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ToyMCSampler.h
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1 // @(#)root/roostats:$Id$
2 // Author: Sven Kreiss and Kyle Cranmer June 2010
3 // Author: Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke
4 // Additions and modifications by Mario Pelliccioni
5 /*************************************************************************
6  * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers. *
7  * All rights reserved. *
8  * *
9  * For the licensing terms see $ROOTSYS/LICENSE. *
10  * For the list of contributors see $ROOTSYS/README/CREDITS. *
11  *************************************************************************/
12 
13 #ifndef ROOSTATS_ToyMCSampler
14 #define ROOSTATS_ToyMCSampler
15 
16 
17 #include "Rtypes.h"
18 
19 #include <vector>
20 #include <list>
21 #include <string>
22 #include <sstream>
23 
26 #include "RooStats/TestStatistic.h"
27 #include "RooStats/ModelConfig.h"
28 #include "RooStats/ProofConfig.h"
29 
30 #include "RooWorkspace.h"
31 #include "RooMsgService.h"
32 #include "RooAbsPdf.h"
33 #include "RooRealVar.h"
34 
35 #include "RooDataSet.h"
36 
37 namespace RooStats {
38 
39  class DetailedOutputAggregator;
40 
42 
43  public:
44  NuisanceParametersSampler(RooAbsPdf *prior=NULL, const RooArgSet *parameters=NULL, Int_t nToys=1000, Bool_t asimov=kFALSE) :
45  fPrior(prior),
46  fParams(parameters),
47  fNToys(nToys),
48  fExpected(asimov),
49  fPoints(NULL),
50  fIndex(0)
51  {
52  if(prior) Refresh();
53  }
55  if(fPoints) { delete fPoints; fPoints = NULL; }
56  }
57 
58  void NextPoint(RooArgSet& nuisPoint, Double_t& weight);
59 
60  protected:
61  void Refresh();
62 
63  private:
64  RooAbsPdf *fPrior; // prior for nuisance parameters
65  const RooArgSet *fParams; // nuisance parameters
68 
69  RooAbsData *fPoints; // generated nuisance parameter points
70  Int_t fIndex; // current index in fPoints array
71 };
72 
74 
75  public:
76 
77  ToyMCSampler();
78  ToyMCSampler(TestStatistic &ts, Int_t ntoys);
79  virtual ~ToyMCSampler();
80 
81  static void SetAlwaysUseMultiGen(Bool_t flag);
82 
83  void SetUseMultiGen(Bool_t flag) { fUseMultiGen = flag ; }
84 
85  // main interface
87  virtual RooDataSet* GetSamplingDistributions(RooArgSet& paramPoint);
89 
91  RooArgSet& allParameters,
93  Int_t additionalMC
94  );
95 
96 
97  // The pdf can be NULL in which case the density from SetPdf()
98  // is used. The snapshot and TestStatistic is also optional.
99  virtual void AddTestStatistic(TestStatistic* t = NULL) {
100  if( t == NULL ) {
101  oocoutI((TObject*)0,InputArguments) << "No test statistic given. Doing nothing." << std::endl;
102  return;
103  }
104 
105  //if( t == NULL && fTestStatistics.size() >= 1 ) t = fTestStatistics[0];
106 
107  fTestStatistics.push_back( t );
108  }
109 
110  // generates toy data
111  // without weight
112  virtual RooAbsData* GenerateToyData(RooArgSet& paramPoint, RooAbsPdf& pdf) const {
113  if(fExpectedNuisancePar) oocoutE((TObject*)NULL,InputArguments) << "ToyMCSampler: using expected nuisance parameters but ignoring weight. Use GetSamplingDistribution(paramPoint, weight) instead." << std::endl;
114  double weight;
115  return GenerateToyData(paramPoint, weight, pdf);
116  }
117  virtual RooAbsData* GenerateToyData(RooArgSet& paramPoint) const { return GenerateToyData(paramPoint,*fPdf); }
118  // with weight
119  virtual RooAbsData* GenerateToyData(RooArgSet& paramPoint, double& weight, RooAbsPdf& pdf) const;
120  virtual RooAbsData* GenerateToyData(RooArgSet& paramPoint, double& weight) const { return GenerateToyData(paramPoint,weight,*fPdf); }
121 
122  // generate global observables
123  virtual void GenerateGlobalObservables(RooAbsPdf& pdf) const;
124 
125 
126  // Main interface to evaluate the test statistic on a dataset
127  virtual Double_t EvaluateTestStatistic(RooAbsData& data, RooArgSet& nullPOI, int i ) {
128  return fTestStatistics[i]->Evaluate(data, nullPOI);
129  }
130  virtual Double_t EvaluateTestStatistic(RooAbsData& data, RooArgSet& nullPOI) { return EvaluateTestStatistic( data,nullPOI, 0 ); }
131  virtual RooArgList* EvaluateAllTestStatistics(RooAbsData& data, const RooArgSet& poi);
132 
133 
134  virtual TestStatistic* GetTestStatistic(unsigned int i) const {
135  if( fTestStatistics.size() <= i ) return NULL;
136  return fTestStatistics[i];
137  }
138  virtual TestStatistic* GetTestStatistic(void) const { return GetTestStatistic(0); }
139 
140  virtual Double_t ConfidenceLevel() const { return 1. - fSize; }
141  virtual void Initialize(
142  RooAbsArg& /*testStatistic*/,
143  RooArgSet& /*paramsOfInterest*/,
144  RooArgSet& /*nuisanceParameters*/
145  ) {}
146 
147  virtual Int_t GetNToys(void) { return fNToys; }
148  virtual void SetNToys(const Int_t ntoy) { fNToys = ntoy; }
149  /// Forces the generation of exactly `n` events even for extended PDFs. Set to 0 to
150  /// use the Poisson-distributed events from the extended PDF.
151  virtual void SetNEventsPerToy(const Int_t nevents) {
152  fNEvents = nevents;
153  }
154 
155 
156  // Set the Pdf, add to the the workspace if not already there
157  virtual void SetParametersForTestStat(const RooArgSet& nullpoi) {
159  fParametersForTestStat = (const RooArgSet*)nullpoi.snapshot();
160  }
161 
162  virtual void SetPdf(RooAbsPdf& pdf) { fPdf = &pdf; ClearCache(); }
163 
164  // How to randomize the prior. Set to NULL to deactivate randomization.
165  virtual void SetPriorNuisance(RooAbsPdf* pdf) {
166  fPriorNuisance = pdf;
170  }
171  }
172  // specify the nuisance parameters (eg. the rest of the parameters)
173  virtual void SetNuisanceParameters(const RooArgSet& np) { fNuisancePars = &np; }
174  // specify the observables in the dataset (needed to evaluate the test statistic)
175  virtual void SetObservables(const RooArgSet& o) { fObservables = &o; }
176  // specify the conditional observables
177  virtual void SetGlobalObservables(const RooArgSet& o) { fGlobalObservables = &o; }
178 
179 
180  // set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
181  virtual void SetTestSize(Double_t size) { fSize = size; }
182  // set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
183  virtual void SetConfidenceLevel(Double_t cl) { fSize = 1. - cl; }
184 
185  // Set the TestStatistic (want the argument to be a function of the data & parameter points
186  virtual void SetTestStatistic(TestStatistic *testStatistic, unsigned int i) {
187  if( fTestStatistics.size() < i ) {
188  oocoutE((TObject*)NULL,InputArguments) << "Cannot set test statistic for this index." << std::endl;
189  return;
190  }
191  if( fTestStatistics.size() == i)
192  fTestStatistics.push_back(testStatistic);
193  else
194  fTestStatistics[i] = testStatistic;
195  }
196  virtual void SetTestStatistic(TestStatistic *t) { return SetTestStatistic(t,0); }
197 
200 
201  // Checks for sufficient information to do a GetSamplingDistribution(...).
202  Bool_t CheckConfig(void);
203 
204  // control to use bin data generation (=> see RooFit::AllBinned() option)
205  void SetGenerateBinned(bool binned = true) { fGenerateBinned = binned; }
206  // name of the tag for individual components to be generated binned (=> see RooFit::GenBinned() option)
207  void SetGenerateBinnedTag( const char* binnedTag = "" ) { fGenerateBinnedTag = binnedTag; }
208  // set auto binned generation (=> see RooFit::AutoBinned() option)
209  void SetGenerateAutoBinned( Bool_t autoBinned = kTRUE ) { fGenerateAutoBinned = autoBinned; }
210 
211  // Set the name of the sampling distribution used for plotting
212  void SetSamplingDistName(const char* name) { if(name) fSamplingDistName = name; }
213  std::string GetSamplingDistName(void) { return fSamplingDistName; }
214 
215  // This option forces a maximum number of total toys.
216  void SetMaxToys(Double_t t) { fMaxToys = t; }
217 
218  void SetToysLeftTail(Double_t toys, Double_t threshold) {
219  fToysInTails = toys;
220  fAdaptiveLowLimit = threshold;
222  }
223  void SetToysRightTail(Double_t toys, Double_t threshold) {
224  fToysInTails = toys;
225  fAdaptiveHighLimit = threshold;
227  }
228  void SetToysBothTails(Double_t toys, Double_t low_threshold, Double_t high_threshold) {
229  fToysInTails = toys;
230  fAdaptiveHighLimit = high_threshold;
231  fAdaptiveLowLimit = low_threshold;
232  }
233 
234  // calling with argument or NULL deactivates proof
236 
237  void SetProtoData(const RooDataSet* d) { fProtoData = d; }
238 
239  protected:
240 
242 
243  // helper for GenerateToyData
244  RooAbsData* Generate(RooAbsPdf &pdf, RooArgSet &observables, const RooDataSet *protoData=NULL, int forceEvents=0) const;
245 
246  // helper method for clearing the cache
247  virtual void ClearCache();
248 
249 
250  // densities, snapshots, and test statistics to reweight to
251  RooAbsPdf *fPdf; // model (can be alt or null)
253  std::vector<TestStatistic*> fTestStatistics;
254 
255  std::string fSamplingDistName; // name of the model
256  RooAbsPdf *fPriorNuisance; // prior pdf for nuisance parameters
260  Int_t fNToys; // number of toys to generate
261  Int_t fNEvents; // number of events per toy (may be ignored depending on settings)
263  Bool_t fExpectedNuisancePar; // whether to use expectation values for nuisance parameters (ie Asimov data set)
267 
268  // minimum no of toys in tails for adaptive sampling
269  // (taking weights into account, therefore double)
270  // Default: 0.0 which means no adaptive sampling
272  // maximum no of toys
273  // (taking weights into account, therefore double)
275  // tails
278 
279  const RooDataSet *fProtoData; // in dev
280 
282 
284 
285  // objects below cache information and are mutable and non-persistent
286  mutable RooArgSet* _allVars ; //!
287  mutable std::list<RooAbsPdf*> _pdfList ; //!
288  mutable std::list<RooArgSet*> _obsList ; //!
289  mutable std::list<RooAbsPdf::GenSpec*> _gsList ; //!
290  mutable RooAbsPdf::GenSpec* _gs1 ; //! GenSpec #1
291  mutable RooAbsPdf::GenSpec* _gs2 ; //! GenSpec #2
292  mutable RooAbsPdf::GenSpec* _gs3 ; //! GenSpec #3
293  mutable RooAbsPdf::GenSpec* _gs4 ; //! GenSpec #4
294 
295  static Bool_t fgAlwaysUseMultiGen ; // Use PrepareMultiGen always
296  Bool_t fUseMultiGen ; // Use PrepareMultiGen?
297 
298  protected:
299  ClassDef(ToyMCSampler,3) // A simple implementation of the TestStatSampler interface
300 };
301 }
302 
303 
304 #endif
RooStats::NuisanceParametersSampler::fIndex
Int_t fIndex
Definition: ToyMCSampler.h:70
RooStats::ToyMCSampler::SetConfidenceLevel
virtual void SetConfidenceLevel(Double_t cl)
Definition: ToyMCSampler.h:183
RooStats::ToyMCSampler::ConfidenceLevel
virtual Double_t ConfidenceLevel() const
Definition: ToyMCSampler.h:140
RooStats::ToyMCSampler::fAdaptiveLowLimit
Double_t fAdaptiveLowLimit
Definition: ToyMCSampler.h:276
RooWorkspace.h
RooStats::ToyMCSampler::fPriorNuisance
RooAbsPdf * fPriorNuisance
Definition: ToyMCSampler.h:256
RooStats::ToyMCSampler::fToysInTails
Double_t fToysInTails
Definition: ToyMCSampler.h:271
RooStats::ToyMCSampler::EvaluateTestStatistic
virtual Double_t EvaluateTestStatistic(RooAbsData &data, RooArgSet &nullPOI, int i)
Definition: ToyMCSampler.h:127
RooStats::ToyMCSampler::SetToysLeftTail
void SetToysLeftTail(Double_t toys, Double_t threshold)
Definition: ToyMCSampler.h:218
kTRUE
const Bool_t kTRUE
Definition: RtypesCore.h:91
RooStats::ToyMCSampler::EvaluateTestStatistic
virtual Double_t EvaluateTestStatistic(RooAbsData &data, RooArgSet &nullPOI)
Definition: ToyMCSampler.h:130
RooStats::ToyMCSampler::GenerateGlobalObservables
virtual void GenerateGlobalObservables(RooAbsPdf &pdf) const
Definition: ToyMCSampler.cxx:474
RooMsgService.h
RooStats::ToyMCSampler::SetGenerateAutoBinned
void SetGenerateAutoBinned(Bool_t autoBinned=kTRUE)
Definition: ToyMCSampler.h:209
RooStats::ToyMCSampler::_gs4
RooAbsPdf::GenSpec * _gs4
GenSpec #3.
Definition: ToyMCSampler.h:293
RooStats::ToyMCSampler::SetAlwaysUseMultiGen
static void SetAlwaysUseMultiGen(Bool_t flag)
Definition: ToyMCSampler.cxx:148
RooStats::TestStatSampler
TestStatSampler is an interface class for a tools which produce RooStats SamplingDistributions.
Definition: TestStatSampler.h:39
RooAbsData
RooAbsData is the common abstract base class for binned and unbinned datasets.
Definition: RooAbsData.h:46
RooStats::SamplingDistribution
This class simply holds a sampling distribution of some test statistic.
Definition: SamplingDistribution.h:28
RooStats::ToyMCSampler::SetTestSize
virtual void SetTestSize(Double_t size)
Definition: ToyMCSampler.h:181
RooStats::NuisanceParametersSampler::fNToys
Int_t fNToys
Definition: ToyMCSampler.h:66
RooFit::InputArguments
@ InputArguments
Definition: RooGlobalFunc.h:68
oocoutI
#define oocoutI(o, a)
Definition: RooMsgService.h:45
RooStats::DetailedOutputAggregator
This class is designed to aid in the construction of RooDataSets and RooArgSets, particularly those n...
Definition: DetailedOutputAggregator.h:24
RooStats::ToyMCSampler::Generate
RooAbsData * Generate(RooAbsPdf &pdf, RooArgSet &observables, const RooDataSet *protoData=NULL, int forceEvents=0) const
This is the generate function to use in the context of the ToyMCSampler instead of the standard RooAb...
Definition: ToyMCSampler.cxx:614
RooStats::ToyMCSampler::_allVars
RooArgSet * _allVars
Definition: ToyMCSampler.h:286
RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
RooStats::ToyMCSampler::fGenerateBinnedTag
TString fGenerateBinnedTag
Definition: ToyMCSampler.h:265
RooStats::ToyMCSampler::AppendSamplingDistribution
virtual SamplingDistribution * AppendSamplingDistribution(RooArgSet &allParameters, SamplingDistribution *last, Int_t additionalMC)
Extended interface to append to sampling distribution more samples.
Definition: ToyMCSampler.cxx:691
RooStats::ToyMCSampler::SetAsimovNuisancePar
virtual void SetAsimovNuisancePar(Bool_t i=kTRUE)
Definition: ToyMCSampler.h:199
RooStats::TestStatistic
TestStatistic is an interface class to provide a facility for construction test statistics distributi...
Definition: TestStatistic.h:31
TGeant4Unit::pc
static constexpr double pc
Definition: TGeant4SystemOfUnits.h:130
RooStats::ToyMCSampler::SetParametersForTestStat
virtual void SetParametersForTestStat(const RooArgSet &nullpoi)
Definition: ToyMCSampler.h:157
RooAbsPdf::GenSpec
Definition: RooAbsPdf.h:70
RooStats::ToyMCSampler::GetSamplingDistribution
virtual SamplingDistribution * GetSamplingDistribution(RooArgSet &paramPoint)
Definition: ToyMCSampler.cxx:303
RooStats::ToyMCSampler::fSize
Double_t fSize
Definition: ToyMCSampler.h:262
RooStats::ToyMCSampler::SetToysRightTail
void SetToysRightTail(Double_t toys, Double_t threshold)
Definition: ToyMCSampler.h:223
RooStats::ToyMCSampler::_gs3
RooAbsPdf::GenSpec * _gs3
GenSpec #2.
Definition: ToyMCSampler.h:292
RooStats::ToyMCSampler::fSamplingDistName
std::string fSamplingDistName
Definition: ToyMCSampler.h:255
RooStats::ToyMCSampler::fAdaptiveHighLimit
Double_t fAdaptiveHighLimit
Definition: ToyMCSampler.h:277
oocoutE
#define oocoutE(o, a)
Definition: RooMsgService.h:48
TString
Basic string class.
Definition: TString.h:136
RooStats::ToyMCSampler::SetProtoData
void SetProtoData(const RooDataSet *d)
Definition: ToyMCSampler.h:237
RooStats::ToyMCSampler::GetSamplingDistributionsSingleWorker
virtual RooDataSet * GetSamplingDistributionsSingleWorker(RooArgSet &paramPoint)
This is the main function for serial runs.
Definition: ToyMCSampler.cxx:380
RooStats::ToyMCSampler::ClearCache
virtual void ClearCache()
clear the cache obtained from the pdf used for speeding the toy and global observables generation nee...
Definition: ToyMCSampler.cxx:714
RooDataSet.h
RooStats::ToyMCSampler::fExpectedNuisancePar
Bool_t fExpectedNuisancePar
Definition: ToyMCSampler.h:263
RooStats::ToyMCSampler::SetSamplingDistName
void SetSamplingDistName(const char *name)
Definition: ToyMCSampler.h:212
bool
RooStats::ToyMCSampler::fGenerateAutoBinned
Bool_t fGenerateAutoBinned
Definition: ToyMCSampler.h:266
RooStats::ToyMCSampler::fPdf
RooAbsPdf * fPdf
Definition: ToyMCSampler.h:251
RooStats::ToyMCSampler::fGlobalObservables
const RooArgSet * fGlobalObservables
Definition: ToyMCSampler.h:259
RooStats::NuisanceParametersSampler::Refresh
void Refresh()
Creates the initial set of nuisance parameter points.
Definition: ToyMCSampler.cxx:92
TestStatSampler.h
RooArgSet::snapshot
RooArgSet * snapshot(bool deepCopy=true) const
Use RooAbsCollection::snapshot(), but return as RooArgSet.
Definition: RooArgSet.h:134
ProofConfig.h
RooStats::ToyMCSampler::SetTestStatistic
virtual void SetTestStatistic(TestStatistic *t)
Definition: ToyMCSampler.h:196
RooStats::ToyMCSampler::fNuisancePars
const RooArgSet * fNuisancePars
Definition: ToyMCSampler.h:257
RooStats::NuisanceParametersSampler::NextPoint
void NextPoint(RooArgSet &nuisPoint, Double_t &weight)
Assigns new nuisance parameter point to members of nuisPoint.
Definition: ToyMCSampler.cxx:67
RooStats::ToyMCSampler::GetNToys
virtual Int_t GetNToys(void)
Definition: ToyMCSampler.h:147
RooStats::ToyMCSampler::SetNEventsPerToy
virtual void SetNEventsPerToy(const Int_t nevents)
Forces the generation of exactly n events even for extended PDFs.
Definition: ToyMCSampler.h:151
RooStats::ToyMCSampler::fGenerateBinned
Bool_t fGenerateBinned
Definition: ToyMCSampler.h:264
RooStats::ToyMCSampler::_gs2
RooAbsPdf::GenSpec * _gs2
GenSpec #1.
Definition: ToyMCSampler.h:291
RooStats::NuisanceParametersSampler::NuisanceParametersSampler
NuisanceParametersSampler(RooAbsPdf *prior=NULL, const RooArgSet *parameters=NULL, Int_t nToys=1000, Bool_t asimov=kFALSE)
Definition: ToyMCSampler.h:44
RooStats::ToyMCSampler::SetNToys
virtual void SetNToys(const Int_t ntoy)
Definition: ToyMCSampler.h:148
ModelConfig.h
RooStats::ToyMCSampler::SetPriorNuisance
virtual void SetPriorNuisance(RooAbsPdf *pdf)
Definition: ToyMCSampler.h:165
RooAbsPdf.h
RooStats::ProofConfig
Holds configuration options for proof and proof-lite.
Definition: ProofConfig.h:46
RooStats::ToyMCSampler::SetUseMultiGen
void SetUseMultiGen(Bool_t flag)
Definition: ToyMCSampler.h:83
kFALSE
const Bool_t kFALSE
Definition: RtypesCore.h:92
RooStats::ToyMCSampler::~ToyMCSampler
virtual ~ToyMCSampler()
Definition: ToyMCSampler.cxx:236
RooStats::ToyMCSampler::fgAlwaysUseMultiGen
static Bool_t fgAlwaysUseMultiGen
GenSpec #4.
Definition: ToyMCSampler.h:295
RooStats::ToyMCSampler::GetTestStatistic
virtual TestStatistic * GetTestStatistic(void) const
Definition: ToyMCSampler.h:138
RooStats::ToyMCSampler::fProtoData
const RooDataSet * fProtoData
Definition: ToyMCSampler.h:279
TestStatistic.h
RooStats::ToyMCSampler::SetToysBothTails
void SetToysBothTails(Double_t toys, Double_t low_threshold, Double_t high_threshold)
Definition: ToyMCSampler.h:228
RooStats::ToyMCSampler::GetTestStatistic
virtual TestStatistic * GetTestStatistic(unsigned int i) const
Definition: ToyMCSampler.h:134
RooStats::NuisanceParametersSampler::fPrior
RooAbsPdf * fPrior
Definition: ToyMCSampler.h:64
RooStats::ToyMCSampler::SetNuisanceParameters
virtual void SetNuisanceParameters(const RooArgSet &np)
Definition: ToyMCSampler.h:173
RooStats::ToyMCSampler::Initialize
virtual void Initialize(RooAbsArg &, RooArgSet &, RooArgSet &)
Definition: ToyMCSampler.h:141
RooStats::ToyMCSampler::_gsList
std::list< RooAbsPdf::GenSpec * > _gsList
Definition: ToyMCSampler.h:289
RooStats::ToyMCSampler::GetSamplingDistributions
virtual RooDataSet * GetSamplingDistributions(RooArgSet &paramPoint)
Use for serial and parallel runs.
Definition: ToyMCSampler.cxx:325
RooStats::ToyMCSampler::EvaluateAllTestStatistics
virtual RooArgList * EvaluateAllTestStatistics(RooAbsData &data, const RooArgSet &poi)
Evaluate all test statistics, returning result and any detailed output.
Definition: ToyMCSampler.cxx:270
RooRealVar.h
RooStats::ToyMCSampler::AddTestStatistic
virtual void AddTestStatistic(TestStatistic *t=NULL)
Definition: ToyMCSampler.h:99
RooStats::ToyMCSampler::fMaxToys
Double_t fMaxToys
Definition: ToyMCSampler.h:274
SamplingDistribution.h
RooStats::ToyMCSampler::SetTestStatistic
virtual void SetTestStatistic(TestStatistic *testStatistic, unsigned int i)
Definition: ToyMCSampler.h:186
RooStats::ToyMCSampler::fTestStatistics
std::vector< TestStatistic * > fTestStatistics
Definition: ToyMCSampler.h:253
RooStats::ToyMCSampler::SetObservables
virtual void SetObservables(const RooArgSet &o)
Definition: ToyMCSampler.h:175
RooStats::ToyMCSampler::GenerateToyData
virtual RooAbsData * GenerateToyData(RooArgSet &paramPoint, RooAbsPdf &pdf) const
Definition: ToyMCSampler.h:112
RooStats::ToyMCSampler::fObservables
const RooArgSet * fObservables
Definition: ToyMCSampler.h:258
RooNumber::infinity
static Double_t infinity()
Return internal infinity representation.
Definition: RooNumber.cxx:49
RooStats::ToyMCSampler::SetProofConfig
void SetProofConfig(ProofConfig *pc=NULL)
Definition: ToyMCSampler.h:235
RooStats::ToyMCSampler::fParametersForTestStat
const RooArgSet * fParametersForTestStat
Definition: ToyMCSampler.h:252
Double_t
double Double_t
Definition: RtypesCore.h:59
RooStats::NuisanceParametersSampler::fParams
const RooArgSet * fParams
Definition: ToyMCSampler.h:65
RooStats::ToyMCSampler::fNEvents
Int_t fNEvents
Definition: ToyMCSampler.h:261
RooStats::ToyMCSampler::SetGenerateBinnedTag
void SetGenerateBinnedTag(const char *binnedTag="")
Definition: ToyMCSampler.h:207
RooStats::ToyMCSampler::SetExpectedNuisancePar
virtual void SetExpectedNuisancePar(Bool_t i=kTRUE)
Definition: ToyMCSampler.h:198
RooStats::ToyMCSampler::fNToys
Int_t fNToys
Definition: ToyMCSampler.h:260
RooStats::ToyMCSampler::_gs1
RooAbsPdf::GenSpec * _gs1
Definition: ToyMCSampler.h:290
RooStats::ToyMCSampler::_pdfList
std::list< RooAbsPdf * > _pdfList
Definition: ToyMCSampler.h:287
RooStats
Namespace for the RooStats classes.
Definition: Asimov.h:19
RooStats::ToyMCSampler
ToyMCSampler is an implementation of the TestStatSampler interface.
Definition: ToyMCSampler.h:73
RooStats::ToyMCSampler::fUseMultiGen
Bool_t fUseMultiGen
Definition: ToyMCSampler.h:296
RooStats::ToyMCSampler::SetMaxToys
void SetMaxToys(Double_t t)
Definition: ToyMCSampler.h:216
TObject
Mother of all ROOT objects.
Definition: TObject.h:37
ClassDef
#define ClassDef(name, id)
Definition: Rtypes.h:325
name
char name[80]
Definition: TGX11.cxx:110
d
#define d(i)
Definition: RSha256.hxx:102
RooStats::NuisanceParametersSampler
Helper class for ToyMCSampler.
Definition: ToyMCSampler.h:41
RooStats::NuisanceParametersSampler::fPoints
RooAbsData * fPoints
Definition: ToyMCSampler.h:69
RooDataSet
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
RooStats::ToyMCSampler::GetSamplingDistName
std::string GetSamplingDistName(void)
Definition: ToyMCSampler.h:213
RooAbsArg
RooAbsArg is the common abstract base class for objects that represent a value (of arbitrary type) an...
Definition: RooAbsArg.h:73
RooAbsPdf
Definition: RooAbsPdf.h:40
RooStats::ToyMCSampler::ToyMCSampler
ToyMCSampler()
Proof constructor. Do not use.
Definition: ToyMCSampler.cxx:153
RooStats::NuisanceParametersSampler::~NuisanceParametersSampler
virtual ~NuisanceParametersSampler()
Definition: ToyMCSampler.h:54
RooStats::ToyMCSampler::_obsList
std::list< RooArgSet * > _obsList
Definition: ToyMCSampler.h:288
RooStats::ToyMCSampler::SetPdf
virtual void SetPdf(RooAbsPdf &pdf)
Definition: ToyMCSampler.h:162
RooStats::NuisanceParametersSampler::fExpected
Bool_t fExpected
Definition: ToyMCSampler.h:67
Rtypes.h
RooStats::ToyMCSampler::CheckConfig
Bool_t CheckConfig(void)
only checks, no guessing/determination (do this in calculators, e.g.
Definition: ToyMCSampler.cxx:246
RooStats::ToyMCSampler::SetGlobalObservables
virtual void SetGlobalObservables(const RooArgSet &o)
Definition: ToyMCSampler.h:177
RooStats::ToyMCSampler::fProofConfig
ProofConfig * fProofConfig
Definition: ToyMCSampler.h:281
RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
RooStats::ToyMCSampler::SetGenerateBinned
void SetGenerateBinned(bool binned=true)
Definition: ToyMCSampler.h:205
int
RooStats::ToyMCSampler::fNuisanceParametersSampler
NuisanceParametersSampler * fNuisanceParametersSampler
Definition: ToyMCSampler.h:283