| 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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