yangyong/Regression/TMVARegGui.C

#include <iostream>
#include <vector>

#include "TROOT.h"
#include "TControlBar.h"
#include "tmvaglob.C"

// some global lists
static TList*               TMVAGui_keyContent;
static std::vector<TString> TMVAGui_inactiveButtons;

TList* GetKeyList( const TString& pattern )
{
   TList* list = new TList();

   TIter next( TMVAGui_keyContent );
   TKey* key(0);
   while ((key = (TKey*)next())) {         
      if (TString(key->GetName()).Contains( pattern )) { list->Add( new TObjString( key->GetName() ) ); }
   }
   return list;
}

// utility function
void ActionButton( TControlBar* cbar, 
                   const TString& title, const TString& macro, const TString& comment, 
                   const TString& buttonType, TString requiredKey = "" ) 
{
   cbar->AddButton( title, macro, comment, buttonType );

   // search    
   if (requiredKey != "") {
      Bool_t found = kFALSE;
      TIter next( TMVAGui_keyContent );
      TKey* key(0);
      while ((key = (TKey*)next())) {         
         if (TString(key->GetName()).Contains( requiredKey )) { found = kTRUE; break; }
      }
      if (!found) TMVAGui_inactiveButtons.push_back( title );
   }
}

// main GUI
void TMVARegGui( const char* fName = "TMVAReg.root" ) 
{   
   // Use this script in order to run the various individual macros
   // that plot the output of TMVA (e.g. running TMVARegression.C),
   // stored in the file "TMVA.Regroot"

   TString curMacroPath(gROOT->GetMacroPath());
   // uncomment next line for macros submitted to next root version
   gROOT->SetMacroPath(curMacroPath+":./:$ROOTSYS/tmva/test/:");

   // for the sourceforge version, including $ROOTSYS/tmva/test in the
   // macro path is a mistake, especially if "./" was not part of path
   // add ../macros to the path (comment out next line for the ROOT version of TMVA)
   // gROOT->SetMacroPath(curMacroPath+":../macros:");

   TString curIncludePath=gSystem->GetIncludePath();
   //std::cout <<"inc path="<<curIncludePath<<std::endl;
   TString newIncludePath=TString("-I../ ")+curIncludePath;
   gSystem->SetIncludePath(newIncludePath);
  
   cout << "--- Launch TMVA GUI to view input file: " << fName << endl;

   // init
   TMVAGui_inactiveButtons.clear();

   // check if file exist
   TFile* file = TFile::Open( fName );
   if (!file) {
      cout << "==> Abort TMVAGui, please verify filename" << endl;
      return;
   }
   // find all references   
   TMVAGui_keyContent = (TList*)file->GetListOfKeys()->Clone();

   // close file
   file->Close();

   TString defaultRequiredClassifier = "";

   //   gROOT->Reset();
   //   gStyle->SetScreenFactor(2); // if you have a large screen, select 1,2 or 1.4

   // create the control bar
   TControlBar* cbar = new TControlBar( "vertical", "TMVA Plotting Macros for Regression", 0, 0 );

   const TString buttonType( "button" );

   // configure buttons   
   Int_t ic = 1;

   // find all input variables types
   TList* keylist = GetKeyList( "InputVariables" );
   TListIter it( keylist );
   TObjString* str = 0;
   char ch = 'a';
   while (str = (TObjString*)it()) {
      TString tmp   = str->GetString();
      TString title = Form( "Input variables and target(s) '%s'-transformed (training sample)", 
                            tmp.ReplaceAll("InputVariables_","").Data() );
      if (tmp.Contains( "Id" )) title = "Input variables and target(s) (training sample)";
      ActionButton( cbar, 
                    Form( "    (%i%c) %s    ", ic, ch++, title.Data() ),
                    Form( ".x variables.C(\"%s\",\"%s\",\"%s\",kTRUE)", fName, str->GetString().Data(), title.Data() ),
                    Form( "Plots all '%s'-transformed input variables and target(s) (macro variables.C(...))", 
                          str->GetString().Data() ),
                    buttonType, str->GetString() );
   }      
   ic++;

   // correlation scatter plots 
   it.Reset(); ch = 'a';
   while (str = (TObjString*)it()) {
      TString tmp   = str->GetString();
      TString title = Form( "Input variable correlations '%s'-transformed (scatter profiles)", 
                            tmp.ReplaceAll("InputVariables_","").Data() );
      if (tmp.Contains( "Id" )) title = "Input variable correlations (scatter profiles)";
      ActionButton( cbar, 
                    Form( "(%i%c) %s", ic, ch++, title.Data() ),
                    Form( ".x CorrGui.C(\"%s\",\"%s\",\"%s\",kTRUE)", fName, str->GetString().Data(), title.Data() ),
                    Form( "Plots all correlation profiles between '%s'-transformed input variables (macro CorrGui.C(...))", 
                          str->GetString().Data() ),
                    buttonType, str->GetString() );
   }      
   
   // coefficients
   ActionButton( cbar,  
                 Form( "(%i) Input Variable Linear Correlation Coefficients", ++ic ),
                 Form( ".x correlations.C(\"%s\",kTRUE)", fName ),
                 "Plots signal and background correlation summaries for all input variables (macro correlations.C)", 
                 buttonType );

   ActionButton( cbar,  
                 Form( "(%ia) Regression Output Deviation versus Target (test sample)", ++ic ),
                 Form( ".x deviations.C(\"%s\",0,kTRUE)", fName ),
                 "Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
                 buttonType, defaultRequiredClassifier );

   ActionButton( cbar,  
                 Form( "(%ib) Regression Output Deviation versus Target (training sample)", ic ),
                 Form( ".x deviations.C(\"%s\",3,kTRUE)", fName ),
                 "Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
                 buttonType, defaultRequiredClassifier );

   ActionButton( cbar,  
                 Form( "(%ic) Regression Output Deviation versus Input Variables (test sample)", ic ),
                 Form( ".x deviations.C(\"%s\",0,kFALSE)", fName ),
                 "Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
                 buttonType, defaultRequiredClassifier );

   ActionButton( cbar,  
                 Form( "   (%id) Regression Output Deviation versus Input Variables (training sample)   ", ic ),
                 Form( ".x deviations.C(\"%s\",3,kFALSE)", fName ),
                 "Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
                 buttonType, defaultRequiredClassifier );

   ActionButton( cbar,  
                 Form( "(%i) Summary of Average Regression Deviations ", ++ic ),
                 Form( ".x regression_averagedevs.C(\"%s\")", fName ),
                 "Plot Summary of average deviations: MVAvalue - target (macro regression_averagedevs.C)",
                 buttonType );

   ActionButton( cbar,  
                 Form( "(%ia) Network Architecture", ++ic ),
                 Form( ".x network.C(\"%s\")", fName ), 
                 "Plots the MLP weights (macro network.C)",
                 buttonType, "MLP" );

   ActionButton( cbar,  
                 Form( "(%ib) Network Convergence Test", ic ),
                 Form( ".x annconvergencetest.C(\"%s\")", fName ), 
                 "Plots error estimator versus training epoch for training and test samples (macro annconvergencetest.C)",
                 buttonType, "MLP" );

   ActionButton( cbar,  
                 Form( "(%i) Plot Foams", ++ic ),
                 Form( ".x PlotFoams.C(\"weights/TMVARegression_PDEFoam.weights_foams.root\")", fName ),
                 "Plot Foams (macro PlotFoams.C)",
                 buttonType, "PDEFoam" );

   ActionButton( cbar,  
                 Form( "(%i) Regression Trees (BDT)", ++ic ),
                 Form( ".x BDT_Reg.C+(\"%s\")", fName ),
                 "Plots the Regression Trees trained by BDT algorithms (macro BDT_Reg.C(itree,...))",
                 buttonType, "BDT" );

   ActionButton( cbar,  
                 Form( "(%i) Regression Tree Control Plots (BDT)", ++ic ),
                 Form( ".x BDTControlPlots.C(\"%s\")", fName ),
                 "Plots to monitor boosting and pruning of regression trees (macro BDTControlPlots.C)",
                 buttonType, "BDT" );

   cbar->AddSeparator();

   cbar->AddButton( Form( "(%i) Quit", ++ic ),   ".q", "Quit", buttonType );

   // set the style 
   cbar->SetTextColor("black");

   // there seems to be a bug in ROOT: font jumps back to default after pressing on >2 different buttons
   // cbar->SetFont("-adobe-helvetica-bold-r-*-*-12-*-*-*-*-*-iso8859-1");
   
   // draw
   cbar->Show();

   // indicate inactive buttons
   for (UInt_t i=0; i<TMVAGui_inactiveButtons.size(); i++) cbar->SetButtonState( TMVAGui_inactiveButtons[i], 3 );
   if (TMVAGui_inactiveButtons.size() > 0) {
      cout << "=== Note: inactive buttons indicate that the corresponding methods were not trained ===" << endl;
   }

   gROOT->SaveContext();
}
Revision:	1.1
Committed:	Mon May 14 11:42:54 2012 UTC (13 years ago) by yangyong
Content type:	text/plain
Branch:	MAIN
CVS Tags:	V00-00-01, HEAD
Log Message:	train regression in tmva
#	User	Rev	Content
1	yangyong	1.1	#include <iostream>
2			#include <vector>
3
4			#include "TROOT.h"
5			#include "TControlBar.h"
6			#include "tmvaglob.C"
7
8			// some global lists
9			static TList* TMVAGui_keyContent;
10			static std::vector<TString> TMVAGui_inactiveButtons;
11
12			TList* GetKeyList( const TString& pattern )
13			{
14			TList* list = new TList();
15
16			TIter next( TMVAGui_keyContent );
17			TKey* key(0);
18			while ((key = (TKey*)next())) {
19			if (TString(key->GetName()).Contains( pattern )) { list->Add( new TObjString( key->GetName() ) ); }
20			}
21			return list;
22			}
23
24			// utility function
25			void ActionButton( TControlBar* cbar,
26			const TString& title, const TString& macro, const TString& comment,
27			const TString& buttonType, TString requiredKey = "" )
28			{
29			cbar->AddButton( title, macro, comment, buttonType );
30
31			// search
32			if (requiredKey != "") {
33			Bool_t found = kFALSE;
34			TIter next( TMVAGui_keyContent );
35			TKey* key(0);
36			while ((key = (TKey*)next())) {
37			if (TString(key->GetName()).Contains( requiredKey )) { found = kTRUE; break; }
38			}
39			if (!found) TMVAGui_inactiveButtons.push_back( title );
40			}
41			}
42
43			// main GUI
44			void TMVARegGui( const char* fName = "TMVAReg.root" )
45			{
46			// Use this script in order to run the various individual macros
47			// that plot the output of TMVA (e.g. running TMVARegression.C),
48			// stored in the file "TMVA.Regroot"
49
50			TString curMacroPath(gROOT->GetMacroPath());
51			// uncomment next line for macros submitted to next root version
52			gROOT->SetMacroPath(curMacroPath+":./:$ROOTSYS/tmva/test/:");
53
54			// for the sourceforge version, including $ROOTSYS/tmva/test in the
55			// macro path is a mistake, especially if "./" was not part of path
56			// add ../macros to the path (comment out next line for the ROOT version of TMVA)
57			// gROOT->SetMacroPath(curMacroPath+":../macros:");
58
59			TString curIncludePath=gSystem->GetIncludePath();
60			//std::cout <<"inc path="<<curIncludePath<<std::endl;
61			TString newIncludePath=TString("-I../ ")+curIncludePath;
62			gSystem->SetIncludePath(newIncludePath);
63
64			cout << "--- Launch TMVA GUI to view input file: " << fName << endl;
65
66			// init
67			TMVAGui_inactiveButtons.clear();
68
69			// check if file exist
70			TFile* file = TFile::Open( fName );
71			if (!file) {
72			cout << "==> Abort TMVAGui, please verify filename" << endl;
73			return;
74			}
75			// find all references
76			TMVAGui_keyContent = (TList*)file->GetListOfKeys()->Clone();
77
78			// close file
79			file->Close();
80
81			TString defaultRequiredClassifier = "";
82
83			// gROOT->Reset();
84			// gStyle->SetScreenFactor(2); // if you have a large screen, select 1,2 or 1.4
85
86			// create the control bar
87			TControlBar* cbar = new TControlBar( "vertical", "TMVA Plotting Macros for Regression", 0, 0 );
88
89			const TString buttonType( "button" );
90
91			// configure buttons
92			Int_t ic = 1;
93
94			// find all input variables types
95			TList* keylist = GetKeyList( "InputVariables" );
96			TListIter it( keylist );
97			TObjString* str = 0;
98			char ch = 'a';
99			while (str = (TObjString*)it()) {
100			TString tmp = str->GetString();
101			TString title = Form( "Input variables and target(s) '%s'-transformed (training sample)",
102			tmp.ReplaceAll("InputVariables_","").Data() );
103			if (tmp.Contains( "Id" )) title = "Input variables and target(s) (training sample)";
104			ActionButton( cbar,
105			Form( " (%i%c) %s ", ic, ch++, title.Data() ),
106			Form( ".x variables.C(\"%s\",\"%s\",\"%s\",kTRUE)", fName, str->GetString().Data(), title.Data() ),
107			Form( "Plots all '%s'-transformed input variables and target(s) (macro variables.C(...))",
108			str->GetString().Data() ),
109			buttonType, str->GetString() );
110			}
111			ic++;
112
113			// correlation scatter plots
114			it.Reset(); ch = 'a';
115			while (str = (TObjString*)it()) {
116			TString tmp = str->GetString();
117			TString title = Form( "Input variable correlations '%s'-transformed (scatter profiles)",
118			tmp.ReplaceAll("InputVariables_","").Data() );
119			if (tmp.Contains( "Id" )) title = "Input variable correlations (scatter profiles)";
120			ActionButton( cbar,
121			Form( "(%i%c) %s", ic, ch++, title.Data() ),
122			Form( ".x CorrGui.C(\"%s\",\"%s\",\"%s\",kTRUE)", fName, str->GetString().Data(), title.Data() ),
123			Form( "Plots all correlation profiles between '%s'-transformed input variables (macro CorrGui.C(...))",
124			str->GetString().Data() ),
125			buttonType, str->GetString() );
126			}
127
128			// coefficients
129			ActionButton( cbar,
130			Form( "(%i) Input Variable Linear Correlation Coefficients", ++ic ),
131			Form( ".x correlations.C(\"%s\",kTRUE)", fName ),
132			"Plots signal and background correlation summaries for all input variables (macro correlations.C)",
133			buttonType );
134
135			ActionButton( cbar,
136			Form( "(%ia) Regression Output Deviation versus Target (test sample)", ++ic ),
137			Form( ".x deviations.C(\"%s\",0,kTRUE)", fName ),
138			"Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
139			buttonType, defaultRequiredClassifier );
140
141			ActionButton( cbar,
142			Form( "(%ib) Regression Output Deviation versus Target (training sample)", ic ),
143			Form( ".x deviations.C(\"%s\",3,kTRUE)", fName ),
144			"Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
145			buttonType, defaultRequiredClassifier );
146
147			ActionButton( cbar,
148			Form( "(%ic) Regression Output Deviation versus Input Variables (test sample)", ic ),
149			Form( ".x deviations.C(\"%s\",0,kFALSE)", fName ),
150			"Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
151			buttonType, defaultRequiredClassifier );
152
153			ActionButton( cbar,
154			Form( " (%id) Regression Output Deviation versus Input Variables (training sample) ", ic ),
155			Form( ".x deviations.C(\"%s\",3,kFALSE)", fName ),
156			"Plots the deviation between regression output and target versus target on test data (macro deviations.C(...,0))",
157			buttonType, defaultRequiredClassifier );
158
159			ActionButton( cbar,
160			Form( "(%i) Summary of Average Regression Deviations ", ++ic ),
161			Form( ".x regression_averagedevs.C(\"%s\")", fName ),
162			"Plot Summary of average deviations: MVAvalue - target (macro regression_averagedevs.C)",
163			buttonType );
164
165			ActionButton( cbar,
166			Form( "(%ia) Network Architecture", ++ic ),
167			Form( ".x network.C(\"%s\")", fName ),
168			"Plots the MLP weights (macro network.C)",
169			buttonType, "MLP" );
170
171			ActionButton( cbar,
172			Form( "(%ib) Network Convergence Test", ic ),
173			Form( ".x annconvergencetest.C(\"%s\")", fName ),
174			"Plots error estimator versus training epoch for training and test samples (macro annconvergencetest.C)",
175			buttonType, "MLP" );
176
177			ActionButton( cbar,
178			Form( "(%i) Plot Foams", ++ic ),
179			Form( ".x PlotFoams.C(\"weights/TMVARegression_PDEFoam.weights_foams.root\")", fName ),
180			"Plot Foams (macro PlotFoams.C)",
181			buttonType, "PDEFoam" );
182
183			ActionButton( cbar,
184			Form( "(%i) Regression Trees (BDT)", ++ic ),
185			Form( ".x BDT_Reg.C+(\"%s\")", fName ),
186			"Plots the Regression Trees trained by BDT algorithms (macro BDT_Reg.C(itree,...))",
187			buttonType, "BDT" );
188
189			ActionButton( cbar,
190			Form( "(%i) Regression Tree Control Plots (BDT)", ++ic ),
191			Form( ".x BDTControlPlots.C(\"%s\")", fName ),
192			"Plots to monitor boosting and pruning of regression trees (macro BDTControlPlots.C)",
193			buttonType, "BDT" );
194
195			cbar->AddSeparator();
196
197			cbar->AddButton( Form( "(%i) Quit", ++ic ), ".q", "Quit", buttonType );
198
199			// set the style
200			cbar->SetTextColor("black");
201
202			// there seems to be a bug in ROOT: font jumps back to default after pressing on >2 different buttons
203			// cbar->SetFont("-adobe-helvetica-bold-r---12-----*-iso8859-1");
204
205			// draw
206			cbar->Show();
207
208			// indicate inactive buttons
209			for (UInt_t i=0; i<TMVAGui_inactiveButtons.size(); i++) cbar->SetButtonState( TMVAGui_inactiveButtons[i], 3 );
210			if (TMVAGui_inactiveButtons.size() > 0) {
211			cout << "=== Note: inactive buttons indicate that the corresponding methods were not trained ===" << endl;
212			}
213
214			gROOT->SaveContext();
215			}