794;
   fWeightMatrix0to1[6][7] = 0.862410005876581;
   fWeightMatrix0to1[7][7] = -2.69900404258983;
   fWeightMatrix0to1[8][7] = 0.0942738314529234;
   fWeightMatrix0to1[9][7] = -1.27686115667907;
   fWeightMatrix0to1[10][7] = -0.149535150657076;
   fWeightMatrix0to1[11][7] = -1.48307084604023;
   fWeightMatrix0to1[12][7] = -2.50481744502547;
   fWeightMatrix0to1[13][7] = -0.525344526290941;
   fWeightMatrix0to1[14][7] = 2.2559732872691;
   fWeightMatrix0to1[15][7] = -1.85914929098405;
   fWeightMatrix0to1[16][7] = 0.15248754399318;
   fWeightMatrix0to1[17][7] = -1.36284743496809;
   fWeightMatrix0to1[18][7] = 1.73123059027757;
   fWeightMatrix0to1[19][7] = 0.106856405813799;
   fWeightMatrix0to1[20][7] = -1.3280894608722;
   fWeightMatrix0to1[21][7] = 0.227141427673872;
   fWeightMatrix0to1[22][7] = -1.70151386069309;
   fWeightMatrix0to1[23][7] = 0.528048000064341;
   fWeightMatrix0to1[0][8] = 4.47561286929006;
   fWeightMatrix0to1[1][8] = 1.39616586947849;
   fWeightMatrix0to1[2][8] = 0.819384653365869;
   fWeightMatrix0to1[3][8] = -1.1473762132681;
   fWeightMatrix0to1[4][8] = -0.376133351342948;
   fWeightMatrix0to1[5][8] = 1.47797162723436;
   fWeightMatrix0to1[6][8] = 1.28207696471698;
   fWeightMatrix0to1[7][8] = -4.38931055387651;
   fWeightMatrix0to1[8][8] = -0.219754104826334;
   fWeightMatrix0to1[9][8] = -0.405731606457692;
   fWeightMatrix0to1[10][8] = 0.0153475316138238;
   fWeightMatrix0to1[11][8] = -0.328329885863528;
   fWeightMatrix0to1[12][8] = 5.34269429074329;
   fWeightMatrix0to1[13][8] = 1.73745002155256;
   fWeightMatrix0to1[14][8] = -0.56189732349327;
   fWeightMatrix0to1[15][8] = -0.797524870062994;
   fWeightMatrix0to1[16][8] = 0.939124913892411;
   fWeightMatrix0to1[17][8] = 0.338208904857656;
   fWeightMatrix0to1[18][8] = 0.285091105280506;
   fWeightMatrix0to1[19][8] = 0.680898994240233;
   fWeightMatrix0to1[20][8] = -1.69638045327679;
   fWeightMatrix0to1[21][8] = -1.01333626456353;
   fWeightMatrix0to1[22][8] = 1.18118588098401;
   fWeightMatrix0to1[23][8] = 2.19283174702044;
   fWeightMatrix0to1[0][9] = 5.14465971653043;
   fWeightMatrix0to1[1][9] = -3.51303987055846;
   fWeightMatrix0to1[2][9] = 1.76318201124022;
   fWeightMatrix0to1[3][9] = -2.15682248058217;
   fWeightMatrix0to1[4][9] = 2.67897964702375;
   fWeightMatrix0to1[5][9] = 0.244072634457963;
   fWeightMatrix0to1[6][9] = -2.56208781251432;
   fWeightMatrix0to1[7][9] = 2.0385154265898;
   fWeightMatrix0to1[8][9] = 1.4237281407589;
   fWeightMatrix0to1[9][9] = -2.89196161885495;
   fWeightMatrix0to1[10][9] = 7.40588854816234;
   fWeightMatrix0to1[11][9] = 0.352197423392436;
   fWeightMatrix0to1[12][9] = 2.27332205460373;
   fWeightMatrix0to1[13][9] = -1.81709666372489;
   fWeightMatrix0to1[14][9] = 0.876787510398306;
   fWeightMatrix0to1[15][9] = -0.479370249664254;
   fWeightMatrix0to1[16][9] = 0.835286214577327;
   fWeightMatrix0to1[17][9] = 0.161276166236492;
   fWeightMatrix0to1[18][9] = 0.961523647080482;
   fWeightMatrix0to1[19][9] = -1.66422342698986;
   fWeightMatrix0to1[20][9] = 0.282356387137674;
   fWeightMatrix0to1[21][9] = -0.128212477614256;
   fWeightMatrix0to1[22][9] = -2.1545135701715;
   fWeightMatrix0to1[23][9] = -1.74670317630826;
   fWeightMatrix0to1[0][10] = -0.868311565506566;
   fWeightMatrix0to1[1][10] = -0.0858208275551451;
   fWeightMatrix0to1[2][10] = -1.55953242777902;
   fWeightMatrix0to1[3][10] = -0.970508877893031;
   fWeightMatrix0to1[4][10] = -0.78125755555945;
   fWeightMatrix0to1[5][10] = 0.54671204911659;
   fWeightMatrix0to1[6][10] = -1.24624904735279;
   fWeightMatrix0to1[7][10] = 0.139708505497295;
   fWeightMatrix0to1[8][10] = 0.33465545271334;
   fWeightMatrix0to1[9][10] = 0.200165965024894;
   fWeightMatrix0to1[10][10] = 0.21616519843586;
   fWeightMatrix0to1[11][10] = -0.458661513520587;
   fWeightMatrix0to1[12][10] = 4.22492201733292;
   fWeightMatrix0to1[13][10] = 1.23103495188706;
   fWeightMatrix0to1[14][10] = 0.912185902880758;
   fWeightMatrix0to1[15][10] = -1.04453011175605;
   fWeightMatrix0to1[16][10] = -1.97831100502498;
   fWeightMatrix0to1[17][10] = 0.616103725100767;
   fWeightMatrix0to1[18][10] = -1.10718165091619;
   fWeightMatrix0to1[19][10] = -1.23794403968032;
   fWeightMatrix0to1[20][10] = -0.164160117917644;
   fWeightMatrix0to1[21][10] = -0.723937705865897;
   fWeightMatrix0to1[22][10] = -0.0104157500044841;
   fWeightMatrix0to1[23][10] = -0.643877495284661;
   fWeightMatrix0to1[0][11] = -0.165685798477024;
   fWeightMatrix0to1[1][11] = -0.330056388711058;
   fWeightMatrix0to1[2][11] = -1.1632821784815;
   fWeightMatrix0to1[3][11] = 1.79437179563822;
   fWeightMatrix0to1[4][11] = -0.0942226519254527;
   fWeightMatrix0to1[5][11] = -0.655559957023541;
   fWeightMatrix0to1[6][11] = 0.166107739090547;
   fWeightMatrix0to1[7][11] = 1.59799459237826;
   fWeightMatrix0to1[8][11] = -0.121208079106622;
   fWeightMatrix0to1[9][11] = 0.0620384461423345;
   fWeightMatrix0to1[10][11] = 0.171423621738395;
   fWeightMatrix0to1[11][11] = -0.025914468308994;
   fWeightMatrix0to1[12][11] = 0.0378010058709372;
   fWeightMatrix0to1[13][11] = 0.27685521567877;
   fWeightMatrix0to1[14][11] = 0.951939970446786;
   fWeightMatrix0to1[15][11] = 0.296712946114534;
   fWeightMatrix0to1[16][11] = 0.422754690404798;
   fWeightMatrix0to1[17][11] = -0.398423082072816;
   fWeightMatrix0to1[18][11] = -1.37896552164877;
   fWeightMatrix0to1[19][11] = -0.419058219298287;
   fWeightMatrix0to1[20][11] = -1.49155500959998;
   fWeightMatrix0to1[21][11] = 0.249506819412431;
   fWeightMatrix0to1[22][11] = -2.45271294326071;
   fWeightMatrix0to1[23][11] = 2.25782957441633;
   fWeightMatrix0to1[0][12] = -25.8294403520502;
   fWeightMatrix0to1[1][12] = 24.6216586919993;
   fWeightMatrix0to1[2][12] = -1.64402135545552;
   fWeightMatrix0to1[3][12] = 0.59471331650933;
   fWeightMatrix0to1[4][12] = -24.1515306180351;
   fWeightMatrix0to1[5][12] = 0.842904953873311;
   fWeightMatrix0to1[6][12] = 2.45753535407519;
   fWeightMatrix0to1[7][12] = -4.02898402993939;
   fWeightMatrix0to1[8][12] = 2.63470625698186;
   fWeightMatrix0to1[9][12] = 18.5325611823356;
   fWeightMatrix0to1[10][12] = -56.0568144053661;
   fWeightMatrix0to1[11][12] = -3.00457121159294;
   fWeightMatrix0to1[12][12] = -26.2119413919136;
   fWeightMatrix0to1[13][12] = 4.89452430632536;
   fWeightMatrix0to1[14][12] = 1.57833457652382;
   fWeightMatrix0to1[15][12] = -0.3065286864515;
   fWeightMatrix0to1[16][12] = 2.01881326983315;
   fWeightMatrix0to1[17][12] = -8.71123169823826;
   fWeightMatrix0to1[18][12] = -1.77186430292862;
   fWeightMatrix0to1[19][12] = -1.60492207673549;
   fWeightMatrix0to1[20][12] = -1.34704845397394;
   fWeightMatrix0to1[21][12] = -0.280136912224123;
   fWeightMatrix0to1[22][12] = 4.99541990120031;
   fWeightMatrix0to1[23][12] = -1.41484937699342;
   fWeightMatrix0to1[0][13] = 4.58747765951964;
   fWeightMatrix0to1[1][13] = -4.45932452710329;
   fWeightMatrix0to1[2][13] = 0.187600273515206;
   fWeightMatrix0to1[3][13] = -0.997234622543896;
   fWeightMatrix0to1[4][13] = 7.64819116746094;
   fWeightMatrix0to1[5][13] = -1.59442480421105;
   fWeightMatrix0to1[6][13] = 0.0995122686389749;
   fWeightMatrix0to1[7][13] = 2.39019612702214;
   fWeightMatrix0to1[8][13] = -1.66743876572512;
   fWeightMatrix0to1[9][13] = -3.80227682801451;
   fWeightMatrix0to1[10][13] = 9.45414231944009;
   fWeightMatrix0to1[11][13] = -0.136468724597363;
   fWeightMatrix0to1[12][13] = 6.31860907751313;
   fWeightMatrix0to1[13][13] = 0.808021647951245;
   fWeightMatrix0to1[14][13] = 1.22610392278162;
   fWeightMatrix0to1[15][13] = 1.07331392876299;
   fWeightMatrix0to1[16][13] = -1.68174965183202;
   fWeightMatrix0to1[17][13] = 2.98333849193782;
   fWeightMatrix0to1[18][13] = -2.59189473749006;
   fWeightMatrix0to1[19][13] = 0.784221208559523;
   fWeightMatrix0to1[20][13] = -2.21859279243695;
   fWeightMatrix0to1[21][13] = -2.46157834925953;
   fWeightMatrix0to1[22][13] = -1.12079867106994;
   fWeightMatrix0to1[23][13] = 0.878007571965835;
   fWeightMatrix0to1[0][14] = 3.14407651543424;
   fWeightMatrix0to1[1][14] = 1.00938450752699;
   fWeightMatrix0to1[2][14] = 0.127736757285959;
   fWeightMatrix0to1[3][14] = -0.519480870109801;
   fWeightMatrix0to1[4][14] = -1.51951130731231;
   fWeightMatrix0to1[5][14] = 0.567760940043158;
   fWeightMatrix0to1[6][14] = 1.45005876490847;
   fWeightMatrix0to1[7][14] = -1.36556394854944;
   fWeightMatrix0to1[8][14] = 0.555227198943836;
   fWeightMatrix0to1[9][14] = -3.26301944722762;
   fWeightMatrix0to1[10][14] = 1.55856896190916;
   fWeightMatrix0to1[11][14] = 0.233902143814796;
   fWeightMatrix0to1[12][14] = 0.670619079270933;
   fWeightMatrix0to1[13][14] = -1.13575159353073;
   fWeightMatrix0to1[14][14] = 0.918870179771671;
   fWeightMatrix0to1[15][14] = 1.24810178790161;
   fWeightMatrix0to1[16][14] = 0.775543004317851;
   fWeightMatrix0to1[17][14] = 0.136278053196288;
   fWeightMatrix0to1[18][14] = -1.61336987384433;
   fWeightMatrix0to1[19][14] = -1.2875327689067;
   fWeightMatrix0to1[20][14] = -2.23213163691734;
   fWeightMatrix0to1[21][14] = 1.26706152670465;
   fWeightMatrix0to1[22][14] = -0.138069633149346;
   fWeightMatrix0to1[23][14] = -1.58074945757306;
   fWeightMatrix0to1[0][15] = 3.29052757605129;
   fWeightMatrix0to1[1][15] = -1.72972337261021;
   fWeightMatrix0to1[2][15] = -1.30819959692696;
   fWeightMatrix0to1[3][15] = -1.9664520833011;
   fWeightMatrix0to1[4][15] = 0.200659984974695;
   fWeightMatrix0to1[5][15] = -0.901841526555122;
   fWeightMatrix0to1[6][15] = -2.2225919265451;
   fWeightMatrix0to1[7][15] = -0.394521620377169;
   fWeightMatrix0to1[8][15] = -0.745325312222529;
   fWeightMatrix0to1[9][15] = -3.4043552251136;
   fWeightMatrix0to1[10][15] = 2.8838409366547;
   fWeightMatrix0to1[11][15] = -1.15329927633476;
   fWeightMatrix0to1[12][15] = -1.01424818332375;
   fWeightMatrix0to1[13][15] = 1.74273279938311;
   fWeightMatrix0to1[14][15] = 0.556447240735249;
   fWeightMatrix0to1[15][15] = -0.159835269593342;
   fWeightMatrix0to1[16][15] = 0.201723409466499;
   fWeightMatrix0to1[17][15] = 1.69684655293189;
   fWeightMatrix0to1[18][15] = 1.02527917149494;
   fWeightMatrix0to1[19][15] = 0.675663913352431;
   fWeightMatrix0to1[20][15] = -1.44516257862106;
   fWeightMatrix0to1[21][15] = -0.590917716286139;
   fWeightMatrix0to1[22][15] = -1.2625500711196;
   fWeightMatrix0to1[23][15] = 0.46178453280627;
   fWeightMatrix0to1[0][16] = 6.80669590061123;
   fWeightMatrix0to1[1][16] = -3.24323314959717;
   fWeightMatrix0to1[2][16] = 0.909347749575479;
   fWeightMatrix0to1[3][16] = 0.825104571661988;
   fWeightMatrix0to1[4][16] = 3.32602013110446;
   fWeightMatrix0to1[5][16] = -1.00922376071031;
   fWeightMatrix0to1[6][16] = 0.945730805761235;
   fWeightMatrix0to1[7][16] = 1.13735547407715;
   fWeightMatrix0to1[8][16] = -2.0527809923935;
   fWeightMatrix0to1[9][16] = -4.22706581189127;
   fWeightMatrix0to1[10][16] = 8.34492340158734;
   fWeightMatrix0to1[11][16] = 1.71367697734685;
   fWeightMatrix0to1[12][16] = 4.31442100746559;
   fWeightMatrix0to1[13][16] = 0.240318412297846;
   fWeightMatrix0to1[14][16] = 1.76957640806039;
   fWeightMatrix0to1[15][16] = -0.935453031444308;
   fWeightMatrix0to1[16][16] = 1.6140427533603;
   fWeightMatrix0to1[17][16] = 2.97628871800556;
   fWeightMatrix0to1[18][16] = -0.469394508018326;
   fWeightMatrix0to1[19][16] = -1.01584647297618;
   fWeightMatrix0to1[20][16] = 1.14180861526244;
   fWeightMatrix0to1[21][16] = -2.17014882303062;
   fWeightMatrix0to1[22][16] = 0.219698512684725;
   fWeightMatrix0to1[23][16] = 1.24472018094629;
   fWeightMatrix0to1[0][17] = -1.06661368607079;
   fWeightMatrix0to1[1][17] = -1.27608206077598;
   fWeightMatrix0to1[2][17] = -0.948099867957388;
   fWeightMatrix0to1[3][17] = -0.70252518737588;
   fWeightMatrix0to1[4][17] = 0.730217084869044;
   fWeightMatrix0to1[5][17] = -1.80465678486885;
   fWeightMatrix0to1[6][17] = 0.933625600291237;
   fWeightMatrix0to1[7][17] = 0.501987915224847;
   fWeightMatrix0to1[8][17] = 1.21769611048697;
   fWeightMatrix0to1[9][17] = 0.427179945613705;
   fWeightMatrix0to1[10][17] = 3.35835115990549;
   fWeightMatrix0to1[11][17] = -0.0301450759441892;
   fWeightMatrix0to1[12][17] = 1.59149274157264;
   fWeightMatrix0to1[13][17] = -0.395618760212678;
   fWeightMatrix0to1[14][17] = 2.01610453364618;
   fWeightMatrix0to1[15][17] = -2.66717275709012;
   fWeightMatrix0to1[16][17] = -1.63523990005489;
   fWeightMatrix0to1[17][17] = 0.860011349846628;
   fWeightMatrix0to1[18][17] = -2.20172284852673;
   fWeightMatrix0to1[19][17] = -1.83109517733858;
   fWeightMatrix0to1[20][17] = -1.69830675060428;
   fWeightMatrix0to1[21][17] = -0.0572653638883186;
   fWeightMatrix0to1[22][17] = -0.288392396269132;
   fWeightMatrix0to1[23][17] = -2.18522242980136;
   fWeightMatrix0to1[0][18] = -4.51627379039564;
   fWeightMatrix0to1[1][18] = 1.33136475361552;
   fWeightMatrix0to1[2][18] = 0.909573514603207;
   fWeightMatrix0to1[3][18] = 2.43565770108186;
   fWeightMatrix0to1[4][18] = -0.487250468427806;
   fWeightMatrix0to1[5][18] = -0.391748057154633;
   fWeightMatrix0to1[6][18] = -0.648318659735676;
   fWeightMatrix0to1[7][18] = -0.231921365742104;
   fWeightMatrix0to1[8][18] = -1.31718678392749;
   fWeightMatrix0to1[9][18] = -0.336087870971263;
   fWeightMatrix0to1[10][18] = -3.23207296060919;
   fWeightMatrix0to1[11][18] = 0.19949166805605;
   fWeightMatrix0to1[12][18] = -1.76295727208;
   fWeightMatrix0to1[13][18] = 1.29823824802262;
   fWeightMatrix0to1[14][18] = 1.40082200518355;
   fWeightMatrix0to1[15][18] = -0.651301825407172;
   fWeightMatrix0to1[16][18] = -0.704237798873337;
   fWeightMatrix0to1[17][18] = -0.629810287359973;
   fWeightMatrix0to1[18][18] = 1.24554999702879;
   fWeightMatrix0to1[19][18] = -0.957112379969696;
   fWeightMatrix0to1[20][18] = 0.0990885040412165;
   fWeightMatrix0to1[21][18] = 1.09805412923759;
   fWeightMatrix0to1[22][18] = 1.90161998512054;
   fWeightMatrix0to1[23][18] = -1.26663908615007;
   fWeightMatrix0to1[0][19] = -0.742578329709265;
   fWeightMatrix0to1[1][19] = -0.0123967562552915;
   fWeightMatrix0to1[2][19] = 2.10914227685872;
   fWeightMatrix0to1[3][19] = 1.46974730672474;
   fWeightMatrix0to1[4][19] = -1.61712178187464;
   fWeightMatrix0to1[5][19] = -1.83811326640408;
   fWeightMatrix0to1[6][19] = 0.990154274276387;
   fWeightMatrix0to1[7][19] = -10.6125425921346;
   fWeightMatrix0to1[8][19] = 2.73559017125021;
   fWeightMatrix0to1[9][19] = 12.4658575726647;
   fWeightMatrix0to1[10][19] = 0.167844729275279;
   fWeightMatrix0to1[11][19] = -1.79276136208859;
   fWeightMatrix0to1[12][19] = 0.809118967430364;
   fWeightMatrix0to1[13][19] = 4.74573809365544;
   fWeightMatrix0to1[14][19] = 0.492319766324828;
   fWeightMatrix0to1[15][19] = -0.121120137721726;
   fWeightMatrix0to1[16][19] = -0.802135197397511;
   fWeightMatrix0to1[17][19] = 2.0477785202328;
   fWeightMatrix0to1[18][19] = 3.16377965646838;
   fWeightMatrix0to1[19][19] = -1.17173936118459;
   fWeightMatrix0to1[20][19] = -0.761831694026452;
   fWeightMatrix0to1[21][19] = -0.733116602003252;
   fWeightMatrix0to1[22][19] = 8.37887024593199;
   fWeightMatrix0to1[23][19] = 1.36854414129602;
   fWeightMatrix0to1[0][20] = -0.163775990210348;
   fWeightMatrix0to1[1][20] = -4.77726956658093;
   fWeightMatrix0to1[2][20] = 0.6877219854977;
   fWeightMatrix0to1[3][20] = 2.39979000087453;
   fWeightMatrix0to1[4][20] = 4.30088277165506;
   fWeightMatrix0to1[5][20] = 0.253015294182422;
   fWeightMatrix0to1[6][20] = -2.73999537154606;
   fWeightMatrix0to1[7][20] = -2.27015676465675;
   fWeightMatrix0to1[8][20] = 1.19901551708167;
   fWeightMatrix0to1[9][20] = 2.08452470699247;
   fWeightMatrix0to1[10][20] = 7.04789546247187;
   fWeightMatrix0to1[11][20] = -1.67107768724573;
   fWeightMatrix0to1[12][20] = -1.50934805164563;
   fWeightMatrix0to1[13][20] = -2.67506528752099;
   fWeightMatrix0to1[14][20] = -0.463355377498325;
   fWeightMatrix0to1[15][20] = -2.19633937717911;
   fWeightMatrix0to1[16][20] = 0.35137111894519;
   fWeightMatrix0to1[17][20] = 0.747882665775568;
   fWeightMatrix0to1[18][20] = 1.59762925962651;
   fWeightMatrix0to1[19][20] = -0.312132563158423;
   fWeightMatrix0to1[20][20] = -2.25517583278189;
   fWeightMatrix0to1[21][20] = 1.26640942657817;
   fWeightMatrix0to1[22][20] = 2.24307678968588;
   fWeightMatrix0to1[23][20] = 0.999103018463038;
   // weight matrix from layer 1 to 2
   fWeightMatrix1to2[0][0] = -1.05968284489602;
   fWeightMatrix1to2[0][1] = 1.23623583263467;
   fWeightMatrix1to2[0][2] = 2.11760619568823;
   fWeightMatrix1to2[0][3] = -1.56141894336629;
   fWeightMatrix1to2[0][4] = -1.45153380161368;
   fWeightMatrix1to2[0][5] = 0.503507802023836;
   fWeightMatrix1to2[0][6] = 0.457085627524681;
   fWeightMatrix1to2[0][7] = -0.48840606724276;
   fWeightMatrix1to2[0][8] = 0.225521111802957;
   fWeightMatrix1to2[0][9] = 1.16932846044233;
   fWeightMatrix1to2[0][10] = -1.54335580686826;
   fWeightMatrix1to2[0][11] = -0.48412673601098;
   fWeightMatrix1to2[0][12] = -1.68820073085584;
   fWeightMatrix1to2[0][13] = 0.418345267765767;
   fWeightMatrix1to2[0][14] = -0.583529044663782;
   fWeightMatrix1to2[0][15] = 0.307157473905695;
   fWeightMatrix1to2[0][16] = 0.322222131646626;
   fWeightMatrix1to2[0][17] = -0.415762535363758;
   fWeightMatrix1to2[0][18] = 1.51397912109678;
   fWeightMatrix1to2[0][19] = -0.206022334585066;
   fWeightMatrix1to2[0][20] = 2.09745951763556;
   fWeightMatrix1to2[0][21] = 0.865765978918695;
   fWeightMatrix1to2[0][22] = 0.557995257976423;
   fWeightMatrix1to2[0][23] = 0.45127512038251;
   fWeightMatrix1to2[0][24] = 0.74897414551806;
}

inline double ReadElectron_Upstream_TMVA::GetMvaValue__( const std::vector<double>& inputValues ) const
{
   if (inputValues.size() != (unsigned int)fLayerSize[0]-1) {
      std::cout << "Input vector needs to be of size " << fLayerSize[0]-1 << std::endl;
      return 0;
   }

   for (int l=0; l<fLayers; l++)
      for (int i=0; i<fLayerSize[l]; i++) fWeights[l][i]=0;

   for (int l=0; l<fLayers-1; l++)
      fWeights[l][fLayerSize[l]-1]=1;

   for (int i=0; i<fLayerSize[0]-1; i++)
      fWeights[0][i]=inputValues[i];

   // layer 0 to 1
   for (int o=0; o<fLayerSize[1]-1; o++) {
      for (int i=0; i<fLayerSize[0]; i++) {
         double inputVal = fWeightMatrix0to1[o][i] * fWeights[0][i];
         fWeights[1][o] += inputVal;
      }
      fWeights[1][o] = ActivationFnc(fWeights[1][o]);
   }
   // layer 1 to 2
   for (int o=0; o<fLayerSize[2]; o++) {
      for (int i=0; i<fLayerSize[1]; i++) {
         double inputVal = fWeightMatrix1to2[o][i] * fWeights[1][i];
         fWeights[2][o] += inputVal;
      }
      fWeights[2][o] = OutputActivationFnc(fWeights[2][o]);
   }

   return fWeights[2][0];
}

double ReadElectron_Upstream_TMVA::ActivationFnc(double x) const {
   // hyperbolic tan
   return tanh(x);
}
double ReadElectron_Upstream_TMVA::OutputActivationFnc(double x) const {
   // sigmoid
   return 1.0/(1.0+exp(-x));
}
   
// Clean up
inline void ReadElectron_Upstream_TMVA::Clear() 
{
   // clean up the arrays
   for (int lIdx = 0; lIdx < 3; lIdx++) {
      delete[] fWeights[lIdx];
   }
}
   inline double ReadElectron_Upstream_TMVA::GetMvaValue( const std::vector<double>& inputValues ) const
   {
      // classifier response value
      double retval = 0;

      // classifier response, sanity check first
      if (!IsStatusClean()) {
         std::cout << "Problem in class \"" << fClassName << "\": cannot return classifier response"
                   << " because status is dirty" << std::endl;
         retval = 0;
      }
      else {
         if (IsNormalised()) {
            // normalise variables
            std::vector<double> iV;
            iV.reserve(inputValues.size());
            int ivar = 0;
            for (std::vector<double>::const_iterator varIt = inputValues.begin();
                 varIt != inputValues.end(); varIt++, ivar++) {
               iV.push_back(NormVariable( *varIt, fVmin[ivar], fVmax[ivar] ));
            }
            Transform( iV, -1 );
            retval = GetMvaValue__( iV );
         }
         else {
            std::vector<double> iV;
            int ivar = 0;
            for (std::vector<double>::const_iterator varIt = inputValues.begin();
                 varIt != inputValues.end(); varIt++, ivar++) {
               iV.push_back(*varIt);
            }
            Transform( iV, -1 );
            retval = GetMvaValue__( iV );
         }
      }

      return retval;
   }

//_______________________________________________________________________
inline void ReadElectron_Upstream_TMVA::InitTransform_1()
{
   // Normalization transformation, initialisation
   fMin_1[0][0] = 256.920013428;
   fMax_1[0][0] = 4793400;
   fMin_1[1][0] = 306.220001221;
   fMax_1[1][0] = 1988186.5;
   fMin_1[2][0] = 256.920013428;
   fMax_1[2][0] = 4793400;
   fMin_1[0][1] = 6.0154671669;
   fMax_1[0][1] = 882678.1875;
   fMin_1[1][1] = 11.0666770935;
   fMax_1[1][1] = 575802.5625;
   fMin_1[2][1] = 6.0154671669;
   fMax_1[2][1] = 882678.1875;
   fMin_1[0][2] = 0.00387042481452;
   fMax_1[0][2] = 2.99801039696;
   fMin_1[1][2] = 0.0166839621961;
   fMax_1[1][2] = 2.9840490818;
   fMin_1[2][2] = 0.00387042481452;
   fMax_1[2][2] = 2.99801039696;
   fMin_1[0][3] = 4;
   fMax_1[0][3] = 28;
   fMin_1[1][3] = 4;
   fMax_1[1][3] = 23;
   fMin_1[2][3] = 4;
   fMax_1[2][3] = 28;
   fMin_1[0][4] = -49.2771110535;
   fMax_1[0][4] = -0.336537152529;
   fMin_1[1][4] = -38.8162269592;
   fMax_1[1][4] = -0.462853044271;
   fMin_1[2][4] = -49.2771110535;
   fMax_1[2][4] = -0.336537152529;
   fMin_1[0][5] = 0.0309826973826;
   fMax_1[0][5] = 1;
   fMin_1[1][5] = 0.0613457001746;
   fMax_1[1][5] = 1;
   fMin_1[2][5] = 0.0309826973826;
   fMax_1[2][5] = 1;
   fMin_1[0][6] = 5.73693614569e-06;
   fMax_1[0][6] = 54.0769615173;
   fMin_1[1][6] = 0.00295716198161;
   fMax_1[1][6] = 38.9773216248;
   fMin_1[2][6] = 5.73693614569e-06;
   fMax_1[2][6] = 54.0769615173;
   fMin_1[0][7] = 1;
   fMax_1[0][7] = 23;
   fMin_1[1][7] = 1;
   fMax_1[1][7] = 19;
   fMin_1[2][7] = 1;
   fMax_1[2][7] = 23;
   fMin_1[0][8] = 0;
   fMax_1[0][8] = 1;
   fMin_1[1][8] = 0;
   fMax_1[1][8] = 1;
   fMin_1[2][8] = 0;
   fMax_1[2][8] = 1;
   fMin_1[0][9] = 0;
   fMax_1[0][9] = 1;
   fMin_1[1][9] = 0;
   fMax_1[1][9] = 1;
   fMin_1[2][9] = 0;
   fMax_1[2][9] = 1;
   fMin_1[0][10] = 0;
   fMax_1[0][10] = 1;
   fMin_1[1][10] = 0;
   fMax_1[1][10] = 1;
   fMin_1[2][10] = 0;
   fMax_1[2][10] = 1;
   fMin_1[0][11] = 0;
   fMax_1[0][11] = 1;
   fMin_1[1][11] = 0;
   fMax_1[1][11] = 1;
   fMin_1[2][11] = 0;
   fMax_1[2][11] = 1;
   fMin_1[0][12] = -999;
   fMax_1[0][12] = 77.415397644;
   fMin_1[1][12] = -999;
   fMax_1[1][12] = 116.291496277;
   fMin_1[2][12] = -999;
   fMax_1[2][12] = 116.291496277;
   fMin_1[0][13] = -999;
   fMax_1[0][13] = 86.09349823;
   fMin_1[1][13] = -999;
   fMax_1[1][13] = 45.6090011597;
   fMin_1[2][13] = -999;
   fMax_1[2][13] = 86.09349823;
   fMin_1[0][14] = -999;
   fMax_1[0][14] = 79.6075973511;
   fMin_1[1][14] = -999;
   fMax_1[1][14] = 24.7677001953;
   fMin_1[2][14] = -999;
   fMax_1[2][14] = 79.6075973511;
   fMin_1[0][15] = -999;
   fMax_1[0][15] = 78.3151016235;
   fMin_1[1][15] = -999;
   fMax_1[1][15] = 27.9862995148;
   fMin_1[2][15] = -999;
   fMax_1[2][15] = 78.3151016235;
   fMin_1[0][16] = -999;
   fMax_1[0][16] = 47.5948982239;
   fMin_1[1][16] = -999;
   fMax_1[1][16] = 33.7803001404;
   fMin_1[2][16] = -999;
   fMax_1[2][16] = 47.5948982239;
   fMin_1[0][17] = 0;
   fMax_1[0][17] = 1;
   fMin_1[1][17] = 0;
   fMax_1[1][17] = 1;
   fMin_1[2][17] = 0;
   fMax_1[2][17] = 1;
   fMin_1[0][18] = -999;
   fMax_1[0][18] = 4.79148387909;
   fMin_1[1][18] = -999;
   fMax_1[1][18] = 4.79148387909;
   fMin_1[2][18] = -999;
   fMax_1[2][18] = 4.79148387909;
   fMin_1[0][19] = 0.498595505953;
   fMax_1[0][19] = 3.5272872448;
   fMin_1[1][19] = 0.60393255949;
   fMax_1[1][19] = 2.31273412704;
   fMin_1[2][19] = 0.498595505953;
   fMax_1[2][19] = 3.5272872448;
}

//_______________________________________________________________________
inline void ReadElectron_Upstream_TMVA::Transform_1( std::vector<double>& iv, int cls) const
{
   // Normalization transformation
   if (cls < 0 || cls > 2) {
   if (2 > 1 ) cls = 2;
      else cls = 2;
   }
   const int nVar = 20;

   // get indices of used variables

   // define the indices of the variables which are transformed by this transformation
   static std::vector<int> indicesGet;
   static std::vector<int> indicesPut;

   if ( indicesGet.empty() ) { 
      indicesGet.reserve(fNvars);
      indicesGet.push_back( 0);
      indicesGet.push_back( 1);
      indicesGet.push_back( 2);
      indicesGet.push_back( 3);
      indicesGet.push_back( 4);
      indicesGet.push_back( 5);
      indicesGet.push_back( 6);
      indicesGet.push_back( 7);
      indicesGet.push_back( 8);
      indicesGet.push_back( 9);
      indicesGet.push_back( 10);
      indicesGet.push_back( 11);
      indicesGet.push_back( 12);
      indicesGet.push_back( 13);
      indicesGet.push_back( 14);
      indicesGet.push_back( 15);
      indicesGet.push_back( 16);
      indicesGet.push_back( 17);
      indicesGet.push_back( 18);
      indicesGet.push_back( 19);
   } 
   if ( indicesPut.empty() ) { 
      indicesPut.reserve(fNvars);
      indicesPut.push_back( 0);
      indicesPut.push_back( 1);
      indicesPut.push_back( 2);
      indicesPut.push_back( 3);
      indicesPut.push_back( 4);
      indicesPut.push_back( 5);
      indicesPut.push_back( 6);
      indicesPut.push_back( 7);
      indicesPut.push_back( 8);
      indicesPut.push_back( 9);
      indicesPut.push_back( 10);
      indicesPut.push_back( 11);
      indicesPut.push_back( 12);
      indicesPut.push_back( 13);
      indicesPut.push_back( 14);
      indicesPut.push_back( 15);
      indicesPut.push_back( 16);
      indicesPut.push_back( 17);
      indicesPut.push_back( 18);
      indicesPut.push_back( 19);
   } 

   static std::vector<double> dv;
   dv.resize(nVar);
   for (int ivar=0; ivar<nVar; ivar++) dv[ivar] = iv[indicesGet.at(ivar)];
   for (int ivar=0;ivar<20;ivar++) {
      double offset = fMin_1[cls][ivar];
      double scale  = 1.0/(fMax_1[cls][ivar]-fMin_1[cls][ivar]);
      iv[indicesPut.at(ivar)] = (dv[ivar]-offset)*scale * 2 - 1;
   }
}

//_______________________________________________________________________
inline void ReadElectron_Upstream_TMVA::InitTransform()
{
   InitTransform_1();
}

//_______________________________________________________________________
inline void ReadElectron_Upstream_TMVA::Transform( std::vector<double>& iv, int sigOrBgd ) const
{
   Transform_1( iv, sigOrBgd );
}