| 1 |
kukartse |
1.1 |
#include "tmvaglob.C"
|
| 2 |
|
|
|
| 3 |
|
|
// this macro plots the MVA probability distributions (Signal and
|
| 4 |
|
|
// Background overlayed) of different MVA methods run in TMVA
|
| 5 |
|
|
// (e.g. running TMVAnalysis.C).
|
| 6 |
|
|
|
| 7 |
|
|
// input: - Input file (result from TMVA)
|
| 8 |
|
|
// - use of TMVA plotting TStyle
|
| 9 |
|
|
void probas( TString fin = "TMVA.root", Bool_t useTMVAStyle = kTRUE )
|
| 10 |
|
|
{
|
| 11 |
|
|
cout << "--- probas.C" << endl;
|
| 12 |
|
|
// set style and remove existing canvas'
|
| 13 |
|
|
TMVAGlob::Initialize( useTMVAStyle );
|
| 14 |
|
|
|
| 15 |
|
|
// switches
|
| 16 |
|
|
const Bool_t Draw_CFANN_Logy = kFALSE;
|
| 17 |
|
|
const Bool_t Save_Images = kTRUE;
|
| 18 |
|
|
|
| 19 |
|
|
// checks if file with name "fin" is already open, and if not opens one
|
| 20 |
|
|
TFile* file = TMVAGlob::OpenFile( fin );
|
| 21 |
|
|
|
| 22 |
|
|
// define Canvas layout here!
|
| 23 |
|
|
Int_t xPad = 1; // no of plots in x
|
| 24 |
|
|
Int_t yPad = 1; // no of plots in y
|
| 25 |
|
|
Int_t noPad = xPad * yPad ;
|
| 26 |
|
|
const Int_t width = 600; // size of canvas
|
| 27 |
|
|
|
| 28 |
|
|
// this defines how many canvases we need
|
| 29 |
|
|
TCanvas *c = 0;
|
| 30 |
|
|
|
| 31 |
|
|
// counter variables
|
| 32 |
|
|
Int_t countCanvas = 0;
|
| 33 |
|
|
|
| 34 |
|
|
// list of existing MVAs
|
| 35 |
|
|
const Int_t nveto = 1;
|
| 36 |
|
|
TString suffixSig = "_tr_S";
|
| 37 |
|
|
TString suffixBgd = "_tr_B";
|
| 38 |
|
|
|
| 39 |
|
|
// search for the right histograms in full list of keys
|
| 40 |
|
|
TList methods;
|
| 41 |
|
|
UInt_t nmethods = TMVAGlob::GetListOfMethods( methods );
|
| 42 |
|
|
if (nmethods==0) {
|
| 43 |
|
|
cout << "No methods found!" << endl;
|
| 44 |
|
|
return;
|
| 45 |
|
|
}
|
| 46 |
|
|
TIter next(&methods);
|
| 47 |
|
|
TKey *key, *hkey;
|
| 48 |
|
|
char fname[200];
|
| 49 |
|
|
TH1* sig(0);
|
| 50 |
|
|
TH1* bgd(0);
|
| 51 |
|
|
while ((key = (TKey*)next())) {
|
| 52 |
|
|
TDirectory * mDir = (TDirectory*)key->ReadObj();
|
| 53 |
|
|
TList titles;
|
| 54 |
|
|
UInt_t ni = TMVAGlob::GetListOfTitles( mDir, titles );
|
| 55 |
|
|
TString methodName;
|
| 56 |
|
|
TMVAGlob::GetMethodName(methodName,key);
|
| 57 |
|
|
if (ni==0) {
|
| 58 |
|
|
cout << "No titles found for " << methodName << endl;
|
| 59 |
|
|
return;
|
| 60 |
|
|
}
|
| 61 |
|
|
TIter nextTitle(&titles);
|
| 62 |
|
|
TKey *instkey;
|
| 63 |
|
|
TDirectory *instDir;
|
| 64 |
|
|
while ((instkey = (TKey *)nextTitle())) {
|
| 65 |
|
|
instDir = (TDirectory *)instkey->ReadObj();
|
| 66 |
|
|
TString instName = instkey->GetName();
|
| 67 |
|
|
TList h1hists;
|
| 68 |
|
|
UInt_t nhists = TMVAGlob::GetListOfKeys( h1hists, "TH1", instDir );
|
| 69 |
|
|
if (nhists==0) cout << "No hists found!" << endl;
|
| 70 |
|
|
TIter nextInDir(&h1hists);
|
| 71 |
|
|
TString methodTitle;
|
| 72 |
|
|
TMVAGlob::GetMethodTitle(methodTitle,instDir);
|
| 73 |
|
|
while (hkey = (TKey*)nextInDir()) {
|
| 74 |
|
|
TH1 *th1 = (TH1*)hkey->ReadObj();
|
| 75 |
|
|
TString hname= th1->GetName();
|
| 76 |
|
|
if (hname.Contains( suffixSig ) && !hname.Contains( "Cut") &&
|
| 77 |
|
|
!hname.Contains("original") && !hname.Contains("smoothed")) {
|
| 78 |
|
|
|
| 79 |
|
|
// retrieve corresponding signal and background histograms
|
| 80 |
|
|
TString hnameS = hname;
|
| 81 |
|
|
TString hnameB = hname; hnameB.ReplaceAll("_S","_B");
|
| 82 |
|
|
|
| 83 |
|
|
sig = (TH1*)instDir->Get( hnameS );
|
| 84 |
|
|
bgd = (TH1*)instDir->Get( hnameB );
|
| 85 |
|
|
|
| 86 |
|
|
if (sig == 0 || bgd == 0) {
|
| 87 |
|
|
cout << "--- probas.C: big troubles in probas.... histogram: " << hname << " not found" << endl;
|
| 88 |
|
|
return;
|
| 89 |
|
|
}
|
| 90 |
|
|
|
| 91 |
|
|
TH1* sigF(0);
|
| 92 |
|
|
TH1* bkgF(0);
|
| 93 |
|
|
for (int i=0; i<= 5; i++) {
|
| 94 |
|
|
TString hspline = hnameS + Form("_smoothed_hist_from_spline%i",i);
|
| 95 |
|
|
sigF = (TH1*)instDir->Get( hspline );
|
| 96 |
|
|
|
| 97 |
|
|
if (sigF) {
|
| 98 |
|
|
bkgF = (TH1*)instDir->Get( hspline.ReplaceAll("_tr_S","_tr_B") );
|
| 99 |
|
|
break;
|
| 100 |
|
|
}
|
| 101 |
|
|
}
|
| 102 |
|
|
if ((sigF == NULL || bkgF == NULL) &&!hname.Contains("hist") ) {
|
| 103 |
|
|
cout << "--- probas.C: big troubles - did not found histogram " << hspline.Data() << " "
|
| 104 |
|
|
<< sigF << " " << bkgF << endl;
|
| 105 |
|
|
return;
|
| 106 |
|
|
}
|
| 107 |
|
|
else {
|
| 108 |
|
|
// remove the signal suffix
|
| 109 |
|
|
|
| 110 |
|
|
// check that exist
|
| 111 |
|
|
if (NULL != sigF && NULL != bkgF && NULL!=sig && NULL!=bgd) {
|
| 112 |
|
|
|
| 113 |
|
|
TString hname = sig->GetName();
|
| 114 |
|
|
|
| 115 |
|
|
// chop off useless stuff
|
| 116 |
|
|
sig->SetTitle( TString("TMVA output for classifier: ") + methodTitle );
|
| 117 |
|
|
|
| 118 |
|
|
// create new canvas
|
| 119 |
|
|
cout << "--- Book canvas no: " << countCanvas << endl;
|
| 120 |
|
|
char cn[20];
|
| 121 |
|
|
sprintf( cn, "canvas%d", countCanvas+1 );
|
| 122 |
|
|
c = new TCanvas( cn, Form("TMVA Output Fit Variables %s",methodTitle.Data()),
|
| 123 |
|
|
countCanvas*50+200, countCanvas*20, width, width*0.78 );
|
| 124 |
|
|
|
| 125 |
|
|
// set the histogram style
|
| 126 |
|
|
TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
|
| 127 |
|
|
TMVAGlob::SetSignalAndBackgroundStyle( sigF, bkgF );
|
| 128 |
|
|
|
| 129 |
|
|
// frame limits (choose judicuous x range)
|
| 130 |
|
|
Float_t nrms = 4;
|
| 131 |
|
|
cout << "--- mean and RMS (S): " << sig->GetMean() << ", " << sig->GetRMS() << endl;
|
| 132 |
|
|
cout << "--- mean and RMS (B): " << bgd->GetMean() << ", " << bgd->GetRMS() << endl;
|
| 133 |
|
|
Float_t xmin = TMath::Max( TMath::Min(sig->GetMean() - nrms*sig->GetRMS(),
|
| 134 |
|
|
bgd->GetMean() - nrms*bgd->GetRMS() ),
|
| 135 |
|
|
sig->GetXaxis()->GetXmin() );
|
| 136 |
|
|
Float_t xmax = TMath::Min( TMath::Max(sig->GetMean() + nrms*sig->GetRMS(),
|
| 137 |
|
|
bgd->GetMean() + nrms*bgd->GetRMS() ),
|
| 138 |
|
|
sig->GetXaxis()->GetXmax() );
|
| 139 |
|
|
Float_t ymin = 0;
|
| 140 |
|
|
Float_t ymax = TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*1.5;
|
| 141 |
|
|
|
| 142 |
|
|
if (Draw_CFANN_Logy && mvaName[imva] == "CFANN") ymin = 0.01;
|
| 143 |
|
|
|
| 144 |
|
|
// build a frame
|
| 145 |
|
|
Int_t nb = 500;
|
| 146 |
|
|
TH2F* frame = new TH2F( TString("frame") + sig->GetName(), sig->GetTitle(),
|
| 147 |
|
|
nb, xmin, xmax, nb, ymin, ymax );
|
| 148 |
|
|
frame->GetXaxis()->SetTitle(methodTitle);
|
| 149 |
|
|
frame->GetYaxis()->SetTitle("Normalized");
|
| 150 |
|
|
TMVAGlob::SetFrameStyle( frame );
|
| 151 |
|
|
|
| 152 |
|
|
// eventually: draw the frame
|
| 153 |
|
|
frame->Draw();
|
| 154 |
|
|
|
| 155 |
|
|
if (Draw_CFANN_Logy && mvaName[imva] == "CFANN") c->SetLogy();
|
| 156 |
|
|
|
| 157 |
|
|
// overlay signal and background histograms
|
| 158 |
|
|
sig->SetMarkerColor(4);
|
| 159 |
|
|
sig->SetMarkerSize( 0.7 );
|
| 160 |
|
|
sig->SetMarkerStyle( 20 );
|
| 161 |
|
|
sig->SetLineWidth(1);
|
| 162 |
|
|
|
| 163 |
|
|
bgd->SetMarkerColor(2);
|
| 164 |
|
|
bgd->SetMarkerSize( 0.7 );
|
| 165 |
|
|
bgd->SetMarkerStyle( 24 );
|
| 166 |
|
|
bgd->SetLineWidth(1);
|
| 167 |
|
|
|
| 168 |
|
|
sig->Draw("samee");
|
| 169 |
|
|
bgd->Draw("samee");
|
| 170 |
|
|
|
| 171 |
|
|
sigF->SetFillStyle( 0 );
|
| 172 |
|
|
bkgF->SetFillStyle( 0 );
|
| 173 |
|
|
sigF->Draw("samehist");
|
| 174 |
|
|
bkgF->Draw("samehist");
|
| 175 |
|
|
|
| 176 |
|
|
// redraw axes
|
| 177 |
|
|
frame->Draw("sameaxis");
|
| 178 |
|
|
|
| 179 |
|
|
// Draw legend
|
| 180 |
|
|
TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.2,
|
| 181 |
|
|
c->GetLeftMargin() + 0.4, 1 - c->GetTopMargin() );
|
| 182 |
|
|
legend->AddEntry(sig,"Signal data","P");
|
| 183 |
|
|
legend->AddEntry(sigF,"Signal PDF","L");
|
| 184 |
|
|
legend->AddEntry(bgd,"Background data","P");
|
| 185 |
|
|
legend->AddEntry(bkgF,"Background PDF","L");
|
| 186 |
|
|
legend->Draw("same");
|
| 187 |
|
|
legend->SetBorderSize(1);
|
| 188 |
|
|
legend->SetMargin( 0.3 );
|
| 189 |
|
|
|
| 190 |
|
|
// save canvas to file
|
| 191 |
|
|
c->Update();
|
| 192 |
|
|
TMVAGlob::plot_logo();
|
| 193 |
|
|
sprintf( fname, "plots/mva_pdf_%s_c%i", methodTitle.Data(), countCanvas+1 );
|
| 194 |
|
|
if (Save_Images) TMVAGlob::imgconv( c, fname );
|
| 195 |
|
|
countCanvas++;
|
| 196 |
|
|
}
|
| 197 |
|
|
}
|
| 198 |
|
|
}
|
| 199 |
|
|
}
|
| 200 |
|
|
}
|
| 201 |
|
|
}
|
| 202 |
|
|
}
|
