/usr/include/root/TMVA/TNeuron.h is in libroot-tmva-dev 5.34.30-0ubuntu8.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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// Author: Matt Jachowski
/**********************************************************************************
* Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
* Package: TMVA *
* Class : TMVA::TNeuron *
* Web : http://tmva.sourceforge.net *
* *
* Description: *
* Neuron class to be used in MethodANNBase and its derivatives. *
* *
* Authors (alphabetical): *
* Matt Jachowski <jachowski@stanford.edu> - Stanford University, USA *
* *
* Copyright (c) 2005: *
* CERN, Switzerland *
* *
* Redistribution and use in source and binary forms, with or without *
* modification, are permitted according to the terms listed in LICENSE *
* (http://tmva.sourceforge.net/LICENSE) *
**********************************************************************************/
#ifndef ROOT_TMVA_TNeuron
#define ROOT_TMVA_TNeuron
//////////////////////////////////////////////////////////////////////////
// //
// TNeuron //
// //
// Neuron used by derivatives of MethodANNBase //
// //
//////////////////////////////////////////////////////////////////////////
#include <iostream>
#ifndef ROOT_TString
#include "TString.h"
#endif
#ifndef ROOT_TObjArray
#include "TObjArray.h"
#endif
#ifndef ROOT_TFormula
#include "TFormula.h"
#endif
#ifndef ROOT_TMVA_TSynapse
#include "TMVA/TSynapse.h"
#endif
#ifndef ROOT_TMVA_TActivation
#include "TMVA/TActivation.h"
#endif
#ifndef ROOT_TMVA_Types
#include "TMVA/Types.h"
#endif
namespace TMVA {
class TNeuronInput;
class TNeuron : public TObject {
public:
TNeuron();
virtual ~TNeuron();
// force the input value
void ForceValue(Double_t value);
// calculate the input value
void CalculateValue();
// calculate the activation value
void CalculateActivationValue();
// calculate the error field of the neuron
void CalculateDelta();
// set the activation function
void SetActivationEqn(TActivation* activation);
// set the input calculator
void SetInputCalculator(TNeuronInput* calculator);
// add a synapse as a pre-link
void AddPreLink(TSynapse* pre);
// add a synapse as a post-link
void AddPostLink(TSynapse* post);
// delete all pre-links
void DeletePreLinks();
// set the error
void SetError(Double_t error);
// update the error fields of all pre-synapses, batch mode
// to actually update the weights, call adjust synapse weights
void UpdateSynapsesBatch();
// update the error fields and weights of all pre-synapses, sequential mode
void UpdateSynapsesSequential();
// update the weights of the all pre-synapses, batch mode
//(call UpdateSynapsesBatch first)
void AdjustSynapseWeights();
// explicitly initialize error fields of pre-synapses, batch mode
void InitSynapseDeltas();
// print activation equation, for debugging
void PrintActivationEqn();
// inlined functions
Double_t GetValue() const { return fValue; }
Double_t GetActivationValue() const { return fActivationValue; }
Double_t GetDelta() const { return fDelta; }
Double_t GetDEDw() const { return fDEDw; }
Int_t NumPreLinks() const { return NumLinks(fLinksIn); }
Int_t NumPostLinks() const { return NumLinks(fLinksOut); }
TSynapse* PreLinkAt ( Int_t index ) const { return (TSynapse*)fLinksIn->At(index); }
TSynapse* PostLinkAt( Int_t index ) const { return (TSynapse*)fLinksOut->At(index); }
void SetInputNeuron() { NullifyLinks(fLinksIn); }
void SetOutputNeuron() { NullifyLinks(fLinksOut); }
void SetBiasNeuron() { NullifyLinks(fLinksIn); }
void SetDEDw( Double_t DEDw ) { fDEDw = DEDw; }
Bool_t IsInputNeuron() const { return fLinksIn == NULL; }
Bool_t IsOutputNeuron() const { return fLinksOut == NULL; }
void PrintPreLinks() const { PrintLinks(fLinksIn); return; }
void PrintPostLinks() const { PrintLinks(fLinksOut); return; }
virtual void Print(Option_t* = "") const {
std::cout << fValue << std::endl;
//PrintPreLinks(); PrintPostLinks();
}
private:
// prviate helper functions
void InitNeuron();
void DeleteLinksArray( TObjArray*& links );
void PrintLinks ( TObjArray* links ) const;
void PrintMessage ( EMsgType, TString message );
// inlined helper functions
Int_t NumLinks(TObjArray* links) const {
if (links == NULL) return 0; return links->GetEntriesFast();
}
void NullifyLinks(TObjArray*& links) {
if (links != NULL) delete links; links = NULL;
}
// private member variables
TObjArray* fLinksIn; // array of input synapses
TObjArray* fLinksOut; // array of output synapses
Double_t fValue; // input value
Double_t fActivationValue; // activation/output value
Double_t fDelta; // error field of neuron
Double_t fDEDw; // sum of all deltas
Double_t fError; // error, only set for output neurons
Bool_t fForcedValue; // flag for forced input value
TActivation* fActivation; // activation equation
TNeuronInput* fInputCalculator; // input calculator
static MsgLogger* fgLogger; //! message logger, static to save resources
MsgLogger& Log() const { return *fgLogger; }
ClassDef(TNeuron,0) // Neuron class used by MethodANNBase derivative ANNs
};
} // namespace TMVA
#endif
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