1 | # Programm zur Bestimmung der Genauigkeit des konvergierten Algorithmus
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2 | #
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3 | # Remo Dietlicher
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4 | #
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5 | #
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6 |
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7 | from optparse import OptionParser
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8 | import pyfact
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9 | from myhisto import *
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10 | from hist import *
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11 | import numpy as np
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12 | import numpy.random as rnd
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13 | from ROOT import *
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14 | from time import time
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15 |
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16 | def periods2(Data, CellTime, h):
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17 |
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18 | NROI = 1024 # length of the DRS pipeline
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19 | fsampling = 2. # sampling frequency
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20 | freq = 250. # testfrequency
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21 | P_nom = 1000./freq # nominal Period due to testfrequency
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22 |
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23 |
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24 | nomCellTime = np.linspace(0., 1024., 1025)/fsampling
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25 |
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26 |
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27 | # FUNCTION TO DETERMINE CROSSINGS
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28 |
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29 | def Crossing(Mean, rCellTime):
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30 | TimeXing = np.zeros(NROI)
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31 | MeanXing = np.zeros(NROI)
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32 | NumXing = 0
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33 |
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34 | for i in range(NROI-1):
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35 | if ((Data[i] > Mean) & (Data[i+1] < Mean)):
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36 | MeanXing[NumXing] = i
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37 |
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38 | FirstCell = rCellTime[i]
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39 | SecondCell = rCellTime[i+1]
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40 |
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41 | TimeXing[NumXing] = FirstCell+(SecondCell-FirstCell)/(1.-Data[i+1]/(Data[i]))*(1.-Mean/(Data[i]))
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42 | NumXing += 1
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43 |
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44 | return MeanXing, TimeXing
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45 |
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46 | def CalculatePeriods(rCellTime, name):
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47 |
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48 | Period = np.zeros(126)
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49 |
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50 | MeanXing, TimeXing = Crossing(np.average(Data), rCellTime)
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51 |
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52 | for i in range(int(126)):
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53 | Period[i] = TimeXing[i+1] - TimeXing[i]
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54 |
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55 | for val in Period:
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56 | h.dict[str(name)].Fill(val)
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57 |
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58 | return
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59 |
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60 | CalculatePeriods(CellTime, "avperiods")
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61 | CalculatePeriods(nomCellTime, "avperiods0")
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62 |
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63 | return
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64 |
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65 |
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66 |
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67 |
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