class THnBase: public TNamed

 Construct a THnBase with "dim" dimensions,
 "nbins" holds the number of bins for each dimension;
 "xmin" and "xmax" the minimal and maximal value for each dimension.
 The arrays "xmin" and "xmax" can be NULL; in that case SetBinEdges()
 must be called for each dimension.

 Destruct a THnBase

 Create a new THnBase object that is of the same type as *this,
 but with dimensions and bins given by axes.
 If keepTargetAxis is true, the axes will keep their original xmin / xmax,
 else they will be restricted to the range selected (first / last).

 Initialize axes and name.

 Create an empty histogram with name and title with a given
 set of axes. Create a TH1D/TH2D/TH3D, depending on the number
 of elements in axes.

 Create a THn / THnSparse object from a histogram deriving from TH1.

 Create a THnSparse (if "sparse") or THn  from "hn", possibly
 converting THn <-> THnSparse.

 Fill the THnBase with the bins of hist that have content
 or error != 0.

   Fit a THnSparse with function f

   since the data is sparse by default a likelihood fit is performed
   merging all the regions with empty bins for betetr performance efficiency

  Since the THnSparse is not drawn no graphics options are passed
  Here is the list of possible options

                = "I"  Use integral of function in bin instead of value at bin center
                = "X"  Use chi2 method (default is log-likelihood method)
                = "U"  Use a User specified fitting algorithm (via SetFCN)
                = "Q"  Quiet mode (minimum printing)
                = "V"  Verbose mode (default is between Q and V)
                = "E"  Perform better Errors estimation using Minos technique
                = "B"  Use this option when you want to fix one or more parameters
                       and the fitting function is like "gaus", "expo", "poln", "landau".
                = "M"  More. Improve fit results
                = "R"  Use the Range specified in the function range

 Generate an n-dimensional random tuple based on the histogrammed
 distribution. If subBinRandom, the returned tuple will be additionally
 randomly distributed within the randomized bin, using a flat
 distribution.

 Check whether bin coord is in range, as defined by TAxis::SetRange().

 Project all bins into a ndim-dimensional THn / THnSparse (whatever
 *this is) or if (ndim < 4 and !wantNDim) a TH1/2/3 histogram,
 keeping only axes in dim (specifying ndim dimensions).
 If "option" contains "E" errors will be calculated.
                      "A" ranges of the taget axes will be ignored.
                      "O" original axis range of the taget axes will be
                          kept, but only bins inside the selected range
                          will be filled.

 Scale contents and errors of this histogram by c:
 this = this * c
 It does not modify the histogram's number of entries.

 Add() implementation for both rebinned histograms and those with identical
 binning. See THnBase::Add().

 Add contents of h scaled by c to this histogram:
 this = this + c * h
 Note that if h has Sumw2 set, Sumw2 is automatically called for this
 if not already set.

 Add contents of h scaled by c to this histogram:
 this = this + c * h
 Note that if h has Sumw2 set, Sumw2 is automatically called for this
 if not already set.
 In contrast to Add(), RebinnedAdd() does not require consistent binning of
 this and h; instead, each bin's center is used to determine the target bin.

 Merge this with a list of THnBase's. All THnBase's provided
 in the list must have the same bin layout!

 Multiply this histogram by histogram h
 this = this * h
 Note that if h has Sumw2 set, Sumw2 is automatically called for this
 if not already set.

 Performs the operation: this = this*c*f1
 if errors are defined, errors are also recalculated.

 Only bins inside the function range are recomputed.
 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after
 calling Multiply()

 Divide this histogram by h
 this = this/(h)
 Note that if h has Sumw2 set, Sumw2 is automatically called for
 this if not already set.
 The resulting errors are calculated assuming uncorrelated content.

 Replace contents of this histogram by multiplication of h1 by h2
 this = (c1*h1)/(c2*h2)
 Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for
 this if not already set.
 The resulting errors are calculated assuming uncorrelated content.
 However, if option ="B" is specified, Binomial errors are computed.
 In this case c1 and c2 do not make real sense and they are ignored.

 Consistency check on (some of) the parameters of two histograms (for operations).

 Set the axis # of bins and bin limits on dimension idim

 Change (i.e. set) the title.

 If title is in the form "stringt;string0;string1;string2 ..."
 the histogram title is set to stringt, the title of axis0 to string0,
 of axis1 to string1, of axis2 to string2, etc, just like it is done
 for TH1/TH2/TH3.
 To insert the character ";" in one of the titles, one should use "#;"
 or "#semicolon".

 Combine the content of "group" neighboring bins into
 a new bin and return the resulting THnBase.
 For group=2 and a 3 dimensional histogram, all "blocks"
 of 2*2*2 bins will be put into a bin.

 Combine the content of "group" neighboring bins for each dimension
 into a new bin and return the resulting THnBase.
 For group={2,1,1} and a 3 dimensional histogram, pairs of x-bins
 will be grouped.

 Clear the histogram

 Calculate the integral of the histogram

 Print bin with linex index "idx".
 For valid options see PrintBin(Long64_t idx, Int_t* bin, Option_t* options).

 Print one bin. If "idx" is != -1 use that to determine the bin,
 otherwise (if "idx" == -1) use the coordinate in "bin".
 If "options" contains:
   '0': only print bins with an error or content != 0
 Return whether the bin was printed (depends on options)

 Print "howmany" entries starting at "from". If "howmany" is -1, print all.
 If "options" contains:
   'x': print in the order of axis bins, i.e. (0,0,...,0), (0,0,...,1),...
   '0': only print bins with content != 0

 Print a THnBase. If "option" contains:
   'a': print axis details
   'm': print memory usage
   's': print statistics
   'c': print its content, too (this can generate a LOT of output!)
 Other options are forwarded to PrintEntries().

 Browse a THnSparse: create an entry (ROOT::THnSparseBrowsable) for each
 dimension.

 Increment the statistics due to filled weight "w",

 Calculate errors (or not if "calc" == kFALSE)

 Project all bins into a 1-dimensional histogram,
 keeping only axis "xDim".
 If "option" contains "E" errors will be calculated.
                      "A" ranges of the taget axes will be ignored.
                      "O" original axis range of the taget axes will be
                          kept, but only bins inside the selected range
                          will be filled.

 Project all bins into a 2-dimensional histogram,
 keeping only axes "xDim" and "yDim".

 WARNING: just like TH3::Project3D("yx") and TTree::Draw("y:x"),
 Projection(y,x) uses the first argument to define the y-axis and the
 second for the x-axis!

 If "option" contains "E" errors will be calculated.
                      "A" ranges of the taget axes will be ignored.

 Project all bins into a 3-dimensional histogram,
 keeping only axes "xDim", "yDim", and "zDim".
 If "option" contains "E" errors will be calculated.
                      "A" ranges of the taget axes will be ignored.
                      "O" original axis range of the taget axes will be
                          kept, but only bins inside the selected range
                          will be filled.