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TMLPAnalyzer.h
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1 // @(#)root/mlp:$Id$
2 // Author: Christophe.Delaere@cern.ch 25/04/04
3 
4 /*************************************************************************
5  * Copyright (C) 1995-2003, Rene Brun and Fons Rademakers. *
6  * All rights reserved. *
7  * *
8  * For the licensing terms see $ROOTSYS/LICENSE. *
9  * For the list of contributors see $ROOTSYS/README/CREDITS. *
10  *************************************************************************/
11 
12 #ifndef ROOT_TMLPAnalyzer
13 #define ROOT_TMLPAnalyzer
14 
15 
16 #include "TObject.h"
17 
18 class TTree;
19 class TNeuron;
20 class TSynapse;
22 class TProfile;
23 class THStack;
24 
25 class TMLPAnalyzer : public TObject {
26 
27 private:
31 
32 protected:
33  Int_t GetLayers();
34  Int_t GetNeurons(Int_t layer);
36  const char* GetInputNeuronTitle(Int_t in);
37  const char* GetOutputNeuronTitle(Int_t out);
38 
39 public:
41  fNetwork(&net), fAnalysisTree(0), fIOTree(0) {}
43  fNetwork(net), fAnalysisTree(0), fIOTree(0) {}
44  virtual ~TMLPAnalyzer();
45  void DrawNetwork(Int_t neuron, const char* signal, const char* bg);
46  void DrawDInput(Int_t i);
47  void DrawDInputs();
48  TProfile* DrawTruthDeviation(Int_t outnode=0, Option_t *option="");
50  TProfile* DrawTruthDeviationInOut(Int_t innode, Int_t outnode=0,
51  Option_t *option="");
52  THStack* DrawTruthDeviationInsOut(Int_t outnode=0, Option_t *option="");
53 
54  void CheckNetwork();
55  void GatherInformations();
56  TTree* GetIOTree() const { return fIOTree;}
57 
58  ClassDef(TMLPAnalyzer, 0) // A simple analysis class for MLP
59 };
60 
61 #endif
TMLPAnalyzer::DrawTruthDeviationInOut
TProfile * DrawTruthDeviationInOut(Int_t innode, Int_t outnode=0, Option_t *option="")
Creates a profile of the difference of the MLP output outnode minus the true value of outnode vs the ...
Definition: TMLPAnalyzer.cxx:474
TMLPAnalyzer::GetNeuronFormula
TString GetNeuronFormula(Int_t idx)
Returns the formula used as input for neuron (idx) in the first layer.
Definition: TMLPAnalyzer.cxx:102
TMultiLayerPerceptron
Definition: TMultiLayerPerceptron.h:26
TMLPAnalyzer::DrawTruthDeviation
TProfile * DrawTruthDeviation(Int_t outnode=0, Option_t *option="")
Create a profile of the difference of the MLP output minus the true value for a given output node out...
Definition: TMLPAnalyzer.cxx:398
THStack
Definition: THStack.h:38
TMLPAnalyzer::DrawTruthDeviations
THStack * DrawTruthDeviations(Option_t *option="")
Creates TProfiles of the difference of the MLP output minus the true value vs the true value,...
Definition: TMLPAnalyzer.cxx:431
TTree
Definition: TTree.h:79
TMLPAnalyzer::TMLPAnalyzer
TMLPAnalyzer(TMultiLayerPerceptron &net)
Definition: TMLPAnalyzer.h:40
Int_t
int Int_t
Definition: RtypesCore.h:45
TMLPAnalyzer::~TMLPAnalyzer
virtual ~TMLPAnalyzer()
Destructor.
Definition: TMLPAnalyzer.cxx:45
TMLPAnalyzer::GetIOTree
TTree * GetIOTree() const
Definition: TMLPAnalyzer.h:56
TMLPAnalyzer::fIOTree
TTree * fIOTree
Definition: TMLPAnalyzer.h:30
TMLPAnalyzer::DrawDInputs
void DrawDInputs()
Draws the distribution (on the test sample) of the impact on the network output of a small variation ...
Definition: TMLPAnalyzer.cxx:311
TString
Definition: TString.h:136
TMLPAnalyzer::TMLPAnalyzer
TMLPAnalyzer(TMultiLayerPerceptron *net)
Definition: TMLPAnalyzer.h:42
TMLPAnalyzer::DrawTruthDeviationInsOut
THStack * DrawTruthDeviationInsOut(Int_t outnode=0, Option_t *option="")
Creates a profile of the difference of the MLP output outnode minus the true value of outnode vs the ...
Definition: TMLPAnalyzer.cxx:506
TMLPAnalyzer::GetLayers
Int_t GetLayers()
Returns the number of layers.
Definition: TMLPAnalyzer.cxx:54
TMLPAnalyzer::GetNeurons
Int_t GetNeurons(Int_t layer)
Returns the number of neurons in given layer.
Definition: TMLPAnalyzer.cxx:63
TMLPAnalyzer
Definition: TMLPAnalyzer.h:25
TMLPAnalyzer::DrawDInput
void DrawDInput(Int_t i)
Draws the distribution (on the test sample) of the impact on the network output of a small variation ...
Definition: TMLPAnalyzer.cxx:284
Option_t
const typedef char Option_t
Definition: RtypesCore.h:66
TMLPAnalyzer::GatherInformations
void GatherInformations()
Collect information about what is useful in the network.
Definition: TMLPAnalyzer.cxx:170
TMLPAnalyzer::fNetwork
TMultiLayerPerceptron * fNetwork
Definition: TMLPAnalyzer.h:28
TMLPAnalyzer::DrawNetwork
void DrawNetwork(Int_t neuron, const char *signal, const char *bg)
Draws the distribution of the neural network (using ith neuron).
Definition: TMLPAnalyzer.cxx:337
TMLPAnalyzer::fAnalysisTree
TTree * fAnalysisTree
Definition: TMLPAnalyzer.h:29
TProfile
Definition: TProfile.h:32
TMLPAnalyzer::GetOutputNeuronTitle
const char * GetOutputNeuronTitle(Int_t out)
Returns the name of any neuron from the output layer.
Definition: TMLPAnalyzer.cxx:137
TMLPAnalyzer::CheckNetwork
void CheckNetwork()
Gives some information about the network in the terminal.
Definition: TMLPAnalyzer.cxx:146
TObject.h
TObject
Definition: TObject.h:37
ClassDef
#define ClassDef(name, id)
Definition: Rtypes.h:325
TMLPAnalyzer::GetInputNeuronTitle
const char * GetInputNeuronTitle(Int_t in)
Returns the name of any neuron from the input layer.
Definition: TMLPAnalyzer.cxx:128
TSynapse
Definition: TSynapse.h:20
int
TNeuron
Definition: TNeuron.h:25