// @(#)root/mlp:$Id: TMLPAnalyzer.h 20882 2007-11-19 11:31:26Z rdm $ // Author: Christophe.Delaere@cern.ch 25/04/04 /************************************************************************* * Copyright (C) 1995-2003, Rene Brun and Fons Rademakers. * * All rights reserved. * * * * For the licensing terms see $ROOTSYS/LICENSE. * * For the list of contributors see $ROOTSYS/README/CREDITS. * *************************************************************************/ #ifndef ROOT_TMLPAnalyzer #define ROOT_TMLPAnalyzer #ifndef ROOT_TObject #include "TObject.h" #endif class TTree; class TNeuron; class TSynapse; class TMultiLayerPerceptron; class TProfile; class THStack; //____________________________________________________________________ // // TMLPAnalyzer // // This utility class contains a set of tests usefull when developing // a neural network. // It allows you to check for unneeded variables, and to control // the network structure. // //-------------------------------------------------------------------- class TMLPAnalyzer : public TObject { private: TMultiLayerPerceptron *fNetwork; TTree *fAnalysisTree; TTree *fIOTree; protected: Int_t GetLayers(); Int_t GetNeurons(Int_t layer); TString GetNeuronFormula(Int_t idx); const char* GetInputNeuronTitle(Int_t in); const char* GetOutputNeuronTitle(Int_t out); public: TMLPAnalyzer(TMultiLayerPerceptron& net): fNetwork(&net), fAnalysisTree(0), fIOTree(0) {} TMLPAnalyzer(TMultiLayerPerceptron* net): fNetwork(net), fAnalysisTree(0), fIOTree(0) {} virtual ~TMLPAnalyzer(); void DrawNetwork(Int_t neuron, const char* signal, const char* bg); void DrawDInput(Int_t i); void DrawDInputs(); TProfile* DrawTruthDeviation(Int_t outnode=0, Option_t *option=""); THStack* DrawTruthDeviations(Option_t *option=""); TProfile* DrawTruthDeviationInOut(Int_t innode, Int_t outnode=0, Option_t *option=""); THStack* DrawTruthDeviationInsOut(Int_t outnode=0, Option_t *option=""); void CheckNetwork(); void GatherInformations(); TTree* GetIOTree() const { return fIOTree;} ClassDef(TMLPAnalyzer, 0) // A simple analysis class for MLP }; #endif