| 1 |
#include "tmvaglob.C"
|
| 2 |
|
| 3 |
// this macro serves to assess the convergence of the MLP ANN.
|
| 4 |
// It compares the error estimator for the training and testing samples.
|
| 5 |
// If overtraining occurred, the estimator for the training sample should
|
| 6 |
// monotoneously decrease, while the estimator of the testing sample should
|
| 7 |
// show a minimum after which it increases.
|
| 8 |
|
| 9 |
// input: - Input file (result from TMVA),
|
| 10 |
// - use of TMVA plotting TStyle
|
| 11 |
void annconvergencetest( TString fin = "TMVA.root", Bool_t useTMVAStyle = kTRUE )
|
| 12 |
{
|
| 13 |
// set style and remove existing canvas'
|
| 14 |
TMVAGlob::Initialize( useTMVAStyle );
|
| 15 |
|
| 16 |
// checks if file with name "fin" is already open, and if not opens one
|
| 17 |
TFile* file = TMVAGlob::OpenFile( fin );
|
| 18 |
|
| 19 |
// get all titles of the method likelihood
|
| 20 |
TList titles;
|
| 21 |
UInt_t ninst = TMVAGlob::GetListOfTitles("Method_MLP",titles);
|
| 22 |
if (ninst==0) {
|
| 23 |
cout << "Could not locate directory 'Method_MLP' in file " << fin << endl;
|
| 24 |
return;
|
| 25 |
}
|
| 26 |
// loop over all titles
|
| 27 |
TIter keyIter(&titles);
|
| 28 |
TDirectory *lhdir;
|
| 29 |
TKey *key;
|
| 30 |
while ((key = TMVAGlob::NextKey(keyIter,"TDirectory"))) {
|
| 31 |
lhdir = (TDirectory *)key->ReadObj();
|
| 32 |
annconvergencetest( lhdir );
|
| 33 |
}
|
| 34 |
}
|
| 35 |
|
| 36 |
void annconvergencetest( TDirectory *lhdir )
|
| 37 |
{
|
| 38 |
TString jobName = lhdir->GetName();
|
| 39 |
static icanvas = -1;
|
| 40 |
icanvas++;
|
| 41 |
TCanvas* c = new TCanvas( Form("MLPConvergenceTest_%s",jobName.Data()), Form("MLP Convergence Test, %s",jobName.Data()),
|
| 42 |
100 + (icanvas)*40, 0 + (icanvas+1)*20, 600, 580*0.8 );
|
| 43 |
|
| 44 |
TH1* estimatorHistTrain = (TH1*)lhdir->Get( "estimatorHistTrain" );
|
| 45 |
TH1* estimatorHistTest = (TH1*)lhdir->Get( "estimatorHistTest" );
|
| 46 |
|
| 47 |
Double_t m1 = estimatorHistTrain->GetMaximum();
|
| 48 |
Double_t m2 = estimatorHistTest ->GetMaximum();
|
| 49 |
Double_t max = TMath::Max( m1, m2 );
|
| 50 |
m1 = estimatorHistTrain->GetMinimum();
|
| 51 |
m2 = estimatorHistTest ->GetMinimum();
|
| 52 |
Double_t min = TMath::Min( m1, m2 );
|
| 53 |
estimatorHistTrain->SetMaximum( max + 0.1*(max - min) );
|
| 54 |
estimatorHistTrain->SetMinimum( min - 0.1*(max - min) );
|
| 55 |
estimatorHistTrain->SetLineColor( 2 );
|
| 56 |
estimatorHistTrain->SetLineWidth( 2 );
|
| 57 |
estimatorHistTrain->SetTitle( TString("MLP Convergence Test") );
|
| 58 |
|
| 59 |
estimatorHistTest->SetLineColor( 4 );
|
| 60 |
estimatorHistTest->SetLineWidth( 2 );
|
| 61 |
|
| 62 |
estimatorHistTrain->GetXaxis()->SetTitle( "Epochs" );
|
| 63 |
estimatorHistTrain->GetYaxis()->SetTitle( "Estimator" );
|
| 64 |
estimatorHistTrain->GetXaxis()->SetTitleOffset( 1.20 );
|
| 65 |
estimatorHistTrain->GetYaxis()->SetTitleOffset( 1.65 );
|
| 66 |
|
| 67 |
estimatorHistTrain->Draw();
|
| 68 |
estimatorHistTest ->Draw("same");
|
| 69 |
|
| 70 |
// need a legend
|
| 71 |
TLegend *legend= new TLegend( 1 - c->GetRightMargin() - 0.45, 1-c->GetTopMargin() - 0.20,
|
| 72 |
1 - c->GetRightMargin() - 0.05, 1-c->GetTopMargin() - 0.05 );
|
| 73 |
|
| 74 |
legend->AddEntry(estimatorHistTrain,"Training Sample","l");
|
| 75 |
legend->AddEntry(estimatorHistTest,"Test sample","l");
|
| 76 |
legend->Draw("same");
|
| 77 |
legend->SetMargin( 0.3 );
|
| 78 |
|
| 79 |
c->cd();
|
| 80 |
TMVAGlob::plot_logo(); // don't understand why this doesn't work ... :-(
|
| 81 |
c->Update();
|
| 82 |
|
| 83 |
TString fname = "plots/annconvergencetest";
|
| 84 |
TMVAGlob::imgconv( c, fname );
|
| 85 |
}
|
