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Page: PlotTMVA.cpp
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AddVariable.cpp B mass model B2Kstmumu B2Kstmumu.pro BDTSelection BDTcutScanner.cpp BackgroundPdf Class BackgroundType Class CompareVariables.cpp Comparison tool Design.cpp Efficiency Class Efficiency.cpp Event generator FCNC Fitter Ganga GlobalFunctions.hh Home InclusiveCheck.cpp Input MVA variables MCtruthmatching.cpp MVA Class MassFit.cpp ParamValues Class Paths.hpp PlotTMVA.cpp RemoveMultipleCandidates.py ReorganizeTGraph.py Rescale pi0 momentum Resolution Plotting Running the FCNC fitter Selection code Signal Study SignalPdf Class SignalType Class Standalone Scripts TMVA Class application TMVA TMsource Utils.hpp Utils3.py flav.io getPathForPython nTrackWeights.cpp
5 PlotTMVA.cpp
Renata Kopecná edited this page 2022-02-08 14:57:37 +01:00
Table of Contents

Table of Contents

Functions

TFile *GetTMVAfile()

  • Parameters
    • int year
    • int Run
    • bool SplitYears
    • bool KShortDecaysInVelo
    • int nConfiguration
    • bool UseLowQ2Range
    • string customTMbranch
    • bool gammaTM
  • Return
    • Opens and returns the TFile with the MVA training information (config file)

TH2F *GetCorrelationMatrix()

  • Parameters
    • TFile *file
    • string type //S or B (for signal or background)
  • Return
    • Returns the signal or background correlation matrix from the config file

TH2F *GetCorrelationMatrixSignal()

  • Parameters
    • TFile *file
  • Return
    • Returns the signal correlation matrix from the config file

TH2F *GetCorrelationMatrixBackground()

  • Parameters
    • TFile *file
  • Return
    • Returns the background correlation matrix from the config file

string oberFolder()

  • Parameters
    • string method
  • Return
    • A string with the name of the folder where the histograms are saved in the TFile

TH1F *GetTMVAresponse()

  • Parameters
    • TFile *file
    • string method
    • string type // S, B, Train_S, Train_B
  • Return
    • Histogram with the MVA responses for the signal and background either from training or from all

TH1F *GetTMVAresponseSignal()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the signal MVA response

TH1F *GetTMVAresponseBackground()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the background MVA response

TH1F *GetTMVAresponseTrainingSignal()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the signal MVA response in the training sample

TH1F *GetTMVAresponseTrainingBackground()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the background MVA response in the training sample

TH1F *GetVariableSignal()

  • Parameters
    • TFile *file
    • string variable
  • Return
    • Histogram with the disrtibution of the desired variable, signal events only

TH1F *GetVariableBackground()

  • Parameters
    • TFile *file
    • string variable
  • Return
    • Histogram with the disrtibution of the desired variable, background events only

TH1F *GetEfficiencySignal()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the MVA efficiency for signal

TH1F *GetEfficiencyBackground()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the MVA efficiency for signal

TH1F *GetROC()

  • Parameters
    • TFile *file
    • string method
  • Return
    • Histogram with the ROC curve for the given method

TTree *GetTrainTree()

  • Parameters
    • TFile *file
  • Return
    • The TTree used for the MVA training

TTree *GetTestTree()

  • Parameters
    • TFile *file
  • Return
    • The TTree used for the MVA testing

int GetTrainEvents()

  • Parameters
    • TFile *file
  • Return
    • The number of events used for the MVA training

int GetTrainSignalEvents()

  • Parameters
    • TFile *file
  • Return
    • The number of signal events used for the MVA training

int GetTrainBackgroundEvents()

  • Parameters
    • TFile *file
  • Return
    • The number of background events used for the MVA training

bool SaveCorrelationPlot()

Read the correlation histograms from the file, makes them pretty and saves them.

  • Parameters
    • TFile *file
    • string type
    • string savePath
  • Return
    • True if everything is fine, False if something fails

vector <string> v_variables()

  • Parameters
    • string DL="" //LL or DD
  • Return
    • A vector with all variable names from the MVA reader (see MVA.cpp )

bool SaveVariablesSignalVsBackground()

Loads the variable distributions in the signal and background sample, plots them both and saves the plot.

  • Parameters
    • TFile *file
    • string savePath
    • string DL="" //LL or DD
  • Return
    • True if everything is fine, False if something fails

bool SaveMVAResponse()

Loads the MVA response in the signal and background samples,plots them both and saves the plot.

  • Parameters
    • TFile *file
    • string savePath
    • string method
  • Return
    • True if everything is fine, False if something fails

bool SaveMVAOvertraining()

Retrieves and plots the training and test sample MVA response for the signal and background. The plot is saved.

  • Parameters
    • TFile *file
    • string savePath
    • string method
  • Return
    • True if everything is fine, False if something fails

bool SaveEfficiency()

Retrieves and plots the MVA efficiency, purity, and significance of the signal and background. The plot is saved.

  • Parameters
    • TFile *file
    • string savePath
    • string method
    • int nSig
    • int nBkg
  • Return
    • True if everything is fine, False if something fails

string getROCmethod()

  • Parameters
    • TH1F *h_ROC
  • Return
    • The name of the ROC histogram stripped of the MVA_ at the begining.

bool SaveROCs()

Retrieves the ROC curves for listed methods, plots them in one canvas, saves the plot.

  • Parameters
    • TFile *file
    • string savePath
    • vector <string> methods
  • Return
    • True if everything is fine, False if something fails

bool SaveMultipleROCS()

Retrieves the ROC curves from the listed files, plots them in one canvas, saves the plot.

  • Parameters
    • vector <TFile *> files
    • string savePath
    • string method
  • Return
    • True if everything is fine, False if something fails

void nEvents()

Saves the number of signal and background events into nSig and nBkg. It has to be checked, as the input is hardcoded!

  • Parameters
    • int year
    • int Run
    • bool SplitYears
    • bool KshortDecaysInVelo
    • int nConfiguration
    • bool UseLowQ2Range
    • int& nSig
    • int& nBkg

bool SaveAllFromOneFile()

Effectivelly saves all plots needed for the MVA training. Calls SaveAllFromOneFile(), SaveVariablesSignalVsBackground(), nEvents(), SaveMVAOvertraining(), SaveEfficiency() and SaveROCs() for the given file.

  • Parameters
    • int year
    • int Run
    • bool SplitYears
    • bool KshortDecaysInVelo
    • int nConfiguration
    • bool UseLowQ2Range
    • string customTMbranch
    • bool gammaTM
  • Return
    • True if everything is fine, False if something fails

bool SaveMultipleROCS()

Gets a list of config files and calls SaveMultipleROCS().

  • Parameters
    • int Run
    • int nLow (lower nConfig number)
    • int nHigh (upper nConfig number)
  • Return
    • True if everything is fine, False if something fails