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

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

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

Method         : MLP::Deuteron_Upstream_TMVA
TMVA Release   : 4.2.1         [262657]
ROOT Release   : 6.12/06       [396294]
Creator        : jonesc
Date           : Tue Apr 10 11:13:13 2018
Host           : Linux lcgapp-slc6-x86-64-2.cern.ch 2.6.32-696.18.7.el6.x86_64 #1 SMP Thu Jan 4 13:27:39 CET 2018 x86_64 x86_64 x86_64 GNU/Linux
Dir            : /var/pcfst/r01/lhcb/jonesc/ANNPID/results/MC2016Deuterons/TrainMixture/TrainPhysTks-EvalPhysTks-NoReweight-EqualSigBck0.25/GhostAccFrac0.05/PrAccF0.5/KaAccF0.5/PiAccF1.0/TMVA-Run2-NoTkLikCDVelodEdx/MLP/Norm/NumLayers1/ScaleF1.4/BP/NCycles750/CE/tanh/CVTest15/CVImp1e-16/NotUseRegulator/Deuteron/Upstream
Training events: 288095
Analysis type  : [Classification]


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

# Set by User:
NCycles: "750" [Number of training cycles]
HiddenLayers: "26" [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 19
TrackP                        TrackP                        TrackP                        TrackP                                                          'F'    [270.440002441,4994126]
TrackPt                       TrackPt                       TrackPt                       TrackPt                                                         'F'    [21.6379623413,805216.125]
TrackChi2PerDof               TrackChi2PerDof               TrackChi2PerDof               TrackChi2PerDof                                                 'F'    [0.00191661447752,3.99388027191]
TrackNumDof                   TrackNumDof                   TrackNumDof                   TrackNumDof                                                     'I'    [4,30]
TrackGhostProbability         TrackGhostProbability         TrackGhostProbability         TrackGhostProbability                                           'F'    [0.0016649417812,0.399999767542]
TrackFitVeloChi2              TrackFitVeloChi2              TrackFitVeloChi2              TrackFitVeloChi2                                                'F'    [0.000152601263835,63.4452209473]
TrackFitVeloNDoF              TrackFitVeloNDoF              TrackFitVeloNDoF              TrackFitVeloNDoF                                                'I'    [1,27]
RichUsedR1Gas                 RichUsedR1Gas                 RichUsedR1Gas                 RichUsedR1Gas                                                   'I'    [0,1]
RichAbovePiThres              RichAbovePiThres              RichAbovePiThres              RichAbovePiThres                                                'I'    [0,1]
RichAboveKaThres              RichAboveKaThres              RichAboveKaThres              RichAboveKaThres                                                'I'    [0,1]
RichAbovePrThres              RichAbovePrThres              RichAbovePrThres              RichAbovePrThres                                                'I'    [0,1]
RichDLLe                      RichDLLe                      RichDLLe                      RichDLLe                                                        'F'    [-999,136.249404907]
RichDLLmu                     RichDLLmu                     RichDLLmu                     RichDLLmu                                                       'F'    [-999,95.2298965454]
RichDLLk                      RichDLLk                      RichDLLk                      RichDLLk                                                        'F'    [-999,103.673202515]
RichDLLp                      RichDLLp                      RichDLLp                      RichDLLp                                                        'F'    [-999,117.643798828]
RichDLLd                      RichDLLd                      RichDLLd                      RichDLLd                                                        'F'    [-999,144.49710083]
RichDLLbt                     RichDLLbt                     RichDLLbt                     RichDLLbt                                                       'F'    [-999,55.7882003784]
InAccBrem                     InAccBrem                     InAccBrem                     InAccBrem                                                       'I'    [0,1]
BremPIDe                      BremPIDe                      BremPIDe                      BremPIDe                                                        'F'    [-999,4.79148387909]
NSpec 0


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

#include <array>
#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 ReadDeuteron_Upstream_TMVA : public IClassifierReader {

 public:

   // constructor
   ReadDeuteron_Upstream_TMVA( std::vector<std::string>& theInputVars ) 
      : IClassifierReader(),
        fClassName( "ReadDeuteron_Upstream_TMVA" ),
        fNvars( 19 ),
        fIsNormalised( false )
   {      
      // the training input variables
      const char* inputVars[] = { "TrackP", "TrackPt", "TrackChi2PerDof", "TrackNumDof", "TrackGhostProbability", "TrackFitVeloChi2", "TrackFitVeloNDoF", "RichUsedR1Gas", "RichAbovePiThres", "RichAboveKaThres", "RichAbovePrThres", "RichDLLe", "RichDLLmu", "RichDLLk", "RichDLLp", "RichDLLd", "RichDLLbt", "InAccBrem", "BremPIDe" };

      // 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] = 1;
      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] = 0.99999988079071;
      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;

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

      // initialize constants
      Initialize();

      // initialize transformation
      InitTransform();
   }

   // destructor
   virtual ~ReadDeuteron_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][19];
   double fMax_1[3][19];
   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[19];
   double fVmax[19];
   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[19];

   // 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[27][20];   // weight matrix from layer 0 to 1
   double fWeightMatrix1to2[1][27];   // weight matrix from layer 1 to 2

};

inline void ReadDeuteron_Upstream_TMVA::Initialize()
{
   // build network structure
   fLayers = 3;
   fLayerSize[0] = 20;
   fLayerSize[1] = 27;
   fLayerSize[2] = 1;
   // weight matrix from layer 0 to 1
   fWeightMatrix0to1[0][0] = 0.38836098003173;
   fWeightMatrix0to1[1][0] = 5.72103845420325;
   fWeightMatrix0to1[2][0] = 12.8020044575159;
   fWeightMatrix0to1[3][0] = -3.16809711379558;
   fWeightMatrix0to1[4][0] = -15.8226343691951;
   fWeightMatrix0to1[5][0] = -0.957970728242954;
   fWeightMatrix0to1[6][0] = 0.0564689930380652;
   fWeightMatrix0to1[7][0] = 3.95718390810445;
   fWeightMatrix0to1[8][0] = -1.48452537030302;
   fWeightMatrix0to1[9][0] = -3.88749390560444;
   fWeightMatrix0to1[10][0] = -54.6851717421128;
   fWeightMatrix0to1[11][0] = -2.03430425817943;
   fWeightMatrix0to1[12][0] = -0.588895001266823;
   fWeightMatrix0to1[13][0] = 10.7742625256975;
   fWeightMatrix0to1[14][0] = -1.53878928211607;
   fWeightMatrix0to1[15][0] = -23.1063699218545;
   fWeightMatrix0to1[16][0] = -2.78731047363012;
   fWeightMatrix0to1[17][0] = 1.63860815574414;
   fWeightMatrix0to1[18][0] = 0.494310954012303;
   fWeightMatrix0to1[19][0] = 1.03356987863421;
   fWeightMatrix0to1[20][0] = 14.6861441584547;
   fWeightMatrix0to1[21][0] = -0.747204085166493;
   fWeightMatrix0to1[22][0] = 9.59871588751406;
   fWeightMatrix0to1[23][0] = -2.04999067937562;
   fWeightMatrix0to1[24][0] = -4.47719069014567;
   fWeightMatrix0to1[25][0] = -0.834809408721726;
   fWeightMatrix0to1[0][1] = 2.35469177083251;
   fWeightMatrix0to1[1][1] = -0.694282930181597;
   fWeightMatrix0to1[2][1] = -4.56579755430257;
   fWeightMatrix0to1[3][1] = -5.13824290571803;
   fWeightMatrix0to1[4][1] = -7.09202516287448;
   fWeightMatrix0to1[5][1] = 3.22703146149308;
   fWeightMatrix0to1[6][1] = -0.0726642360423257;
   fWeightMatrix0to1[7][1] = -0.0373740786362527;
   fWeightMatrix0to1[8][1] = 0.509713342126754;
   fWeightMatrix0to1[9][1] = -2.23330457694275;
   fWeightMatrix0to1[10][1] = -4.56077507733538;
   fWeightMatrix0to1[11][1] = 3.02961384454886;
   fWeightMatrix0to1[12][1] = -1.58281069330822;
   fWeightMatrix0to1[13][1] = 10.4454425514138;
   fWeightMatrix0to1[14][1] = 0.027197831496922;
   fWeightMatrix0to1[15][1] = -14.8264821419276;
   fWeightMatrix0to1[16][1] = 4.27036753711824;
   fWeightMatrix0to1[17][1] = 1.31508397666043;
   fWeightMatrix0to1[18][1] = 0.178735063839115;
   fWeightMatrix0to1[19][1] = -1.62298470069418;
   fWeightMatrix0to1[20][1] = 0.944620281893089;
   fWeightMatrix0to1[21][1] = 0.0723118415040191;
   fWeightMatrix0to1[22][1] = 2.36516835845601;
   fWeightMatrix0to1[23][1] = -0.592845535275722;
   fWeightMatrix0to1[24][1] = -0.890099238974856;
   fWeightMatrix0to1[25][1] = 0.59159227838596;
   fWeightMatrix0to1[0][2] = 1.06851685726909;
   fWeightMatrix0to1[1][2] = 1.84224193503949;
   fWeightMatrix0to1[2][2] = 0.561037900532814;
   fWeightMatrix0to1[3][2] = 0.489734824889766;
   fWeightMatrix0to1[4][2] = -1.96338210943574;
   fWeightMatrix0to1[5][2] = 1.55553865543782;
   fWeightMatrix0to1[6][2] = -0.920227999078723;
   fWeightMatrix0to1[7][2] = 1.94150216780981;
   fWeightMatrix0to1[8][2] = 0.517523464787384;
   fWeightMatrix0to1[9][2] = 2.55709018577549;
   fWeightMatrix0to1[10][2] = -0.398709646375301;
   fWeightMatrix0to1[11][2] = -0.478247905634575;
   fWeightMatrix0to1[12][2] = 0.441365750462977;
   fWeightMatrix0to1[13][2] = -0.219651160092308;
   fWeightMatrix0to1[14][2] = -0.0601876332904632;
   fWeightMatrix0to1[15][2] = -0.301068041453661;
   fWeightMatrix0to1[16][2] = 2.41774095726963;
   fWeightMatrix0to1[17][2] = -6.45300516368277;
   fWeightMatrix0to1[18][2] = -2.11479079097969;
   fWeightMatrix0to1[19][2] = -2.12468315218121;
   fWeightMatrix0to1[20][2] = 2.70103286242922;
   fWeightMatrix0to1[21][2] = 1.13397677478659;
   fWeightMatrix0to1[22][2] = 1.21773844840943;
   fWeightMatrix0to1[23][2] = -0.124351685939586;
   fWeightMatrix0to1[24][2] = -4.01977525199225;
   fWeightMatrix0to1[25][2] = -4.54734047958073;
   fWeightMatrix0to1[0][3] = -8.71497086325002;
   fWeightMatrix0to1[1][3] = 0.172129921323266;
   fWeightMatrix0to1[2][3] = 2.22871615671153;
   fWeightMatrix0to1[3][3] = 5.29446444523213;
   fWeightMatrix0to1[4][3] = -0.977354356129581;
   fWeightMatrix0to1[5][3] = -1.30304673191615;
   fWeightMatrix0to1[6][3] = 1.42294103930988;
   fWeightMatrix0to1[7][3] = 3.94638901961466;
   fWeightMatrix0to1[8][3] = 0.181413243367731;
   fWeightMatrix0to1[9][3] = -0.963058931952781;
   fWeightMatrix0to1[10][3] = 0.335021853705218;
   fWeightMatrix0to1[11][3] = -4.11475900896281;
   fWeightMatrix0to1[12][3] = 2.35597939534419;
   fWeightMatrix0to1[13][3] = -0.0651434943027774;
   fWeightMatrix0to1[14][3] = 3.9509423242182;
   fWeightMatrix0to1[15][3] = 0.0872335822093658;
   fWeightMatrix0to1[16][3] = 0.38828710731274;
   fWeightMatrix0to1[17][3] = -1.27297262069489;
   fWeightMatrix0to1[18][3] = -3.12605499922184;
   fWeightMatrix0to1[19][3] = -0.752711972011013;
   fWeightMatrix0to1[20][3] = 3.30593763645409;
   fWeightMatrix0to1[21][3] = 0.0990378016657627;
   fWeightMatrix0to1[22][3] = -4.24335269878451;
   fWeightMatrix0to1[23][3] = 0.732182475267643;
   fWeightMatrix0to1[24][3] = -0.171595507523768;
   fWeightMatrix0to1[25][3] = 0.543921824794633;
   fWeightMatrix0to1[0][4] = 0.20350061601337;
   fWeightMatrix0to1[1][4] = 0.275210960619204;
   fWeightMatrix0to1[2][4] = 0.204508750566974;
   fWeightMatrix0to1[3][4] = -1.26873839484495;
   fWeightMatrix0to1[4][4] = -0.589742430830944;
   fWeightMatrix0to1[5][4] = -0.684546007943524;
   fWeightMatrix0to1[6][4] = -0.00522792799361274;
   fWeightMatrix0to1[7][4] = -1.08386970079034;
   fWeightMatrix0to1[8][4] = 0.0611749452902984;
   fWeightMatrix0to1[9][4] = -0.0253457257486569;
   fWeightMatrix0to1[10][4] = -0.0117901498325262;
   fWeightMatrix0to1[11][4] = 4.63518825100046;
   fWeightMatrix0to1[12][4] = 0.730356351319962;
   fWeightMatrix0to1[13][4] = -0.192080851564093;
   fWeightMatrix0to1[14][4] = -0.0909192933031786;
   fWeightMatrix0to1[15][4] = 0.322737103338125;
   fWeightMatrix0to1[16][4] = 1.31957961006157;
   fWeightMatrix0to1[17][4] = 0.276464939999263;
   fWeightMatrix0to1[18][4] = -0.137869080127785;
   fWeightMatrix0to1[19][4] = 4.26357109372539;
   fWeightMatrix0to1[20][4] = -8.63296383396607;
   fWeightMatrix0to1[21][4] = -0.0278803850146138;
   fWeightMatrix0to1[22][4] = -0.246203773853104;
   fWeightMatrix0to1[23][4] = -0.256457469077436;
   fWeightMatrix0to1[24][4] = 0.056970097348599;
   fWeightMatrix0to1[25][4] = -0.0251737158075282;
   fWeightMatrix0to1[0][5] = -3.77512729825623;
   fWeightMatrix0to1[1][5] = -0.340594662417051;
   fWeightMatrix0to1[2][5] = -0.459499548560995;
   fWeightMatrix0to1[3][5] = -0.921477141797077;
   fWeightMatrix0to1[4][5] = 1.95073318885459;
   fWeightMatrix0to1[5][5] = 0.43713600685249;
   fWeightMatrix0to1[6][5] = 1.24619573176945;
   fWeightMatrix0to1[7][5] = -3.14422476179712;
   fWeightMatrix0to1[8][5] = -0.0522439210641198;
   fWeightMatrix0to1[9][5] = 3.83589804735825;
   fWeightMatrix0to1[10][5] = 0.672055493675404;
   fWeightMatrix0to1[11][5] = 4.35114614904423;
   fWeightMatrix0to1[12][5] = -1.17918605769398;
   fWeightMatrix0to1[13][5] = 0.589956738812387;
   fWeightMatrix0to1[14][5] = -1.41148053151291;
   fWeightMatrix0to1[15][5] = 0.400627433208521;
   fWeightMatrix0to1[16][5] = -1.95135139016924;
   fWeightMatrix0to1[17][5] = 3.32540884937969;
   fWeightMatrix0to1[18][5] = 1.09027739881593;
   fWeightMatrix0to1[19][5] = 0.330690688950289;
   fWeightMatrix0to1[20][5] = -4.62569597921531;
   fWeightMatrix0to1[21][5] = 0.608784051604893;
   fWeightMatrix0to1[22][5] = -1.28878971408136;
   fWeightMatrix0to1[23][5] = -0.147217194516057;
   fWeightMatrix0to1[24][5] = 8.01322378629057;
   fWeightMatrix0to1[25][5] = 2.44376854315531;
   fWeightMatrix0to1[0][6] = 11.151131485192;
   fWeightMatrix0to1[1][6] = 0.913722403943776;
   fWeightMatrix0to1[2][6] = -2.33920537307833;
   fWeightMatrix0to1[3][6] = -4.28149755858109;
   fWeightMatrix0to1[4][6] = 1.04283113836158;
   fWeightMatrix0to1[5][6] = 1.67633840040126;
   fWeightMatrix0to1[6][6] = -2.29231409160709;
   fWeightMatrix0to1[7][6] = -1.71984537015765;
   fWeightMatrix0to1[8][6] = -0.614282930972408;
   fWeightMatrix0to1[9][6] = -3.7276686189807;
   fWeightMatrix0to1[10][6] = -0.674918548690826;
   fWeightMatrix0to1[11][6] = 4.21269408436655;
   fWeightMatrix0to1[12][6] = 1.6369299867817;
   fWeightMatrix0to1[13][6] = -1.0833170954921;
   fWeightMatrix0to1[14][6] = 2.91070155028458;
   fWeightMatrix0to1[15][6] = 0.0710719707295679;
   fWeightMatrix0to1[16][6] = -2.03364309773972;
   fWeightMatrix0to1[17][6] = 2.5774364292161;
   fWeightMatrix0to1[18][6] = 3.33528154166744;
   fWeightMatrix0to1[19][6] = -0.848086839979553;
   fWeightMatrix0to1[20][6] = -1.56887397374295;
   fWeightMatrix0to1[21][6] = -0.00761809426666883;
   fWeightMatrix0to1[22][6] = 3.53033115682951;
   fWeightMatrix0to1[23][6] = -0.418560820955842;
   fWeightMatrix0to1[24][6] = -4.29873338340967;
   fWeightMatrix0to1[25][6] = -2.02858418091607;
   fWeightMatrix0to1[0][7] = 1.46130098953511;
   fWeightMatrix0to1[1][7] = 0.782119160470244;
   fWeightMatrix0to1[2][7] = 0.855240541495793;
   fWeightMatrix0to1[3][7] = 0.066803577541223;
   fWeightMatrix0to1[4][7] = -0.421847817788509;
   fWeightMatrix0to1[5][7] = -0.271497979924245;
   fWeightMatrix0to1[6][7] = -2.31342948584016;
   fWeightMatrix0to1[7][7] = -1.27250561152937;
   fWeightMatrix0to1[8][7] = -1.36387738399645;
   fWeightMatrix0to1[9][7] = 1.6756914091572;
   fWeightMatrix0to1[10][7] = 6.79210920875151;
   fWeightMatrix0to1[11][7] = -0.320778399018433;
   fWeightMatrix0to1[12][7] = 0.308682610852872;
   fWeightMatrix0to1[13][7] = -3.42071540499635;
   fWeightMatrix0to1[14][7] = -2.67177398954373;
   fWeightMatrix0to1[15][7] = 3.99896090860544;
   fWeightMatrix0to1[16][7] = 6.14720612003822;
   fWeightMatrix0to1[17][7] = -1.59245556902498;
   fWeightMatrix0to1[18][7] = -1.04970148477822;
   fWeightMatrix0to1[19][7] = 0.664805284583389;
   fWeightMatrix0to1[20][7] = -3.91062813457314;
   fWeightMatrix0to1[21][7] = -1.96366842372805;
   fWeightMatrix0to1[22][7] = -0.0246273036884962;
   fWeightMatrix0to1[23][7] = 2.55690416748629;
   fWeightMatrix0to1[24][7] = -0.234485706060936;
   fWeightMatrix0to1[25][7] = -0.33257816034048;
   fWeightMatrix0to1[0][8] = 3.1356736561596;
   fWeightMatrix0to1[1][8] = 1.10914136775944;
   fWeightMatrix0to1[2][8] = 1.54934518293764;
   fWeightMatrix0to1[3][8] = 0.436322127009038;
   fWeightMatrix0to1[4][8] = -0.329388698121237;
   fWeightMatrix0to1[5][8] = -2.35570252469212;
   fWeightMatrix0to1[6][8] = -0.732875600335524;
   fWeightMatrix0to1[7][8] = 0.466852703394403;
   fWeightMatrix0to1[8][8] = 0.183195064691882;
   fWeightMatrix0to1[9][8] = 0.287361638873154;
   fWeightMatrix0to1[10][8] = 7.16800936854802;
   fWeightMatrix0to1[11][8] = -6.57121108506665;
   fWeightMatrix0to1[12][8] = 0.107692428296504;
   fWeightMatrix0to1[13][8] = 0.997547251816823;
   fWeightMatrix0to1[14][8] = -3.39391215118198;
   fWeightMatrix0to1[15][8] = 3.72942591550622;
   fWeightMatrix0to1[16][8] = 7.40663645798514;
   fWeightMatrix0to1[17][8] = -0.851488663774107;
   fWeightMatrix0to1[18][8] = -0.0913799528579438;
   fWeightMatrix0to1[19][8] = 1.6842904810437;
   fWeightMatrix0to1[20][8] = -8.82916049039358;
   fWeightMatrix0to1[21][8] = -1.07884837777823;
   fWeightMatrix0to1[22][8] = 0.484348620693587;
   fWeightMatrix0to1[23][8] = -0.205092248805561;
   fWeightMatrix0to1[24][8] = 0.890640226603044;
   fWeightMatrix0to1[25][8] = 0.0652010283071746;
   fWeightMatrix0to1[0][9] = 2.17656424421397;
   fWeightMatrix0to1[1][9] = -4.44596328343669;
   fWeightMatrix0to1[2][9] = 1.9298866656835;
   fWeightMatrix0to1[3][9] = -0.146802201570778;
   fWeightMatrix0to1[4][9] = 0.539706034801958;
   fWeightMatrix0to1[5][9] = 0.148558365217022;
   fWeightMatrix0to1[6][9] = -4.3724043633991;
   fWeightMatrix0to1[7][9] = 0.237820907593657;
   fWeightMatrix0to1[8][9] = 0.118183666986985;
   fWeightMatrix0to1[9][9] = -3.90647425687394;
   fWeightMatrix0to1[10][9] = 3.29194391875901;
   fWeightMatrix0to1[11][9] = -0.6483362671712;
   fWeightMatrix0to1[12][9] = -1.24601973047928;
   fWeightMatrix0to1[13][9] = 1.69748672149643;
   fWeightMatrix0to1[14][9] = 2.59527744859327;
   fWeightMatrix0to1[15][9] = -0.0576387070267809;
   fWeightMatrix0to1[16][9] = -1.4327433296973;
   fWeightMatrix0to1[17][9] = -1.98549717556799;
   fWeightMatrix0to1[18][9] = 0.631880825988704;
   fWeightMatrix0to1[19][9] = 2.04246243194562;
   fWeightMatrix0to1[20][9] = 0.0904179032917848;
   fWeightMatrix0to1[21][9] = -0.887024223781245;
   fWeightMatrix0to1[22][9] = -5.29425287335506;
   fWeightMatrix0to1[23][9] = -0.213233859199034;
   fWeightMatrix0to1[24][9] = -0.0633875352834765;
   fWeightMatrix0to1[25][9] = -2.93886259713441;
   fWeightMatrix0to1[0][10] = 0.680167293569929;
   fWeightMatrix0to1[1][10] = 1.91434439385344;
   fWeightMatrix0to1[2][10] = 3.34943809757181;
   fWeightMatrix0to1[3][10] = -0.121919123175356;
   fWeightMatrix0to1[4][10] = -0.193611031565769;
   fWeightMatrix0to1[5][10] = 0.0356250253955841;
   fWeightMatrix0to1[6][10] = -0.0393199657005283;
   fWeightMatrix0to1[7][10] = 0.501064631346245;
   fWeightMatrix0to1[8][10] = 2.81790434616404;
   fWeightMatrix0to1[9][10] = 1.03632983481549;
   fWeightMatrix0to1[10][10] = 4.11060864739968;
   fWeightMatrix0to1[11][10] = 0.428922302943579;
   fWeightMatrix0to1[12][10] = 2.12326263194942;
   fWeightMatrix0to1[13][10] = -0.173409882767729;
   fWeightMatrix0to1[14][10] = -2.00944994623467;
   fWeightMatrix0to1[15][10] = -0.128412073556168;
   fWeightMatrix0to1[16][10] = 0.3693369096363;
   fWeightMatrix0to1[17][10] = 0.128507571135226;
   fWeightMatrix0to1[18][10] = -1.74476510969438;
   fWeightMatrix0to1[19][10] = -0.120931793586977;
   fWeightMatrix0to1[20][10] = 0.0536640626318068;
   fWeightMatrix0to1[21][10] = -0.286769956327085;
   fWeightMatrix0to1[22][10] = -4.57843629043682;
   fWeightMatrix0to1[23][10] = -0.175693779019015;
   fWeightMatrix0to1[24][10] = -3.21939052153774;
   fWeightMatrix0to1[25][10] = -1.24077764823137;
   fWeightMatrix0to1[0][11] = -5.94922144163616;
   fWeightMatrix0to1[1][11] = 3.15726488827904;
   fWeightMatrix0to1[2][11] = -0.305943790649766;
   fWeightMatrix0to1[3][11] = 1.12154988688109;
   fWeightMatrix0to1[4][11] = -7.09120909806517;
   fWeightMatrix0to1[5][11] = 1.55802674930365;
   fWeightMatrix0to1[6][11] = 1.66626088433057;
   fWeightMatrix0to1[7][11] = -0.0470698390825632;
   fWeightMatrix0to1[8][11] = 0.716219339103651;
   fWeightMatrix0to1[9][11] = -1.43273124607105;
   fWeightMatrix0to1[10][11] = 5.39641185097483;
   fWeightMatrix0to1[11][11] = 4.56196917915422;
   fWeightMatrix0to1[12][11] = -2.52505166719373;
   fWeightMatrix0to1[13][11] = 2.4003649410227;
   fWeightMatrix0to1[14][11] = -1.23249855176017;
   fWeightMatrix0to1[15][11] = -7.22456152387531;
   fWeightMatrix0to1[16][11] = 0.444623666321414;
   fWeightMatrix0to1[17][11] = 1.69970848225059;
   fWeightMatrix0to1[18][11] = 0.532654761530655;
   fWeightMatrix0to1[19][11] = 1.114763827135;
   fWeightMatrix0to1[20][11] = 2.23997873688747;
   fWeightMatrix0to1[21][11] = -1.70379568567907;
   fWeightMatrix0to1[22][11] = -4.22817762041748;
   fWeightMatrix0to1[23][11] = -1.11504284454573;
   fWeightMatrix0to1[24][11] = 4.70824367627896;
   fWeightMatrix0to1[25][11] = 0.119603834355287;
   fWeightMatrix0to1[0][12] = -2.83071110410986;
   fWeightMatrix0to1[1][12] = 4.94549668005069;
   fWeightMatrix0to1[2][12] = 1.35865024895224;
   fWeightMatrix0to1[3][12] = 0.345253135126548;
   fWeightMatrix0to1[4][12] = 3.27486520868123;
   fWeightMatrix0to1[5][12] = -2.49150018237354;
   fWeightMatrix0to1[6][12] = 1.83148325439369;
   fWeightMatrix0to1[7][12] = 0.231693545810088;
   fWeightMatrix0to1[8][12] = -1.17820316504069;
   fWeightMatrix0to1[9][12] = -0.143167424246954;
   fWeightMatrix0to1[10][12] = 5.13841877232265;
   fWeightMatrix0to1[11][12] = 1.86374258540432;
   fWeightMatrix0to1[12][12] = 0.321849671996303;
   fWeightMatrix0to1[13][12] = 0.56174306717732;
   fWeightMatrix0to1[14][12] = 0.778943919327772;
   fWeightMatrix0to1[15][12] = 3.31009035474593;
   fWeightMatrix0to1[16][12] = 2.56926308236112;
   fWeightMatrix0to1[17][12] = 2.66858076817075;
   fWeightMatrix0to1[18][12] = -2.25897218567567;
   fWeightMatrix0to1[19][12] = 2.40387395095245;
   fWeightMatrix0to1[20][12] = -2.66941727593403;
   fWeightMatrix0to1[21][12] = -1.84104472946741;
   fWeightMatrix0to1[22][12] = -4.26071041866185;
   fWeightMatrix0to1[23][12] = 2.67410741469914;
   fWeightMatrix0to1[24][12] = 2.67913715889669;
   fWeightMatrix0to1[25][12] = 1.85516691947675;
   fWeightMatrix0to1[0][13] = 2.51955848107905;
   fWeightMatrix0to1[1][13] = -0.778275285755364;
   fWeightMatrix0to1[2][13] = -5.70226371440545;
   fWeightMatrix0to1[3][13] = 2.29756537661094;
   fWeightMatrix0to1[4][13] = 1.70432489129563;
   fWeightMatrix0to1[5][13] = -5.37979658497237;
   fWeightMatrix0to1[6][13] = -10.7626856415911;
   fWeightMatrix0to1[7][13] = -1.50948414978247;
   fWeightMatrix0to1[8][13] = -0.244033796316033;
   fWeightMatrix0to1[9][13] = -2.21728722564721;
   fWeightMatrix0to1[10][13] = 5.36592312894354;
   fWeightMatrix0to1[11][13] = -2.25088745367351;
   fWeightMatrix0to1[12][13] = 1.29272121987962;
   fWeightMatrix0to1[13][13] = 8.89130560060399;
   fWeightMatrix0to1[14][13] = 0.172239585633059;
   fWeightMatrix0to1[15][13] = -5.59138958243064;
   fWeightMatrix0to1[16][13] = -2.50845753975799;
   fWeightMatrix0to1[17][13] = -1.87918597970709;
   fWeightMatrix0to1[18][13] = -2.51879595552059;
   fWeightMatrix0to1[19][13] = 1.04705400136332;
   fWeightMatrix0to1[20][13] = -5.82030244776392;
   fWeightMatrix0to1[21][13] = -1.14882187950323;
   fWeightMatrix0to1[22][13] = 2.11797098306286;
   fWeightMatrix0to1[23][13] = -3.01913752712832;
   fWeightMatrix0to1[24][13] = -1.04898941162953;
   fWeightMatrix0to1[25][13] = -2.24303286934855;
   fWeightMatrix0to1[0][14] = 3.26027257841074;
   fWeightMatrix0to1[1][14] = -3.00077611794362;
   fWeightMatrix0to1[2][14] = -3.86124652641184;
   fWeightMatrix0to1[3][14] = -3.90320988646515;
   fWeightMatrix0to1[4][14] = -12.507331208879;
   fWeightMatrix0to1[5][14] = -0.860546609298446;
   fWeightMatrix0to1[6][14] = 1.77582241456881;
   fWeightMatrix0to1[7][14] = -1.26722657669188;
   fWeightMatrix0to1[8][14] = -1.10057696535196;
   fWeightMatrix0to1[9][14] = -1.29504846401178;
   fWeightMatrix0to1[10][14] = 5.71706255644962;
   fWeightMatrix0to1[11][14] = -0.891865886153585;
   fWeightMatrix0to1[12][14] = 0.346102927802706;
   fWeightMatrix0to1[13][14] = 14.3293014065632;
   fWeightMatrix0to1[14][14] = 2.7837047514734;
   fWeightMatrix0to1[15][14] = -18.3416118787267;
   fWeightMatrix0to1[16][14] = -10.3761744196325;
   fWeightMatrix0to1[17][14] = -1.13902646269841;
   fWeightMatrix0to1[18][14] = -0.485889223962339;
   fWeightMatrix0to1[19][14] = 0.899182396848078;
   fWeightMatrix0to1[20][14] = 6.85604933801651;
   fWeightMatrix0to1[21][14] = 0.0911830477255558;
   fWeightMatrix0to1[22][14] = 2.7717506483243;
   fWeightMatrix0to1[23][14] = -1.63042225644784;
   fWeightMatrix0to1[24][14] = -0.279998848583099;
   fWeightMatrix0to1[25][14] = -1.98957850478812;
   fWeightMatrix0to1[0][15] = 3.93226077140141;
   fWeightMatrix0to1[1][15] = -0.327612338100234;
   fWeightMatrix0to1[2][15] = -5.38690628639822;
   fWeightMatrix0to1[3][15] = -3.14917285683221;
   fWeightMatrix0to1[4][15] = -3.74360270802816;
   fWeightMatrix0to1[5][15] = 1.6008962397801;
   fWeightMatrix0to1[6][15] = 5.84714825122814;
   fWeightMatrix0to1[7][15] = 0.795174498623574;
   fWeightMatrix0to1[8][15] = 2.08855981834311;
   fWeightMatrix0to1[9][15] = -2.89003559927193;
   fWeightMatrix0to1[10][15] = 6.95540485439462;
   fWeightMatrix0to1[11][15] = 0.682133177337932;
   fWeightMatrix0to1[12][15] = 0.480875223003846;
   fWeightMatrix0to1[13][15] = 1.4104632739367;
   fWeightMatrix0to1[14][15] = 1.32978538182304;
   fWeightMatrix0to1[15][15] = -10.5957240905831;
   fWeightMatrix0to1[16][15] = -3.03719825311836;
   fWeightMatrix0to1[17][15] = 1.30133343564263;
   fWeightMatrix0to1[18][15] = 0.463353692067052;
   fWeightMatrix0to1[19][15] = -0.830357477101535;
   fWeightMatrix0to1[20][15] = 2.49981490281873;
   fWeightMatrix0to1[21][15] = -1.33196967185489;
   fWeightMatrix0to1[22][15] = 2.01182739816141;
   fWeightMatrix0to1[23][15] = -3.2866441852921;
   fWeightMatrix0to1[24][15] = -1.5794726344811;
   fWeightMatrix0to1[25][15] = -0.824101168918932;
   fWeightMatrix0to1[0][16] = 4.06636416120293;
   fWeightMatrix0to1[1][16] = -1.54245159918031;
   fWeightMatrix0to1[2][16] = 4.5117846682568;
   fWeightMatrix0to1[3][16] = -8.21290346725603;
   fWeightMatrix0to1[4][16] = -10.9770731301414;
   fWeightMatrix0to1[5][16] = 5.40923628156708;
   fWeightMatrix0to1[6][16] = 11.3912548856467;
   fWeightMatrix0to1[7][16] = -2.12932374850994;
   fWeightMatrix0to1[8][16] = -0.954600628139285;
   fWeightMatrix0to1[9][16] = -2.70114977582242;
   fWeightMatrix0to1[10][16] = 3.66974453115445;
   fWeightMatrix0to1[11][16] = -3.00359857339901;
   fWeightMatrix0to1[12][16] = -1.14669690024944;
   fWeightMatrix0to1[13][16] = 13.0439024091346;
   fWeightMatrix0to1[14][16] = 3.00658514857216;
   fWeightMatrix0to1[15][16] = -18.5857760418084;
   fWeightMatrix0to1[16][16] = -13.8169804042926;
   fWeightMatrix0to1[17][16] = -0.684009275364615;
   fWeightMatrix0to1[18][16] = 5.02618614683236;
   fWeightMatrix0to1[19][16] = 1.8205817161726;
   fWeightMatrix0to1[20][16] = 10.6535722135941;
   fWeightMatrix0to1[21][16] = -0.66299112857142;
   fWeightMatrix0to1[22][16] = -0.0483419911580712;
   fWeightMatrix0to1[23][16] = -2.11257912040611;
   fWeightMatrix0to1[24][16] = -3.68498819522837;
   fWeightMatrix0to1[25][16] = -2.27652756601279;
   fWeightMatrix0to1[0][17] = 0.612304153833575;
   fWeightMatrix0to1[1][17] = -0.051487480504418;
   fWeightMatrix0to1[2][17] = -1.11455057187654;
   fWeightMatrix0to1[3][17] = 1.0125148222184;
   fWeightMatrix0to1[4][17] = 1.8126915684299;
   fWeightMatrix0to1[5][17] = 1.14634386603206;
   fWeightMatrix0to1[6][17] = -0.75238357522657;
   fWeightMatrix0to1[7][17] = -2.44924228096596;
   fWeightMatrix0to1[8][17] = 2.31432860824479;
   fWeightMatrix0to1[9][17] = -1.2754504846421;
   fWeightMatrix0to1[10][17] = -0.334204875883582;
   fWeightMatrix0to1[11][17] = 2.95038962499376;
   fWeightMatrix0to1[12][17] = 1.0440708619664;
   fWeightMatrix0to1[13][17] = -3.35471681304511;
   fWeightMatrix0to1[14][17] = 0.410990952065304;
   fWeightMatrix0to1[15][17] = -1.38167882006739;
   fWeightMatrix0to1[16][17] = 7.31650830233285;
   fWeightMatrix0to1[17][17] = 1.09571411371696;
   fWeightMatrix0to1[18][17] = 1.20560970300227;
   fWeightMatrix0to1[19][17] = 0.52348172219817;
   fWeightMatrix0to1[20][17] = -0.808613336477501;
   fWeightMatrix0to1[21][17] = -0.616769938329901;
   fWeightMatrix0to1[22][17] = 1.08323910605945;
   fWeightMatrix0to1[23][17] = 0.829339978735641;
   fWeightMatrix0to1[24][17] = -2.86270037868758;
   fWeightMatrix0to1[25][17] = -0.262104999249338;
   fWeightMatrix0to1[0][18] = 0.948664438511293;
   fWeightMatrix0to1[1][18] = 1.79178009335385;
   fWeightMatrix0to1[2][18] = 1.03559086479978;
   fWeightMatrix0to1[3][18] = -1.50499656856105;
   fWeightMatrix0to1[4][18] = -1.73953041999838;
   fWeightMatrix0to1[5][18] = 3.07416724144701;
   fWeightMatrix0to1[6][18] = 0.920017287380015;
   fWeightMatrix0to1[7][18] = -2.67503853790331;
   fWeightMatrix0to1[8][18] = 0.277498292490839;
   fWeightMatrix0to1[9][18] = -1.66155973849262;
   fWeightMatrix0to1[10][18] = 0.493693189343488;
   fWeightMatrix0to1[11][18] = 2.92234024159569;
   fWeightMatrix0to1[12][18] = -1.25080886386019;
   fWeightMatrix0to1[13][18] = -3.03366632724262;
   fWeightMatrix0to1[14][18] = 0.695427416126589;
   fWeightMatrix0to1[15][18] = 1.08561107018201;
   fWeightMatrix0to1[16][18] = 5.66496568873061;
   fWeightMatrix0to1[17][18] = -0.507497757749253;
   fWeightMatrix0to1[18][18] = 0.207612154181713;
   fWeightMatrix0to1[19][18] = -0.384206386136652;
   fWeightMatrix0to1[20][18] = 0.556112447839549;
   fWeightMatrix0to1[21][18] = 0.35344046835909;
   fWeightMatrix0to1[22][18] = 0.279569370808045;
   fWeightMatrix0to1[23][18] = -1.25354816133684;
   fWeightMatrix0to1[24][18] = -3.7780987031809;
   fWeightMatrix0to1[25][18] = -0.711596351835522;
   fWeightMatrix0to1[0][19] = -0.655881327654699;
   fWeightMatrix0to1[1][19] = 1.49854259505875;
   fWeightMatrix0to1[2][19] = 7.76196017790917;
   fWeightMatrix0to1[3][19] = 0.999904389807736;
   fWeightMatrix0to1[4][19] = 0.938605243192859;
   fWeightMatrix0to1[5][19] = 0.24309474234421;
   fWeightMatrix0to1[6][19] = -3.72654884318289;
   fWeightMatrix0to1[7][19] = 1.79616126288035;
   fWeightMatrix0to1[8][19] = 1.35862495061425;
   fWeightMatrix0to1[9][19] = 1.76052472550093;
   fWeightMatrix0to1[10][19] = -5.49733281435455;
   fWeightMatrix0to1[11][19] = -2.81465229665845;
   fWeightMatrix0to1[12][19] = 2.27294067442038;
   fWeightMatrix0to1[13][19] = -4.27662442152929;
   fWeightMatrix0to1[14][19] = 0.123808293452846;
   fWeightMatrix0to1[15][19] = 1.79652804739467;
   fWeightMatrix0to1[16][19] = -2.33942980550828;
   fWeightMatrix0to1[17][19] = -1.9072729250354;
   fWeightMatrix0to1[18][19] = -0.443819706145758;
   fWeightMatrix0to1[19][19] = -0.516406159020614;
   fWeightMatrix0to1[20][19] = 6.89037995211395;
   fWeightMatrix0to1[21][19] = -0.608940339670462;
   fWeightMatrix0to1[22][19] = 1.2107529647974;
   fWeightMatrix0to1[23][19] = 2.49642163369405;
   fWeightMatrix0to1[24][19] = 1.20587357095256;
   fWeightMatrix0to1[25][19] = 0.633122814078459;
   // weight matrix from layer 1 to 2
   fWeightMatrix1to2[0][0] = 2.91937028841987;
   fWeightMatrix1to2[0][1] = -1.07792509969511;
   fWeightMatrix1to2[0][2] = 1.87259108951503;
   fWeightMatrix1to2[0][3] = -0.722782301508786;
   fWeightMatrix1to2[0][4] = -1.04616191645844;
   fWeightMatrix1to2[0][5] = 0.74019859119675;
   fWeightMatrix1to2[0][6] = 1.72415371198305;
   fWeightMatrix1to2[0][7] = 0.446956372005812;
   fWeightMatrix1to2[0][8] = -0.2190645164796;
   fWeightMatrix1to2[0][9] = -0.362149846121459;
   fWeightMatrix1to2[0][10] = -4.95905373890172;
   fWeightMatrix1to2[0][11] = -1.35745750683344;
   fWeightMatrix1to2[0][12] = -0.482244927553041;
   fWeightMatrix1to2[0][13] = 1.04435881929907;
   fWeightMatrix1to2[0][14] = 0.293861055131917;
   fWeightMatrix1to2[0][15] = -1.13800874939433;
   fWeightMatrix1to2[0][16] = -0.254641700976114;
   fWeightMatrix1to2[0][17] = -1.54427984760634;
   fWeightMatrix1to2[0][18] = 1.00813030150424;
   fWeightMatrix1to2[0][19] = -1.4386994523207;
   fWeightMatrix1to2[0][20] = 0.471890675905275;
   fWeightMatrix1to2[0][21] = -0.955766887572356;
   fWeightMatrix1to2[0][22] = 0.873233339710397;
   fWeightMatrix1to2[0][23] = 1.77980967619831;
   fWeightMatrix1to2[0][24] = -0.8156297837771;
   fWeightMatrix1to2[0][25] = -0.664206443287842;
   fWeightMatrix1to2[0][26] = 0.0860353964432913;
}

inline double ReadDeuteron_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;
   }

   std::array<double, 20> fWeights0 {{}};
   std::array<double, 27> fWeights1 {{}};
   std::array<double, 1> fWeights2 {{}};
   fWeights0.back() = 1.;
   fWeights1.back() = 1.;

   for (int i=0; i<fLayerSize[0]-1; i++)
      fWeights0[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] * fWeights0[i];
         fWeights1[o] += inputVal;
      } // loop over i
      fWeights1[o] = ActivationFnc(fWeights1[o]);
   } // loop over 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] * fWeights1[i];
         fWeights2[o] += inputVal;
      } // loop over i
      fWeights2[o] = OutputActivationFnc(fWeights2[o]);
   } // loop over o

   return fWeights2[0];
}

double ReadDeuteron_Upstream_TMVA::ActivationFnc(double x) const {
   // hyperbolic tan
   return tanh(x);
}
double ReadDeuteron_Upstream_TMVA::OutputActivationFnc(double x) const {
   // sigmoid
   return 1.0/(1.0+exp(-x));
}
   
// Clean up
inline void ReadDeuteron_Upstream_TMVA::Clear() 
{
}
   inline double ReadDeuteron_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 ReadDeuteron_Upstream_TMVA::InitTransform_1()
{
   // Normalization transformation, initialisation
   fMin_1[0][0] = 515.130004883;
   fMax_1[0][0] = 4994126;
   fMin_1[1][0] = 270.440002441;
   fMax_1[1][0] = 4909704.5;
   fMin_1[2][0] = 270.440002441;
   fMax_1[2][0] = 4994126;
   fMin_1[0][1] = 23.427822113;
   fMax_1[0][1] = 805216.125;
   fMin_1[1][1] = 21.6379623413;
   fMax_1[1][1] = 456651.5625;
   fMin_1[2][1] = 21.6379623413;
   fMax_1[2][1] = 805216.125;
   fMin_1[0][2] = 0.00191661447752;
   fMax_1[0][2] = 3.99318790436;
   fMin_1[1][2] = 0.00571004347876;
   fMax_1[1][2] = 3.99388027191;
   fMin_1[2][2] = 0.00191661447752;
   fMax_1[2][2] = 3.99388027191;
   fMin_1[0][3] = 4;
   fMax_1[0][3] = 30;
   fMin_1[1][3] = 4;
   fMax_1[1][3] = 28;
   fMin_1[2][3] = 4;
   fMax_1[2][3] = 30;
   fMin_1[0][4] = 0.0016649417812;
   fMax_1[0][4] = 0.399961650372;
   fMin_1[1][4] = 0.00192681478802;
   fMax_1[1][4] = 0.399999767542;
   fMin_1[2][4] = 0.0016649417812;
   fMax_1[2][4] = 0.399999767542;
   fMin_1[0][5] = 0.00105275434908;
   fMax_1[0][5] = 47.814994812;
   fMin_1[1][5] = 0.000152601263835;
   fMax_1[1][5] = 63.4452209473;
   fMin_1[2][5] = 0.000152601263835;
   fMax_1[2][5] = 63.4452209473;
   fMin_1[0][6] = 1;
   fMax_1[0][6] = 27;
   fMin_1[1][6] = 1;
   fMax_1[1][6] = 24;
   fMin_1[2][6] = 1;
   fMax_1[2][6] = 27;
   fMin_1[0][7] = 0;
   fMax_1[0][7] = 1;
   fMin_1[1][7] = 0;
   fMax_1[1][7] = 1;
   fMin_1[2][7] = 0;
   fMax_1[2][7] = 1;
   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] = -999;
   fMax_1[0][11] = 74.1856002808;
   fMin_1[1][11] = -999;
   fMax_1[1][11] = 136.249404907;
   fMin_1[2][11] = -999;
   fMax_1[2][11] = 136.249404907;
   fMin_1[0][12] = -999;
   fMax_1[0][12] = 45.3797988892;
   fMin_1[1][12] = -999;
   fMax_1[1][12] = 95.2298965454;
   fMin_1[2][12] = -999;
   fMax_1[2][12] = 95.2298965454;
   fMin_1[0][13] = -999;
   fMax_1[0][13] = 94.5334014893;
   fMin_1[1][13] = -999;
   fMax_1[1][13] = 103.673202515;
   fMin_1[2][13] = -999;
   fMax_1[2][13] = 103.673202515;
   fMin_1[0][14] = -999;
   fMax_1[0][14] = 117.643798828;
   fMin_1[1][14] = -999;
   fMax_1[1][14] = 107.83380127;
   fMin_1[2][14] = -999;
   fMax_1[2][14] = 117.643798828;
   fMin_1[0][15] = -999;
   fMax_1[0][15] = 144.49710083;
   fMin_1[1][15] = -999;
   fMax_1[1][15] = 84.462600708;
   fMin_1[2][15] = -999;
   fMax_1[2][15] = 144.49710083;
   fMin_1[0][16] = -999;
   fMax_1[0][16] = 55.7882003784;
   fMin_1[1][16] = -999;
   fMax_1[1][16] = 49.8718986511;
   fMin_1[2][16] = -999;
   fMax_1[2][16] = 55.7882003784;
   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;
}

//_______________________________________________________________________
inline void ReadDeuteron_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 = 19;

   // 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);
   } 
   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);
   } 

   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<19;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 ReadDeuteron_Upstream_TMVA::InitTransform()
{
   InitTransform_1();
}

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