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class RooAbsData: public TNamed, public RooPrintable



RooAbsData is the common abstract base class for binned and unbinned datasets. The abstract interface defines plotting and tabulating entry points for its contents and provides an iterator over its elements (bins for binned data sets, data points for unbinned datasets).


Function Members (Methods)

 
    This is an abstract class, constructors will not be documented.
    Look at the header to check for available constructors.

public:
virtual~RooAbsData()
voidTObject::AbstractMethod(const char* method) const
virtual voidadd(const RooArgSet& row, Double_t weight = 1, Double_t weightError = 0)
voidaddOwnedComponent(const char* idxlabel, RooAbsData& data)
virtual voidTObject::AppendPad(Option_t* option = "")
virtual voidTObject::Browse(TBrowser* b)
Bool_tcanSplitFast() const
virtual Bool_tchangeObservableName(const char* from, const char* to)
voidcheckInit() const
static voidclaimVars(RooAbsData*)
static TClass*Class()
virtual const char*TObject::ClassName() const
virtual voidTNamed::Clear(Option_t* option = "")
virtual TObject*TNamed::Clone(const char* newname = "") const
virtual Int_tTNamed::Compare(const TObject* obj) const
virtual voidTNamed::Copy(TObject& named) const
Double_tcorrelation(RooRealVar& x, RooRealVar& y, const char* cutSpec = 0, const char* cutRange = 0) const
TMatrixDSym*correlationMatrix(const char* cutSpec = 0, const char* cutRange = 0) const
TMatrixDSym*correlationMatrix(const RooArgList& vars, const char* cutSpec = 0, const char* cutRange = 0) const
Double_tcovariance(RooRealVar& x, RooRealVar& y, const char* cutSpec = 0, const char* cutRange = 0) const
TMatrixDSym*covarianceMatrix(const char* cutSpec = 0, const char* cutRange = 0) const
TMatrixDSym*covarianceMatrix(const RooArgList& vars, const char* cutSpec = 0, const char* cutRange = 0) const
TH1*createHistogram(const char* name, const RooAbsRealLValue& xvar, const RooLinkedList& argList) const
TH1*createHistogram(const char* varNameList, Int_t xbins = 0, Int_t ybins = 0, Int_t zbins = 0) const
TH1*createHistogram(const char* name, const RooAbsRealLValue& xvar, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none()) const
virtual Int_tdefaultPrintContents(Option_t* opt) const
static ostream&RooPrintable::defaultPrintStream(ostream* os = 0)
virtual RooPrintable::StyleOptionRooPrintable::defaultPrintStyle(Option_t* opt) const
virtual voidTObject::Delete(Option_t* option = "")MENU
virtual Int_tTObject::DistancetoPrimitive(Int_t px, Int_t py)
virtual voidDraw(Option_t* option = "")
virtual voidTObject::DrawClass() constMENU
virtual TObject*TObject::DrawClone(Option_t* option = "") constMENU
virtual voidTObject::Dump() constMENU
virtual RooAbsData*emptyClone(const char* newName = 0, const char* newTitle = 0, const RooArgSet* vars = 0) const
virtual voidTObject::Error(const char* method, const char* msgfmt) const
virtual voidTObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual voidTObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual voidTObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual voidfill()
virtual voidTNamed::FillBuffer(char*& buffer)
virtual TH1*fillHistogram(TH1* hist, const RooArgList& plotVars, const char* cuts = "", const char* cutRange = 0) const
virtual TObject*TObject::FindObject(const char* name) const
virtual TObject*TObject::FindObject(const TObject* obj) const
virtual const RooArgSet*get() const
virtual const RooArgSet*get(Int_t index) const
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
virtual const char*TObject::GetIconName() const
virtual const char*TNamed::GetName() const
virtual char*TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Option_t*TObject::GetOption() const
Bool_tgetRange(RooRealVar& var, Double_t& lowest, Double_t& highest, Double_t marginFrac = 0, Bool_t symMode = kFALSE) const
RooAbsData*getSimData(const char* idxstate)
virtual const char*TNamed::GetTitle() const
virtual UInt_tTObject::GetUniqueID() const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
Bool_thasFilledCache() const
virtual ULong_tTNamed::Hash() const
virtual voidTObject::Info(const char* method, const char* msgfmt) const
virtual Bool_tTObject::InheritsFrom(const char* classname) const
virtual Bool_tTObject::InheritsFrom(const TClass* cl) const
virtual voidTObject::Inspect() constMENU
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
virtual Bool_tisNonPoissonWeighted() const
Bool_tTObject::IsOnHeap() const
virtual Bool_tTNamed::IsSortable() const
virtual Bool_tisWeighted() const
Bool_tTObject::IsZombie() const
Double_tkurtosis(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
virtual voidTNamed::ls(Option_t* option = "") const
voidTObject::MayNotUse(const char* method) const
Double_tmean(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
RooRealVar*meanVar(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
Double_tmoment(RooRealVar& var, Double_t order, const char* cutSpec = 0, const char* cutRange = 0) const
Double_tmoment(RooRealVar& var, Double_t order, Double_t offset, const char* cutSpec = 0, const char* cutRange = 0) const
static voidRooPrintable::nameFieldLength(Int_t newLen)
virtual Bool_tTObject::Notify()
virtual Int_tnumEntries() const
voidTObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
static voidTObject::operator delete(void* ptr)
static voidTObject::operator delete(void* ptr, void* vp)
static voidTObject::operator delete[](void* ptr)
static voidTObject::operator delete[](void* ptr, void* vp)
void*TObject::operator new(size_t sz)
void*TObject::operator new(size_t sz, void* vp)
void*TObject::operator new[](size_t sz)
void*TObject::operator new[](size_t sz, void* vp)
RooAbsData&operator=(const RooAbsData&)
virtual voidTObject::Paint(Option_t* option = "")
virtual RooPlot*plotOn(RooPlot* frame, const RooLinkedList& cmdList) const
virtual RooPlot*plotOn(RooPlot* frame, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none()) const
virtual voidTObject::Pop()
virtual voidPrint(Option_t* options = 0) const
virtual voidRooPrintable::printAddress(ostream& os) const
virtual voidRooPrintable::printArgs(ostream& os) const
virtual voidprintClassName(ostream& os) const
virtual voidRooPrintable::printExtras(ostream& os) const
virtual voidprintMultiline(ostream& os, Int_t contents, Bool_t verbose = kFALSE, TString indent = "") const
virtual voidprintName(ostream& os) const
virtual voidRooPrintable::printStream(ostream& os, Int_t contents, RooPrintable::StyleOption style, TString indent = "") const
virtual voidprintTitle(ostream& os) const
virtual voidRooPrintable::printTree(ostream& os, TString indent = "") const
virtual voidRooPrintable::printValue(ostream& os) const
virtual Int_tTObject::Read(const char* name)
virtual voidTObject::RecursiveRemove(TObject* obj)
RooAbsData*reduce(const char* cut)
RooAbsData*reduce(const RooFormulaVar& cutVar)
RooAbsData*reduce(const RooArgSet& varSubset, const char* cut = 0)
RooAbsData*reduce(const RooArgSet& varSubset, const RooFormulaVar& cutVar)
RooAbsData*reduce(const RooCmdArg& arg1, const RooCmdArg& arg2 = RooCmdArg(), const RooCmdArg& arg3 = RooCmdArg(), const RooCmdArg& arg4 = RooCmdArg(), const RooCmdArg& arg5 = RooCmdArg(), const RooCmdArg& arg6 = RooCmdArg(), const RooCmdArg& arg7 = RooCmdArg(), const RooCmdArg& arg8 = RooCmdArg())
static Bool_treleaseVars(RooAbsData*)
virtual voidreset()
voidTObject::ResetBit(UInt_t f)
RooRealVar*rmsVar(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual voidTObject::SavePrimitive(ostream& out, Option_t* option = "")
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
voidsetDirtyProp(Bool_t flag)
virtual voidTObject::SetDrawOption(Option_t* option = "")MENU
static voidTObject::SetDtorOnly(void* obj)
virtual voidTNamed::SetName(const char* name)MENU
virtual voidTNamed::SetNameTitle(const char* name, const char* title)
static voidTObject::SetObjectStat(Bool_t stat)
virtual voidTNamed::SetTitle(const char* title = "")MENU
virtual voidTObject::SetUniqueID(UInt_t uid)
virtual voidShowMembers(TMemberInspector& insp)
Double_tsigma(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
virtual Int_tTNamed::Sizeof() const
Double_tskewness(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
virtual TList*split(const RooAbsCategory& splitCat, Bool_t createEmptyDataSets = kFALSE) const
Double_tstandMoment(RooRealVar& var, Double_t order, const char* cutSpec = 0, const char* cutRange = 0) const
virtual RooPlot*statOn(RooPlot* frame, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none())
virtual RooPlot*statOn(RooPlot* frame, const char* what, const char* label = "", Int_t sigDigits = 2, Option_t* options = "NELU", Double_t xmin = 0.15, Double_t xmax = 0.65, Double_t ymax = 0.85, const char* cutSpec = 0, const char* cutRange = 0, const RooCmdArg* formatCmd = 0)
RooAbsDataStore*store()
const RooAbsDataStore*store() const
virtual voidStreamer(TBuffer& b)
voidStreamerNVirtual(TBuffer& b)
virtual Double_tsumEntries(const char* cutSpec = 0, const char* cutRange = 0) const
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
virtual Roo1DTable*table(const RooArgSet& catSet, const char* cuts = "", const char* opts = "") const
virtual Roo1DTable*table(const RooAbsCategory& cat, const char* cuts = "", const char* opts = "") const
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
const TTree*tree() const
virtual voidTObject::UseCurrentStyle()
virtual Bool_tvalid() const
virtual voidTObject::Warning(const char* method, const char* msgfmt) const
virtual Double_tweight() const
virtual Double_tweightError(RooAbsData::ErrorType etype = Poisson) const
virtual voidweightError(Double_t& lo, Double_t& hi, RooAbsData::ErrorType etype = Poisson) const
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const
protected:
Bool_tallClientsCached(RooAbsArg*, const RooArgSet&)
virtual voidattachCache(const RooAbsArg* newOwner, const RooArgSet& cachedVars)
virtual voidcacheArgs(const RooAbsArg* owner, RooArgSet& varSet, const RooArgSet* nset = 0)
virtual RooAbsData*cacheClone(const RooAbsArg* newCacheOwner, const RooArgSet* newCacheVars, const char* newName = 0)
Double_tcorrcov(RooRealVar& x, RooRealVar& y, const char* cutSpec, const char* cutRange, Bool_t corr) const
TMatrixDSym*corrcovMatrix(const RooArgList& vars, const char* cutSpec, const char* cutRange, Bool_t corr) const
RooRealVar*dataRealVar(const char* methodname, RooRealVar& extVar) const
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const
voidTObject::MakeZombie()
virtual voidoptimizeReadingWithCaching(RooAbsArg& arg, const RooArgSet& cacheList, const RooArgSet& keepObsList)
virtual RooPlot*plotAsymOn(RooPlot* frame, const RooAbsCategoryLValue& asymCat, RooAbsData::PlotOpt o) const
virtual RooPlot*plotEffOn(RooPlot* frame, const RooAbsCategoryLValue& effCat, RooAbsData::PlotOpt o) const
virtual RooPlot*plotOn(RooPlot* frame, RooAbsData::PlotOpt o) const
virtual RooAbsData*reduceEng(const RooArgSet& varSubset, const RooFormulaVar* cutVar, const char* cutRange = 0, Int_t nStart = 0, Int_t nStop = 2000000000, Bool_t copyCache = kTRUE)
virtual voidresetCache()
virtual voidsetArgStatus(const RooArgSet& set, Bool_t active)

Data Members

public:
enum ErrorType { Poisson
SumW2
None
Auto
};
enum TObject::EStatusBits { kCanDelete
kMustCleanup
kObjInCanvas
kIsReferenced
kHasUUID
kCannotPick
kNoContextMenu
kInvalidObject
};
enum TObject::[unnamed] { kIsOnHeap
kNotDeleted
kZombie
kBitMask
kSingleKey
kOverwrite
kWriteDelete
};
enum RooPrintable::ContentsOption { kName
kClassName
kValue
kArgs
kExtras
kAddress
kTitle
kCollectionHeader
};
enum RooPrintable::StyleOption { kInline
kSingleLine
kStandard
kVerbose
kTreeStructure
};
protected:
TIterator*_cacheIter! Iterator over cached variables
RooArgSet_cachedVars! External variables cached with this data set
RooAbsDataStore*_dstoreData storage implementation
TIterator*_iterator! Iterator over dimension variables
static Int_tRooPrintable::_nameLength
map<std::string,RooAbsData*>_ownedComponentsOwned external components
RooArgSet_varsDimensions of this data set
TStringTNamed::fNameobject identifier
TStringTNamed::fTitleobject title

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

void claimVars(RooAbsData* )
Bool_t releaseVars(RooAbsData* )
 If return value is true variables can be deleted
~RooAbsData()
 Destructor
cout << "deleting dataset " << this << endl ;
Bool_t changeObservableName(const char* from, const char* to)
void fill()
Int_t numEntries() const
void reset()
const RooArgSet* get(Int_t index) const
void cacheArgs(const RooAbsArg* owner, RooArgSet& varSet, const RooArgSet* nset = 0)
 Internal method -- Cache given set of functions with data
void resetCache()
 Internal method -- Remove cached function values
void attachCache(const RooAbsArg* newOwner, const RooArgSet& cachedVars)
 Internal method -- Attach dataset copied with cache contents to copied instances of functions
void setArgStatus(const RooArgSet& set, Bool_t active)
void setDirtyProp(Bool_t flag)
 Control propagation of dirty flags from observables in dataset
RooAbsData* reduce(const RooCmdArg& arg1, const RooCmdArg& arg2 = RooCmdArg(), const RooCmdArg& arg3 = RooCmdArg(), const RooCmdArg& arg4 = RooCmdArg(), const RooCmdArg& arg5 = RooCmdArg(), const RooCmdArg& arg6 = RooCmdArg(), const RooCmdArg& arg7 = RooCmdArg(), const RooCmdArg& arg8 = RooCmdArg())
 Create a reduced copy of this dataset. The caller takes ownership of the returned dataset

 The following optional named arguments are accepted

   SelectVars(const RooArgSet& vars) -- Only retain the listed observables in the output dataset
   Cut(const char* expression)       -- Only retain event surviving the given cut expression
   Cut(const RooFormulaVar& expr)    -- Only retain event surviving the given cut formula
   CutRange(const char* name)        -- Only retain events inside range with given name. Multiple CutRange
                                        arguments may be given to select multiple ranges
   EventRange(int lo, int hi)        -- Only retain events with given sequential event numbers
   Name(const char* name)            -- Give specified name to output dataset
   Title(const char* name)           -- Give specified title to output dataset

RooAbsData* reduce(const char* cut)
 Create a subset of the data set by applying the given cut on the data points.
 The cut expression can refer to any variable in the data set. For cuts involving
 other variables, such as intermediate formula objects, use the equivalent
 reduce method specifying the as a RooFormulVar reference.
RooAbsData* reduce(const RooFormulaVar& cutVar)
 Create a subset of the data set by applying the given cut on the data points.
 The 'cutVar' formula variable is used to select the subset of data points to be
 retained in the reduced data collection.
RooAbsData* reduce(const RooArgSet& varSubset, const char* cut = 0)
 Create a subset of the data set by applying the given cut on the data points
 and reducing the dimensions to the specified set.

 The cut expression can refer to any variable in the data set. For cuts involving
 other variables, such as intermediate formula objects, use the equivalent
 reduce method specifying the as a RooFormulVar reference.
RooAbsData* reduce(const RooArgSet& varSubset, const RooFormulaVar& cutVar)
 Create a subset of the data set by applying the given cut on the data points
 and reducing the dimensions to the specified set.

 The 'cutVar' formula variable is used to select the subset of data points to be
 retained in the reduced data collection.
Double_t weightError(RooAbsData::ErrorType etype = Poisson) const
 Return error on current weight (dummy implementation returning zero)
void weightError(Double_t& lo, Double_t& hi, RooAbsData::ErrorType etype = Poisson) const
 Return asymmetric error on weight. (Dummy implementation returning zero)
RooPlot* plotOn(RooPlot* frame, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none()) const
 Plot dataset on specified frame. By default an unbinned dataset will use the default binning of
 the target frame. A binned dataset will by default retain its intrinsic binning.

 The following optional named arguments can be used to modify the default behavior

 Data representation options

 Asymmetry(const RooCategory& c) -- Show the asymmetry of the daya in given two-state category [F(+)-F(-)] / [F(+)+F(-)].
                                    Category must have two states with indices -1 and +1 or three states with indeces -1,0 and +1.
 DataError(RooAbsData::EType)    -- Select the type of error drawn: Poisson (default) draws asymmetric Poisson
                                    confidence intervals. SumW2 draws symmetric sum-of-weights error
 Binning(double xlo, double xhi, -- Use specified binning to draw dataset
                      int nbins)
 Binning(const RooAbsBinning&)   -- Use specified binning to draw dataset
 Binning(const char* name)       -- Use binning with specified name to draw dataset
 RefreshNorm(Bool_t flag)        -- Force refreshing for PDF normalization information in frame.
                                    If set, any subsequent PDF will normalize to this dataset, even if it is
                                    not the first one added to the frame. By default only the 1st dataset
                                    added to a frame will update the normalization information
 Rescale(Double_t factor)        -- Apply global rescaling factor to histogram

 Histogram drawing options

 DrawOption(const char* opt)     -- Select ROOT draw option for resulting TGraph object
 LineStyle(Int_t style)          -- Select line style by ROOT line style code, default is solid
 LineColor(Int_t color)          -- Select line color by ROOT color code, default is black
 LineWidth(Int_t width)          -- Select line with in pixels, default is 3
 MarkerStyle(Int_t style)        -- Select the ROOT marker style, default is 21
 MarkerColor(Int_t color)        -- Select the ROOT marker color, default is black
 MarkerSize(Double_t size)       -- Select the ROOT marker size
 XErrorSize(Double_t frac)       -- Select size of X error bar as fraction of the bin width, default is 1


 Misc. other options

 Name(const chat* name)          -- Give curve specified name in frame. Useful if curve is to be referenced later
 Invisble(Bool_t flag)           -- Add curve to frame, but do not display. Useful in combination AddTo()
 AddTo(const char* name,         -- Add constructed histogram to already existing histogram with given name and relative weight factors
 double_t wgtSelf, double_t wgtOther)


TH1 * createHistogram(const char* varNameList, Int_t xbins = 0, Int_t ybins = 0, Int_t zbins = 0) const
 Create and fill a ROOT histogram TH1,TH2 or TH3 with the values of this dataset for the variables with given names
 The range of each observable that is histogrammed is always automatically calculated from the distribution in
 the dataset. The number of bins can be controlled using the [xyz]bins parameters. For a greater degree of control
 use the createHistogram() method below with named arguments

 The caller takes ownership of the returned histogram
TH1 * createHistogram(const char* name, const RooAbsRealLValue& xvar, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none()) const
 Create and fill a ROOT histogram TH1,TH2 or TH3 with the values of this dataset.

 This function accepts the following arguments

 name -- Name of the ROOT histogram
 xvar -- Observable to be mapped on x axis of ROOT histogram

 AutoBinning(Int_t nbins, Double_y margin)    -- Automatically calculate range with given added fractional margin, set binning to nbins
 AutoSymBinning(Int_t nbins, Double_y margin) -- Automatically calculate range with given added fractional margin,
                                                 with additional constraint that mean of data is in center of range, set binning to nbins
 Binning(const char* name)                    -- Apply binning with given name to x axis of histogram
 Binning(RooAbsBinning& binning)              -- Apply specified binning to x axis of histogram
 Binning(int nbins, double lo, double hi)     -- Apply specified binning to x axis of histogram

 YVar(const RooAbsRealLValue& var,...)    -- Observable to be mapped on y axis of ROOT histogram
 ZVar(const RooAbsRealLValue& var,...)    -- Observable to be mapped on z axis of ROOT histogram

 The YVar() and ZVar() arguments can be supplied with optional Binning() Auto(Sym)Range() arguments to control the binning of the Y and Z axes, e.g.
 createHistogram("histo",x,Binning(-1,1,20), YVar(y,Binning(-1,1,30)), ZVar(z,Binning("zbinning")))

 The caller takes ownership of the returned histogram
TH1 * createHistogram(const char* name, const RooAbsRealLValue& xvar, const RooLinkedList& argList) const
 Internal method that implements histogram filling
Roo1DTable* table(const RooArgSet& catSet, const char* cuts = "", const char* opts = "") const
 Construct table for product of categories in catSet
void printName(ostream& os) const
 Print name of dataset
void printTitle(ostream& os) const
 Print title of dataset
void printClassName(ostream& os) const
 Print class name of dataset
void printMultiline(ostream& os, Int_t contents, Bool_t verbose = kFALSE, TString indent = "") const
Int_t defaultPrintContents(Option_t* opt) const
 Define default print options, for a given print style
Double_t standMoment(RooRealVar& var, Double_t order, const char* cutSpec = 0, const char* cutRange = 0) const
 Calculate standardized moment < (X - <X>)^n > / sigma^n,  where n = order.

 If cutSpec and/or cutRange are specified
 the moment is calculated on the subset of the data which pass the C++ cut specification expression 'cutSpec'
 and/or are inside the range named 'cutRange'
Double_t moment(RooRealVar& var, Double_t order, const char* cutSpec = 0, const char* cutRange = 0) const
 Calculate moment < (X - <X>)^n > where n = order.

 If cutSpec and/or cutRange are specified
 the moment is calculated on the subset of the data which pass the C++ cut specification expression 'cutSpec'
 and/or are inside the range named 'cutRange'
Double_t moment(RooRealVar& var, Double_t order, Double_t offset, const char* cutSpec = 0, const char* cutRange = 0) const
 Return the 'order'-ed moment of observable 'var' in this dataset. If offset is non-zero it is subtracted
 from the values of 'var' prior to the moment calculation. If cutSpec and/or cutRange are specified
 the moment is calculated on the subset of the data which pass the C++ cut specification expression 'cutSpec'
 and/or are inside the range named 'cutRange'
RooRealVar* dataRealVar(const char* methodname, RooRealVar& extVar) const
 Internal method to check if given RooRealVar maps to a RooRealVar in this dataset
Double_t corrcov(RooRealVar& x, RooRealVar& y, const char* cutSpec, const char* cutRange, Bool_t corr) const
 Internal method to calculate single correlation and covariance elements
TMatrixDSym* corrcovMatrix(const RooArgList& vars, const char* cutSpec, const char* cutRange, Bool_t corr) const
 Return covariance matrix from data for given list of observables
RooRealVar* meanVar(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
 Create a RooRealVar containing the mean of observable 'var' in
 this dataset.  If cutSpec and/or cutRange are specified the
 moment is calculated on the subset of the data which pass the C++
 cut specification expression 'cutSpec' and/or are inside the
 range named 'cutRange'
RooRealVar* rmsVar(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
 Create a RooRealVar containing the RMS of observable 'var' in
 this dataset.  If cutSpec and/or cutRange are specified the
 moment is calculated on the subset of the data which pass the C++
 cut specification expression 'cutSpec' and/or are inside the
 range named 'cutRange'
RooPlot* statOn(RooPlot* frame, const RooCmdArg& arg1 = RooCmdArg::none(), const RooCmdArg& arg2 = RooCmdArg::none(), const RooCmdArg& arg3 = RooCmdArg::none(), const RooCmdArg& arg4 = RooCmdArg::none(), const RooCmdArg& arg5 = RooCmdArg::none(), const RooCmdArg& arg6 = RooCmdArg::none(), const RooCmdArg& arg7 = RooCmdArg::none(), const RooCmdArg& arg8 = RooCmdArg::none())
 Add a box with statistics information to the specified frame. By default a box with the
 event count, mean and rms of the plotted variable is added.

 The following optional named arguments are accepted

   What(const char* whatstr)          -- Controls what is printed: "N" = count, "M" is mean, "R" is RMS.
   Format(const char* optStr)         -- Classing [arameter formatting options, provided for backward compatibility
   Format(const char* what,...)       -- Parameter formatting options, details given below
   Label(const chat* label)           -- Add header label to parameter box
   Layout(Double_t xmin,              -- Specify relative position of left,right side of box and top of box. Position of
       Double_t xmax, Double_t ymax)     bottom of box is calculated automatically from number lines in box
   Cut(const char* expression)        -- Apply given cut expression to data when calculating statistics
   CutRange(const char* rangeName)    -- Only consider events within given range when calculating statistics. Multiple
                                         CutRange() argument may be specified to combine ranges

 The Format(const char* what,...) has the following structure

   const char* what          -- Controls what is shown. "N" adds name, "E" adds error,
                                "A" shows asymmetric error, "U" shows unit, "H" hides the value
   FixedPrecision(int n)     -- Controls precision, set fixed number of digits
   AutoPrecision(int n)      -- Controls precision. Number of shown digits is calculated from error
                                + n specified additional digits (1 is sensible default)
   VerbatimName(Bool_t flag) -- Put variable name in a \verb+   + clause.

RooPlot* statOn(RooPlot* frame, const char* what, const char* label = "", Int_t sigDigits = 2, Option_t* options = "NELU", Double_t xmin = 0.15, Double_t xmax = 0.65, Double_t ymax = 0.85, const char* cutSpec = 0, const char* cutRange = 0, const RooCmdArg* formatCmd = 0)
 Implementation back-end of statOn() mehtod with named arguments
TH1 * fillHistogram(TH1* hist, const RooArgList& plotVars, const char* cuts = "", const char* cutRange = 0) const
 Loop over columns of our tree data and fill the input histogram. Returns a pointer to the
 input histogram, or zero in case of an error. The input histogram can be any TH1 subclass, and
 therefore of arbitrary dimension. Variables are matched with the (x,y,...) dimensions of the input
 histogram according to the order in which they appear in the input plotVars list.
TList* split(const RooAbsCategory& splitCat, Bool_t createEmptyDataSets = kFALSE) const
 Split dataset into subsets based on states of given splitCat in this dataset.
 A TList of RooDataSets is returned in which each RooDataSet is named
 after the state name of splitCat of which it contains the dataset subset.
 The observables splitCat itself is no longer present in the sub datasets.
 If createEmptyDataSets is kFALSE (default) this method only creates datasets for states
 which have at least one entry The caller takes ownership of the returned list and its contents
RooPlot* plotOn(RooPlot* frame, const RooLinkedList& cmdList) const
 Plot dataset on specified frame. By default an unbinned dataset will use the default binning of
 the target frame. A binned dataset will by default retain its intrinsic binning.

 The following optional named arguments can be used to modify the default behavior

 Data representation options

 Asymmetry(const RooCategory& c) -- Show the asymmetry of the data in given two-state category [F(+)-F(-)] / [F(+)+F(-)].
                                    Category must have two states with indices -1 and +1 or three states with indeces -1,0 and +1.
 Efficiency(const RooCategory& c)-- Show the efficiency F(acc)/[F(acc)+F(rej)]. Category must have two states with indices 0 and 1
 DataError(RooAbsData::EType)    -- Select the type of error drawn:
                                     - Auto(default) results in Poisson for unweighted data and SumW2 for weighted data
                                     - Poisson draws asymmetric Poisson confidence intervals.
                                     - SumW2 draws symmetric sum-of-weights error ( sum(w)^2/sum(w^2) )
                                     - None draws no error bars
 Binning(double xlo, double xhi, -- Use specified binning to draw dataset
                      int nbins)
 Binning(const RooAbsBinning&)   -- Use specified binning to draw dataset
 Binning(const char* name)       -- Use binning with specified name to draw dataset
 RefreshNorm(Bool_t flag)        -- Force refreshing for PDF normalization information in frame.
                                    If set, any subsequent PDF will normalize to this dataset, even if it is
                                    not the first one added to the frame. By default only the 1st dataset
                                    added to a frame will update the normalization information
 Rescale(Double_t f)             -- Rescale drawn histogram by given factor

 Histogram drawing options

 DrawOption(const char* opt)     -- Select ROOT draw option for resulting TGraph object
 LineStyle(Int_t style)          -- Select line style by ROOT line style code, default is solid
 LineColor(Int_t color)          -- Select line color by ROOT color code, default is black
 LineWidth(Int_t width)          -- Select line with in pixels, default is 3
 MarkerStyle(Int_t style)        -- Select the ROOT marker style, default is 21
 MarkerColor(Int_t color)        -- Select the ROOT marker color, default is black
 MarkerSize(Double_t size)       -- Select the ROOT marker size
 FillStyle(Int_t style)          -- Select fill style, default is filled.
 FillColor(Int_t color)          -- Select fill color by ROOT color code
 XErrorSize(Double_t frac)       -- Select size of X error bar as fraction of the bin width, default is 1


 Misc. other options

 Name(const chat* name)          -- Give curve specified name in frame. Useful if curve is to be referenced later
 Invisble()                      -- Add curve to frame, but do not display. Useful in combination AddTo()
 AddTo(const char* name,         -- Add constructed histogram to already existing histogram with given name and relative weight factors
 double_t wgtSelf, double_t wgtOther)



RooPlot * plotOn(RooPlot* frame, RooAbsData::PlotOpt o) const
 Create and fill a histogram of the frame's variable and append it to the frame.
 The frame variable must be one of the data sets dimensions.

 The plot range and the number of plot bins is determined by the parameters
 of the plot variable of the frame (RooAbsReal::setPlotRange(), RooAbsReal::setPlotBins())

 The optional cut string expression can be used to select the events to be plotted.
 The cut specification may refer to any variable contained in the data set

 The drawOptions are passed to the TH1::Draw() method
RooPlot* plotAsymOn(RooPlot* frame, const RooAbsCategoryLValue& asymCat, RooAbsData::PlotOpt o) const
 Create and fill a histogram with the asymmetry N[+] - N[-] / ( N[+] + N[-] ),
 where N(+/-) is the number of data points with asymCat=+1 and asymCat=-1
 as function of the frames variable. The asymmetry category 'asymCat' must
 have exactly 2 (or 3) states defined with index values +1,-1 (and 0)

 The plot range and the number of plot bins is determined by the parameters
 of the plot variable of the frame (RooAbsReal::setPlotRange(), RooAbsReal::setPlotBins())

 The optional cut string expression can be used to select the events to be plotted.
 The cut specification may refer to any variable contained in the data set

 The drawOptions are passed to the TH1::Draw() method
RooPlot* plotEffOn(RooPlot* frame, const RooAbsCategoryLValue& effCat, RooAbsData::PlotOpt o) const
 Create and fill a histogram with the effiency N[1] / ( N[1] + N[0] ),
 where N(1/0) is the number of data points with effCat=1 and effCat=0
 as function of the frames variable. The efficiency category 'effCat' must
 have exactly 2 +1 and 0.

 The plot range and the number of plot bins is determined by the parameters
 of the plot variable of the frame (RooAbsReal::setPlotRange(), RooAbsReal::setPlotBins())

 The optional cut string expression can be used to select the events to be plotted.
 The cut specification may refer to any variable contained in the data set

 The drawOptions are passed to the TH1::Draw() method
Roo1DTable* table(const RooAbsCategory& cat, const char* cuts = "", const char* opts = "") const
 Create and fill a 1-dimensional table for given category column
 This functions is the equivalent of plotOn() for category dimensions.

 The optional cut string expression can be used to select the events to be tabulated
 The cut specification may refer to any variable contained in the data set

 The option string is currently not used
Bool_t getRange(RooRealVar& var, Double_t& lowest, Double_t& highest, Double_t marginFrac = 0, Bool_t symMode = kFALSE) const
 Fill Doubles 'lowest' and 'highest' with the lowest and highest value of
 observable 'var' in this dataset. If the return value is kTRUE and error
 occurred
void optimizeReadingWithCaching(RooAbsArg& arg, const RooArgSet& cacheList, const RooArgSet& keepObsList)
 Prepare dataset for use with cached constant terms listed in
 'cacheList' of expression 'arg'. Deactivate tree branches
 for any dataset observable that is either not used at all,
 or is used exclusively by cached branch nodes.
Bool_t allClientsCached(RooAbsArg* , const RooArgSet& )
 Utility function that determines if all clients of object 'var'
 appear in given list of cached nodes.
Bool_t canSplitFast() const
RooAbsData* getSimData(const char* idxstate)
void addOwnedComponent(const char* idxlabel, RooAbsData& data)
void checkInit() const
void Draw(Option_t* option = "")
 Forward draw command to data store
Bool_t hasFilledCache() const
const TTree* tree() const
RooAbsData* emptyClone(const char* newName = 0, const char* newTitle = 0, const RooArgSet* vars = 0) const
RooAbsDataStore* store()
{ return _dstore ; }
const RooAbsDataStore* store() const
{ return _dstore ; }
void add(const RooArgSet& row, Double_t weight = 1, Double_t weightError = 0)
 Add one ore more rows of data
const RooArgSet* get() const
 Load a given row of data
Double_t weight() const
Bool_t valid() const
{ return kTRUE ; }
Double_t sumEntries(const char* cutSpec = 0, const char* cutRange = 0) const
Bool_t isWeighted() const
 Do events in dataset have weights?
Bool_t isNonPoissonWeighted() const
 Do events in dataset have non-integer weights?
void Print(Option_t* options = 0) const
 Printing interface (human readable)
Double_t mean(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
{ return moment(var,1,0,cutSpec,cutRange) ; }
Double_t sigma(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
{ return sqrt(moment(var,2,cutSpec,cutRange)) ; }
Double_t skewness(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
{ return standMoment(var,3,cutSpec,cutRange) ; }
Double_t kurtosis(RooRealVar& var, const char* cutSpec = 0, const char* cutRange = 0) const
{ return standMoment(var,4,cutSpec,cutRange) ; }
Double_t covariance(RooRealVar& x, RooRealVar& y, const char* cutSpec = 0, const char* cutRange = 0) const
{ return corrcov(x,y,cutSpec,cutRange,kFALSE) ; }
Double_t correlation(RooRealVar& x, RooRealVar& y, const char* cutSpec = 0, const char* cutRange = 0) const
{ return corrcov(x,y,cutSpec,cutRange,kTRUE) ; }
TMatrixDSym* covarianceMatrix(const char* cutSpec = 0, const char* cutRange = 0) const
{ return covarianceMatrix(*get(),cutSpec,cutRange) ; }
TMatrixDSym* correlationMatrix(const char* cutSpec = 0, const char* cutRange = 0) const
{ return correlationMatrix(*get(),cutSpec,cutRange) ; }
TMatrixDSym* covarianceMatrix(const RooArgList& vars, const char* cutSpec = 0, const char* cutRange = 0) const
{ return corrcovMatrix(vars,cutSpec,cutRange,kFALSE) ; }
TMatrixDSym* correlationMatrix(const RooArgList& vars, const char* cutSpec = 0, const char* cutRange = 0) const
{ return corrcovMatrix(vars,cutSpec,cutRange,kTRUE) ; }
RooAbsData* cacheClone(const RooAbsArg* newCacheOwner, const RooArgSet* newCacheVars, const char* newName = 0)
RooAbsData* reduceEng(const RooArgSet& varSubset, const RooFormulaVar* cutVar, const char* cutRange = 0, Int_t nStart = 0, Int_t nStop = 2000000000, Bool_t copyCache = kTRUE)