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 analyzing 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 | ! Author(s): Thomas Bretz <mailto:tbretz@astro.uni-wuerzbrug.de>
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18 | ! Author(s): Markus Gaug 09/2004 <mailto:markus@ifae.es>
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19 | !
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20 | ! Copyright: MAGIC Software Development, 2002-2006
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21 | !
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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 | // MExtralgoSpline
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28 | //
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29 | // Fast Spline extractor using a cubic spline algorithm, adapted from
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30 | // Numerical Recipes in C++, 2nd edition, pp. 116-119.
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31 | //
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32 | // The coefficients "ya" are here denoted as "fVal" corresponding to
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33 | // the FADC value subtracted by the clock-noise corrected pedestal.
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34 | //
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35 | // The coefficients "y2a" get immediately divided 6. and are called here
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36 | // fDer2 although they are now not exactly the second derivative
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37 | // coefficients any more.
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38 | //
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39 | // The calculation of the cubic-spline interpolated value "y" on a point
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40 | // "x" along the FADC-slices axis becomes: EvalAt(x)
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41 | //
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42 | // The coefficients fDer2 are calculated with the simplified
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43 | // algorithm in InitDerivatives.
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44 | //
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45 | // This algorithm takes advantage of the fact that the x-values are all
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46 | // separated by exactly 1 which simplifies the Numerical Recipes algorithm.
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47 | // (Note that the variables fDer are not real first derivative coefficients.)
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48 | //
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49 | //////////////////////////////////////////////////////////////////////////////
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50 | #include "MExtralgoSpline.h"
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51 |
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52 | #include "../mbase/MMath.h"
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53 |
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54 | using namespace std;
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55 |
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56 | // --------------------------------------------------------------------------
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57 | //
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58 | // Calculate the first and second derivative for the splie.
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59 | //
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60 | // The coefficients are calculated such that
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61 | // 1) fVal[i] = Eval(i, 0)
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62 | // 2) Eval(i-1, 1)==Eval(i, 0)
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63 | //
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64 | // In other words: The values with the index i describe the spline
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65 | // between fVal[i] and fVal[i+1]
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66 | //
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67 | void MExtralgoSpline::InitDerivatives() const
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68 | {
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69 | fDer1[0] = 0.;
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70 | fDer2[0] = 0.;
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71 |
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72 | for (Int_t i=1; i<fNum-1; i++)
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73 | {
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74 | const Float_t pp = fDer2[i-1] + 4.;
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75 |
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76 | fDer2[i] = -1.0/pp;
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77 |
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78 | const Float_t d1 = fVal[i+1] - 2*fVal[i] + fVal[i-1];
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79 | fDer1[i] = (6.0*d1-fDer1[i-1])/pp;
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80 | }
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81 |
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82 | fDer2[fNum-1] = 0.;
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83 |
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84 | for (Int_t k=fNum-2; k>=0; k--)
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85 | fDer2[k] = fDer2[k]*fDer2[k+1] + fDer1[k];
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86 |
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87 | for (Int_t k=fNum-2; k>=0; k--)
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88 | fDer2[k] /= 6.;
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89 | }
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90 |
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91 | // --------------------------------------------------------------------------
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92 | //
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93 | // Returns the highest x value in [min;max[ at which the spline in
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94 | // the bin i is equal to y
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95 | //
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96 | // min and max are defined to be [0;1]
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97 | //
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98 | // The default for min is 0, the default for max is 1
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99 | // The defaule for y is 0
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100 | //
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101 | Double_t MExtralgoSpline::FindY(Int_t i, Double_t y, Double_t min, Double_t max) const
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102 | {
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103 | // y = a*x^3 + b*x^2 + c*x + d'
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104 | // 0 = a*x^3 + b*x^2 + c*x + d' - y
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105 |
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106 | // Calculate coefficients
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107 | const Double_t a = fDer2[i+1]-fDer2[i];
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108 | const Double_t b = 3*fDer2[i];
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109 | const Double_t c = fVal[i+1]-fVal[i] -2*fDer2[i]-fDer2[i+1];
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110 | const Double_t d = fVal[i] - y;
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111 |
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112 | Double_t x1, x2, x3;
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113 | const Int_t rc = MMath::SolvePol3(a, b, c, d, x1, x2, x3);
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114 |
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115 | Double_t x = -1;
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116 | if (rc>0 && x1>=min && x1<max && x1>x)
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117 | x = x1;
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118 | if (rc>1 && x2>=min && x2<max && x2>x)
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119 | x = x2;
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120 | if (rc>2 && x3>=min && x3<max && x3>x)
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121 | x = x3;
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122 |
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123 | return x<0 ? -1 : x+i;
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124 | }
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125 |
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126 | // --------------------------------------------------------------------------
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127 | //
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128 | // Search analytically downward for the value y of the spline, starting
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129 | // at x, until x==0. If y is not found -1 is returned.
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130 | //
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131 | Double_t MExtralgoSpline::SearchY(Float_t x, Float_t y) const
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132 | {
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133 | if (x>=fNum-1)
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134 | x = fNum-1.0001;
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135 |
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136 | Int_t i = TMath::FloorNint(x);
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137 | Double_t rc = FindY(i, y, 0, x-i);
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138 | while (--i>=0 && rc<0)
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139 | rc = FindY(i, y);
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140 |
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141 | return rc;
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142 | }
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143 |
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144 | // --------------------------------------------------------------------------
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145 | //
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146 | // Do a range check an then calculate the integral from start-fRiseTime
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147 | // to start+fFallTime. An extrapolation of 0.5 slices is allowed.
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148 | //
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149 | Float_t MExtralgoSpline::CalcIntegral(Float_t pos) const
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150 | {
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151 | /*
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152 | // The number of steps is calculated directly from the integration
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153 | // window. This is the only way to ensure we are not dealing with
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154 | // numerical rounding uncertanties, because we always get the same
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155 | // value under the same conditions -- it might still be different on
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156 | // other machines!
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157 | const Float_t start = pos-fRiseTime;
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158 | const Float_t step = 0.2;
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159 | const Float_t width = fRiseTime+fFallTime;
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160 | const Float_t max = fNum-1 - (width+step);
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161 | const Int_t num = TMath::Nint(width/step);
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162 |
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163 | // The order is important. In some cases (limlo-/limup-check) it can
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164 | // happen that max<0. In this case we start at 0
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165 | if (start > max)
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166 | start = max;
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167 | if (start < 0)
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168 | start = 0;
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169 |
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170 | start += step/2;
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171 |
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172 | Double_t sum = 0.;
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173 | for (Int_t i=0; i<num; i++)
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174 | {
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175 | // Note: if x is close to one integer number (= a FADC sample)
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176 | // we get the same result by using that sample as klo, and the
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177 | // next one as khi, or using the sample as khi and the previous
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178 | // one as klo (the spline is of course continuous). So we do not
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179 | // expect problems from rounding issues in the argument of
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180 | // Floor() above (we have noticed differences in roundings
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181 | // depending on the compilation options).
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182 |
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183 | sum += EvalAt(start + i*step);
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184 |
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185 | // FIXME? Perhaps the integral should be done analitically
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186 | // between every two FADC slices, instead of numerically
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187 | }
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188 | sum *= step; // Transform sum in integral
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189 |
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190 | return sum;
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191 | */
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192 |
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193 | // In the future we will calculate the intgeral analytically.
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194 | // It has been tested that it gives identical results within
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195 | // acceptable differences.
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196 |
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197 | // We allow extrapolation of 1/2 slice.
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198 | const Float_t min = fRiseTime; //-0.5+fRiseTime;
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199 | const Float_t max = fNum-1-fFallTime; //fNum-0.5+fFallTime;
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200 |
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201 | if (pos<min)
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202 | pos = min;
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203 | if (pos>max)
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204 | pos = max;
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205 |
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206 | return EvalInteg(pos-fRiseTime, pos+fFallTime);
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207 | }
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208 |
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209 | Float_t MExtralgoSpline::ExtractNoise(Int_t iter)
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210 | {
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211 | const Float_t nsx = iter * fResolution;
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212 |
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213 | if (fExtractionType == kAmplitude)
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214 | return Eval(1, nsx);
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215 | else
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216 | return CalcIntegral(2. + nsx);
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217 | }
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218 |
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219 | void MExtralgoSpline::Extract(Byte_t sat, Int_t maxbin)
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220 | {
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221 | fSignal = 0;
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222 | fTime = 0;
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223 | fSignalDev = -1;
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224 | fTimeDev = -1;
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225 |
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226 | //
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227 | // Allow no saturated slice and
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228 | // Don't start if the maxpos is too close to the limits.
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229 | //
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230 |
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231 | /*
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232 | const Bool_t limlo = maxbin < TMath::Ceil(fRiseTime);
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233 | const Bool_t limup = maxbin > fNum-TMath::Ceil(fFallTime)-1;
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234 | if (sat || limlo || limup)
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235 | {
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236 | fTimeDev = 1.0;
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237 | if (fExtractionType == kAmplitude)
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238 | {
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239 | fSignal = fVal[maxbin];
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240 | fTime = maxbin;
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241 | fSignalDev = 0; // means: is valid
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242 | return;
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243 | }
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244 |
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245 | fSignal = CalcIntegral(limlo ? 0 : fNum);
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246 | fTime = maxbin - 1;
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247 | fSignalDev = 0; // means: is valid
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248 | return;
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249 | }
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250 | */
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251 |
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252 | fTimeDev = fResolution;
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253 |
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254 | //
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255 | // Now find the maximum
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256 | //
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257 |
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258 |
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259 | /*
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260 | Float_t step = 0.2; // start with step size of 1ns and loop again with the smaller one
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261 |
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262 | Int_t klo = maxbin-1;
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263 |
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264 | Float_t maxpos = maxbin;//! Current position of the maximum of the spline
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265 | Float_t max = fVal[maxbin];//! Current maximum of the spline
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266 |
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267 | //
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268 | // Search for the maximum, starting in interval maxpos-1 in steps of 0.2 till maxpos-0.2.
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269 | // If no maximum is found, go to interval maxpos+1.
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270 | //
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271 | for (Int_t i=0; i<TMath::Nint(TMath::Ceil((1-0.3)/step)); i++)
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272 | {
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273 | const Float_t x = klo + step*(i+1);
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274 | //const Float_t y = Eval(klo, x);
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275 | const Float_t y = Eval(klo, x-klo);
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276 | if (y > max)
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277 | {
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278 | max = y;
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279 | maxpos = x;
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280 | }
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281 | }
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282 |
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283 | //
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284 | // Search for the absolute maximum from maxpos to maxpos+1 in steps of 0.2
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285 | //
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286 | if (maxpos > maxbin - 0.1)
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287 | {
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288 | klo = maxbin;
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289 |
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290 | for (Int_t i=0; i<TMath::Nint(TMath::Ceil((1-0.3)/step)); i++)
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291 | {
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292 | const Float_t x = klo + step*(i+1);
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293 | //const Float_t y = Eval(klo, x);
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294 | const Float_t y = Eval(klo, x-klo);
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295 | if (y > max)
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296 | {
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297 | max = y;
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298 | maxpos = x;
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299 | }
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300 | }
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301 | }
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302 |
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303 | //
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304 | // Now, the time, abmax and khicont and klocont are set correctly within the previous precision.
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305 | // Try a better precision.
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306 | //
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307 | const Float_t up = maxpos+step - 3.0*fResolution;
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308 | const Float_t lo = maxpos-step + 3.0*fResolution;
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309 | const Float_t abmaxpos = maxpos;
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310 |
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311 | step = 2.*fResolution; // step size of 0.1 FADC slices
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312 |
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313 | for (int i=0; i<TMath::Nint(TMath::Ceil((up-abmaxpos)/step)); i++)
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314 | {
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315 | const Float_t x = abmaxpos + (i+1)*step;
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316 | //const Float_t y = Eval(klo, x);
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317 | const Float_t y = Eval(klo, x-klo);
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318 | if (y > max)
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319 | {
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320 | max = y;
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321 | maxpos = x;
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322 | }
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323 | }
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324 |
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325 | //
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326 | // Second, try from time down to time-0.2 in steps of fResolution.
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327 | //
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328 |
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329 | //
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330 | // Test the possibility that the absolute maximum has not been found between
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331 | // maxpos and maxpos+0.05, then we have to look between maxpos-0.05 and maxpos
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332 | // which requires new setting of klocont and khicont
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333 | //
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334 | if (abmaxpos < klo + fResolution)
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335 | klo--;
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336 |
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337 | for (int i=TMath::Nint(TMath::Ceil((abmaxpos-lo)/step))-1; i>=0; i--)
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338 | {
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339 | const Float_t x = abmaxpos - (i+1)*step;
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340 | //const Float_t y = Eval(klo, x);
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341 | const Float_t y = Eval(klo, x-klo);
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342 | if (y > max)
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343 | {
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344 | max = y;
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345 | maxpos = x;
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346 | }
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347 | }
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348 | */
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349 |
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350 | // --- Start NEW ---
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351 |
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352 | // This block extracts values very similar to the old algorithm...
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353 | // for max>10
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354 | /* Most accurate (old identical) version:
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355 |
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356 | Float_t xmax=maxpos, ymax=Eval(maxpos-1, 1);
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357 | Int_t rc = GetMaxPos(maxpos-1, xmax, ymax);
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358 | if (xmax==maxpos)
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359 | {
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360 | GetMaxPos(maxpos, xmax, ymax);
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361 |
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362 | Float_t y = Eval(maxpos, 1);
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363 | if (y>ymax)
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364 | {
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365 | ymax = y;
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366 | xmax = maxpos+1;
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367 | }
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368 | }*/
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369 |
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370 | Float_t maxpos, maxval;
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371 | GetMaxAroundI(maxbin, maxpos, maxval);
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372 |
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373 | // --- End NEW ---
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374 |
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375 | if (fExtractionType == kAmplitude)
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376 | {
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377 | fTime = maxpos;
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378 | fSignal = maxval;
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379 | fSignalDev = 0; // means: is valid
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380 | return;
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381 | }
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382 |
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383 | //
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384 | // Loop from the beginning of the slice upwards to reach the maxhalf:
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385 | // With means of bisection:
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386 | //
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387 | /*
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388 | static const Float_t sqrt2 = TMath::Sqrt(2.);
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389 |
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390 | step = sqrt2*3*0.061;//fRiseTime;
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391 | Float_t x = maxpos-0.86-3*0.061;//fRiseTime*1.25;
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392 |
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393 | // step = sqrt2*0.5;//fRiseTime;
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394 | // Float_t x = maxpos-1.25;//fRiseTime*1.25;
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395 |
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396 | Int_t cnt =0;
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397 | while (cnt++<30)
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398 | {
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399 | const Float_t y=EvalAt(x);
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400 |
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401 | if (TMath::Abs(y-maxval/2)<fResolution)
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402 | break;
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403 |
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404 | step /= sqrt2; // /2
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405 | x += y>maxval/2 ? -step : +step;
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406 | }
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407 | */
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408 |
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409 | // Search downwards for maxval/2
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410 | // By doing also a search upwards we could extract the pulse width
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411 | const Double_t x1 = SearchY(maxpos, maxval/2);
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412 |
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413 | fTime = x1;
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414 | fSignal = CalcIntegral(maxpos);
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415 | fSignalDev = 0; // means: is valid
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416 |
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417 | //if (fSignal>100)
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418 | // cout << "V=" << maxpos-x1 << endl;
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419 |
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420 | //
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421 | // Now integrate the whole thing!
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422 | //
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423 | // fTime = cnt==31 ? -1 : x;
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424 | // fSignal = cnt==31 ? CalcIntegral(x) : CalcIntegral(maxpos);
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425 | // fSignalDev = 0; // means: is valid
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426 | }
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