class TMVA::PDEFoam: public TObject

 Default constructor for streamer, user should not use it.

 User constructor, to be employed by the user

 Default destructor

 Copy Constructor  NOT IMPLEMENTED (NEVER USED)

 Sets dimension of cubical space

 set lower foam bound in dimension idim

 set upper foam bound in dimension idim

 Basic initialization of FOAM invoked by the user.
 IMPORTANT: Random number generator and the distribution object has to be
 provided using SetPseRan and SetRho prior to invoking this initializator!

 Internal subprogram used by Create.
 It initializes "root part" of the FOAM of the tree of cells.

 Internal subprogram used by Create.
 It initializes content of the newly allocated active cell.

 Internal subprogram used by Create.
 It explores newly defined cell with help of special short MC sampling.
 As a result, estimates of kTRUE and drive volume is defined/determined
 Average and dispersion of the weight distribution will is found along
 each edge and the best edge (minimum dispersion, best maximum weight)
 is memorized for future use.
 The optimal division point for eventual future cell division is
 determined/recorded. Recorded are also minimum and maximum weight etc.
 The volume estimate in all (inactive) parent cells is updated.
 Note that links to parents and initial volume = 1/2 parent has to be
 already defined prior to calling this routine.

 This function is overridden from the original PDEFoam::Explore()
 to provide an extra option:   Filling edge histograms directly from the
 input distributions, w/o MC sampling if fNSampl == 0
 Warning:  This option is not tested jet!

 Internal subrogram used by Create.
 In determines the best edge candidate and the position of the cell division plane
 in case of the variance reduction for future cell division,
 using results of the MC exploration run stored in fHistEdg

 Internal subrogram used by Create.
 Provides random vector Alpha  0< Alpha(i) < 1

 Internal subprogram used by Create.
 It finds cell with maximal driver integral for the purpose of the division.
 This function is overridden by the PDEFoam Class to apply cuts
 on Nmin and RMSmin during cell buildup.

 Internal subrogram used by Create.
 It divides cell iCell into two daughter cells.
 The iCell is retained and tagged as inactive, daughter cells are appended
 at the end of the buffer.
 New vertex is added to list of vertices.
 List of active cells is updated, iCell removed, two daughters added
 and their properties set with help of MC sampling (PDEFoam_Explore)
 Returns Code RC=-1 of buffer limit is reached,  fLastCe=fnBuf.

 Internal subprogram.
 Evaluates distribution to be generated.

 Internal subrogram used by Create.
 It grow new cells by the binary division process.
 This function is overridden by the PDEFoam class to stop the foam buildup process
 if one of the cut conditions stop the cell split.

 This can be called before Create, after setting kDim
 It defines which variables are excluded in the process of the cell division.
 For example 'FoamX->SetInhiDiv(1, 1);' inhibits division of y-variable.

  User utility, miscellaneous and debug.
  Checks all pointers in the tree of cells. This is useful autodiagnostic.
  level=0, no printout, failures causes STOP
  level=1, printout, failures lead to WARNINGS only

 Prints geometry of ALL cells of the FOAM

 This function removes a cell iCell, which has a volume equal to zero.
 It works the following way:
 1) find grandparent to iCell
 2) set daughter of the grandparent cell to the sister of iCell
 Result:
 iCell and its parent are alone standing ==> will be removed

 debug function: checks all cells with respect to critical
 values, f.e. cell volume, ...

 This debug function prints the cell elements of all active
 cells.

 creates a TVectorD object with fNElements in every cell
 and initializes them by zero.
 The TVectorD object is used to store classification or
 regression data in every foam cell.

 Parameter:
   allcells == true  : create TVectorD on every cell
   allcells == false : create TVectorD on active cells with
                       cell index <= fLastCe (default)

 Calculate average cell target in every cell and save them to the cell.
 This function is called when the Mono target regression option is set.

 Calc discriminator and its error for every cell and save it to the cell.
 This function is called when the fSigBgSeparated==False option is set.

 Get discriminator saved in cell (previously calculated in CalcCellDiscr())
 which encloses the coordinates given in xvec.
 This function is used, when the fSigBgSeparated==False option is set
 (unified foams).

 This function fills an event into the foam.

 In case of Mono-Target regression this function prepares the
 calculation of the average target value in every cell.  Note,
 that only target 0 is saved in the cell!

 In case of a unified foam this function prepares the calculation of
 the cell discriminator in every cell.

 If 'NoNegWeights' is true, an event with negative weight will
 not be filled into the foam.  (Default value: false)

 Get regression value 0 from cell that contains xvec.
 This function is used when the MultiTargetRegression==False option is set.

 This function returns the average value 'cv' of only nearest
 neighbor cells.  It is used in cases, where empty cells shall
 not be evaluated.

 Parameters:
 - txvec - event vector, transformed into foam [0, 1]
 - cv - cell value, see definition of ECellValue

 Returns true, if the value of the given cell is undefined.

 This function is used when the MultiTargetRegression==True
 option is set.  It calculates the mean target or most probable
 target values if 'tvals' variables are given ('tvals' does not
 contain targets)

 Parameters:
 - tvals - transformed event variables (element of [0,1]) (no targets!)
 - ts - method of target selection (kMean, kMpv)

 Result:
 vetor of mean targets or most probable targets over all cells
 which first coordinates enclose 'tvals'

 This function is used when the MultiTargetRegression==True option is set.
 Returns regression value i, given the event variables 'vals'.
 Note: number of foam dimensions = number of variables + number of targets

 Parameters:
 - vals - event variables (no targets)
 - kernel - used kernel (None or Gaus)
 - ts - method of target selection (Mean or Mpv)

 Returns density (=number of entries / volume) of cell that encloses 'xvec'.
 This function is called by GetMvaValue() in case of two separated foams
 (signal and background).
 'kernel' can be either kNone or kGaus.

 This function returns a value, which was saved in the foam cell,
 depending on the foam type.  The value to return is specified
 with the 'cv' parameter.

 This function finds the cell, which corresponds to the given
 event vector 'xvec' and return its value, which is given by the
 parameter 'cv'.

 Returns the number of events, saved in the 'cell' during foam build-up.
 Only used during foam build-up!

 results the cell value, corresponding to txvec, weighted by the
 neighor cells via a linear function

 Parameters
  - txvec - event vector, transformed to interval [0,1]
  - cv - cell value to be weighted
  - dim1, dim2 - dimensions for two-dimensional projection.
    Default values: dim1 = dim2 = -1
    If dim1 and dim2 are set to values >=0 and <fDim, than
    the function GetProjectionCellValue() is used to get cell
    value.  This is used for projection to two dimensions within
    Project2().
  - TreatEmptyCells - if this option is set false (default),
    it is not checked, wether the cell or its neighbors are empty
    or not.  If this option is set true, than only non-empty
    neighbor cells are taken into account for weighting.  If the
    cell, which contains txvec is empty, than its value is
    replaced by the average value of the non-empty neighbor cells

 Returns the gauss weight between the 'cell' and a given coordinate 'txvec'.

 Parameters:
 - cell - the cell
 - txvec - the transformed event variables (in [0,1]) (coordinates <0 are
   set to 0, >1 are set to 1)
 - dim - number of dimensions for the calculation of the euclidean distance.
   If dim=0, all dimensions of the foam are taken.  Else only the first 'dim'
   coordinates of 'txvec' are used for the calculation of the euclidean distance.

 Returns:
 exp(-(d/sigma)^2/2), where
  - d - is the euclidean distance between 'txvec' and the point of the 'cell'
    which is most close to 'txvec' (in order to avoid artefacts because of the
    form of the cells).
  - sigma = 1/VolFrac

 Find cell that contains xvec

 loop to find cell that contains xvec start from root Cell, uses
 binary tree to find cell quickly

 This is a helper function for FindCells().  It saves in 'cells'
 all cells, which contain txvec.  It works analogous to
 FindCell().

 Parameters:

 - txvec - vector of variables (no targets!) (transformed into
   foam)

 - cell - cell to start searching with (usually root cell
   fCells[0])

 - cells - list of cells found

 Find all cells, that contain txvec.  This function can be used,
 when the dimension of the foam is greater than the dimension of
 txvec.  E.G this is the case for multi-target regression

 Parameters:

 - txvec - vector of variables (no targets!) (transformed into
   foam)

 Return value:

 - vector of cells, that fit txvec

 Draws 1-dimensional foam (= histogram)

 Parameters:

 - opt - cell_value, rms, rms_ov_mean
   if cell_value is set, the following values will be filled into
   the result histogram:
    - number of events - in case of classification with 2 separate
                         foams or multi-target regression
    - discriminator    - in case of classification with one
                         unified foam
    - target           - in case of mono-target regression

 - nbin - number of bins of result histogram

 Warning: This function is not well tested!

 Project foam variable idim1 and variable idim2 to histogram.

 Parameters:

 - idim1, idim2 - dimensions to project to

 - opt - cell_value, rms, rms_ov_mean
   if cell_value is set, the following values will be filled into
   the result histogram:
    - number of events - in case of classification with 2 separate
                         foams or multi-target regression
    - discriminator    - in case of classification with one
                         unified foam
    - target           - in case of mono-target regression

 - ker - kGaus, kNone (warning: Gaus may be very slow!)

 - maxbins - maximal number of bins in result histogram.
   Set maxbins to 0 if no maximum bin number should be used.

 Returns:
 a 2-dimensional histogram

 Helper function for projection function Project2().  It returns
 the cell value of 'cell' corresponding to the given option 'cv'.
 The two dimensions are needed for weighting the return value,
 because Project2() projects the foam to two dimensions.

 Returns pointer to cell elements.  The given event vector 'xvec'
 must be untransformed (i.e. [xmin, xmax]).

 Returns cell element i of cell 'cell'.

 Set cell element i of cell to value.

 Overridden function of PDEFoam to avoid native foam output.
 Draw TMVA-process bar instead.

 Debugging tool which plots 2-dimensional cells as rectangles
 in C++ format readable for root.

 Parameters:
 - filename - filename of ouput root macro
 - CreateCanvas - whether to create a new canvas or not

 set VolFrac to internal foam density PDEFoamDistr

 Insert event to internal foam density PDEFoamDistr.

 Initialize internal foam density PDEFoamDistr

 Set the foam type.  This determinates the method of the
 calculation of the density during the foam build-up.

 Read PDEFoam variables from stream 'istr'.

 Write PDEFoam variables to stream 'os'.

 write foam variables to xml

METHODS

 Getters and Setters for user cut options

 Getters and Setters for variable names