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benhoob |
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#include "TLegend.h"
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#include "TText.h"
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#include "TH2.h"
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#include "tmvaglob.C"
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// this macro plots the resulting MVA distributions (Signal and
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// Background overlayed) of different MVA methods run in TMVA
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// (e.g. running TMVAnalysis.C).
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enum HistType { MVAType = 0, ProbaType = 1, RarityType = 2, CompareType = 3 };
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// input: - Input file (result from TMVA)
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// - use of TMVA plotting TStyle
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void deviations( TString fin = "TMVAReg.root",
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HistType htype = MVAType, Bool_t showTarget, Bool_t useTMVAStyle = kTRUE )
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{
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// set style and remove existing canvas'
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TMVAGlob::Initialize( useTMVAStyle );
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gStyle->SetNumberContours(999);
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// switches
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const Bool_t Save_Images = kTRUE;
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// checks if file with name "fin" is already open, and if not opens one
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TFile* file = TMVAGlob::OpenFile( fin );
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// define Canvas layout here!
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Int_t xPad = 1; // no of plots in x
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Int_t yPad = 1; // no of plots in y
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Int_t noPad = xPad * yPad ;
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const Int_t width = 650; // size of canvas
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// this defines how many canvases we need
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TCanvas* c[100];
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// counter variables
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Int_t countCanvas = 0;
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// search for the right histograms in full list of keys
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// TList* methods = new TMap();
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TIter next(file->GetListOfKeys());
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TKey *key(0);
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while ((key = (TKey*)next())) {
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if (!TString(key->GetName()).BeginsWith("Method_")) continue;
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if (!gROOT->GetClass(key->GetClassName())->InheritsFrom("TDirectory")) continue;
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TString methodName;
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TMVAGlob::GetMethodName(methodName,key);
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cout << "--- Plotting deviation for method: " << methodName << endl;
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TObjString *mN = new TObjString( methodName );
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TDirectory* mDir = (TDirectory*)key->ReadObj();
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TList* jobNames = new TList();
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TIter keyIt(mDir->GetListOfKeys());
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TKey *titkey;
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while ((titkey = (TKey*)keyIt())) {
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if (!gROOT->GetClass(titkey->GetClassName())->InheritsFrom("TDirectory")) continue;
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TDirectory *titDir = (TDirectory *)titkey->ReadObj();
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TObjString *jN = new TObjString( titDir->GetName() );
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if (!jobNames->Contains( jN )) jobNames->Add( jN );
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else delete jN;
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TString methodTitle;
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TMVAGlob::GetMethodTitle(methodTitle,titDir);
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TString hname = "MVA_" + methodTitle;
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TIter dirKeyIt( titDir->GetListOfKeys() );
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TKey* dirKey;
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Int_t countPlots = 0;
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while ((dirKey = (TKey*)dirKeyIt())){
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if (dirKey->ReadObj()->InheritsFrom("TH2F")) {
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TString s(dirKey->ReadObj()->GetName());
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if (s.Contains("_reg_") &&
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( (showTarget && s.Contains("_tgt")) || (!showTarget && !s.Contains("_tgt")) ) &&
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s.Contains( (htype == CompareType ? "train" : "test" ))) {
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c[countCanvas] = new TCanvas( Form("canvas%d", countCanvas+1),
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Form( "Regression output deviation versus %s for method: %s",
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(showTarget ? "target" : "input variables"), methodName.Data() ),
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countCanvas*50+100, (countCanvas+1)*20, width, (Int_t)width*0.72 );
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c[countCanvas]->SetRightMargin(0.10); // leave space for border
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TH1* h = (TH1*)dirKey->ReadObj();
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h->SetTitle( Form("Output deviation for method: %s (%s sample)",
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hname.Data(), (htype == CompareType ? "training" : "test" )) );
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// methodName.Data(), (htype == CompareType ? "training" : "test" )) );
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h->Draw("colz");
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TLine* l = new TLine( h->GetXaxis()->GetXmin(), 0, h->GetXaxis()->GetXmax(), 0 );
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l->SetLineStyle(2);
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l->Draw();
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// update and print
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cout << "plotting logo" << endl;
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TMVAGlob::plot_logo(1.058);
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c[countCanvas]->Update();
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TString fname = Form( "plots/deviation_%s_%s_%s_c%i",
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methodName.Data(),
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(showTarget ? "target" : "vars"),
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(htype == CompareType ? "training" : "test" ), countPlots );
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TMVAGlob::imgconv( c[countCanvas], fname );
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countPlots++;
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countCanvas++;
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}
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}
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}
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}
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}
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}
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