| 1 | /* ======================================================================== *\
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| 2 | !
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| 3 | ! *
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| 4 | ! * This file is part of MARS, the MAGIC Analysis and Reconstruction
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| 5 | ! * Software. It is distributed to you in the hope that it can be a useful
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| 6 | ! * and timesaving tool in analysing Data of imaging Cerenkov telescopes.
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| 7 | ! * It is distributed WITHOUT ANY WARRANTY.
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| 8 | ! *
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| 9 | ! * Permission to use, copy, modify and distribute this software and its
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| 10 | ! * documentation for any purpose is hereby granted without fee,
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| 11 | ! * provided that the above copyright notice appear in all copies and
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| 12 | ! * that both that copyright notice and this permission notice appear
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| 13 | ! * in supporting documentation. It is provided "as is" without express
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| 14 | ! * or implied warranty.
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| 15 | ! *
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| 16 | !
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| 17 | !
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| 18 | !   Author(s): Thomas Bretz, 8/2002 <mailto:tbretz@astro.uni-wuerzburg.de>
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| 19 | !   Author(s): Wolfgang Wittek, 1/2002 <mailto:wittek@mppmu.mpg.de>
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| 20 | !
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| 21 | !   Copyright: MAGIC Software Development, 2000-2008
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| 22 | !
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| 23 | !
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| 24 | \* ======================================================================== */
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| 25 | 
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| 26 | //////////////////////////////////////////////////////////////////////////////
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| 27 | //
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| 28 | //  MHEffectiveOnTime
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| 29 | //
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| 30 | //  Filling this you will get the effective on-time versus theta and
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| 31 | //  observation time.
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| 32 | //
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| 33 | //  From this histogram the effective on-time is determined by a fit.
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| 34 | //  The result of the fit (see Fit()) and the fit-parameters (like chi^2)
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| 35 | //  are stored in corresponding histograms
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| 36 | //
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| 37 | //  To determin the efective on time a poisson fit is done. For more details
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| 38 | //  please have a look into the source code of FitH() it should be simple
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| 39 | //  to understand. In this function a Delta-T distribution is fitted, while
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| 40 | //  Delta-T is the time between two consecutive events.
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| 41 | //
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| 42 | //  The fit is done for projections of a 2D histogram in Theta and Delta T.
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| 43 | //  So you get the effective on time versus theta.
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| 44 | //
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| 45 | //  To get the effective on-time versus time a histogram is filled with
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| 46 | //  the Delta-T distribution of a number of events set by SetNumEvents().
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| 47 | //  The default is 12000 (roughly 1min at 200Hz)
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| 48 | //
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| 49 | //  For each "time-bin" the histogram is fitted and the resulting effective
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| 50 | //  on-time is stored in the fHTimeEffOn histogram. Each entry in this
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| 51 | //  histogram is the effective observation time between the upper and
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| 52 | //  lower edges of the bins.
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| 53 | //
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| 54 | //  In addition the calculated effective on time is stored in a
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| 55 | //  "MEffectiveOnTime [MParameterDerr]" and the corresponding time-stamp
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| 56 | //  (the upper edge of the bin) "MTimeEffectiveOnTime [MTime]"
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| 57 | //
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| 58 | //  The class takes two binnings from the Parameter list; if these binnings
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| 59 | //  are not available the defaultbinning is used:
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| 60 | //      MBinning("BinningDeltaT"); // Units of seconds
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| 61 | //      MBinning("BinningTheta");  // Units of degrees
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| 62 | //
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| 63 | //
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| 64 | //  Usage:
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| 65 | //  ------
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| 66 | //    MFillH fill("MHEffectiveOnTime", "MTime");
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| 67 | //    tlist.AddToList(&fill);
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| 68 | //
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| 69 | //
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| 70 | //  Input Container:
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| 71 | //    MPointingPos
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| 72 | //    MRawRunHeader
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| 73 | //    MTime
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| 74 | //
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| 75 | //  Output Container:
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| 76 | //    MEffectiveOnTime [MParameterDerr]
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| 77 | //    MTimeEffectiveOnTime [MTime]
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| 78 | //
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| 79 | //
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| 80 | //  Class version 2:
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| 81 | //  ----------------
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| 82 | //   +  UInt_t fFirstBin;
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| 83 | //   +  UInt_t fNumEvents;
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| 84 | //   -  Int_t fNumEvents;
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| 85 | //
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| 86 | //  Class version 3:
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| 87 | //  ----------------
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| 88 | //   +  Double_t fTotalTime;
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| 89 | //
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| 90 | //  Class version 4:
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| 91 | //  ----------------
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| 92 | //   +  Double_t fEffOnTime;    //[s] On time as fitted from the DeltaT distribution
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| 93 | //   +  Double_t fEffOnTimeErr; //[s] On time error as fitted from the DeltaT distribution
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| 94 | //
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| 95 | // ==========================================================================
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| 96 | // Dear Colleagues,
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| 97 | //
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| 98 | // for the case that we are taking calibration events interleaved with
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| 99 | // cosmics events the calculation of the effective observation time has to
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| 100 | // be modified. I have summarized the proposed procedures in the note at the
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| 101 | // end of this message. The formulas have been checked by a simulation.
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| 102 | //
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| 103 | // Comments are welcome.
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| 104 | //
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| 105 | // Regards,  Wolfgang
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| 106 | // --------------------------------------------------------------------------
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| 107 | //                                                       Wolfgang Wittek
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| 108 | //                                                         2 Dec. 2004
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| 109 | //
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| 110 | // Calculation of the effective observation time when cosmics and calibration
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| 111 | // events are taken simultaneously.
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| 112 | // --------------------------------
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| 113 | //
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| 114 | // I. Introduction
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| 115 | // ---------------
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| 116 | // It is planned to take light calibration events (at a certain fixed frequency
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| 117 | // lambda_calib) interlaced with cosmics events. The advantages of this
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| 118 | // procedure are :
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| 119 | //
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| 120 | // - the pedestals, which would be determined from the cosmics, could be
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| 121 | //   used for both the calibration and the cosmics events
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| 122 | //
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| 123 | // - because calibration and cosmics events are taken quasi simultaneously,
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| 124 | //   rapid variations (in the order of a few minutes) of base lines and of the
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| 125 | //   photon/ADC conversion factors could be recognized and taken into account
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| 126 | //
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| 127 | // The effective observation time T_eff is defined as that time range, within
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| 128 | // which the recorded number of events N_cosmics would be obtained under ideal
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| 129 | // conditions (only cosmics, no dead time, no calibration events, ...).
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| 130 | //
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| 131 | // In the absence of calibration events the effective observation time can
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| 132 | // be determined from the distribution of time differences 'dt' between
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| 133 | // successive cosmics events (see first figure in the attached ps file).
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| 134 | // The exponential slope 'lambda' of this distribution is the ideal cosmics
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| 135 | // event rate. If 'N_cosmics' is the total number of recorded cosmics events,
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| 136 | // T_eff is obtained by
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| 137 | //
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| 138 | //    T_eff = N_cosmics / lambda
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| 139 | //
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| 140 | // In the case of a finite dead time 'dead', the distribution (for dt > dead) is
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| 141 | // still exponential with the same slope 'lambda'. 'lambda' should be determined
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| 142 | // in a region of 'dt' which is not affected by the dead time, i.e. at not too
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| 143 | // low 'dt'.
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| 144 | //
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| 145 | //
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| 146 | //
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| 147 | // II. Problems in the presence of calibration events
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| 148 | // --------------------------------------------------
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| 149 | // If calibration events are taken interlaced with cosmics, and if the dead time
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| 150 | // is negligible, the distribution of time differences 'dt' between cosmics can
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| 151 | // be used for calculating the effective observation time, as if the calibration
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| 152 | // events were not present.
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| 153 | //
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| 154 | // In the case of a non-negligible dead time 'dead', however, the distribution of
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| 155 | // time differences between cosmics is distorted, because a cosmics event may be
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| 156 | // lost due to the dead time after a calibration event. Even if the time
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| 157 | // intervals are ignored which contain a calibration event,
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| 158 | //
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| 159 | //
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| 160 | //        ---|---------o--------|--------->  t
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| 161 | //
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| 162 | //        cosmics    calib    cosmics
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| 163 | //
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| 164 | //            <---------------->           <==== time interval to be ignored
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| 165 | //
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| 166 | //
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| 167 | // the distribution of 'dt' is still distorted, because there would be no
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| 168 | // 'dt' with dt > tau_calib = 1/lambda_calib. The distribution would also be
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| 169 | // distorted in the region dt < tau_calib, due to calibration events occuring
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| 170 | // shortly after cosmics events. As a result, the slope of the distribution of
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| 171 | // 'dt' would not reflect the ideal cosmics event rate (see second figure; the
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| 172 | // values assumed in the simulation are lambda = 200 Hz, lambda_calib = 50
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| 173 | // Hz, dead = 0.001 sec, total time = 500 sec, number of generated cosmics
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| 174 | // events = 100 000).
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| 175 | //
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| 176 | //
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| 177 | // Note also that some calibration events will not be recorded due to the dead
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| 178 | // time after a cosmics event.
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| 179 | //
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| 180 | //
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| 181 | // III. Proposed procedures
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| 182 | // ------------------------
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| 183 | //
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| 184 | // A) The ideal event rate 'lambda' may be calculated from the distribution of
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| 185 | // the time difference 'dt_first' between a calibration event and the first
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| 186 | // recorded cosmics event after the calibration event. In the region
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| 187 | //
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| 188 | //     dead < dt_first < tau_calib
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| 189 | //
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| 190 | // the probability distribution of dt_first is given by
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| 191 | //
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| 192 | //     p(dt_first) = c * exp(-lambda*dt_first)
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| 193 | //
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| 194 | // where c is a normalization constant. 'lambda' can be obtained by a simple
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| 195 | // exponential fit to the experimental distribution of dt_first (see third
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| 196 | // figure). The fit range should start well above the average value of the dead
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| 197 | // time 'dead'.
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| 198 | //
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| 199 | //
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| 200 | // B) One may consider those time intervals between recorded cosmics events, which
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| 201 | // are completely contained in the region
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| 202 | //
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| 203 | //    t_calib < t < t_calib + tau_calib
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| 204 | //
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| 205 | // where t_calib is the time of a recorded calibration event.
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| 206 | //
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| 207 | //
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| 208 | //          <--------------- tau_calib ----------->
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| 209 | //
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| 210 | //
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| 211 | //           0   1  2   3 4  5   6  7    8  9   10
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| 212 | //      --|-o---|-|---|--|-|----|--|---|---|-|----o-|---|-|--------->  t
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| 213 | //          ^                                     ^
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| 214 | //          |                                     |
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| 215 | //        t_calib                               t_calib + tau_calib
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| 216 | //
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| 217 | //
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| 218 | // In this example, of the time intervals 0 to 10 only the intervals 1 to 9
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| 219 | // should be retained and plotted. The distribution of the length 'dt' of these
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| 220 | // intervals in the region
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| 221 | //
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| 222 | //     dead < dt < tau_calib
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| 223 | //
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| 224 | // is given by
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| 225 | //
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| 226 | //     p(dt) = c * (tau_calib-dt-dead) * exp(-lambda*dt)
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| 227 | //
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| 228 | // A fit of this expression to the experimental distribution of 'dt' yields
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| 229 | // 'lambda' (see fourth figure). For 'dead' an average value of the dead time
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| 230 | // should be chosen, and the fit range should end well before dt = tau_calib-dead.
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| 231 | //
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| 232 | //
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| 233 | // Method A has the advantage that the p(dt_first) does not depend on 'dead'.
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| 234 | // 'dead' has to be considered when defining the fit range, both in method A and
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| 235 | // in method B. In method B the event statistics is larger leading to a smaller
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| 236 | // fitted error of 'lambda' than method A (see the figures).
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| 237 | //
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| 238 | //
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| 239 | // The effective observation time is again obtained by
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| 240 | //
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| 241 | //    T_eff = N_cosmics / lambda
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| 242 | //
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| 243 | // where N_cosmics is the total number of recorded cosmics events. Note that
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| 244 | // N_cosmics is equal to
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| 245 | //
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| 246 | //    N_cosmics = N_tot - N_calib
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| 247 | //
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| 248 | // where N_tot is the total number of recorded events (including the calibration
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| 249 | // events) and N_calib is the number of recorded calibration events.
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| 250 | //
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| 251 | // Note that if time intervals are discarded for the determination of lambda,
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| 252 | // the corresponding cosmics events need not and should not be discarded.
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| 253 | //
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| 254 | //
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| 255 | // IV. Procedure if the calibration events are taken in bunches
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| 256 | // ------------------------------------------------------------
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| 257 | // In November 2004 the rate of calibration events is not constant. The events
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| 258 | // are taken in 200 Hz bunches every second, such that the rate is 200 Hz for
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| 259 | // 0.25 sec, followed by a gap of 0.75 sec. Then follows the next 200 Hz bunch.
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| 260 | //
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| 261 | // In this case it is proposed to consider for the calculation of 'lambda' only
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| 262 | // the cosmics events within the gaps of 0.75 sec. For these cosmics events one
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| 263 | // of the methods described in III. can be applied.
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| 264 | //
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| 265 | //
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| 266 | // V. Alternative pocedure
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| 267 | // -----------------------
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| 268 | // The effective observation time can also be determined from the total
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| 269 | // observation time and the total dead time. The latter is written out by the DAQ.
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| 270 | // In this case it has to be made sure that the dead time is available in Mars
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| 271 | // when the effective observation time is calculated.
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| 272 | //
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| 273 | //////////////////////////////////////////////////////////////////////////////
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| 274 | #include "MHEffectiveOnTime.h"
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| 275 | 
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| 276 | #include <TF1.h>
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| 277 | #include <TMinuit.h>
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| 278 | #include <TRandom.h>
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| 279 | 
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| 280 | #include <TLatex.h>
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| 281 | #include <TGaxis.h>
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| 282 | #include <TCanvas.h>
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| 283 | #include <TPaveStats.h>
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| 284 | 
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| 285 | #include "MTime.h"
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| 286 | #include "MString.h"
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| 287 | #include "MParameters.h"
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| 288 | #include "MPointingPos.h"
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| 289 | #include "MRawRunHeader.h"
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| 290 | 
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| 291 | #include "MBinning.h"
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| 292 | #include "MParList.h"
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| 293 | 
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| 294 | #include "MLog.h"
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| 295 | #include "MLogManip.h"
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| 296 | 
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| 297 | ClassImp(MHEffectiveOnTime);
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| 298 | 
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| 299 | using namespace std;
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| 300 | 
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| 301 | // --------------------------------------------------------------------------
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| 302 | //
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| 303 | // Default Constructor. It initializes all histograms.
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| 304 | //
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| 305 | MHEffectiveOnTime::MHEffectiveOnTime(const char *name, const char *title)
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| 306 |     : fPointPos(0), fTime(0), fParam(0), fIsFinalized(kFALSE), 
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| 307 |     fNumEvents(200*60), fFirstBin(3), fTotalTime(-1),
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| 308 |     fEffOnTime(-1), fEffOnTimeErr(0)
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| 309 |     //fNumEvents(2*60), fFirstBin(1)
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| 310 | {
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| 311 |     //
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| 312 |     //   set the name and title of this object
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| 313 |     //
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| 314 |     fName  = name  ? name  : "MHEffectiveOnTime";
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| 315 |     fTitle = title ? title : "Histogram to determin effective On-Time vs Time and Zenith Angle";
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| 316 | 
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| 317 |     // Main histogram
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| 318 |     fH2DeltaT.SetName("DeltaT");
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| 319 |     fH2DeltaT.SetXTitle("\\Delta t [s]");
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| 320 |     fH2DeltaT.SetYTitle("\\Theta [\\circ]");
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| 321 |     fH2DeltaT.SetZTitle("Count");
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| 322 |     fH2DeltaT.UseCurrentStyle();
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| 323 |     fH2DeltaT.SetDirectory(NULL);
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| 324 | 
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| 325 |     // Main histogram
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| 326 |     fH1DeltaT.SetName("DeltaT");
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| 327 |     fH1DeltaT.SetXTitle("\\Delta t [s]");
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| 328 |     fH1DeltaT.SetYTitle("Counts");
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| 329 |     fH1DeltaT.UseCurrentStyle();
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| 330 |     fH1DeltaT.SetDirectory(NULL);
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| 331 | 
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| 332 |     // effective on time versus theta
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| 333 |     fHThetaEffOn.SetName("EffOnTheta");
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| 334 |     fHThetaEffOn.SetTitle("Effective On Time T_{eff}");
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| 335 |     fHThetaEffOn.SetXTitle("\\Theta [\\circ]");
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| 336 |     fHThetaEffOn.SetYTitle("T_{eff} [s]");
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| 337 |     fHThetaEffOn.UseCurrentStyle();
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| 338 |     fHThetaEffOn.SetDirectory(NULL);
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| 339 |     fHThetaEffOn.GetYaxis()->SetTitleOffset(1.2);
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| 340 |     fHThetaEffOn.GetYaxis()->SetTitleColor(kBlue);
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| 341 |     fHThetaEffOn.SetLineColor(kBlue);
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| 342 |     //fHEffOn.Sumw2();
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| 343 | 
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| 344 |     // effective on time versus time
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| 345 |     fHTimeEffOn.SetName("EffOnTime");
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| 346 |     fHTimeEffOn.SetTitle("Effective On Time T_{eff}");
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| 347 |     fHTimeEffOn.SetXTitle("Time");
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| 348 |     fHTimeEffOn.SetYTitle("T_{eff} [s]");
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| 349 |     fHTimeEffOn.UseCurrentStyle();
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| 350 |     fHTimeEffOn.SetDirectory(NULL);
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| 351 |     fHTimeEffOn.GetYaxis()->SetTitleOffset(1.2);
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| 352 |     fHTimeEffOn.GetXaxis()->SetLabelSize(0.033);
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| 353 |     fHTimeEffOn.GetXaxis()->SetTimeFormat("%H:%M:%S %F1995-01-01 00:00:00 GMT");
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| 354 |     fHTimeEffOn.GetXaxis()->SetTimeDisplay(1);
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| 355 |     fHTimeEffOn.GetYaxis()->SetTitleColor(kBlue);
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| 356 |     fHTimeEffOn.SetLineColor(kBlue);
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| 357 | 
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| 358 |     // chi2 probability
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| 359 |     fHThetaProb.SetName("ProbTheta");
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| 360 |     fHThetaProb.SetTitle("\\chi^{2} Probability of Fit");
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| 361 |     fHThetaProb.SetXTitle("\\Theta [\\circ]");
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| 362 |     fHThetaProb.SetYTitle("p [%]");
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| 363 |     fHThetaProb.UseCurrentStyle();
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| 364 |     fHThetaProb.SetDirectory(NULL);
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| 365 |     fHThetaProb.GetYaxis()->SetTitleOffset(1.2);
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| 366 |     fHThetaProb.SetMaximum(101);
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| 367 |     fHThetaProb.GetYaxis()->SetTitleColor(kBlue);
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| 368 |     fHThetaProb.SetLineColor(kBlue);
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| 369 | 
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| 370 |     // chi2 probability
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| 371 |     fHTimeProb.SetName("ProbTime");
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| 372 |     fHTimeProb.SetTitle("\\chi^{2} Probability of Fit");
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| 373 |     fHTimeProb.SetXTitle("Time");
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| 374 |     fHTimeProb.SetYTitle("p [%]");
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| 375 |     fHTimeProb.UseCurrentStyle();
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| 376 |     fHTimeProb.SetDirectory(NULL);
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| 377 |     fHTimeProb.GetYaxis()->SetTitleOffset(1.2);
 | 
|---|
| 378 |     fHTimeProb.GetXaxis()->SetLabelSize(0.033);
 | 
|---|
| 379 |     fHTimeProb.GetXaxis()->SetTimeFormat("%H:%M:%S %F1995-01-01 00:00:00 GMT");
 | 
|---|
| 380 |     fHTimeProb.GetXaxis()->SetTimeDisplay(1);
 | 
|---|
| 381 |     fHTimeProb.SetMaximum(101);
 | 
|---|
| 382 |     fHTimeProb.GetYaxis()->SetTitleColor(kBlue);
 | 
|---|
| 383 |     fHTimeProb.SetLineColor(kBlue);
 | 
|---|
| 384 | 
 | 
|---|
| 385 |     // lambda versus theta
 | 
|---|
| 386 |     fHThetaLambda.SetName("LambdaTheta");
 | 
|---|
| 387 |     fHThetaLambda.SetTitle("Slope (Rate) vs Theta");
 | 
|---|
| 388 |     fHThetaLambda.SetXTitle("\\Theta [\\circ]");
 | 
|---|
| 389 |     fHThetaLambda.SetYTitle("\\lambda [s^{-1}]");
 | 
|---|
| 390 |     fHThetaLambda.UseCurrentStyle();
 | 
|---|
| 391 |     fHThetaLambda.SetDirectory(NULL);
 | 
|---|
| 392 |     fHThetaLambda.SetLineColor(kGreen);
 | 
|---|
| 393 | 
 | 
|---|
| 394 |     // lambda versus time
 | 
|---|
| 395 |     fHTimeLambda.SetName("LambdaTime");
 | 
|---|
| 396 |     fHTimeLambda.SetTitle("Slope (Rate) vs Time");
 | 
|---|
| 397 |     fHTimeLambda.SetXTitle("\\Time [\\circ]");
 | 
|---|
| 398 |     fHTimeLambda.SetYTitle("\\lambda [s^{-1}]");
 | 
|---|
| 399 |     fHTimeLambda.UseCurrentStyle();
 | 
|---|
| 400 |     fHTimeLambda.SetDirectory(NULL);
 | 
|---|
| 401 |     fHTimeLambda.GetYaxis()->SetTitleOffset(1.2);
 | 
|---|
| 402 |     fHTimeLambda.GetXaxis()->SetLabelSize(0.033);
 | 
|---|
| 403 |     fHTimeLambda.GetXaxis()->SetTimeFormat("%H:%M:%S %F1995-01-01 00:00:00 GMT");
 | 
|---|
| 404 |     fHTimeLambda.GetXaxis()->SetTimeDisplay(1);
 | 
|---|
| 405 |     fHTimeLambda.SetLineColor(kGreen);
 | 
|---|
| 406 | 
 | 
|---|
| 407 |     // NDoF versus theta
 | 
|---|
| 408 |     fHThetaNDF.SetName("NDofTheta");
 | 
|---|
| 409 |     fHThetaNDF.SetTitle("Number of Degrees of freedom vs Theta");
 | 
|---|
| 410 |     fHThetaNDF.SetXTitle("\\Theta [\\circ]");
 | 
|---|
| 411 |     fHThetaNDF.SetYTitle("NDoF [#]");
 | 
|---|
| 412 |     fHThetaNDF.UseCurrentStyle();
 | 
|---|
| 413 |     fHThetaNDF.SetDirectory(NULL);
 | 
|---|
| 414 |     fHThetaNDF.SetLineColor(kGreen);
 | 
|---|
| 415 | 
 | 
|---|
| 416 |     // NDoF versus time
 | 
|---|
| 417 |     /*
 | 
|---|
| 418 |     fHTimeNDF.SetName("NDofTime");
 | 
|---|
| 419 |     fHTimeNDF.SetTitle("Number of Degrees of freedom vs Time");
 | 
|---|
| 420 |     fHTimeNDF.SetXTitle("Time");
 | 
|---|
| 421 |     fHTimeNDF.SetYTitle("NDoF [#]");
 | 
|---|
| 422 |     fHTimeNDF.UseCurrentStyle();
 | 
|---|
| 423 |     fHTimeNDF.SetDirectory(NULL);
 | 
|---|
| 424 |     fHTimeNDF.GetYaxis()->SetTitleOffset(1.2);
 | 
|---|
| 425 |     fHTimeNDF.GetXaxis()->SetLabelSize(0.033);
 | 
|---|
| 426 |     fHTimeNDF.GetXaxis()->SetTimeFormat("%H:%M:%S %F1995-01-01 00:00:00 GMT");
 | 
|---|
| 427 |     fHTimeNDF.GetXaxis()->SetTimeDisplay(1);
 | 
|---|
| 428 |     fHTimeNDF.SetLineColor(kBlue);
 | 
|---|
| 429 |     */
 | 
|---|
| 430 |     // setup binning
 | 
|---|
| 431 |     MBinning btheta("BinningTheta");
 | 
|---|
| 432 |     btheta.SetEdgesASin(67, -0.005, 0.665);
 | 
|---|
| 433 | 
 | 
|---|
| 434 |     MBinning btime("BinningDeltaT");
 | 
|---|
| 435 |     btime.SetEdges(50, 0, 0.1);
 | 
|---|
| 436 | 
 | 
|---|
| 437 |     MH::SetBinning(fH2DeltaT, btime, btheta);
 | 
|---|
| 438 | 
 | 
|---|
| 439 |     btime.Apply(fH1DeltaT);
 | 
|---|
| 440 | 
 | 
|---|
| 441 |     btheta.Apply(fHThetaEffOn);
 | 
|---|
| 442 |     btheta.Apply(fHThetaLambda);
 | 
|---|
| 443 |     btheta.Apply(fHThetaNDF);
 | 
|---|
| 444 |     btheta.Apply(fHThetaProb);
 | 
|---|
| 445 |     //btheta.Apply(fHChi2);
 | 
|---|
| 446 | }
 | 
|---|
| 447 | 
 | 
|---|
| 448 | // --------------------------------------------------------------------------
 | 
|---|
| 449 | //
 | 
|---|
| 450 | // Set the binnings and prepare the filling of the histogram
 | 
|---|
| 451 | //
 | 
|---|
| 452 | Bool_t MHEffectiveOnTime::SetupFill(const MParList *plist)
 | 
|---|
| 453 | {
 | 
|---|
| 454 |    fPointPos = (MPointingPos*)plist->FindObject("MPointingPos");
 | 
|---|
| 455 |    if (!fPointPos)
 | 
|---|
| 456 |    {
 | 
|---|
| 457 |        *fLog << err << dbginf << "MPointingPos not found... aborting." << endl;
 | 
|---|
| 458 |        return kFALSE;
 | 
|---|
| 459 |    }
 | 
|---|
| 460 | 
 | 
|---|
| 461 |    // FIXME: Remove const-qualifier from base-class!
 | 
|---|
| 462 |    fTime = (MTime*)const_cast<MParList*>(plist)->FindCreateObj("MTime", "MTimeEffectiveOnTime");
 | 
|---|
| 463 |    if (!fTime)
 | 
|---|
| 464 |        return kFALSE;
 | 
|---|
| 465 |    fParam = (MParameterDerr*)const_cast<MParList*>(plist)->FindCreateObj("MParameterDerr", "MEffectiveOnTime");
 | 
|---|
| 466 |    if (!fParam)
 | 
|---|
| 467 |        return kFALSE;
 | 
|---|
| 468 | 
 | 
|---|
| 469 |    const MBinning* binsdtime = (MBinning*)plist->FindObject("BinningDeltaT");
 | 
|---|
| 470 |    const MBinning* binstheta = (MBinning*)plist->FindObject("BinningTheta");
 | 
|---|
| 471 |    if (binsdtime)
 | 
|---|
| 472 |        binsdtime->Apply(fH1DeltaT);
 | 
|---|
| 473 |    if (binstheta)
 | 
|---|
| 474 |    {
 | 
|---|
| 475 |        binstheta->Apply(fHThetaEffOn);
 | 
|---|
| 476 |        binstheta->Apply(fHThetaLambda);
 | 
|---|
| 477 |        binstheta->Apply(fHThetaNDF);
 | 
|---|
| 478 |        binstheta->Apply(fHThetaProb);
 | 
|---|
| 479 |        //binstheta->Apply(fHChi2);
 | 
|---|
| 480 |    }
 | 
|---|
| 481 |    if (binstheta && binsdtime)
 | 
|---|
| 482 |        SetBinning(fH2DeltaT, *binsdtime, *binstheta);
 | 
|---|
| 483 | 
 | 
|---|
| 484 |    fTotalTime = 0;
 | 
|---|
| 485 | 
 | 
|---|
| 486 |    fEffOnTime    = -1;
 | 
|---|
| 487 |    fEffOnTimeErr =  0;
 | 
|---|
| 488 | 
 | 
|---|
| 489 |    return kTRUE;
 | 
|---|
| 490 | }
 | 
|---|
| 491 | 
 | 
|---|
| 492 | Bool_t MHEffectiveOnTime::ReInit(MParList *pList)
 | 
|---|
| 493 | {
 | 
|---|
| 494 |     MRawRunHeader *header = (MRawRunHeader*)pList->FindObject("MRawRunHeader");
 | 
|---|
| 495 |     if (!header)
 | 
|---|
| 496 |     {
 | 
|---|
| 497 |         *fLog << err << "MRawRunHeader not found... aborting." << endl;
 | 
|---|
| 498 |         return kFALSE;
 | 
|---|
| 499 |     }
 | 
|---|
| 500 | 
 | 
|---|
| 501 |     fTotalTime += header->GetRunLength();
 | 
|---|
| 502 | 
 | 
|---|
| 503 |     return kTRUE;
 | 
|---|
| 504 | }
 | 
|---|
| 505 | 
 | 
|---|
| 506 | // --------------------------------------------------------------------------
 | 
|---|
| 507 | //
 | 
|---|
| 508 | // Fit a single Delta-T distribution. See source code for more details
 | 
|---|
| 509 | //
 | 
|---|
| 510 | Bool_t MHEffectiveOnTime::FitH(TH1D *h, Double_t *res, Bool_t paint) const
 | 
|---|
| 511 | {
 | 
|---|
| 512 |     // Count also events in under-/overflowbins
 | 
|---|
| 513 |     const Double_t Nm = h->Integral(0, h->GetNbinsX()+1);
 | 
|---|
| 514 | 
 | 
|---|
| 515 |     // FIXME: Do fit only if contents of bin has changed
 | 
|---|
| 516 |     if (Nm<=0 || h->GetBinContent(1)<=0)
 | 
|---|
| 517 |         return kFALSE;
 | 
|---|
| 518 | 
 | 
|---|
| 519 |     // determine range (yq[0], yq[1]) of time differences
 | 
|---|
| 520 |     // where fit should be performed;
 | 
|---|
| 521 |     // require a fraction >=xq[0] of all entries to lie below yq[0]
 | 
|---|
| 522 |     //     and a fraction <=xq[1] of all entries to lie below yq[1];
 | 
|---|
| 523 |     // within the range (yq[0], yq[1]) there must be no empty bin;
 | 
|---|
| 524 |     // choose pedestrian approach as long as GetQuantiles is not available
 | 
|---|
| 525 |     Double_t xq[2] = { 0.6, 0.95 }; // previously 0.99
 | 
|---|
| 526 |     Double_t yq[2];
 | 
|---|
| 527 |     h->GetQuantiles(2, yq, xq);
 | 
|---|
| 528 | 
 | 
|---|
| 529 |     //
 | 
|---|
| 530 |     // Determine a good starting value for the slope
 | 
|---|
| 531 |     //
 | 
|---|
| 532 |     const TAxis  &axe = *h->GetXaxis();
 | 
|---|
| 533 |     const UInt_t ibin = axe.FindFixBin(yq[1]);
 | 
|---|
| 534 |     const Double_t x1 = axe.GetBinCenter(ibin<=fFirstBin?fFirstBin+1:ibin);
 | 
|---|
| 535 |     const Double_t x0 = axe.GetBinCenter(fFirstBin);
 | 
|---|
| 536 |     const Double_t y1 = h->GetBinContent(ibin)>1 ? TMath::Log(h->GetBinContent(ibin)) : 0;
 | 
|---|
| 537 |     const Double_t y0 = TMath::Log(h->GetBinContent(fFirstBin));
 | 
|---|
| 538 | 
 | 
|---|
| 539 |     // Estimated slope
 | 
|---|
| 540 |     const Float_t m = -(y1-y0)/(x1-x0);
 | 
|---|
| 541 | 
 | 
|---|
| 542 |     //
 | 
|---|
| 543 |     // Setup exponential function for the fit:
 | 
|---|
| 544 |     //
 | 
|---|
| 545 |     // parameter 0 = rate [Hz]
 | 
|---|
| 546 |     // parameter 1 = normalization
 | 
|---|
| 547 |     //
 | 
|---|
| 548 |     TF1 func("Exp", " exp([1]-[0]*x)");
 | 
|---|
| 549 | 
 | 
|---|
| 550 |     func.SetParameter(0, m);       // Hz
 | 
|---|
| 551 |     func.SetParameter(1, log(h->GetBinContent(1)));       // Hz
 | 
|---|
| 552 | 
 | 
|---|
| 553 |     // We set a limit to make sure that almost empty histograms which
 | 
|---|
| 554 |     // are fitted dont't produce hang ups or crashes
 | 
|---|
| 555 |     func.SetParLimits(0, 0, 15000); // Hz
 | 
|---|
| 556 | 
 | 
|---|
| 557 |     // options : N  do not store the function, do not draw
 | 
|---|
| 558 |     //           I  use integral of function in bin rather than value at bin center
 | 
|---|
| 559 |     //           R  use the range specified in the function range
 | 
|---|
| 560 |     //           Q  quiet mode
 | 
|---|
| 561 |     //           L  Use log-likelihood (better for low statistics)
 | 
|---|
| 562 |     h->Fit(&func, "NIQEL", "", h->GetBinLowEdge(fFirstBin)/*yq[0]*/, yq[1]);
 | 
|---|
| 563 | 
 | 
|---|
| 564 |     const Double_t chi2 = func.GetChisquare();
 | 
|---|
| 565 |     const Double_t prob = func.GetProb();
 | 
|---|
| 566 |     const Int_t    NDF  = func.GetNDF();
 | 
|---|
| 567 | 
 | 
|---|
| 568 |     // was fit successful ?
 | 
|---|
| 569 |     const Bool_t ok = prob>0.001; //NDF>0 && chi2<3*NDF;
 | 
|---|
| 570 | 
 | 
|---|
| 571 |     if (paint)
 | 
|---|
| 572 |     {
 | 
|---|
| 573 |         func.SetLineWidth(2);
 | 
|---|
| 574 |         func.SetLineColor(ok ? kGreen : kRed);
 | 
|---|
| 575 |         func.Paint("same");
 | 
|---|
| 576 |     }
 | 
|---|
| 577 | 
 | 
|---|
| 578 |     // The effective on time is the "real rate" (slope of the exponential)
 | 
|---|
| 579 |     // divided by the total number of events (histogram integral including 
 | 
|---|
| 580 |     // under- and overflows)
 | 
|---|
| 581 |     const Double_t lambda = func.GetParameter(0);
 | 
|---|
| 582 |     const Double_t dldl   = func.GetParError(0)*func.GetParError(0);
 | 
|---|
| 583 |     const Double_t teff   = lambda==0 ? 0 : Nm / lambda;
 | 
|---|
| 584 |     const Double_t dteff  = lambda==0 ? 0 : teff * TMath::Sqrt(dldl/(lambda*lambda) + 1.0/Nm);
 | 
|---|
| 585 |     const Double_t dl     = TMath::Sqrt(dldl);
 | 
|---|
| 586 | 
 | 
|---|
| 587 |     // the effective on time is Nm/lambda
 | 
|---|
| 588 |     res[0] = teff;
 | 
|---|
| 589 |     res[1] = dteff;
 | 
|---|
| 590 | 
 | 
|---|
| 591 |     // plot chi2-probability of fit
 | 
|---|
| 592 |     res[2] = prob*100;
 | 
|---|
| 593 | 
 | 
|---|
| 594 |     // lambda of fit
 | 
|---|
| 595 |     res[3] = lambda;
 | 
|---|
| 596 |     res[4] = dl;
 | 
|---|
| 597 | 
 | 
|---|
| 598 |     // NDoF of fit
 | 
|---|
| 599 |     res[5] = NDF;
 | 
|---|
| 600 | 
 | 
|---|
| 601 |     // Chi2
 | 
|---|
| 602 |     res[6] = chi2;
 | 
|---|
| 603 | 
 | 
|---|
| 604 |     return ok;
 | 
|---|
| 605 | }
 | 
|---|
| 606 | 
 | 
|---|
| 607 | // --------------------------------------------------------------------------
 | 
|---|
| 608 | //
 | 
|---|
| 609 | // Fit a all bins of the distribution in theta. Store the result in the
 | 
|---|
| 610 | // Theta-Histograms
 | 
|---|
| 611 | //
 | 
|---|
| 612 | void MHEffectiveOnTime::FitThetaBins()
 | 
|---|
| 613 | {
 | 
|---|
| 614 |     fHThetaEffOn.Reset();
 | 
|---|
| 615 |     fHThetaProb.Reset();
 | 
|---|
| 616 |     fHThetaLambda.Reset();
 | 
|---|
| 617 |     fHThetaNDF.Reset();
 | 
|---|
| 618 | 
 | 
|---|
| 619 |     // Use a random name to make sure the object is unique
 | 
|---|
| 620 |     const TString name = MString::Format("CalcTheta%d", (UInt_t)gRandom->Uniform(999999999));
 | 
|---|
| 621 | 
 | 
|---|
| 622 |     // nbins = number of Theta bins
 | 
|---|
| 623 |     const Int_t nbins = fH2DeltaT.GetNbinsY();
 | 
|---|
| 624 | 
 | 
|---|
| 625 |     TH1D *h=0;
 | 
|---|
| 626 |     for (int i=1; i<=nbins; i++)
 | 
|---|
| 627 |     {
 | 
|---|
| 628 |         //        TH1D &h = *hist->ProjectionX("Calc-theta", i, i);
 | 
|---|
| 629 |         h = fH2DeltaT.ProjectionX(name, i, i, "E");
 | 
|---|
| 630 | 
 | 
|---|
| 631 |         Double_t res[7] = {0, 0, 0, 0, 0, 0, 0};
 | 
|---|
| 632 |         //if (!FitH(h, res))
 | 
|---|
| 633 |         //    continue;
 | 
|---|
| 634 |         FitH(h, res);
 | 
|---|
| 635 | 
 | 
|---|
| 636 |         if (res[0]==0)
 | 
|---|
| 637 |             continue;
 | 
|---|
| 638 | 
 | 
|---|
| 639 |         // the effective on time is Nm/lambda
 | 
|---|
| 640 |         fHThetaEffOn.SetBinContent(i, res[0]);
 | 
|---|
| 641 |         fHThetaEffOn.SetBinError  (i, res[1]);
 | 
|---|
| 642 | 
 | 
|---|
| 643 |         // plot chi2-probability of fit
 | 
|---|
| 644 |         fHThetaProb.SetBinContent(i, res[2]);
 | 
|---|
| 645 | 
 | 
|---|
| 646 |         // plot chi2/NDF of fit
 | 
|---|
| 647 |         //fHChi2.SetBinContent(i, res[3]);
 | 
|---|
| 648 | 
 | 
|---|
| 649 |         // lambda of fit
 | 
|---|
| 650 |         fHThetaLambda.SetBinContent(i, res[3]);
 | 
|---|
| 651 |         fHThetaLambda.SetBinError  (i, res[4]);
 | 
|---|
| 652 | 
 | 
|---|
| 653 |         // NDoF of fit
 | 
|---|
| 654 |         fHThetaNDF.SetBinContent(i, res[5]);
 | 
|---|
| 655 | 
 | 
|---|
| 656 |         // Rdead (from fit) is the fraction from real time lost by the dead time
 | 
|---|
| 657 |         //fHRdead.SetBinContent(i, Rdead);
 | 
|---|
| 658 |         //fHRdead.SetBinError  (i,dRdead);
 | 
|---|
| 659 |     }
 | 
|---|
| 660 | 
 | 
|---|
| 661 |     // Histogram is reused via gROOT->FindObject()
 | 
|---|
| 662 |     // Need to be deleted only once
 | 
|---|
| 663 |     if (h)
 | 
|---|
| 664 |         delete h;
 | 
|---|
| 665 | }
 | 
|---|
| 666 | 
 | 
|---|
| 667 | // --------------------------------------------------------------------------
 | 
|---|
| 668 | //
 | 
|---|
| 669 | // Fit the single-time-bin histogram. Store the result in the
 | 
|---|
| 670 | // Time-Histograms
 | 
|---|
| 671 | //
 | 
|---|
| 672 | void MHEffectiveOnTime::FitTimeBin()
 | 
|---|
| 673 | {
 | 
|---|
| 674 |     //
 | 
|---|
| 675 |     // Fit histogram
 | 
|---|
| 676 |     //
 | 
|---|
| 677 |     Double_t res[7];
 | 
|---|
| 678 |     if (!FitH(&fH1DeltaT, res))
 | 
|---|
| 679 |         return;
 | 
|---|
| 680 | 
 | 
|---|
| 681 |     // Reset Histogram
 | 
|---|
| 682 |     fH1DeltaT.Reset();
 | 
|---|
| 683 | 
 | 
|---|
| 684 |     //
 | 
|---|
| 685 |     // Prepare Histogram
 | 
|---|
| 686 |     //
 | 
|---|
| 687 | 
 | 
|---|
| 688 |     // Get number of bins
 | 
|---|
| 689 |     const Int_t n = fHTimeEffOn.GetNbinsX();
 | 
|---|
| 690 | 
 | 
|---|
| 691 |     // Enhance binning
 | 
|---|
| 692 |     MBinning bins;
 | 
|---|
| 693 |     bins.SetEdges(fHTimeEffOn, 'x');
 | 
|---|
| 694 |     bins.AddEdge(fLastTime.GetAxisTime());
 | 
|---|
| 695 |     bins.Apply(fHTimeEffOn);
 | 
|---|
| 696 |     bins.Apply(fHTimeProb);
 | 
|---|
| 697 |     bins.Apply(fHTimeLambda);
 | 
|---|
| 698 |     //bins.Apply(fHTimeNDF);
 | 
|---|
| 699 | 
 | 
|---|
| 700 |     //
 | 
|---|
| 701 |     // Fill histogram
 | 
|---|
| 702 |     //
 | 
|---|
| 703 |     fHTimeEffOn.SetBinContent(n, res[0]);
 | 
|---|
| 704 |     fHTimeEffOn.SetBinError(n, res[1]);
 | 
|---|
| 705 | 
 | 
|---|
| 706 |     fHTimeProb.SetBinContent(n, res[2]);
 | 
|---|
| 707 | 
 | 
|---|
| 708 |     fHTimeLambda.SetBinContent(n, res[3]);
 | 
|---|
| 709 |     fHTimeLambda.SetBinError(n, res[4]);
 | 
|---|
| 710 | 
 | 
|---|
| 711 |     //fHTimeNDF.SetBinContent(n, res[5]);
 | 
|---|
| 712 | 
 | 
|---|
| 713 |     //
 | 
|---|
| 714 |     // Now prepare output
 | 
|---|
| 715 |     //
 | 
|---|
| 716 |     fParam->SetVal(res[0], res[1]);
 | 
|---|
| 717 |     fParam->SetReadyToSave();
 | 
|---|
| 718 | 
 | 
|---|
| 719 |     *fTime = fLastTime;
 | 
|---|
| 720 | 
 | 
|---|
| 721 |     // Include the current event
 | 
|---|
| 722 |     fTime->Plus1ns();
 | 
|---|
| 723 | 
 | 
|---|
| 724 |     *fLog << inf2 << fLastTime << ":  Val=" << res[0] << "  Err=" << res[1] << endl;
 | 
|---|
| 725 | }
 | 
|---|
| 726 | 
 | 
|---|
| 727 | // --------------------------------------------------------------------------
 | 
|---|
| 728 | //
 | 
|---|
| 729 | //  Fill the histogram
 | 
|---|
| 730 | //
 | 
|---|
| 731 | Int_t MHEffectiveOnTime::Fill(const MParContainer *par, const Stat_t w)
 | 
|---|
| 732 | {
 | 
|---|
| 733 |     const MTime *time = dynamic_cast<const MTime*>(par);
 | 
|---|
| 734 |     if (!time)
 | 
|---|
| 735 |     {
 | 
|---|
| 736 |         *fLog << err << "ERROR - MHEffectiveOnTime::Fill without argument or container doesn't inherit from MTime... abort." << endl;
 | 
|---|
| 737 |         return kERROR;
 | 
|---|
| 738 |     }
 | 
|---|
| 739 | 
 | 
|---|
| 740 |     //
 | 
|---|
| 741 |     // If this is the first call we have to initialize the time-histogram
 | 
|---|
| 742 |     //
 | 
|---|
| 743 |     if (fLastTime==MTime())
 | 
|---|
| 744 |     {
 | 
|---|
| 745 |         MBinning bins;
 | 
|---|
| 746 |         bins.SetEdges(1, time->GetAxisTime()-fNumEvents/200, time->GetAxisTime());
 | 
|---|
| 747 |         bins.Apply(fHTimeEffOn);
 | 
|---|
| 748 |         bins.Apply(fHTimeProb);
 | 
|---|
| 749 |         bins.Apply(fHTimeLambda);
 | 
|---|
| 750 |         //bins.Apply(fHTimeNDF);
 | 
|---|
| 751 | 
 | 
|---|
| 752 |         fParam->SetVal(0, 0);
 | 
|---|
| 753 |         fParam->SetReadyToSave();
 | 
|---|
| 754 | 
 | 
|---|
| 755 |         *fTime = *time;
 | 
|---|
| 756 | 
 | 
|---|
| 757 |         // Make this 1ns before the first event!
 | 
|---|
| 758 |         fTime->Minus1ns();
 | 
|---|
| 759 |     }
 | 
|---|
| 760 | 
 | 
|---|
| 761 |     //
 | 
|---|
| 762 |     // Fill time difference into the histograms
 | 
|---|
| 763 |     //
 | 
|---|
| 764 |     const Double_t dt = *time-fLastTime;
 | 
|---|
| 765 |     fLastTime = *time;
 | 
|---|
| 766 | 
 | 
|---|
| 767 |     fH2DeltaT.Fill(dt, fPointPos->GetZd(), w);
 | 
|---|
| 768 |     fH1DeltaT.Fill(dt, w);
 | 
|---|
| 769 | 
 | 
|---|
| 770 |     //
 | 
|---|
| 771 |     // If we reached the event number limit for the time-bins fit the
 | 
|---|
| 772 |     // histogram - if it fails try again when 1.6% more events available
 | 
|---|
| 773 |     //
 | 
|---|
| 774 |     const UInt_t n = (UInt_t)fH1DeltaT.GetEntries();
 | 
|---|
| 775 |     if (n>=fNumEvents && n%(fNumEvents/60)==0)
 | 
|---|
| 776 |         FitTimeBin();
 | 
|---|
| 777 | 
 | 
|---|
| 778 |     return kTRUE;
 | 
|---|
| 779 | }
 | 
|---|
| 780 | 
 | 
|---|
| 781 | // --------------------------------------------------------------------------
 | 
|---|
| 782 | //
 | 
|---|
| 783 | //  Fit the theta projections of the 2D histogram and the 1D Delta-T
 | 
|---|
| 784 | // distribution
 | 
|---|
| 785 | //
 | 
|---|
| 786 | Bool_t MHEffectiveOnTime::Finalize()
 | 
|---|
| 787 | {
 | 
|---|
| 788 |     FitThetaBins();
 | 
|---|
| 789 |     FitTimeBin();
 | 
|---|
| 790 | 
 | 
|---|
| 791 | 
 | 
|---|
| 792 |     TH1D *h = fH2DeltaT.ProjectionX("FinalizeProjDeltaT", -1, -1, "E");
 | 
|---|
| 793 |     Double_t res[7];
 | 
|---|
| 794 |     if (FitH(h, res))
 | 
|---|
| 795 |     {
 | 
|---|
| 796 |         fEffOnTime    = res[0];
 | 
|---|
| 797 |         fEffOnTimeErr = res[1];
 | 
|---|
| 798 |     }
 | 
|---|
| 799 |     delete h;
 | 
|---|
| 800 | 
 | 
|---|
| 801 | 
 | 
|---|
| 802 |     fIsFinalized = kTRUE;
 | 
|---|
| 803 | 
 | 
|---|
| 804 |     return kTRUE;
 | 
|---|
| 805 | }
 | 
|---|
| 806 | 
 | 
|---|
| 807 | // --------------------------------------------------------------------------
 | 
|---|
| 808 | //
 | 
|---|
| 809 | //  Paint the integral and the error on top of the histogram
 | 
|---|
| 810 | //
 | 
|---|
| 811 | void MHEffectiveOnTime::PaintText(Double_t val, Double_t error, Double_t range) const
 | 
|---|
| 812 | {
 | 
|---|
| 813 |     TLatex text;
 | 
|---|
| 814 |     text.SetBit(TLatex::kTextNDC);
 | 
|---|
| 815 |     text.SetTextSize(0.04);
 | 
|---|
| 816 | 
 | 
|---|
| 817 |     TString txt = MString::Format("T_{eff} = %.1fs \\pm %.1fs", val, error);
 | 
|---|
| 818 |     if (range>0)
 | 
|---|
| 819 |         txt += MString::Format("     T_{axe} = %.1fs", range);
 | 
|---|
| 820 |     if (fTotalTime>0)
 | 
|---|
| 821 |         txt += MString::Format("     T_{max} = %.1fs", fTotalTime);
 | 
|---|
| 822 | 
 | 
|---|
| 823 |     text.SetText(0.35, 0.94, txt);
 | 
|---|
| 824 |     text.Paint();
 | 
|---|
| 825 | }
 | 
|---|
| 826 | 
 | 
|---|
| 827 | void MHEffectiveOnTime::PaintText(Double_t *res) const
 | 
|---|
| 828 | {
 | 
|---|
| 829 |     TLatex text(0.27, 0.94, MString::Format("T_{eff}=%.1fs\\pm%.1fs  \\lambda=%.1f\\pm%.1fHz  p=%.1f%%  \\chi^{2}/%d=%.1f",
 | 
|---|
| 830 |                                             res[0], res[1], res[3], res[4], res[2], (int)res[5], res[6]/res[5]));
 | 
|---|
| 831 |     text.SetBit(TLatex::kTextNDC);
 | 
|---|
| 832 |     text.SetTextSize(0.04);
 | 
|---|
| 833 |     text.Paint();
 | 
|---|
| 834 | }
 | 
|---|
| 835 | 
 | 
|---|
| 836 | void MHEffectiveOnTime::PaintProb(TH1 &h) const
 | 
|---|
| 837 | {
 | 
|---|
| 838 |     Double_t sum = 0;
 | 
|---|
| 839 |     Int_t    n = 0;
 | 
|---|
| 840 |     for (int i=0; i<h.GetNbinsX(); i++)
 | 
|---|
| 841 |         if (h.GetBinContent(i+1)>0)
 | 
|---|
| 842 |         {
 | 
|---|
| 843 |             sum += h.GetBinContent(i+1);
 | 
|---|
| 844 |             n++;
 | 
|---|
| 845 |         }
 | 
|---|
| 846 | 
 | 
|---|
| 847 |     if (n==0)
 | 
|---|
| 848 |         return;
 | 
|---|
| 849 | 
 | 
|---|
| 850 |     TLatex text(0.47, 0.94, MString::Format("\\bar{p} = %.1f%%", sum/n));
 | 
|---|
| 851 |     text.SetBit(TLatex::kTextNDC);
 | 
|---|
| 852 |     text.SetTextSize(0.04);
 | 
|---|
| 853 |     text.Paint();
 | 
|---|
| 854 | }
 | 
|---|
| 855 | 
 | 
|---|
| 856 | void MHEffectiveOnTime::UpdateRightAxis(TH1 &h)
 | 
|---|
| 857 | {
 | 
|---|
| 858 |     const Double_t max = h.GetMaximum()*1.1;
 | 
|---|
| 859 |     if (max==0)
 | 
|---|
| 860 |         return;
 | 
|---|
| 861 | 
 | 
|---|
| 862 |     h.SetNormFactor(h.Integral()*gPad->GetUymax()/max);
 | 
|---|
| 863 | 
 | 
|---|
| 864 |     TGaxis *axis = (TGaxis*)gPad->FindObject("RightAxis");
 | 
|---|
| 865 |     if (!axis)
 | 
|---|
| 866 |         return;
 | 
|---|
| 867 | 
 | 
|---|
| 868 |     axis->SetX1(gPad->GetUxmax());
 | 
|---|
| 869 |     axis->SetX2(gPad->GetUxmax());
 | 
|---|
| 870 |     axis->SetY1(gPad->GetUymin());
 | 
|---|
| 871 |     axis->SetY2(gPad->GetUymax());
 | 
|---|
| 872 |     axis->SetWmax(max);
 | 
|---|
| 873 | }
 | 
|---|
| 874 | 
 | 
|---|
| 875 | // --------------------------------------------------------------------------
 | 
|---|
| 876 | //
 | 
|---|
| 877 | //  Prepare painting the histograms
 | 
|---|
| 878 | //
 | 
|---|
| 879 | void MHEffectiveOnTime::Paint(Option_t *opt)
 | 
|---|
| 880 | {
 | 
|---|
| 881 |     TH1D *h=0;
 | 
|---|
| 882 |     TPaveStats *st=0;
 | 
|---|
| 883 | 
 | 
|---|
| 884 |     TString o(opt);
 | 
|---|
| 885 |     if (o==(TString)"fit")
 | 
|---|
| 886 |     {
 | 
|---|
| 887 |         TVirtualPad *pad = gPad;
 | 
|---|
| 888 | 
 | 
|---|
| 889 |         for (int x=0; x<2; x++)
 | 
|---|
| 890 |             for (int y=0; y<3; y++)
 | 
|---|
| 891 |             {
 | 
|---|
| 892 |                 TVirtualPad *p=gPad->GetPad(x+1)->GetPad(y+1);
 | 
|---|
| 893 |                 if (!(st = dynamic_cast<TPaveStats*>(p->GetPrimitive("stats"))))
 | 
|---|
| 894 |                     continue;
 | 
|---|
| 895 | 
 | 
|---|
| 896 |                 if (st->GetOptStat()==11)
 | 
|---|
| 897 |                     continue;
 | 
|---|
| 898 | 
 | 
|---|
| 899 |                 const Double_t y1 = st->GetY1NDC();
 | 
|---|
| 900 |                 const Double_t y2 = st->GetY2NDC();
 | 
|---|
| 901 |                 const Double_t x1 = st->GetX1NDC();
 | 
|---|
| 902 |                 const Double_t x2 = st->GetX2NDC();
 | 
|---|
| 903 | 
 | 
|---|
| 904 |                 st->SetY1NDC((y2-y1)/3+y1);
 | 
|---|
| 905 |                 st->SetX1NDC((x2-x1)/3+x1);
 | 
|---|
| 906 |                 st->SetOptStat(11);
 | 
|---|
| 907 |             }
 | 
|---|
| 908 | 
 | 
|---|
| 909 |         pad->GetPad(1)->cd(1);
 | 
|---|
| 910 |         if ((h = (TH1D*)gPad->FindObject("ProjDeltaT"/*fNameProjDeltaT*/)))
 | 
|---|
| 911 |         {
 | 
|---|
| 912 |             h = fH2DeltaT.ProjectionX("ProjDeltaT"/*fNameProjDeltaT*/, -1, -1, "E");
 | 
|---|
| 913 |             if (h->GetEntries()>0)
 | 
|---|
| 914 |                 gPad->SetLogy();
 | 
|---|
| 915 |         }
 | 
|---|
| 916 | 
 | 
|---|
| 917 |         pad->GetPad(2)->cd(1);
 | 
|---|
| 918 |         if ((h = (TH1D*)gPad->FindObject("ProjTheta"/*fNameProjTheta*/)))
 | 
|---|
| 919 |             fH2DeltaT.ProjectionY("ProjTheta"/*fNameProjTheta*/, -1, -1, "E");
 | 
|---|
| 920 | 
 | 
|---|
| 921 |         if (!fIsFinalized)
 | 
|---|
| 922 |             FitThetaBins();
 | 
|---|
| 923 |         return;
 | 
|---|
| 924 |     }
 | 
|---|
| 925 |     if (o==(TString)"paint")
 | 
|---|
| 926 |     {
 | 
|---|
| 927 |         if ((h = (TH1D*)gPad->FindObject("ProjDeltaT"/*fNameProjDeltaT*/)))
 | 
|---|
| 928 |         {
 | 
|---|
| 929 |             Double_t res[7];
 | 
|---|
| 930 |             if (FitH(h, res, kTRUE))
 | 
|---|
| 931 |                 PaintText(res);
 | 
|---|
| 932 |         }
 | 
|---|
| 933 |         return;
 | 
|---|
| 934 |     }
 | 
|---|
| 935 | 
 | 
|---|
| 936 |     if (o==(TString)"timendf")
 | 
|---|
| 937 |     {
 | 
|---|
| 938 |         //    UpdateRightAxis(fHTimeNDF);
 | 
|---|
| 939 |         // FIXME: first bin?
 | 
|---|
| 940 |         PaintProb(fHTimeProb);
 | 
|---|
| 941 |     }
 | 
|---|
| 942 | 
 | 
|---|
| 943 |     if (o==(TString)"thetandf")
 | 
|---|
| 944 |     {
 | 
|---|
| 945 |         UpdateRightAxis(fHThetaNDF);
 | 
|---|
| 946 |         // FIXME: first bin?
 | 
|---|
| 947 |         PaintProb(fHThetaProb);
 | 
|---|
| 948 |     }
 | 
|---|
| 949 | 
 | 
|---|
| 950 |     h=0;
 | 
|---|
| 951 | 
 | 
|---|
| 952 |     Double_t range=-1;
 | 
|---|
| 953 |     if (o==(TString)"theta")
 | 
|---|
| 954 |     {
 | 
|---|
| 955 |         h = &fHThetaEffOn;
 | 
|---|
| 956 |         UpdateRightAxis(fHThetaLambda);
 | 
|---|
| 957 |     }
 | 
|---|
| 958 |     if (o==(TString)"time")
 | 
|---|
| 959 |     {
 | 
|---|
| 960 |         h = &fHTimeEffOn;
 | 
|---|
| 961 |         UpdateRightAxis(fHTimeLambda);
 | 
|---|
| 962 |         range = h->GetXaxis()->GetXmax() - h->GetXaxis()->GetXmin();
 | 
|---|
| 963 |     }
 | 
|---|
| 964 | 
 | 
|---|
| 965 |     if (!h)
 | 
|---|
| 966 |         return;
 | 
|---|
| 967 | 
 | 
|---|
| 968 |     Double_t error = 0;
 | 
|---|
| 969 |     for (int i=0; i<h->GetXaxis()->GetNbins(); i++)
 | 
|---|
| 970 |         error += h->GetBinError(i);
 | 
|---|
| 971 | 
 | 
|---|
| 972 |     PaintText(h->Integral(), error, range);
 | 
|---|
| 973 | }
 | 
|---|
| 974 | 
 | 
|---|
| 975 | void MHEffectiveOnTime::DrawRightAxis(const char *title)
 | 
|---|
| 976 | {
 | 
|---|
| 977 |     TGaxis *axis = new TGaxis(gPad->GetUxmax(), gPad->GetUymin(),
 | 
|---|
| 978 |                               gPad->GetUxmax(), gPad->GetUymax(),
 | 
|---|
| 979 |                               0, 1, 510, "+L");
 | 
|---|
| 980 |     axis->SetName("RightAxis");
 | 
|---|
| 981 |     axis->SetTitle(title);
 | 
|---|
| 982 |     axis->SetTitleOffset(0.9);
 | 
|---|
| 983 |     axis->SetTextColor(kGreen);
 | 
|---|
| 984 |     axis->CenterTitle();
 | 
|---|
| 985 |     axis->SetBit(kCanDelete);
 | 
|---|
| 986 |     axis->Draw();
 | 
|---|
| 987 | }
 | 
|---|
| 988 | 
 | 
|---|
| 989 | // --------------------------------------------------------------------------
 | 
|---|
| 990 | //
 | 
|---|
| 991 | // Draw the histogram
 | 
|---|
| 992 | //
 | 
|---|
| 993 | void MHEffectiveOnTime::Draw(Option_t *opt)
 | 
|---|
| 994 | {
 | 
|---|
| 995 |     TVirtualPad *pad = gPad ? gPad : MakeDefCanvas(this);
 | 
|---|
| 996 |     pad->SetBorderMode(0);
 | 
|---|
| 997 | 
 | 
|---|
| 998 |     AppendPad("fit");
 | 
|---|
| 999 | 
 | 
|---|
| 1000 |     pad->Divide(2, 1, 1e-10, 1e-10);
 | 
|---|
| 1001 | 
 | 
|---|
| 1002 |     TH1 *h;
 | 
|---|
| 1003 | 
 | 
|---|
| 1004 |     pad->cd(1);
 | 
|---|
| 1005 |     gPad->SetBorderMode(0);
 | 
|---|
| 1006 |     gPad->Divide(1, 3, 1e-10, 1e-10);
 | 
|---|
| 1007 |     pad->GetPad(1)->cd(1);
 | 
|---|
| 1008 |     gPad->SetBorderMode(0);
 | 
|---|
| 1009 |     h = fH2DeltaT.ProjectionX("ProjDeltaT"/*fNameProjDeltaT*/, -1, -1, "E");
 | 
|---|
| 1010 |     h->SetTitle("Distribution of \\Delta t [s]");
 | 
|---|
| 1011 |     h->SetXTitle("\\Delta t [s]");
 | 
|---|
| 1012 |     h->SetYTitle("Counts");
 | 
|---|
| 1013 |     h->SetDirectory(NULL);
 | 
|---|
| 1014 |     h->SetMarkerStyle(kFullDotMedium);
 | 
|---|
| 1015 |     h->SetBit(kCanDelete);
 | 
|---|
| 1016 |     h->Draw();
 | 
|---|
| 1017 |     AppendPad("paint");
 | 
|---|
| 1018 | 
 | 
|---|
| 1019 |     pad->GetPad(1)->cd(2);
 | 
|---|
| 1020 |     gPad->SetBorderMode(0);
 | 
|---|
| 1021 |     fHTimeProb.Draw();
 | 
|---|
| 1022 |     AppendPad("timendf");
 | 
|---|
| 1023 |     //fHTimeNDF.Draw("same");
 | 
|---|
| 1024 |     //DrawRightAxis("NDF");
 | 
|---|
| 1025 | 
 | 
|---|
| 1026 |     pad->GetPad(1)->cd(3);
 | 
|---|
| 1027 |     gPad->SetBorderMode(0);
 | 
|---|
| 1028 |     fHTimeEffOn.Draw();
 | 
|---|
| 1029 |     AppendPad("time");
 | 
|---|
| 1030 |     fHTimeLambda.Draw("same");
 | 
|---|
| 1031 |     DrawRightAxis("\\lambda [s^{-1}]");
 | 
|---|
| 1032 | 
 | 
|---|
| 1033 |     pad->cd(2);
 | 
|---|
| 1034 |     gPad->SetBorderMode(0);
 | 
|---|
| 1035 |     gPad->Divide(1, 3, 1e-10, 1e-10);
 | 
|---|
| 1036 | 
 | 
|---|
| 1037 |     pad->GetPad(2)->cd(1);
 | 
|---|
| 1038 |     gPad->SetBorderMode(0);
 | 
|---|
| 1039 |     h = fH2DeltaT.ProjectionY("ProjTheta"/*fNameProjTheta*/, -1, -1, "E");
 | 
|---|
| 1040 |     h->SetTitle("Distribution of  \\Theta [\\circ]");
 | 
|---|
| 1041 |     h->SetXTitle("\\Theta [\\circ]");
 | 
|---|
| 1042 |     h->SetYTitle("Counts");
 | 
|---|
| 1043 |     h->SetDirectory(NULL);
 | 
|---|
| 1044 |     h->SetMarkerStyle(kFullDotMedium);
 | 
|---|
| 1045 |     h->SetBit(kCanDelete);
 | 
|---|
| 1046 |     h->GetYaxis()->SetTitleOffset(1.1);
 | 
|---|
| 1047 |     h->Draw();
 | 
|---|
| 1048 | 
 | 
|---|
| 1049 |     pad->GetPad(2)->cd(2);
 | 
|---|
| 1050 |     gPad->SetBorderMode(0);
 | 
|---|
| 1051 |     fHThetaProb.Draw();
 | 
|---|
| 1052 |     AppendPad("thetandf");
 | 
|---|
| 1053 |     fHThetaNDF.Draw("same");
 | 
|---|
| 1054 |     DrawRightAxis("NDF");
 | 
|---|
| 1055 | 
 | 
|---|
| 1056 |     pad->GetPad(2)->cd(3);
 | 
|---|
| 1057 |     gPad->SetBorderMode(0);
 | 
|---|
| 1058 |     fHThetaEffOn.Draw();
 | 
|---|
| 1059 |     AppendPad("theta");
 | 
|---|
| 1060 |     fHThetaLambda.Draw("same");
 | 
|---|
| 1061 |     DrawRightAxis("\\lambda [s^{-1}]");
 | 
|---|
| 1062 | }
 | 
|---|
| 1063 | 
 | 
|---|
| 1064 | // --------------------------------------------------------------------------
 | 
|---|
| 1065 | //
 | 
|---|
| 1066 | // The following resources are available:
 | 
|---|
| 1067 | //
 | 
|---|
| 1068 | //    MHEffectiveOnTime.FistBin:   3
 | 
|---|
| 1069 | //    MHEffectiveOnTime.NumEvents: 12000
 | 
|---|
| 1070 | //
 | 
|---|
| 1071 | Int_t MHEffectiveOnTime::ReadEnv(const TEnv &env, TString prefix, Bool_t print)
 | 
|---|
| 1072 | {
 | 
|---|
| 1073 |     Bool_t rc = kFALSE;
 | 
|---|
| 1074 |     if (IsEnvDefined(env, prefix, "FirstBin", print))
 | 
|---|
| 1075 |     {
 | 
|---|
| 1076 |         rc = kTRUE;
 | 
|---|
| 1077 |         SetFirstBin(GetEnvValue(env, prefix, "FirstBin", (Int_t)fFirstBin));
 | 
|---|
| 1078 |     }
 | 
|---|
| 1079 |     if (IsEnvDefined(env, prefix, "NumEvents", print))
 | 
|---|
| 1080 |     {
 | 
|---|
| 1081 |         rc = kTRUE;
 | 
|---|
| 1082 |         SetNumEvents(GetEnvValue(env, prefix, "NumEvents", (Int_t)fNumEvents));
 | 
|---|
| 1083 |     }
 | 
|---|
| 1084 |     return rc;
 | 
|---|
| 1085 | }
 | 
|---|