class AliUEHist: public TObject

 Constructor

 combine default binning with custom binning
 replaces binnings in default binning if it is defined in custom binning

 takes the binning from <configuration> identified by <tag>
 configuration syntax example:
 eta: 2.4, -2.3, -2.2, -2.1, -2.0, -1.9, -1.8, -1.7, -1.6, -1.5, -1.4, -1.3, -1.2, -1.1, -1.0, -0.9, -0.8, -0.7, -0.6, -0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4
 phi: .....

 returns bin edges which have to be deleted by the caller

 AliUEHist copy constructor

 sets the names of the correction steps

 Destructor

 assigment operator

 copy function

 Merge a list of AliUEHist objects with this (needed for
 PROOF).
 Returns the number of merged objects (including this).

 sets the bin limits in eta and pT defined by fEtaMin/Max, fPtMin/Max

 sets the bin limits in eta and pT defined by fEtaMin/Max, fPtMin/Max

 resets all bin limits

 resets all bin limits

 prints the number of empty bins in the track end event histograms in the given step

 Extracts the UE histogram at the given step and in the given region by projection and dividing tracks by events

 ptLeadMin, ptLeadMax: Only meaningful for vs. delta phi plot (third axis is ptLead)
 Histogram has to be deleted by the caller of the function

 twoD: 0: 1D histogram as function of phi
       1: 2D histogram, deltaphi, deltaeta
       10: 1D histogram, within |deltaeta| < 0.8
       11: 1D histogram, within 0.8 < |deltaeta| < 1.6

 etaNorm: if kTRUE (default), the distributions are divided by the area in delta eta

 normEvents: if non-0 the number of events/trigger particles for the normalization is filled

 Calculates a 3d histogram with deltaphi, deltaeta, zvtx on track level and a 1d histogram on event level (as fct of zvtx)
 Histogram has to be deleted by the caller of the function

 Calculates a 4d histogram with deltaphi, deltaeta, zvtx, multiplicity on track level and
 a 2d histogram on event level (as fct of zvtx, multiplicity)
 Histograms has to be deleted by the caller of the function

 Calls GetUEHist(...) for *each* vertex bin and multiplicity bin and performs a sum of ratios:
 1_N [ (same/mixed)_1 + (same/mixed)_2 + (same/mixed)_3 + ... ]
 where N is the total number of events/trigger particles and the subscript is the vertex/multiplicity bin
 where mixed is normalized such that the information about the number of pairs in same is kept

 returns a 2D histogram: deltaphi, deltaeta

 Parameters:
   mixed: AliUEHist containing mixed event corresponding to this object (the histograms are taken from step <stepForMixed> if defined otherwise from step <step>)
   <other parameters> : check documentation of AliUEHist::GetUEHist
  normalizePerTrigger: divide through number of triggers

 returns the distribution of triggers as function of centrality/multiplicity

 Calls GetUEHist(...) for *each* multiplicity bin and performs a sum of ratios:
 1_N [ (same/mixed)_1 + (same/mixed)_2 + (same/mixed)_3 + ... ]
 where N is the total number of events/trigger particles and the subscript is the multiplicity bin

 Can only be used for the 2D histogram at present

 Parameters:
   mixed: AliUEHist containing mixed event corresponding to this object
   <other parameters> : check documentation of AliUEHist::GetUEHist

 returns a histogram projected to pT,assoc with the provided cuts

 multiplies <grid> with <histogram> and put the result in <target>
 <grid> has usually more dimensions than histogram. The axis which are used to choose the value
 from <histogram> are given in <var1> and <var2>

 if <histogram> is 0, just copies content from step1 to step2

 corrects from step1 to step2 by multiplying the tracks with trackCorrection
 trackCorrection can be a function of eta (var1 == 0), pT (var1 == 1), leading pT (var1 == 2), multiplicity (var1 == 3), delta phi (var1 == 4)
 if var2 >= 0 a two dimension correction is assumed in trackCorrection

 if trackCorrection is 0, just copies content from step1 to step2

 see documentation of CorrectTracks above

 corrects from step1 to step2 by multiplying the events with eventCorrection
 eventCorrection is as function of leading pT (var == 0) or multiplicity (var == 1)

 if eventCorrection is 0, just copies content from step1 to step2

 applies the given corrections to extract from the step kCFStepReconstructed all previous steps

 in this object the data is expected in the step kCFStepReconstructed

 creates a track-level efficiency by dividing step2 by step1
 in all dimensions but the particle species one

 creates a track-level efficiency by dividing step2 by step1
 projected to axis1 and axis2 (optional if >= 0)

 source: 0 = fTrackHist; 1 = fTrackHistEfficiency; 2 = fTrackHistEfficiency rebinned for pT,T / pT,lead binning

 creates a event-level efficiency by dividing step2 by step1
 projected to axis1 and axis2 (optional if >= 0)

 weights each entry of the 3d histogram hist1 with the 1d histogram hist2
 where the matching is done of the z axis of hist1 with the x axis of hist2

 extracts the track-level bias (integrating out the multiplicity) between two steps (dividing step2 by step1)
 in the given region (sum over all regions is calculated if region == -1)
 done by weighting the track-level distribution with the number of events as function of leading pT
 and then calculating the ratio between the distributions
 projected to axis which is a TH3::Project3D string, e.g. "x", or "yx"
   no projection is done if axis == 0
 weighting: 0 = tracks weighted with events (as discussed above)
            1 = only track bias is returned
            2 = only event bias is returned

 corrects for the given factor in a small delta-eta and delta-phi window as function of pT,A and pT,T

 contamination correlated with the trigger particle is evaluated between step kCFStepTracked and kCFStepTrackedOnlyPrim in the region of delta eta and delta phi < 0.1 (smallest bin!)

 extracts the tracking efficiency by calculating the efficiency from step kCFStepAnaTopology to kCFStepTrackedOnlyPrim
 integrates over the regions and all other variables than pT and eta to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking efficiency by calculating the efficiency from step kCFStepAnaTopology to kCFStepTrackedOnlyPrim
 integrates over the regions and all other variables than pT, centrality to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking efficiency by calculating the efficiency from step kCFStepAnaTopology to kCFStepTrackedOnlyPrim
 integrates over the regions and all other variables than pT (axis == 0) and eta (axis == 1) to increase the statistics

 extracts the tracking correction by calculating the efficiency from step kCFStepAnaTopology to kCFStepTracked
 integrates over the regions and all other variables than pT and eta to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking correction by calculating the efficiency from step kCFStepAnaTopology to kCFStepTracked
 integrates over the regions and all other variables than pT (axis == 0) and eta (axis == 1) to increase the statistics

 extracts the tracking correction by calculating the efficiency from step kCFStepAnaTopology to kCFStepTracked
 integrates over the regions and all other variables than pT and eta to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking correction by calculating the efficiency from step kCFStepAnaTopology to kCFStepTracked
 integrates over the regions and all other variables than pT and centrality to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking correction by calculating the efficiency from step kCFStepAnaTopology to kCFStepTracked
 integrates over the regions and all other variables than pT (axis == 0) and eta (axis == 1) to increase the statistics

 extracts the tracking contamination by secondaries by calculating the efficiency from step kCFStepTrackedOnlyPrim to kCFStepTracked
 integrates over the regions and all other variables than pT and eta to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking contamination by secondaries by calculating the efficiency from step kCFStepTrackedOnlyPrim to kCFStepTracked
 integrates over the regions and all other variables than pT and centrality to increase the statistics

 returned histogram has to be deleted by the user

 extracts the tracking contamination by secondaries by calculating the efficiency from step kCFStepTrackedOnlyPrim to kCFStepTracked
 integrates over the regions and all other variables than pT (axis == 0) and eta (axis == 1) to increase the statistics

 returns the name of the given region

 returns the name of the given step

 copies those histograms extracted from ESD to this object

 copies the entries of this object's members from the object <from> to this object
 fills using the fill function and thus allows that the objects have different binning

 copy pt,a < pt,t bins to pt,a > pt,t (inverting deltaphi and delta eta as it should be) including symmetric bins

 fits the tracking efficiency at high pT with a constant and fills all bins with this tracking efficiency

 corrects the dphi distribution with an extra factor close to dphi ~ 0

 scales all contained histograms by the given factor

 resets all contained histograms

 change the object to THn for faster processing

 loops through the histogram and moves all entries to a single point <targetValue> on the axis <axis>
 if <from> and <to> are set, then moving only occurs if value on <axis> is betweem <from> and <to>

 loops through the histogram at <step> and moves all entries to a single point <targetValue> on the axes
 <trackAxis> and <eventAxis>. <tmpStep> is used to temporary store the data
 This is useful e.g. to move bin content around for MC productions where the centrality selection did
 not yield the desired result