class RooAbsData: public TNamed, public RooPrintable

 Destructor

 Internal method -- Cache given set of functions with data

 Internal method -- Remove cached function values

 Internal method -- Attach dataset copied with cache contents to copied instances of functions

 Control propagation of dirty flags from observables in dataset

 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

 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.

 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.

 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.

 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.

 Return error on current weight (dummy implementation returning zero)

 Return asymmetric error on weight. (Dummy implementation returning zero)

 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)

 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

 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

 Internal method that implements histogram filling

 Construct table for product of categories in catSet

 Print name of dataset

 Print title of dataset

 Print class name of dataset

 Define default print options, for a given print style

 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'

 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'

 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'

 Internal method to check if given RooRealVar maps to a RooRealVar in this dataset

 Internal method to calculate single correlation and covariance elements

 Return covariance matrix from data for given list of observables

 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'

 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'

 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.

 Implementation back-end of statOn() mehtod with named arguments

 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.

 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

 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)

 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

 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

 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

 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

 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

 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.

 Utility function that determines if all clients of object 'var'
 appear in given list of cached nodes.

 Forward draw command to data store

 Add one ore more rows of data

 Load a given row of data

 Do events in dataset have weights?

 Do events in dataset have non-integer weights?

 Printing interface (human readable)