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MaCh3 2.2.1
Reference Guide
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Class to calculate pvalue produce posterior predictive and many fancy Bayesian stuff [10]. More...
#include <Fitters/SampleSummary.h>
Public Member Functions | |
SampleSummary (const int n_Samples, const std::string &Filename, SampleHandlerBase *const sample, const int nSteps) | |
Constructor. | |
~SampleSummary () | |
Destructor. | |
void | AddData (std::vector< TH2Poly * > &DataHist) |
KS: Add data histograms. | |
void | AddNominal (std::vector< TH2Poly * > &NominalHist, std::vector< TH2Poly * > &W2Nom) |
KS: Add prior histograms. | |
void | AddThrow (std::vector< TH2Poly * > &MCHist, std::vector< TH2Poly * > &W2Hist, const double LLHPenalty=0.0, const double Weight=1.0, const int DrawNumber=0) |
KS: Add histograms with throws. | |
void | AddThrowByMode (std::vector< std::vector< TH2Poly * > > &SampleVector_ByMode) |
KS: Add histograms for each mode. | |
void | Write () |
KS: Write results into root file. | |
void | SetLikelihood (const TestStatistic TestStat) |
KS: Set likelihood type. | |
void | SetNModelParams (const int nPars) |
Set number of model params used for BIC. | |
Private Member Functions | |
void | MakePredictive () |
Finalise the distributions from the thrown samples. | |
void | PrepareOutput () |
KS: Prepare output tree and necessary variables. | |
void | CalcLLH (TH2Poly *const &Data, TH2Poly *const &MC, TH2Poly *const &W2) |
Helper functions to calculate likelihoods using TH2Poly, will modify MC hist tittle to include LLH. | |
void | CalcLLH (TH1D *const &Data, TH1D *const &MC, TH1D *const &W2) |
Helper functions to calculate likelihoods using TH1D, will modify MC hist tittle to include LLH. | |
double | GetLLH (TH2Poly *const &Data, TH2Poly *const &MC, TH2Poly *const &W2) |
Helper functions to calculate likelihoods using TH2Poly. | |
double | GetLLH (TH1D *const &Data, TH1D *const &MC, TH1D *const &W2) |
Helper functions to calculate likelihoods using TH1D. | |
void | PlotBetaParameters () |
KS: In Barlow Beeston we have Beta Parameters which scale generated MC. | |
void | StudyKinematicCorrelations () |
KS: Study how correlated are sample or kinematic bins. | |
void | MakeCutLLH () |
Make the cut LLH histogram. | |
void | MakeCutLLH1D (TH1D *Histogram, double llh_ref=-999) |
void | MakeCutEventRate (TH1D *Histogram, const double DataRate) |
Make the 1D Event Rate Hist. | |
void | MakeChi2Hists () |
Make the fluctuated histograms (2D and 1D) for the chi2s Essentially taking the MCMC draws and calculating their LLH to the Posterior predictive distribution And additionally taking the data histogram and calculating the LLH to the predictive distribution Additionally we calculate the chi2 of the draws (fluctuated) of the MC with the prior/posterior predictive and plot it vs the chi2 from the draws of MCMC and the data. | |
bool | CheckSamples (const int Length) |
Check the length of samples agrees. | |
TH1D * | ProjectHist (TH2D *Histogram, const bool ProjectX) |
Helper to project TH2D onto axis. | |
TH1D * | ProjectPoly (TH2Poly *Histogram, const bool ProjectX, const int selection, const bool MakeErrorHist=false) |
Helper to project TH2Poly onto axis. | |
void | MakeFluctuatedHistogram (TH1D *FluctHist, TH1D *PolyHist) |
Make Poisson fluctuation of TH1D hist. | |
void | MakeFluctuatedHistogram (TH2Poly *FluctHist, TH2Poly *PolyHist) |
Make Poisson fluctuation of TH2Poly hist. | |
void | StudyInformationCriterion (M3::kInfCrit Criterion) |
Information Criterion. | |
void | StudyBIC () |
Study Bayesian Information Criterion (BIC) [11]. | |
void | StudyDIC () |
KS: Get the Deviance Information Criterion (DIC) [26] [28]. | |
void | StudyWAIC () |
KS: Get the Watanabe-Akaike information criterion (WAIC) [11] [14]. | |
Private Attributes | |
std::unique_ptr< TRandom3 > | rnd |
Random number generator. | |
bool | first_pass |
KS: Hacky flag to let us know if this is first toy. | |
bool | StandardFluctuation |
KS: We have two methods for Poissonian fluctuation. | |
std::vector< std::vector< TH2Poly * > > | MCVector |
Vector of vectors which holds the loaded MC histograms. | |
std::vector< std::vector< TH2Poly * > > | W2MCVector |
Vector of vectors which holds the loaded W2 histograms. | |
std::vector< std::vector< std::vector< TH2Poly * > > > | MCVectorByMode |
Vector of vectors which holds the loaded MC histograms for each mode. | |
std::vector< double > | LLHPenaltyVector |
Vector to hold the penalty term. | |
std::vector< double > | WeightVector |
Vector holding weight. | |
int | nSamples |
Number of samples. | |
std::vector< std::string > | SampleNames |
name for each sample | |
std::vector< std::vector< std::unique_ptr< TH1D > > > | PosteriorHist |
The posterior predictive for the whole selection: this gets built after adding in the toys. Now an array of Th1ds, 1 for each poly bin, for each sample. | |
std::vector< std::vector< std::unique_ptr< TH1D > > > | w2Hist |
The posterior predictive for the whole selection: this gets built after adding in the toys. Now an array of Th1ds, 1 for each poly bin, for each sample for W2. | |
std::vector< TH2D * > | ViolinHists_ProjectX |
Posterior predictive but for X projection but as a violin plot. | |
std::vector< TH2D * > | ViolinHists_ProjectY |
Posterior predictive but for Y projection but as a violin plot. | |
std::vector< TH2Poly * > | DataHist |
The data histogram for the selection. | |
std::vector< TH1D * > | DataHist_ProjectX |
The data histogram for the selection X projection. | |
std::vector< TH1D * > | DataHist_ProjectY |
The data histogram for the selection Y projection. | |
std::vector< TH2Poly * > | NominalHist |
The nominal histogram for the selection. | |
std::vector< TH2Poly * > | W2NomHist |
Pointer to the w2 histograms (for nominal values). | |
std::vector< TH2Poly * > | W2MeanHist |
Pointer to the w2 histograms (for mean values). | |
std::vector< TH2Poly * > | W2ModeHist |
Pointer to the w2 histograms (for mode values). | |
std::unique_ptr< TH1D > | lnLHist |
The histogram containing the lnL for each throw. | |
std::unique_ptr< TH1D > | lnLHist_drawfluc |
The lnLhist for the draw vs MC fluctuated. | |
std::unique_ptr< TH1D > | lnLHist_drawflucdraw |
The lnLhist for the draw vs draw fluctuated. | |
std::unique_ptr< TH1D > | lnLHist_drawdata |
The lnLhist for the draw vs data. | |
std::unique_ptr< TH2D > | lnLDrawHist |
The 2D lnLhist, showing (draw vs data) and (draw vs fluct), anything above y=x axis is the p-value. | |
std::unique_ptr< TH2D > | lnLFlucHist |
The 2D lnLHist, showing (draw vs data) and (draw vs draw fluct), anything above y=x axis is the p-value. | |
std::unique_ptr< TH2D > | lnLDrawHistRate |
The 2D lnLhist, showing (draw vs data) and (draw vs fluct), using rate, anything above y=x axis is the p-value. | |
std::unique_ptr< TH2D > | lnLFlucHist_ProjectX |
The 2D lnLHist but for ProjectionX histogram (pmu), showing (draw vs data) and (draw vs draw fluct), anything above y=x axis is the p-value. | |
std::vector< TH1D * > | lnLHist_Sample_DrawData |
The histogram containing the lnL (draw vs data) for each throw for each sample. | |
std::vector< TH1D * > | lnLHist_Sample_DrawflucDraw |
The histogram containing the lnL (draw vs draw fluct) for each throw for each sample. | |
std::vector< TH1D * > | lnLHist_Sample_PredflucDraw |
The histogram containing the lnL (draw vs pred fluct) for each throw for each sample. | |
std::vector< TH2Poly * > | lnLHist_Mean |
The LLH distribution in pmu cosmu for using the mean in each bin. | |
std::vector< TH2Poly * > | lnLHist_Mode |
The LLH distribution in pmu cosmu for using the mode in each bin. | |
std::vector< TH1D * > | lnLHist_Mean_ProjectX |
The LLH distribution in pmu using the mean in each bin. | |
std::vector< TH2Poly * > | MeanHist |
The posterior predictive distribution in pmu cosmu using the mean. | |
std::vector< TH2Poly * > | MeanHistCorrected |
The posterior predictive distribution in pmu cosmu using the mean after applying Barlow-Beeston Correction. | |
std::vector< TH2Poly * > | ModeHist |
The posterior predictive distribution in pmu cosmu using the mode. | |
std::vector< TH1D * > | lnLHist_Mean1D |
Holds the bin-by-bin LLH for the mean posterior predictive vs the data. | |
std::vector< TH1D * > | lnLHist_Mode1D |
Holds the bin-by-bin LLH for the mode posterior predictive vs the data. | |
std::unique_ptr< TH1D > | RandomHist |
Holds the history of which entries have been drawn in the MCMC file. | |
std::vector< std::vector< std::unique_ptr< TH1D > > > | BetaHist |
Distribution of beta parameters in Barlow Beeston formalisms. | |
bool | DoBetaParam |
Are we making Beta Histograms. | |
unsigned int | nChainSteps |
Number of throws by user. | |
bool | isPriorPredictive |
bool whether we have Prior or Posterior Predictive | |
bool | doShapeOnly |
bool whether to normalise each toy to have shape based p-value and pos pred distribution | |
unsigned int | nThrows |
Number of throws. | |
std::vector< int > | maxBins |
Max Number of Bins per each sample. | |
double | llh_total |
Total LLH for the posterior predictive distribution. | |
std::string | OutputName |
Output filename. | |
TFile * | Outputfile |
Output filename. | |
std::vector< TDirectory * > | Dir |
Directory for each sample. | |
TTree * | OutputTree |
TTree which we save useful information to. | |
std::vector< double > | llh_data_draw |
Data vs Draw. | |
std::vector< double > | llh_drawfluc_draw |
Fluctuated Draw vs Draw. | |
std::vector< double > | llh_predfluc_draw |
Fluctuated Predictive vs Draw. | |
std::vector< double > | llh_rate_data_draw |
Data vs Draw using rate only. | |
std::vector< double > | llh_rate_predfluc_draw |
Fluctuated Predictive vs Draw using rate only. | |
std::vector< double > | llh_data_drawfluc |
Data vs Fluctuated Draw. | |
std::vector< double > | llh_data_predfluc |
Data vs Fluctuated Predictive. | |
std::vector< double > | llh_draw_pred |
Draw vs Predictive. | |
std::vector< double > | llh_drawfluc_pred |
Fluctuated Draw vs Predictive. | |
std::vector< double > | llh_predfluc_pred |
Fluctuated Predictive vs Predictive. | |
std::vector< double > | llh_drawfluc_predfluc |
Fluctuated Draw vs Fluctuated Predictive. | |
std::vector< double > | llh_datafluc_draw |
Fluctuated Data vs Draw. | |
std::vector< double > | llh_data_draw_ProjectX |
Projection X (most likely muon momentum) of LLH. | |
std::vector< double > | llh_drawfluc_draw_ProjectX |
double | llh_penalty |
LLH penalty for each throw. | |
double | total_llh_data_draw |
Data vs Draw. | |
double | total_llh_drawfluc_draw |
Fluctuated Draw vs Draw. | |
double | total_llh_predfluc_draw |
Fluctuated Predictive vs Draw. | |
double | total_llh_rate_data_draw |
Rate Data vs Draw. | |
double | total_llh_rate_predfluc_draw |
Fluctuated Predictive vs Draw using Rate. | |
double | total_llh_data_predfluc |
Data vs Fluctuated Predictive. | |
double | total_llh_data_drawfluc |
Data vs Fluctuated Draw. | |
double | total_llh_draw_pred |
Draw vs Predictive. | |
double | total_llh_drawfluc_pred |
Fluctuated Draw vs Predictive. | |
double | total_llh_drawfluc_predfluc |
Fluctuated Draw vs Fluctuated Predictive. | |
double | total_llh_datafluc_draw |
Fluctuated Data vs Draw. | |
double | total_llh_predfluc_pred |
Fluctuated Predictive vs Predictive. | |
double | total_llh_data_draw_ProjectX |
Data vs Draw for projection X (most likely muon momentum) | |
double | total_llh_drawfluc_draw_ProjectX |
Fluctuated Draw vs Draw for projection X (most likely muon momentum) | |
bool | DoByModePlots |
By mode variables. | |
std::vector< std::vector< TH2Poly * > > | MeanHist_ByMode |
The posterior predictive distribution in pmu cosmu using the mean. | |
TH1D **** | PosteriorHist_ByMode |
Histogram which corresponds to each bin in the sample's th2poly. | |
SampleHandlerBase * | SampleHandler |
Pointer to SampleHandler object, mostly used to get sample names, binning etc. | |
MaCh3Modes * | Modes |
MaCh3 Modes. | |
TestStatistic | likelihood |
Type of likelihood for example Poisson, Barlow-Beeston or Ice Cube. | |
int | nModelParams |
Number of parameters. | |
int | Debug |
Tells Debug level to save additional histograms. | |
Class to calculate pvalue produce posterior predictive and many fancy Bayesian stuff [10].
For more information, visit the Wiki.
Definition at line 22 of file SampleSummary.h.
SampleSummary::SampleSummary | ( | const int | n_Samples, |
const std::string & | Filename, | ||
SampleHandlerBase *const | sample, | ||
const int | nSteps | ||
) |
Constructor.
n_Samples | total number of samples |
Filename | name of output file |
sample | pointer to sample PDF object |
nChainSteps | number of steps in a chain, 0 indicate prior predictive was used |
Definition at line 9 of file SampleSummary.cpp.
SampleSummary::~SampleSummary | ( | ) |
Destructor.
Definition at line 163 of file SampleSummary.cpp.
void SampleSummary::AddData | ( | std::vector< TH2Poly * > & | DataHist | ) |
KS: Add data histograms.
DataHist | Histogram with data even rates for each sample |
Definition at line 233 of file SampleSummary.cpp.
void SampleSummary::AddNominal | ( | std::vector< TH2Poly * > & | NominalHist, |
std::vector< TH2Poly * > & | W2Nom | ||
) |
KS: Add prior histograms.
Definition at line 264 of file SampleSummary.cpp.
void SampleSummary::AddThrow | ( | std::vector< TH2Poly * > & | MCHist, |
std::vector< TH2Poly * > & | W2Hist, | ||
const double | LLHPenalty = 0.0 , |
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const double | Weight = 1.0 , |
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const int | DrawNumber = 0 |
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) |
KS: Add histograms with throws.
Definition at line 408 of file SampleSummary.cpp.
void SampleSummary::AddThrowByMode | ( | std::vector< std::vector< TH2Poly * > > & | SampleVector_ByMode | ) |
KS: Add histograms for each mode.
Definition at line 486 of file SampleSummary.cpp.
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Helper functions to calculate likelihoods using TH1D, will modify MC hist tittle to include LLH.
Data | histogram with data distribution for a single sample |
MC | histogram with MC distribution for a single sample |
W2 | histogram with W2 distribution for a single sample |
Definition at line 1561 of file SampleSummary.cpp.
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Helper functions to calculate likelihoods using TH2Poly, will modify MC hist tittle to include LLH.
Data | histogram with data distribution for a single sample |
MC | histogram with MC distribution for a single sample |
W2 | histogram with W2 distribution for a single sample |
Definition at line 1572 of file SampleSummary.cpp.
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Check the length of samples agrees.
Definition at line 217 of file SampleSummary.cpp.
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Helper functions to calculate likelihoods using TH1D.
Data | histogram with data distribution for a single sample |
MC | histogram with MC distribution for a single sample |
W2 | histogram with W2 distribution for a single sample |
Definition at line 1597 of file SampleSummary.cpp.
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Helper functions to calculate likelihoods using TH2Poly.
Data | histogram with data distribution for a single sample |
MC | histogram with MC distribution for a single sample |
W2 | histogram with W2 distribution for a single sample |
Definition at line 1582 of file SampleSummary.cpp.
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Make the fluctuated histograms (2D and 1D) for the chi2s Essentially taking the MCMC draws and calculating their LLH to the Posterior predictive distribution And additionally taking the data histogram and calculating the LLH to the predictive distribution Additionally we calculate the chi2 of the draws (fluctuated) of the MC with the prior/posterior predictive and plot it vs the chi2 from the draws of MCMC and the data.
Definition at line 1134 of file SampleSummary.cpp.
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Make the 1D Event Rate Hist.
Definition at line 1511 of file SampleSummary.cpp.
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Make the cut LLH histogram.
Definition at line 1433 of file SampleSummary.cpp.
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Definition at line 1449 of file SampleSummary.cpp.
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Make Poisson fluctuation of TH1D hist.
Definition at line 2183 of file SampleSummary.cpp.
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Make Poisson fluctuation of TH2Poly hist.
Definition at line 2191 of file SampleSummary.cpp.
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Finalise the distributions from the thrown samples.
Definition at line 978 of file SampleSummary.cpp.
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KS: In Barlow Beeston we have Beta Parameters which scale generated MC.
Definition at line 1612 of file SampleSummary.cpp.
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KS: Prepare output tree and necessary variables.
Definition at line 556 of file SampleSummary.cpp.
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Helper to project TH2D onto axis.
Definition at line 2147 of file SampleSummary.cpp.
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Helper to project TH2Poly onto axis.
Definition at line 2163 of file SampleSummary.cpp.
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KS: Set likelihood type.
Definition at line 48 of file SampleSummary.h.
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Set number of model params used for BIC.
Definition at line 50 of file SampleSummary.h.
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Study Bayesian Information Criterion (BIC) [11].
Definition at line 2227 of file SampleSummary.cpp.
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KS: Get the Deviance Information Criterion (DIC) [26] [28].
Definition at line 2251 of file SampleSummary.cpp.
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Information Criterion.
Definition at line 2199 of file SampleSummary.cpp.
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KS: Study how correlated are sample or kinematic bins.
Definition at line 1690 of file SampleSummary.cpp.
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KS: Get the Watanabe-Akaike information criterion (WAIC) [11] [14].
Definition at line 2285 of file SampleSummary.cpp.
void SampleSummary::Write | ( | ) |
KS: Write results into root file.
Definition at line 669 of file SampleSummary.cpp.
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Distribution of beta parameters in Barlow Beeston formalisms.
Definition at line 230 of file SampleSummary.h.
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The data histogram for the selection.
Definition at line 167 of file SampleSummary.h.
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The data histogram for the selection X projection.
Definition at line 169 of file SampleSummary.h.
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The data histogram for the selection Y projection.
Definition at line 171 of file SampleSummary.h.
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Tells Debug level to save additional histograms.
Definition at line 348 of file SampleSummary.h.
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Directory for each sample.
Definition at line 257 of file SampleSummary.h.
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Are we making Beta Histograms.
Definition at line 232 of file SampleSummary.h.
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By mode variables.
Definition at line 329 of file SampleSummary.h.
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bool whether to normalise each toy to have shape based p-value and pos pred distribution
Definition at line 241 of file SampleSummary.h.
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KS: Hacky flag to let us know if this is first toy.
Definition at line 133 of file SampleSummary.h.
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bool whether we have Prior or Posterior Predictive
Definition at line 238 of file SampleSummary.h.
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Type of likelihood for example Poisson, Barlow-Beeston or Ice Cube.
Definition at line 342 of file SampleSummary.h.
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Data vs Draw.
Definition at line 262 of file SampleSummary.h.
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Projection X (most likely muon momentum) of LLH.
Definition at line 290 of file SampleSummary.h.
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Data vs Fluctuated Draw.
Definition at line 274 of file SampleSummary.h.
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Data vs Fluctuated Predictive.
Definition at line 276 of file SampleSummary.h.
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Fluctuated Data vs Draw.
Definition at line 287 of file SampleSummary.h.
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Draw vs Predictive.
Definition at line 278 of file SampleSummary.h.
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Fluctuated Draw vs Draw.
Definition at line 264 of file SampleSummary.h.
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Definition at line 291 of file SampleSummary.h.
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Fluctuated Draw vs Predictive.
Definition at line 280 of file SampleSummary.h.
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Fluctuated Draw vs Fluctuated Predictive.
Definition at line 285 of file SampleSummary.h.
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LLH penalty for each throw.
Definition at line 294 of file SampleSummary.h.
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Fluctuated Predictive vs Draw.
Definition at line 266 of file SampleSummary.h.
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Fluctuated Predictive vs Predictive.
Definition at line 283 of file SampleSummary.h.
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Data vs Draw using rate only.
Definition at line 269 of file SampleSummary.h.
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Fluctuated Predictive vs Draw using rate only.
Definition at line 271 of file SampleSummary.h.
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Total LLH for the posterior predictive distribution.
Definition at line 250 of file SampleSummary.h.
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Vector to hold the penalty term.
Definition at line 146 of file SampleSummary.h.
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The 2D lnLhist, showing (draw vs data) and (draw vs fluct), anything above y=x axis is the p-value.
Definition at line 190 of file SampleSummary.h.
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The 2D lnLhist, showing (draw vs data) and (draw vs fluct), using rate, anything above y=x axis is the p-value.
Definition at line 195 of file SampleSummary.h.
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The 2D lnLHist, showing (draw vs data) and (draw vs draw fluct), anything above y=x axis is the p-value.
Definition at line 192 of file SampleSummary.h.
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The 2D lnLHist but for ProjectionX histogram (pmu), showing (draw vs data) and (draw vs draw fluct), anything above y=x axis is the p-value.
Definition at line 197 of file SampleSummary.h.
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The histogram containing the lnL for each throw.
Definition at line 182 of file SampleSummary.h.
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The lnLhist for the draw vs data.
Definition at line 188 of file SampleSummary.h.
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The lnLhist for the draw vs MC fluctuated.
Definition at line 184 of file SampleSummary.h.
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The lnLhist for the draw vs draw fluctuated.
Definition at line 186 of file SampleSummary.h.
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The LLH distribution in pmu cosmu for using the mean in each bin.
Definition at line 207 of file SampleSummary.h.
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Holds the bin-by-bin LLH for the mean posterior predictive vs the data.
Definition at line 222 of file SampleSummary.h.
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The LLH distribution in pmu using the mean in each bin.
Definition at line 212 of file SampleSummary.h.
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The LLH distribution in pmu cosmu for using the mode in each bin.
Definition at line 209 of file SampleSummary.h.
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Holds the bin-by-bin LLH for the mode posterior predictive vs the data.
Definition at line 224 of file SampleSummary.h.
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The histogram containing the lnL (draw vs data) for each throw for each sample.
Definition at line 200 of file SampleSummary.h.
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The histogram containing the lnL (draw vs draw fluct) for each throw for each sample.
Definition at line 202 of file SampleSummary.h.
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The histogram containing the lnL (draw vs pred fluct) for each throw for each sample.
Definition at line 204 of file SampleSummary.h.
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Max Number of Bins per each sample.
Definition at line 247 of file SampleSummary.h.
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Vector of vectors which holds the loaded MC histograms.
Definition at line 139 of file SampleSummary.h.
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Vector of vectors which holds the loaded MC histograms for each mode.
Definition at line 143 of file SampleSummary.h.
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The posterior predictive distribution in pmu cosmu using the mean.
Definition at line 215 of file SampleSummary.h.
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The posterior predictive distribution in pmu cosmu using the mean.
Definition at line 331 of file SampleSummary.h.
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The posterior predictive distribution in pmu cosmu using the mean after applying Barlow-Beeston Correction.
Definition at line 217 of file SampleSummary.h.
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The posterior predictive distribution in pmu cosmu using the mode.
Definition at line 219 of file SampleSummary.h.
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MaCh3 Modes.
Definition at line 339 of file SampleSummary.h.
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Number of throws by user.
Definition at line 235 of file SampleSummary.h.
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Number of parameters.
Definition at line 345 of file SampleSummary.h.
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The nominal histogram for the selection.
Definition at line 173 of file SampleSummary.h.
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Number of samples.
Definition at line 151 of file SampleSummary.h.
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Number of throws.
Definition at line 244 of file SampleSummary.h.
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Output filename.
Definition at line 255 of file SampleSummary.h.
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Output filename.
Definition at line 253 of file SampleSummary.h.
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TTree which we save useful information to.
Definition at line 260 of file SampleSummary.h.
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The posterior predictive for the whole selection: this gets built after adding in the toys. Now an array of Th1ds, 1 for each poly bin, for each sample.
Definition at line 157 of file SampleSummary.h.
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Histogram which corresponds to each bin in the sample's th2poly.
Definition at line 333 of file SampleSummary.h.
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Holds the history of which entries have been drawn in the MCMC file.
Definition at line 227 of file SampleSummary.h.
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Random number generator.
Definition at line 131 of file SampleSummary.h.
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Pointer to SampleHandler object, mostly used to get sample names, binning etc.
Definition at line 336 of file SampleSummary.h.
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name for each sample
Definition at line 154 of file SampleSummary.h.
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KS: We have two methods for Poissonian fluctuation.
Definition at line 136 of file SampleSummary.h.
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Data vs Draw.
Definition at line 297 of file SampleSummary.h.
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Data vs Draw for projection X (most likely muon momentum)
Definition at line 324 of file SampleSummary.h.
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Data vs Fluctuated Draw.
Definition at line 311 of file SampleSummary.h.
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Data vs Fluctuated Predictive.
Definition at line 309 of file SampleSummary.h.
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Fluctuated Data vs Draw.
Definition at line 319 of file SampleSummary.h.
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Draw vs Predictive.
Definition at line 313 of file SampleSummary.h.
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Fluctuated Draw vs Draw.
Definition at line 299 of file SampleSummary.h.
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Fluctuated Draw vs Draw for projection X (most likely muon momentum)
Definition at line 326 of file SampleSummary.h.
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Fluctuated Draw vs Predictive.
Definition at line 315 of file SampleSummary.h.
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Fluctuated Draw vs Fluctuated Predictive.
Definition at line 317 of file SampleSummary.h.
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Fluctuated Predictive vs Draw.
Definition at line 301 of file SampleSummary.h.
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Fluctuated Predictive vs Predictive.
Definition at line 321 of file SampleSummary.h.
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Rate Data vs Draw.
Definition at line 304 of file SampleSummary.h.
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Fluctuated Predictive vs Draw using Rate.
Definition at line 306 of file SampleSummary.h.
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Posterior predictive but for X projection but as a violin plot.
Definition at line 162 of file SampleSummary.h.
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Posterior predictive but for Y projection but as a violin plot.
Definition at line 164 of file SampleSummary.h.
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The posterior predictive for the whole selection: this gets built after adding in the toys. Now an array of Th1ds, 1 for each poly bin, for each sample for W2.
Definition at line 159 of file SampleSummary.h.
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Vector of vectors which holds the loaded W2 histograms.
Definition at line 141 of file SampleSummary.h.
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Pointer to the w2 histograms (for mean values).
Definition at line 177 of file SampleSummary.h.
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Pointer to the w2 histograms (for mode values).
Definition at line 179 of file SampleSummary.h.
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Pointer to the w2 histograms (for nominal values).
Definition at line 175 of file SampleSummary.h.
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Vector holding weight.
Definition at line 148 of file SampleSummary.h.