72 fCallerName (callerName),
88 std::vector<Ranking*>::const_iterator it = fRanking.begin();
89 for (; it != fRanking.end(); ++it)
delete *it;
91 fTransformations.SetOwner();
100 fLogger->SetSource(
TString(
"TFHandler_" + fCallerName).Data() );
109 fTransformations.Add(trf);
110 fTransformationsReferenceClasses.push_back( cls );
127 Log() << kWARNING <<
"Variable \"" << Variable(ivar).GetExpression()
128 <<
"\" has zero, negative, or NaN RMS^2: "
130 <<
" ==> set to zero. Please check the variable content" <<
Endl;
135 fVariableStats.at(k).at(ivar) = stat;
144 for (
UInt_t i = 0; i < fTransformationsReferenceClasses.size(); i++) {
145 fTransformationsReferenceClasses.at( i ) = cls;
155 std::vector<Int_t>::const_iterator rClsIt = fTransformationsReferenceClasses.begin();
156 const Event* trEv = ev;
158 if (rClsIt == fTransformationsReferenceClasses.end())
Log() << kFATAL<<
"invalid read in TransformationHandler::Transform " <<
Endl;
159 trEv = trf->Transform(trEv, (*rClsIt) );
169 if (fTransformationsReferenceClasses.empty()){
175 std::vector< Int_t >::const_iterator rClsIt = fTransformationsReferenceClasses.end();
177 const Event* trEv = ev;
178 UInt_t nvars = 0, ntgts = 0, nspcts = 0;
180 if (trf->IsCreated()) {
181 trf->CountVariableTypes( nvars, ntgts, nspcts );
182 if( !(suppressIfNoTargets && ntgts==0) )
183 trEv = trf->InverseTransform(ev, (*rClsIt) );
214 if (fTransformations.GetEntries() <= 0)
221 std::vector<Event*> *transformedEvents =
new std::vector<TMVA::Event*>(events.size());
222 for (
UInt_t ievt = 0; ievt<events.size(); ievt++)
223 transformedEvents->at(ievt) =
new Event(*events.at(ievt));
226 std::vector< Int_t >::iterator rClsIt = fTransformationsReferenceClasses.begin();
228 if (trf->PrepareTransformation(*transformedEvents)) {
229 for (
UInt_t ievt = 0; ievt<transformedEvents->size(); ievt++) {
230 *(*transformedEvents)[ievt] = *trf->Transform((*transformedEvents)[ievt],(*rClsIt));
236 CalcStats(*transformedEvents);
239 PlotVariables(*transformedEvents);
243 if (!createNewVector) {
244 for (
UInt_t ievt = 0; ievt<transformedEvents->size(); ievt++)
245 delete (*transformedEvents)[ievt];
246 delete transformedEvents;
247 transformedEvents=NULL;
250 return transformedEvents;
259 UInt_t nevts = events.size();
262 Log() << kFATAL <<
"No events available to find min, max, mean and rms" <<
Endl;
265 const UInt_t nvar = events[0]->GetNVariables();
266 const UInt_t ntgt = events[0]->GetNTargets();
274 for (
Int_t cls=0; cls<fNumC; cls++) {
278 varMin[cls] =
new Double_t[nvar+ntgt];
279 varMax[cls] =
new Double_t[nvar+ntgt];
280 for (
UInt_t ivar=0; ivar<nvar+ntgt; ivar++) {
281 x0[cls][ivar] =
x2[cls][ivar] = 0;
282 varMin[cls][ivar] = DBL_MAX;
283 varMax[cls][ivar] = -DBL_MAX;
287 for (
UInt_t ievt=0; ievt<nevts; ievt++) {
288 const Event* ev = events[ievt];
292 sumOfWeights[cls] += weight;
293 if (fNumC > 1 ) sumOfWeights[fNumC-1] += weight;
294 for (
UInt_t var_tgt = 0; var_tgt < 2; var_tgt++ ){
295 UInt_t nloop = ( var_tgt==0?nvar:ntgt );
296 for (
UInt_t ivar=0; ivar<nloop; ivar++) {
299 if (
x < varMin[cls][(var_tgt*nvar)+ivar]) varMin[cls][(var_tgt*nvar)+ivar]=
x;
300 if (
x > varMax[cls][(var_tgt*nvar)+ivar]) varMax[cls][(var_tgt*nvar)+ivar]=
x;
302 x0[cls][(var_tgt*nvar)+ivar] +=
x*weight;
303 x2[cls][(var_tgt*nvar)+ivar] +=
x*
x*weight;
306 if (
x < varMin[fNumC-1][(var_tgt*nvar)+ivar]) varMin[fNumC-1][(var_tgt*nvar)+ivar]=
x;
307 if (
x > varMax[fNumC-1][(var_tgt*nvar)+ivar]) varMax[fNumC-1][(var_tgt*nvar)+ivar]=
x;
309 x0[fNumC-1][(var_tgt*nvar)+ivar] +=
x*weight;
310 x2[fNumC-1][(var_tgt*nvar)+ivar] +=
x*
x*weight;
318 for (
UInt_t var_tgt = 0; var_tgt < 2; var_tgt++ ){
319 UInt_t nloop = ( var_tgt==0?nvar:ntgt );
320 for (
UInt_t ivar=0; ivar<nloop; ivar++) {
321 for (
Int_t cls = 0; cls < fNumC; cls++) {
322 Double_t mean = x0[cls][(var_tgt*nvar)+ivar]/sumOfWeights[cls];
324 AddStats(cls, (var_tgt*nvar)+ivar, mean, rms, varMin[cls][(var_tgt*nvar)+ivar], varMax[cls][(var_tgt*nvar)+ivar]);
331 UInt_t maxL = 8, maxV = 0;
332 std::vector<UInt_t> vLengths;
333 for (
UInt_t ivar=0; ivar<nvar+ntgt; ivar++) {
341 UInt_t clen = maxL + 4*maxV + 11;
347 Log() << std::setw(maxL) <<
"Variable";
348 Log() <<
" " << std::setw(maxV) <<
"Mean";
349 Log() <<
" " << std::setw(maxV) <<
"RMS";
350 Log() <<
" " << std::setw(maxV) <<
"[ Min ";
351 Log() <<
" " << std::setw(maxV) <<
" Max ]"<<
Endl;;
352 for (
UInt_t i=0; i<clen; i++)
Log() <<
"-";
357 for (
UInt_t ivar=0; ivar<nvar+ntgt; ivar++) {
359 Log() << std::setw(maxL) << Variable(ivar).GetLabel() <<
":";
361 Log() << std::setw(maxL) << Target(ivar-nvar).GetLabel() <<
":";
362 Log() << std::setw(maxV) <<
Form( format.
Data(), GetMean(ivar) );
363 Log() << std::setw(maxV) <<
Form( format.
Data(), GetRMS(ivar) );
364 Log() <<
" [" << std::setw(maxV) <<
Form( format.
Data(), GetMin(ivar) );
365 Log() << std::setw(maxV) <<
Form( format.
Data(), GetMax(ivar) ) <<
" ]";
368 for (
UInt_t i=0; i<clen; i++)
Log() <<
"-";
372 delete[] sumOfWeights;
373 for (
Int_t cls=0; cls<fNumC; cls++) {
376 delete [] varMin[cls];
377 delete [] varMax[cls];
391 std::vector< Int_t >::const_iterator rClsIt = fTransformationsReferenceClasses.begin();
394 trf->MakeFunction(fout, fncName, part, trCounter++, (*rClsIt) );
398 for (
Int_t i=0; i<fTransformations.GetSize(); i++) {
399 fout <<
" void InitTransform_"<<i+1<<
"();" << std::endl;
400 fout <<
" void Transform_"<<i+1<<
"( std::vector<double> & iv, int sigOrBgd ) const;" << std::endl;
405 fout <<
"//_______________________________________________________________________" << std::endl;
406 fout <<
"inline void " << fncName <<
"::InitTransform()" << std::endl;
407 fout <<
"{" << std::endl;
408 for (
Int_t i=0; i<fTransformations.GetSize(); i++)
409 fout <<
" InitTransform_"<<i+1<<
"();" << std::endl;
410 fout <<
"}" << std::endl;
412 fout <<
"//_______________________________________________________________________" << std::endl;
413 fout <<
"inline void " << fncName <<
"::Transform( std::vector<double>& iv, int sigOrBgd ) const" << std::endl;
414 fout <<
"{" << std::endl;
415 for (
Int_t i=0; i<fTransformations.GetSize(); i++)
416 fout <<
" Transform_"<<i+1<<
"( iv, sigOrBgd );" << std::endl;
418 fout <<
"}" << std::endl;
444 if (fTransformations.GetSize() >= 1) {
445 if (fTransformations.GetSize() > 1 ||
447 xtit +=
" (" +
GetName() +
")";
461 if (fRootBaseDir==0 && theDirectory == 0)
return;
463 Log() << kDEBUG <<
"Plot event variables for ";
469 if (theDirectory == 0) {
476 const UInt_t nvar = fDataSetInfo.GetNVariables();
477 const UInt_t ntgt = fDataSetInfo.GetNTargets();
478 const Int_t ncls = fDataSetInfo.GetNClasses();
482 std::vector<std::vector<TH1*> > hVars( ncls );
483 std::vector<std::vector<std::vector<TH2F*> > > mycorr( ncls );
484 std::vector<std::vector<std::vector<TProfile*> > > myprof( ncls );
486 for (
Int_t cls = 0; cls < ncls; cls++) {
487 hVars.at(cls).resize ( nvar+ntgt );
488 hVars.at(cls).assign ( nvar+ntgt, 0 );
489 mycorr.at(cls).resize( nvar+ntgt );
490 myprof.at(cls).resize( nvar+ntgt );
491 for (
UInt_t ivar=0; ivar < nvar+ntgt; ivar++) {
492 mycorr.at(cls).at(ivar).resize( nvar+ntgt );
493 myprof.at(cls).at(ivar).resize( nvar+ntgt );
494 mycorr.at(cls).at(ivar).assign( nvar+ntgt, 0 );
495 myprof.at(cls).at(ivar).assign( nvar+ntgt, 0 );
502 if (nvar+ntgt > (
UInt_t)
gConfig().GetVariablePlotting().fMaxNumOfAllowedVariablesForScatterPlots) {
503 Int_t nhists = (nvar+ntgt)*(nvar+ntgt - 1)/2;
505 Log() << kINFO <<
"<PlotVariables> Will not produce scatter plots ==> " <<
Endl;
507 <<
"| The number of " << nvar <<
" input variables and " << ntgt <<
" target values would require "
508 << nhists <<
" two-dimensional" <<
Endl;
510 <<
"| histograms, which would occupy the computer's memory. Note that this" <<
Endl;
512 <<
"| suppression does not have any consequences for your analysis, other" <<
Endl;
514 <<
"| than not disposing of these scatter plots. You can modify the maximum" <<
Endl;
516 <<
"| number of input variables allowed to generate scatter plots in your" <<
Endl;
517 Log() <<
"| script via the command line:" <<
Endl;
519 <<
"| \"(TMVA::gConfig().GetVariablePlotting()).fMaxNumOfAllowedVariablesForScatterPlots = <some int>;\""
522 Log() << kINFO <<
"Some more output" <<
Endl;
529 for (
UInt_t var_tgt = 0; var_tgt < 2; var_tgt++) {
530 UInt_t nloops = ( var_tgt == 0? nvar:ntgt );
531 for (
UInt_t ivar=0; ivar<nloops; ivar++) {
532 const VariableInfo& info = ( var_tgt == 0 ? Variable( ivar ) : Target(ivar) );
535 Double_t mean = fVariableStats.at(fNumC-1).at( ( var_tgt*nvar )+ivar).fMean;
536 Double_t rms = fVariableStats.at(fNumC-1).at( ( var_tgt*nvar )+ivar).fRMS;
538 for (
Int_t cls = 0; cls < ncls; cls++) {
540 TString className = fDataSetInfo.GetClassInfo(cls)->GetName();
543 className += (ntgt == 1 && var_tgt == 1 ?
"_target" :
"");
571 h->GetXaxis()->SetTitle(
gTools().GetXTitleWithUnit( GetVariableAxisTitle( info ), info.
GetUnit() ) );
573 hVars.at(cls).at((var_tgt*nvar)+ivar) =
h;
576 if (nvar+ntgt <= (
UInt_t)
gConfig().GetVariablePlotting().fMaxNumOfAllowedVariablesForScatterPlots) {
578 for (
UInt_t v_t = 0; v_t < 2; v_t++) {
579 UInt_t nl = ( v_t==0?nvar:ntgt );
580 UInt_t start = ( v_t==0? (var_tgt==0?ivar+1:0):(var_tgt==0?nl:ivar+1) );
581 for (
UInt_t j=start; j<nl; j++) {
583 const VariableInfo& infoj = ( v_t == 0 ? Variable( j ) : Target(j) );
586 Double_t rxmin = fVariableStats.at(fNumC-1).at( ( v_t*nvar )+ivar).fMin;
587 Double_t rxmax = fVariableStats.at(fNumC-1).at( ( v_t*nvar )+ivar).fMax;
588 Double_t rymin = fVariableStats.at(fNumC-1).at( ( v_t*nvar )+j).fMin;
589 Double_t rymax = fVariableStats.at(fNumC-1).at( ( v_t*nvar )+j).fMax;
593 className.
Data(), transfType.
Data() ),
595 className.
Data(), transfType.
Data() ),
596 nbins2D, rxmin , rxmax,
597 nbins2D, rymin , rymax );
601 mycorr.at(cls).at((var_tgt*nvar)+ivar).at((v_t*nvar)+j) = h2;
607 Form(
"profile %s versus %s (%s)%s",
609 className.
Data(), transfType.
Data() ), nbins1D,
615 myprof.at(cls).at((var_tgt*nvar)+ivar).at((v_t*nvar)+j) = p;
623 UInt_t nevts = events.size();
626 std::vector<Double_t> xregmean ( nvar+1, 0 );
627 std::vector<Double_t> x2regmean( nvar+1, 0 );
628 std::vector<Double_t> xCregmean( nvar+1, 0 );
631 for (
UInt_t ievt=0; ievt<nevts; ievt++) {
633 const Event* ev = events[ievt];
641 xregmean[nvar] += valr;
642 x2regmean[nvar] += valr*valr;
643 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
645 xregmean[ivar] += vali;
646 x2regmean[ivar] += vali*vali;
647 xCregmean[ivar] += vali*valr;
652 for (
UInt_t var_tgt = 0; var_tgt < 2; var_tgt++) {
653 UInt_t nloops = ( var_tgt == 0? nvar:ntgt );
654 for (
UInt_t ivar=0; ivar<nloops; ivar++) {
658 hVars.at(cls).at( ( var_tgt*nvar )+ivar)->Fill( vali, weight );
663 for (
UInt_t v_t = 0; v_t < 2; v_t++) {
664 UInt_t nl = ( v_t==0 ? nvar : ntgt );
665 UInt_t start = ( v_t==0 ? (var_tgt==0?ivar+1:0) : (var_tgt==0?nl:ivar+1) );
666 for (
UInt_t j=start; j<nl; j++) {
668 mycorr.at(cls).at( ( var_tgt*nvar )+ivar).at( ( v_t*nvar )+j)->Fill( vali, valj, weight );
669 myprof.at(cls).at( ( var_tgt*nvar )+ivar).at( ( v_t*nvar )+j)->Fill( vali, valj, weight );
679 for (
UInt_t ivar=0; ivar<=nvar; ivar++) {
680 xregmean[ivar] /= nevts;
681 x2regmean[ivar] = x2regmean[ivar]/nevts - xregmean[ivar]*xregmean[ivar];
683 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
684 xCregmean[ivar] = xCregmean[ivar]/nevts - xregmean[ivar]*xregmean[nvar];
685 xCregmean[ivar] /=
TMath::Sqrt( x2regmean[ivar]*x2regmean[nvar] );
688 fRanking.push_back(
new Ranking(
GetName() +
"Transformation",
"|Correlation with target|" ) );
689 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
691 fRanking.back()->AddRank(
Rank( fDataSetInfo.GetVariableInfo(ivar).GetLabel(), abscor ) );
694 if (nvar+ntgt <= (
UInt_t)
gConfig().GetVariablePlotting().fMaxNumOfAllowedVariablesForScatterPlots) {
697 fRanking.push_back(
new Ranking(
GetName() +
"Transformation",
"Mutual information" ) );
698 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
699 TH2F*
h1 = mycorr.at(0).at( nvar ).at( ivar );
701 fRanking.back()->AddRank(
Rank( fDataSetInfo.GetVariableInfo(ivar).GetLabel(), mi ) );
705 fRanking.push_back(
new Ranking(
GetName() +
"Transformation",
"Correlation Ratio" ) );
706 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
707 TH2F* h2 = mycorr.at(0).at( nvar ).at( ivar );
709 fRanking.back()->AddRank(
Rank( fDataSetInfo.GetVariableInfo(ivar).GetLabel(), cr ) );
713 fRanking.push_back(
new Ranking(
GetName() +
"Transformation",
"Correlation Ratio (T)" ) );
714 for (
UInt_t ivar=0; ivar<nvar; ivar++) {
717 fRanking.back()->AddRank(
Rank( fDataSetInfo.GetVariableInfo(ivar).GetLabel(), cr ) );
724 else if (fDataSetInfo.GetNClasses() == 2
725 && fDataSetInfo.GetClassInfo(
"Signal") != NULL
726 && fDataSetInfo.GetClassInfo(
"Background") != NULL
728 fRanking.push_back(
new Ranking(
GetName() +
"Transformation",
"Separation" ) );
729 for (
UInt_t i=0; i<nvar; i++) {
731 hVars.at(fDataSetInfo.GetClassInfo(
"Background")->GetNumber()).at(i) );
732 fRanking.back()->AddRank(
Rank( hVars.at(fDataSetInfo.GetClassInfo(
"Signal")->GetNumber()).at(i)->GetTitle(),
742 if (theDirectory == 0) {
748 outputDir +=
"_" +
TString(trf->GetShortName());
750 TString uniqueOutputDir = outputDir;
753 while( (o = fRootBaseDir->
FindObject(uniqueOutputDir)) != 0 ){
754 uniqueOutputDir = outputDir+
Form(
"_%d",counter);
755 Log() << kINFO <<
"A " << o->
ClassName() <<
" with name " << o->
GetName() <<
" already exists in "
756 << fRootBaseDir->GetPath() <<
", I will try with "<<uniqueOutputDir<<
"." <<
Endl;
765 localDir = fRootBaseDir->
mkdir( uniqueOutputDir );
768 Log() << kVERBOSE <<
"Create and switch to directory " << localDir->
GetPath() <<
Endl;
774 for (
UInt_t i=0; i<nvar+ntgt; i++) {
775 for (
Int_t cls = 0; cls < ncls; cls++) {
776 if (hVars.at(cls).at(i) != 0) {
777 hVars.at(cls).at(i)->Write();
778 hVars.at(cls).at(i)->SetDirectory(0);
779 delete hVars.at(cls).at(i);
785 if (nvar+ntgt <= (
UInt_t)
gConfig().GetVariablePlotting().fMaxNumOfAllowedVariablesForScatterPlots) {
787 localDir = localDir->
mkdir(
"CorrelationPlots" );
789 Log() << kDEBUG <<
"Create scatter and profile plots in target-file directory: " <<
Endl;
793 for (
UInt_t i=0; i<nvar+ntgt; i++) {
794 for (
UInt_t j=i+1; j<nvar+ntgt; j++) {
795 for (
Int_t cls = 0; cls < ncls; cls++) {
796 if (mycorr.at(cls).at(i).at(j) != 0 ) {
797 mycorr.at(cls).at(i).at(j)->
Write();
798 mycorr.at(cls).at(i).at(j)->SetDirectory(0);
799 delete mycorr.at(cls).at(i).at(j);
801 if (myprof.at(cls).at(i).at(j) != 0) {
802 myprof.at(cls).at(i).at(j)->Write();
803 myprof.at(cls).at(i).at(j)->SetDirectory(0);
804 delete myprof.at(cls).at(i).at(j);
810 if (theDirectory != 0 ) theDirectory->
cd();
811 else fRootBaseDir->cd();
840 std::vector< Int_t >::const_iterator rClsIt = fTransformationsReferenceClasses.begin();
842 o <<
"NTransformtations " << fTransformations.GetSize() << std::endl << std::endl;
847 o <<
"#TR -*-*-*-*-*-*-* transformation " << i++ <<
": " << trf->
GetName() <<
" -*-*-*-*-*-*-*-" << std::endl;
848 trf->WriteTransformationToStream(o);
849 ci = fDataSetInfo.GetClassInfo( (*rClsIt) );
851 if (ci == 0 ) clsName =
"AllClasses";
853 o <<
"ReferenceClass " << clsName << std::endl;
866 gTools().
AddAttr( trfs,
"NTransformations", fTransformations.GetSize() );
875 Log() << kFATAL <<
"Read transformations not implemented" <<
Endl;
891 if (trfname ==
"Decorrelation" ) {
894 else if (trfname ==
"PCA" ) {
897 else if (trfname ==
"Gauss" ) {
900 else if (trfname ==
"Uniform" ) {
903 else if (trfname ==
"Normalize" ) {
906 else if (trfname ==
"Rearrange" ) {
909 else if (trfname !=
"None") {
912 Log() << kFATAL <<
"<ReadFromXML> Variable transform '"
913 << trfname <<
"' unknown." <<
Endl;
916 AddTransformation( newtrf, idxCls );
927 Log() << kINFO <<
"Ranking input variables (method unspecific)..." <<
Endl;
928 std::vector<Ranking*>::const_iterator it = fRanking.begin();
929 for (; it != fRanking.end(); ++it) (*it)->
Print();
937 return fVariableStats.at(cls).at(ivar).fMean;
941 return fVariableStats.at(fNumC-1).at(ivar).fMean;
944 Log() << kWARNING <<
"Inconsistent variable state when reading the mean value. " <<
Endl;
947 Log() << kWARNING <<
"Inconsistent variable state when reading the mean value. Value 0 given back" <<
Endl;
956 return fVariableStats.at(cls).at(ivar).fRMS;
960 return fVariableStats.at(fNumC-1).at(ivar).fRMS;
963 Log() << kWARNING <<
"Inconsistent variable state when reading the RMS value. " <<
Endl;
966 Log() << kWARNING <<
"Inconsistent variable state when reading the RMS value. Value 0 given back" <<
Endl;
975 return fVariableStats.at(cls).at(ivar).fMin;
979 return fVariableStats.at(fNumC-1).at(ivar).fMin;
982 Log() << kWARNING <<
"Inconsistent variable state when reading the minimum value. " <<
Endl;
985 Log() << kWARNING <<
"Inconsistent variable state when reading the minimum value. Value 0 given back" <<
Endl;
994 return fVariableStats.at(cls).at(ivar).fMax;
998 return fVariableStats.at(fNumC-1).at(ivar).fMax;
1001 Log() << kWARNING <<
"Inconsistent variable state when reading the maximum value. " <<
Endl;
1004 Log() << kWARNING <<
"Inconsistent variable state when reading the maximum value. Value 0 given back" <<
Endl;
static const double x2[5]
const Bool_t kIterBackward
char * Form(const char *fmt,...)
Describe directory structure in memory.
virtual const char * GetPath() const
Returns the full path of the directory.
virtual TDirectory * mkdir(const char *name, const char *title="", Bool_t returnExistingDirectory=kFALSE)
Create a sub-directory "a" or a hierarchy of sub-directories "a/b/c/...".
virtual Bool_t cd(const char *path=nullptr)
Change current directory to "this" directory.
1-D histogram with a float per channel (see TH1 documentation)}
TAxis * GetXaxis()
Get the behaviour adopted by the object about the statoverflows. See EStatOverflows for more informat...
2-D histogram with a float per channel (see TH1 documentation)}
Class that contains all the information of a class.
Int_t fMaxNumOfAllowedVariablesForScatterPlots
VariablePlotting & GetVariablePlotting()
Class that contains all the data information.
UInt_t GetNVariables() const
UInt_t GetNClasses() const
UInt_t GetNTargets() const
Float_t GetValue(UInt_t ivar) const
return value of i'th variable
Double_t GetWeight() const
return the event weight - depending on whether the flag IgnoreNegWeightsInTraining is or not.
Float_t GetTarget(UInt_t itgt) const
ostringstream derivative to redirect and format output
void SetSource(const std::string &source)
Ranking for variables in method (implementation)
Class for type info of MVA input variable.
const TString & GetInternalName() const
const TString & GetUnit() const
virtual void SetTitle(const char *title="")
Set the title of the TNamed.
virtual const char * GetTitle() const
Returns title of object.
virtual const char * GetName() const
Returns name of object.
Mother of all ROOT objects.
virtual Int_t Write(const char *name=0, Int_t option=0, Int_t bufsize=0)
Write this object to the current directory.
virtual const char * GetName() const
Returns name of object.
virtual const char * ClassName() const
Returns name of class to which the object belongs.
virtual TObject * FindObject(const char *name) const
Must be redefined in derived classes.
virtual void Print(Option_t *option="") const
This method must be overridden when a class wants to print itself.
const char * Data() const
std::string GetName(const std::string &scope_name)
MsgLogger & Endl(MsgLogger &ml)
Int_t Nint(T x)
Round to nearest integer. Rounds half integers to the nearest even integer.
Short_t Max(Short_t a, Short_t b)
Double_t Sqrt(Double_t x)
Short_t Min(Short_t a, Short_t b)