class AliITSPlaneEffSSD: public AliITSPlaneEff

 destructor
 Inputs:
    none.
 Outputs:
    none.
 Return:
     none.

     Copy Constructor
 Inputs:
    AliITSPlaneEffSSD &s The original class for which
                                this class is a copy of
 Outputs:
    none.
 Return:

    Add-to-me operator
 Inputs:
    const AliITSPlaneEffSSD &add  simulation class to be added
 Outputs:
    none.
 Return:
    none

    Assignment operator
 Inputs:
    AliITSPlaneEffSSD &s The original class for which
                                this class is a copy of
 Outputs:
    none.
 Return:

 protected method. copy this to obj

 protected method: copy histos from this to target

   Estimate the number of tracks still to be collected to attain a
   given efficiency eff, with relative error RelErr
   Inputs:
         eff    -> Expected efficiency (e.g. those from actual estimate)
         RelErr -> tollerance [0,1]
         im     -> module number [0,1697]
   Outputs: none
   Return: the estimated n. of tracks

 Compute the efficiency for a basic block,
 Inputs:
        im     -> module number [0,1697]

 Compute the statistical error on efficiency for a basic block,
 using binomial statistics
 Inputs:
        im     -> module number [0,1697]

 Update efficiency for a basic block

 get key given a basic block

 get mod. from key

 returns plane efficieny after adding the fraction of sensor which is bad

 returns error on live plane efficiency

 returns the fraction of the sensor area which is OK (neither noisy nor dead)
 As for now, it computes only the fraction of good strips / total strips.
 If this fraction is large, then the computation is a good approximation.
 In any case, it is a lower limit of the fraction of the live area.
 The next upgrades would be to add the fraction of area of superoposition
 between bad N-side strips and bad P-side strips.

 returns the number of dead and noisy strips (sum of P and N sides).

 returns 1-fractional live

 write onto CDB

 read from CDB

 Read (actually add the statistics) plane eff. from Data Base

 method to locate a basic block from Detector Local coordinate (to be used in tracking)

 for the moment let's create the histograms
 module by  module

 Delete histograms and remove them from memory

 this method fill the histograms
 input: - key: unique key of the basic block
        - found: Boolean to asses whether a cluster has been associated to the track or not
        - tr[0],tr[1] local X and Z coordinates of the track prediction, respectively
        - tr[2],tr[3] error on local X and Z coordinates of the track prediction, respectively
        - clu[0],clu[1] local X and Z coordinates of the cluster associated to the track, respectively
        - clu[2],clu[3] error on local X and Z coordinates of the cluster associated to the track, respectively
        - csize[0][1] cluster size in X and Z, respectively
 output: kTRUE if filling was succesfull kFALSE otherwise
 side effects: updating of the histograms.

 Saves the histograms into a tree and saves the trees into a file

 Read histograms from an already existing file

  This method return the geometrical boundaries of the active volume of a given
  basic block, in the detector reference system.

 Methods for dealing with auxiliary histograms
 method to set on/off the creation/updates of histograms (Histos are created/destroyed)