/usr/include/root/TMVA/Tools.h is in libroot-tmva-dev 5.34.30-0ubuntu8.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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// Author: Andreas Hoecker, Joerg Stelzer, Helge Voss, Kai Voss
/**********************************************************************************
* Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
* Package: TMVA *
* Class : Tools *
* Web : http://tmva.sourceforge.net *
* *
* Description: *
* Global auxiliary applications and data treatment routines *
* *
* Authors (alphabetical): *
* Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
* Peter Speckmayer <peter.speckmayer@cern.ch> - CERN, Switzerland *
* Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
* Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada *
* *
* Copyright (c) 2005: *
* CERN, Switzerland *
* U. of Victoria, Canada *
* MPI-K Heidelberg, Germany *
* *
* Redistribution and use in source and binary forms, with or without *
* modification, are permitted according to the terms listed in LICENSE *
* (http://tmva.sourceforge.net/LICENSE) *
**********************************************************************************/
#ifndef ROOT_TMVA_Tools
#define ROOT_TMVA_Tools
//////////////////////////////////////////////////////////////////////////
// //
// Tools (namespace) //
// //
// Global auxiliary applications and data treatment routines //
// //
//////////////////////////////////////////////////////////////////////////
#include <vector>
#include <sstream>
#include <iostream>
#include <iomanip>
#ifndef ROOT_TXMLEngine
#include "TXMLEngine.h"
#endif
#ifndef ROOT_TMatrixDSymfwd
#include "TMatrixDSymfwd.h"
#endif
#ifndef ROOT_TMatrixDfwd
#include "TMatrixDfwd.h"
#endif
#ifndef ROOT_TVectorDfwd
#include "TVectorDfwd.h"
#endif
#ifndef ROOT_TVectorDfwd
#include "TVectorDfwd.h"
#endif
#ifndef ROOT_TMVA_Types
#include "TMVA/Types.h"
#endif
#ifndef ROOT_TMVA_VariableTransformBase
#include "TMVA/VariableTransformBase.h"
#endif
class TList;
class TTree;
class TString;
class TH1;
class TH2;
class TH2F;
class TSpline;
class TXMLEngine;
namespace TMVA {
class Event;
class PDF;
class MsgLogger;
class Tools {
private:
Tools();
public:
// destructor
~Tools();
// accessor to single instance
static Tools& Instance();
static void DestroyInstance();
template <typename T> Double_t Mean(Long64_t n, const T *a, const Double_t *w=0);
template <typename Iterator, typename WeightIterator> Double_t Mean ( Iterator first, Iterator last, WeightIterator w);
template <typename T> Double_t RMS(Long64_t n, const T *a, const Double_t *w=0);
template <typename Iterator, typename WeightIterator> Double_t RMS(Iterator first, Iterator last, WeightIterator w);
// simple statistics operations on tree entries
void ComputeStat( const std::vector<TMVA::Event*>&,
std::vector<Float_t>*,
Double_t&, Double_t&, Double_t&,
Double_t&, Double_t&, Double_t&, Int_t signalClass,
Bool_t norm = kFALSE );
// compute variance from sums
inline Double_t ComputeVariance( Double_t sumx2, Double_t sumx, Int_t nx );
// creates histograms normalized to one
TH1* projNormTH1F( TTree* theTree, const TString& theVarName,
const TString& name, Int_t nbins,
Double_t xmin, Double_t xmax, const TString& cut );
// normalize histogram by its integral
Double_t NormHist( TH1* theHist, Double_t norm = 1.0 );
// parser for TString phrase with items separated by a character
TList* ParseFormatLine( TString theString, const char * sep = ":" );
// parse option string for ANN methods
std::vector<Int_t>* ParseANNOptionString( TString theOptions, Int_t nvar,
std::vector<Int_t>* nodes );
// returns the square-root of a symmetric matrix: symMat = sqrtMat*sqrtMat
TMatrixD* GetSQRootMatrix( TMatrixDSym* symMat );
// returns the covariance matrix of of the different classes (and the sum)
// given the event sample
std::vector<TMatrixDSym*>* CalcCovarianceMatrices( const std::vector<Event*>& events, Int_t maxCls, VariableTransformBase* transformBase=0 );
std::vector<TMatrixDSym*>* CalcCovarianceMatrices( const std::vector<const Event*>& events, Int_t maxCls, VariableTransformBase* transformBase=0 );
// turns covariance into correlation matrix
const TMatrixD* GetCorrelationMatrix( const TMatrixD* covMat );
// check spline quality by comparison with initial histogram
Bool_t CheckSplines( const TH1*, const TSpline* );
// normalization of variable output
Double_t NormVariable( Double_t x, Double_t xmin, Double_t xmax );
// return separation of two histograms
Double_t GetSeparation( TH1* S, TH1* B ) const;
Double_t GetSeparation( const PDF& pdfS, const PDF& pdfB ) const;
// vector rescaling
std::vector<Double_t> MVADiff( std::vector<Double_t>&, std::vector<Double_t>& );
void Scale( std::vector<Double_t>&, Double_t );
void Scale( std::vector<Float_t>&, Float_t );
// re-arrange a vector of arrays (vectors) in a way such that the first array
// is ordered, and the other arrays reshuffeld accordingly
void UsefulSortDescending( std::vector< std::vector<Double_t> >&, std::vector<TString>* vs = 0 );
void UsefulSortAscending ( std::vector< std::vector<Double_t> >&, std::vector<TString>* vs = 0 );
void UsefulSortDescending( std::vector<Double_t>& );
void UsefulSortAscending ( std::vector<Double_t>& );
Int_t GetIndexMaxElement ( std::vector<Double_t>& );
Int_t GetIndexMinElement ( std::vector<Double_t>& );
// check if input string contains regular expression
Bool_t ContainsRegularExpression( const TString& s );
TString ReplaceRegularExpressions( const TString& s, const TString& replace = "+" );
// routines for formatted output -----------------
void FormattedOutput( const std::vector<Double_t>&, const std::vector<TString>&,
const TString titleVars, const TString titleValues, MsgLogger& logger,
TString format = "%+1.3f" );
void FormattedOutput( const TMatrixD&, const std::vector<TString>&, MsgLogger& logger );
void FormattedOutput( const TMatrixD&, const std::vector<TString>& vert, const std::vector<TString>& horiz,
MsgLogger& logger );
void WriteFloatArbitraryPrecision( Float_t val, std::ostream& os );
void ReadFloatArbitraryPrecision ( Float_t& val, std::istream& is );
// for histogramming
TString GetXTitleWithUnit( const TString& title, const TString& unit );
TString GetYTitleWithUnit( const TH1& h, const TString& unit, Bool_t normalised );
// Mutual Information method for non-linear correlations estimates in 2D histogram
// Author: Moritz Backes, Geneva (2009)
Double_t GetMutualInformation( const TH2F& );
// Correlation Ratio method for non-linear correlations estimates in 2D histogram
// Author: Moritz Backes, Geneva (2009)
Double_t GetCorrelationRatio( const TH2F& );
TH2F* TransposeHist ( const TH2F& );
// check if "silent" or "verbose" option in configuration string
Bool_t CheckForSilentOption ( const TString& ) const;
Bool_t CheckForVerboseOption( const TString& ) const;
// color information
const TString& Color( const TString& );
// print welcome message (to be called from, eg, .TMVAlogon)
enum EWelcomeMessage { kStandardWelcomeMsg = 1,
kIsometricWelcomeMsg,
kBlockWelcomeMsg,
kLeanWelcomeMsg,
kLogoWelcomeMsg,
kSmall1WelcomeMsg,
kSmall2WelcomeMsg,
kOriginalWelcomeMsgColor,
kOriginalWelcomeMsgBW };
// print TMVA citation (to be called from, eg, .TMVAlogon)
enum ECitation { kPlainText = 1,
kBibTeX,
kLaTeX,
kHtmlLink };
void TMVAWelcomeMessage();
void TMVAWelcomeMessage( MsgLogger& logger, EWelcomeMessage m = kStandardWelcomeMsg );
void TMVAVersionMessage( MsgLogger& logger );
void ROOTVersionMessage( MsgLogger& logger );
void TMVACitation( MsgLogger& logger, ECitation citType = kPlainText );
// string tools
std::vector<TString> SplitString( const TString& theOpt, const char separator ) const;
// variables
const TString fRegexp;
mutable MsgLogger* fLogger;
MsgLogger& Log() const { return *fLogger; }
static Tools* fgTools;
// xml tools
TString StringFromInt ( Long_t i );
TString StringFromDouble ( Double_t d );
void WriteTMatrixDToXML ( void* node, const char* name, TMatrixD* mat );
void WriteTVectorDToXML ( void* node, const char* name, TVectorD* vec );
void ReadTMatrixDFromXML( void* node, const char* name, TMatrixD* mat );
void ReadTVectorDFromXML( void* node, const char* name, TVectorD* vec );
Bool_t HistoHasEquidistantBins(const TH1& h);
Bool_t HasAttr ( void* node, const char* attrname );
template<typename T>
inline void ReadAttr ( void* node, const char* , T& value );
void ReadAttr ( void* node, const char* attrname, TString& value );
template<typename T>
void AddAttr ( void* node, const char* , const T& value, Int_t precision = 16 );
void AddAttr ( void* node, const char* attrname, const char* value );
void* AddChild ( void* parent, const char* childname, const char* content = 0, bool isRootNode = false );
Bool_t AddRawLine ( void* node, const char * raw );
Bool_t AddComment ( void* node, const char* comment );
void* GetParent( void* child);
void* GetChild ( void* parent, const char* childname=0 );
void* GetNextChild( void* prevchild, const char* childname=0 );
const char* GetContent ( void* node );
const char* GetName ( void* node );
TXMLEngine& xmlengine() { return *fXMLEngine; }
int xmlenginebuffersize() { return 10000000; }
TXMLEngine* fXMLEngine;
TH1* GetCumulativeDist( TH1* h);
private:
// utilities for correlation ratio
Double_t GetYMean_binX( const TH2& , Int_t bin_x );
}; // Common tools
Tools& gTools(); // global accessor
} // namespace TMVA
//_______________________________________________________________________
template<typename T> void TMVA::Tools::ReadAttr( void* node, const char* attrname, T& value )
{
// read attribute from xml
TString val;
ReadAttr( node, attrname, val );
std::stringstream s(val.Data());
// coverity[tainted_data_argument]
s >> value;
}
//_______________________________________________________________________
template<typename T>
void TMVA::Tools::AddAttr( void* node, const char* attrname, const T& value, Int_t precision )
{
// add attribute to xml
std::stringstream s;
s.precision( precision );
s << std::scientific << value;
AddAttr( node, attrname, s.str().c_str() );
}
//_______________________________________________________________________
inline Double_t TMVA::Tools::ComputeVariance( Double_t sumx2, Double_t sumx, Int_t nx )
{
// compute variance from given sums
if (nx<2) return 0;
return (sumx2 - ((sumx*sumx)/static_cast<Double_t>(nx)))/static_cast<Double_t>(nx-1);
}
#endif
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