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Reference Guide
TMVAClassificationCategoryApplication.C
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1/// \file
2/// \ingroup tutorial_tmva
3/// \notebook -nodraw
4/// This macro provides a simple example on how to use the trained classifiers
5/// (with categories) within an analysis module
6/// - Project : TMVA - a Root-integrated toolkit for multivariate data analysis
7/// - Package : TMVA
8/// - Executable: TMVAClassificationCategoryApplication
9///
10/// \macro_output
11/// \macro_code
12/// \author Andreas Hoecker
13
14
15#include <cstdlib>
16#include <vector>
17#include <iostream>
18#include <map>
19#include <string>
20
21#include "TFile.h"
22#include "TTree.h"
23#include "TString.h"
24#include "TSystem.h"
25#include "TROOT.h"
26#include "TH1F.h"
27#include "TStopwatch.h"
28
29#if not defined(__CINT__) || defined(__MAKECINT__)
30#include "TMVA/Tools.h"
31#include "TMVA/Reader.h"
32#include "TMVA/MethodCuts.h"
33#endif
34
35// two types of category methods are implemented
36Bool_t UseOffsetMethod = kTRUE;
37
38void TMVAClassificationCategoryApplication()
39{
40 // ---------------------------------------------------------------
41 // default MVA methods to be trained + tested
42 std::map<std::string,int> Use;
43 //
44 Use["LikelihoodCat"] = 1;
45 Use["FisherCat"] = 1;
46 // ---------------------------------------------------------------
47
48 std::cout << std::endl
49 << "==> Start TMVAClassificationCategoryApplication" << std::endl;
50
51 // Create the Reader object
52
53 TMVA::Reader *reader = new TMVA::Reader( "!Color:!Silent" );
54
55 // Create a set of variables and spectators and declare them to the reader
56 // - the variable names MUST corresponds in name and type to those given in the weight file(s) used
57 Float_t var1, var2, var3, var4, eta;
58 reader->AddVariable( "var1", &var1 );
59 reader->AddVariable( "var2", &var2 );
60 reader->AddVariable( "var3", &var3 );
61 reader->AddVariable( "var4", &var4 );
62
63 reader->AddSpectator( "eta", &eta );
64
65 // Book the MVA methods
66
67 for (std::map<std::string,int>::iterator it = Use.begin(); it != Use.end(); it++) {
68 if (it->second) {
69 TString methodName = it->first + " method";
70 TString weightfile = "dataset/weights/TMVAClassificationCategory_" + TString(it->first) + ".weights.xml";
71 reader->BookMVA( methodName, weightfile );
72 }
73 }
74
75 // Book output histograms
76 UInt_t nbin = 100;
77 std::map<std::string,TH1*> hist;
78 hist["LikelihoodCat"] = new TH1F( "MVA_LikelihoodCat", "MVA_LikelihoodCat", nbin, -1, 0.9999 );
79 hist["FisherCat"] = new TH1F( "MVA_FisherCat", "MVA_FisherCat", nbin, -4, 4 );
80
81 // Prepare input tree (this must be replaced by your data source)
82 // in this example, there is a toy tree with signal and one with background events
83 // we'll later on use only the "signal" events for the test in this example.
84 //
85 TString fname = gSystem->GetDirName(__FILE__) + "/data/";
86 // if directory data not found try using tutorials dir
87 if (gSystem->AccessPathName( fname + "toy_sigbkg_categ_offset.root" )) {
88 fname = gROOT->GetTutorialDir() + "/tmva/data/";
89 }
90 if (UseOffsetMethod) fname += "toy_sigbkg_categ_offset.root";
91 else fname += "toy_sigbkg_categ_varoff.root";
92 std::cout << "--- TMVAClassificationApp : Accessing " << fname << "!" << std::endl;
93 TFile *input = TFile::Open(fname);
94 if (!input) {
95 std::cout << "ERROR: could not open data file: " << fname << std::endl;
96 exit(1);
97 }
98
99 // Event loop
100
101 // Prepare the tree
102 // - here the variable names have to corresponds to your tree
103 // - you can use the same variables as above which is slightly faster,
104 // but of course you can use different ones and copy the values inside the event loop
105 //
106 TTree* theTree = (TTree*)input->Get("TreeS");
107 std::cout << "--- Use signal sample for evaluation" << std::endl;
108 theTree->SetBranchAddress( "var1", &var1 );
109 theTree->SetBranchAddress( "var2", &var2 );
110 theTree->SetBranchAddress( "var3", &var3 );
111 theTree->SetBranchAddress( "var4", &var4 );
112
113 theTree->SetBranchAddress( "eta", &eta ); // spectator
114
115 std::cout << "--- Processing: " << theTree->GetEntries() << " events" << std::endl;
116 TStopwatch sw;
117 sw.Start();
118 for (Long64_t ievt=0; ievt<theTree->GetEntries();ievt++) {
119
120 if (ievt%1000 == 0) std::cout << "--- ... Processing event: " << ievt << std::endl;
121
122 theTree->GetEntry(ievt);
123
124 // Return the MVA outputs and fill into histograms
125
126 for (std::map<std::string,int>::iterator it = Use.begin(); it != Use.end(); it++) {
127 if (!it->second) continue;
128 TString methodName = it->first + " method";
129 hist[it->first]->Fill( reader->EvaluateMVA( methodName ) );
130 }
131
132 }
133 sw.Stop();
134 std::cout << "--- End of event loop: "; sw.Print();
135
136 // Write histograms
137
138 TFile *target = new TFile( "TMVApp.root","RECREATE" );
139 for (std::map<std::string,int>::iterator it = Use.begin(); it != Use.end(); it++)
140 if (it->second) hist[it->first]->Write();
141
142 target->Close();
143 std::cout << "--- Created root file: \"TMVApp.root\" containing the MVA output histograms" << std::endl;
144
145 delete reader;
146 std::cout << "==> TMVAClassificationApplication is done!" << std::endl << std::endl;
147}
148
149int main( int argc, char** argv )
150{
151 TMVAClassificationCategoryApplication();
152 return 0;
153}
unsigned int UInt_t
Definition: RtypesCore.h:46
bool Bool_t
Definition: RtypesCore.h:63
long long Long64_t
Definition: RtypesCore.h:80
float Float_t
Definition: RtypesCore.h:57
const Bool_t kTRUE
Definition: RtypesCore.h:100
#define gROOT
Definition: TROOT.h:404
R__EXTERN TSystem * gSystem
Definition: TSystem.h:559
int main(int argc, char *argv[])
Definition: cef_main.cxx:54
TObject * Get(const char *namecycle) override
Return pointer to object identified by namecycle.
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format.
Definition: TFile.h:54
static TFile * Open(const char *name, Option_t *option="", const char *ftitle="", Int_t compress=ROOT::RCompressionSetting::EDefaults::kUseCompiledDefault, Int_t netopt=0)
Create / open a file.
Definition: TFile.cxx:4011
void Close(Option_t *option="") override
Close a file.
Definition: TFile.cxx:889
1-D histogram with a float per channel (see TH1 documentation)}
Definition: TH1.h:575
The Reader class serves to use the MVAs in a specific analysis context.
Definition: Reader.h:64
Double_t EvaluateMVA(const std::vector< Float_t > &, const TString &methodTag, Double_t aux=0)
Evaluate a std::vector<float> of input data for a given method The parameter aux is obligatory for th...
Definition: Reader.cxx:468
IMethod * BookMVA(const TString &methodTag, const TString &weightfile)
read method name from weight file
Definition: Reader.cxx:368
void AddSpectator(const TString &expression, Float_t *)
Add a float spectator or expression to the reader.
Definition: Reader.cxx:321
void AddVariable(const TString &expression, Float_t *)
Add a float variable or expression to the reader.
Definition: Reader.cxx:303
Stopwatch class.
Definition: TStopwatch.h:28
void Start(Bool_t reset=kTRUE)
Start the stopwatch.
Definition: TStopwatch.cxx:58
void Stop()
Stop the stopwatch.
Definition: TStopwatch.cxx:77
void Print(Option_t *option="") const
Print the real and cpu time passed between the start and stop events.
Definition: TStopwatch.cxx:219
Basic string class.
Definition: TString.h:136
virtual Bool_t AccessPathName(const char *path, EAccessMode mode=kFileExists)
Returns FALSE if one can access a file using the specified access mode.
Definition: TSystem.cxx:1296
virtual TString GetDirName(const char *pathname)
Return the directory name in pathname.
Definition: TSystem.cxx:1032
A TTree represents a columnar dataset.
Definition: TTree.h:79
virtual Int_t GetEntry(Long64_t entry, Int_t getall=0)
Read all branches of entry and return total number of bytes read.
Definition: TTree.cxx:5606
virtual Int_t SetBranchAddress(const char *bname, void *add, TBranch **ptr=0)
Change branch address, dealing with clone trees properly.
Definition: TTree.cxx:8340
virtual Long64_t GetEntries() const
Definition: TTree.h:459