| 1 | #!/usr/bin/python
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| 2 | #
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| 3 | # Werner Lustermann
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| 4 | # ETH Zurich
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| 5 | #
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| 6 | from ROOT import TH1F
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| 7 | import pyfact
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| 8 |
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| 9 | from hist import histogramList
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| 10 |
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| 11 | class bslHistograms( histogramList ):
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| 12 |
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| 13 | def book( self ):
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| 14 |
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| 15 | # print 'bslHistograms::book'
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| 16 |
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| 17 | self.h1d( "histo_mean","Value of maximal probability",
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| 18 | 400, -99.5, 100.5, 'max value (mV)', 'Entries / 0.5 mV')
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| 19 |
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| 20 | self.h1d("hplt_mean","Value of maximal probability",
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| 21 | 1440, -0.5, 1439.5, 'max value in mV', 'Entries / 0.5 mV')
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| 22 |
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| 23 | self.h1d("histo_rms","RMS in mV",
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| 24 | 2000, -99.5, 100.5, 'RMS (mV)', 'Entries / 0.5 mV' )
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| 25 |
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| 26 | self.h1d( 'hplt_rms', 'Value of maximal probability',
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| 27 | 1440, -0.5, 1439.5, 'pixel', 'RMS in mV' )
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| 28 |
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| 29 | def H1d( name, title, Nbin, first, last, xtitle, ytitle ):
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| 30 |
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| 31 | h = TH1F( name, title, Nbin, first, last );
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| 32 | h.GetXaxis().SetTitle( xtitle );
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| 33 | h.GetYaxis().SetTitle( ytitle );
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| 34 |
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| 35 | return h
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| 36 |
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| 37 |
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| 38 | def BookBslSummaryHistos( list ):
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| 39 |
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| 40 | list.add( 'hbsl_mean', H1d( "histo_mean","Value of maximal probability",
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| 41 | 400, -99.5, 100.5,
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| 42 | 'max value (mV)', 'Entries / 0.5 mV') )
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| 43 |
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| 44 | h = H1d("hplt_mean","Value of maximal probability",
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| 45 | 1440, -0.5, 1439.5, 'max value in mV', 'Entries / 0.5 mV')
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| 46 | list.add( 'hplt_mean', h )
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| 47 |
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| 48 | h = H1d("histo_rms","RMS in mV",2000,-99.5,100.5, 'RMS (mV)', 'Entries / 0.5 mV' )
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| 49 | list.add( 'hbsl_rms', h )
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| 50 |
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| 51 | list.add( 'hplt_rms',
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| 52 | H1d( 'hplt_rms', 'Value of maximal probability',
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| 53 | 1440,-0.5,1439.5, 'pixel', 'RMS in mV' ) )
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| 54 |
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| 55 | class tcalHistograms( histogramList ):
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| 56 |
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| 57 | def book( self ):
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| 58 |
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| 59 | self.h1d("diff_dev", "Differential Deviation", 1024, 0, 1024,
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| 60 | "Bin in DRS4 pipeline", "Deviation per bin in ns")
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| 61 |
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| 62 | self.h1d("int_dev", "Integral Deviation", 1024, 0, 1024,
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| 63 | "Bin in DRS4 pipeline", "Total Deviation in ns")
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| 64 |
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| 65 | self.h1d("start", "distribution of startcells", 1024, 0, 1024,
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| 66 | "Bin in DRS4 pipeline", "counts")
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| 67 |
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| 68 | self.h1d("numxing", "number of crossings", 200, 0, 200,
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| 69 | "number of crossings", "counts")
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| 70 |
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| 71 | self.h1d("lomeanxing", "Distribution of logic Meancrossing", 1024, 0, 1024,
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| 72 | "Cell of Meancrossing", "counts")
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| 73 |
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| 74 | self.h1d("meanxing", "Distribution of physical Meancrossing", 1024, 0, 1024,
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| 75 | "Cell of Meancrossing", "counts")
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| 76 |
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| 77 | self.h1d("corr", "Distribution of positive Corrections", 1024, 0, 1024,
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| 78 | "Bin in DRS4 pipeline", "counts")
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| 79 |
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| 80 | self.h1d("loleftout", "Distribution of left out Crossings", 1024, 0, 1024,
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| 81 | "Bin in DRS4 pipeline", "counts")
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| 82 |
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| 83 | self.h1d("leftout", "Distribution of left out Crossings", 1024, 0, 1024,
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| 84 | "Bin in DRS4 pipeline", "counts")
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| 85 |
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| 86 | self.h1d("period", "Distribution of Period lenght", 10, 0, 10,
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| 87 | "number of cells within Period", "counts")
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| 88 |
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| 89 | self.h1d("freq", "calculated Frequency of the Testwave", 100, 200, 300,
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| 90 | "Frequenz", "counts")
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| 91 |
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| 92 |
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| 93 | class tcalsimHistograms( histogramList ):
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| 94 |
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| 95 | def book( self ):
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| 96 |
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| 97 | self.h1d("diff_dev", "Differential Deviation", 1024, 0., 1024.,
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| 98 | "Bin in DRS4 pipeline", "Deviation per bin in ns")
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| 99 |
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| 100 | self.h1d("int_dev", "Integral Deviation", 1024, 0., 1024.,
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| 101 | "Bin in DRS4 pipeline", "Total Deviation in ns")
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| 102 |
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| 103 | self.h1d("start", "distribution of startcells", 1024, 0., 1024.,
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| 104 | "Bin in DRS4 pipeline", "counts")
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| 105 |
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| 106 | self.h1d("numxing", "number of crossings", 200, 0, 200,
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| 107 | "number of crossings", "counts")
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| 108 |
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| 109 | self.h1d("lomeanxing", "Distribution of logic Meancrossing", 1024, 0, 1024,
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| 110 | "Cell of Meancrossing", "counts")
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| 111 |
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| 112 | self.h1d("meanxing", "Distribution of physical Meancrossing", 1024, 0, 1024,
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| 113 | "Cell of Meancrossing", "counts")
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| 114 |
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| 115 | self.h1d("loleftout", "Distribution of left out Crossings", 1024, 0, 1024,
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| 116 | "Bin in DRS4 pipeline", "counts")
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| 117 |
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| 118 | self.h1d("leftout", "Distribution of left our Crossings", 1024, 0, 1024,
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| 119 | "Bin in DRS4 pipeline", "counts")
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| 120 |
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| 121 | self.h1d("period", "Distribution of Period lenght", 1000, 2.5, 5.5,
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| 122 | "leght of Period", "counts")
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| 123 |
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| 124 | self.h1d("data", "simulated Data", 1024, 0, 1024,
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| 125 | "Bin in DRS4 pipeline", "Data")
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| 126 |
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| 127 | self.h1d("freq", "calculated Frequency of the Testwave", 100, 200, 300,
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| 128 | "Frequenz", "counts")
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| 129 |
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| 130 | self.h1d("meanfreq", "mean calculated Frequency of the Testwave", 100, 200, 300,
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| 131 | "Frequenz", "counts")
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| 132 |
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| 133 | self.h1d("conv", "Convergence of the Deviation", 200, 0, 200,
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| 134 | "Event", "Deviation from the true value")
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| 135 |
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| 136 | self.h1d("perioddev", "Mean deviation from nominal Period for each Iteration", 1000, 0, 1000,
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| 137 | "number of iterations", "mean deviation")
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| 138 |
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| 139 | self.h1d("perioddevproj", "Distribution of mean nominal Periods for each Iteration", 1000, -0.2, 0.2,
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| 140 | "Deviation of Period", "Counts")
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| 141 |
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| 142 | class tcalanaHistograms( histogramList ):
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| 143 |
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| 144 | def book( self ):
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| 145 |
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| 146 | self.h1d("int_dev", "Integral Deviation", 1024, 0, 1024,
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| 147 | "Bin in DRS4 pipeline", "counts")
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| 148 |
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| 149 | self.h1d("diff_dev", "Differential Deviation", 1024, 0, 1024,
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| 150 | "Bin in DRS4 pipeline", "counts")
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| 151 |
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| 152 | self.h1d("diff_dev_true", "True Differential Deviation", 1024, 0, 1024,
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| 153 | "Bin in DRS4 pipeline", "counts")
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| 154 |
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| 155 | self.h1d("int_dev_true", "True Integral Deviation", 1024, 0, 1024,
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| 156 | "Bin in DRS4 pipeline", "counts")
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| 157 |
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| 158 | self.h1d("data", "simulierte Daten", 1024, 0, 1024,
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| 159 | "Bin in DRS4 pipeline", "Data")
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| 160 |
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| 161 | self.h1d("start", "distribution of startcells", 1024, 0., 1024.,
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| 162 | "Bin in DRS4 pipeline", "counts")
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| 163 |
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| 164 |
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| 165 | class periodHistograms( histogramList ):
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| 166 |
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| 167 | def book ( self ):
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| 168 |
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| 169 | self.h1d("periods", "Lenght of Periods", 2000, 0, 10,
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| 170 | "Period in ns", "counts")
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| 171 |
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| 172 | self.h1d("diff", "PeriodOliver - PeriodRemo", 100, -0.3, 0.3,
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| 173 | "difference in ns", "counts")
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| 174 |
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| 175 | class amplitudesHistograms( histogramList ):
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| 176 |
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| 177 | def book ( self ):
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| 178 |
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| 179 | self.h1d("std", "Standard deviation", 20, 0, 20,
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| 180 | "Standardabweichung in mV", "count")
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| 181 |
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| 182 |
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| 183 | class jitterHistograms( histogramList ):
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| 184 |
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| 185 | def book ( self ):
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| 186 |
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| 187 | self.h1d("diff", "Jitter Calculation", 500, 200, 230,
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| 188 | "difference between pulses in ns", "bin content")
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| 189 |
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| 190 |
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| 191 | self.h1d("data0", "Data", 1024, 0, 1024,
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| 192 | "Bin in DRS4 pipeline", "Data")
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| 193 |
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| 194 | self.h1d("data8", "Data", 1024, 0, 1024,
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| 195 | "Bin in DRS4 pipeline", "Data")
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| 196 |
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| 197 | class ftcalappHistograms( histogramList ):
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| 198 |
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| 199 | def book ( self ):
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| 200 |
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| 201 | self.h1d("avperiods", "distribution of periods for average data", 1000, 2, 6,
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| 202 | "period in ns", "bin content")
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| 203 |
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| 204 | self.h1d("avperiods0", "distribution of periods at beginning for average data", 400, 2, 6,
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| 205 | "period in ns", "bin content")
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| 206 |
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| 207 | self.h1d("periods", "distribution of periods", 400, 2, 6,
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| 208 | "period in ns", "bin content")
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| 209 |
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| 210 | self.h1d("periods0", "distribution of periods at beginning", 400, 2, 6,
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| 211 | "period in ns", "bin content")
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| 212 |
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| 213 | self.h1d("perioddev", "Mean deviation from nominal Period for each Iteration", 1000, 0, 1000,
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| 214 | "number of iterations", "mean deviation")
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| 215 |
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| 216 | self.h1d("perioddevproj", "Distribution of mean nominal Periods for each Iteration", 1000, -0.2, 0.2,
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| 217 | "Deviation of Period", "Counts")
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| 218 |
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| 219 | self.h1d("int_dev", "integral deviation", 1024, 0., 1024.,
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| 220 | "bin in DRS4 pipeline", "total deviation in ns")
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| 221 |
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| 222 |
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| 223 |
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| 224 |
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| 225 |
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