| 1 | /* ======================================================================== *\
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| 2 | !
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| 3 | ! *
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| 4 | ! * This file is part of MARS, the MAGIC Analysis and Reconstruction
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| 5 | ! * Software. It is distributed to you in the hope that it can be a useful
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| 6 | ! * and timesaving tool in analysing Data of imaging Cerenkov telescopes.
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| 7 | ! * It is distributed WITHOUT ANY WARRANTY.
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| 8 | ! *
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| 9 | ! * Permission to use, copy, modify and distribute this software and its
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| 10 | ! * documentation for any purpose is hereby granted without fee,
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| 11 | ! * provided that the above copyright notice appear in all copies and
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| 12 | ! * that both that copyright notice and this permission notice appear
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| 13 | ! * in supporting documentation. It is provided "as is" without express
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| 14 | ! * or implied warranty.
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| 15 | ! *
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| 16 | !
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| 17 | !
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| 18 | ! Author(s): Hendrik Bartko, 09/2004 <mailto:hbartko@mppmu.mpg.de>
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| 19 | ! Author(s): Thomas Bretz, 08/2006 <mailto:tbretz@astro.uni-wuerzburg.de>
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| 20 | !
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| 21 | ! Copyright: MAGIC Software Development, 2000-2008
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| 22 | !
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| 23 | !
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| 24 | \* ======================================================================== */
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| 25 |
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| 26 | //////////////////////////////////////////////////////////////////////////////
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| 27 | //
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| 28 | // MExtralgoDigitalFilter
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| 29 | //
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| 30 | //////////////////////////////////////////////////////////////////////////////
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| 31 | #include "MExtralgoDigitalFilter.h"
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| 32 |
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| 33 | #include <TMath.h>
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| 34 | #include <TRandom.h>
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| 35 |
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| 36 | using namespace std;
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| 37 |
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| 38 | Float_t MExtralgoDigitalFilter::ExtractNoise() const
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| 39 | {
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| 40 | const Int_t pos = gRandom->Integer(fNum-fWindowSize+1);
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| 41 | const Int_t frac = gRandom->Integer(fWeightsPerBin);
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| 42 |
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| 43 | return Eval(fWeightsAmp, pos, frac-fWeightsPerBin/2);
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| 44 | }
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| 45 |
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| 46 | // -----------------------------------------------------------------------------
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| 47 | //
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| 48 | // Calculates the chi2 of the fit, once the weights have been iterated.
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| 49 | // Argument: time, obtained after a call to EvalDigitalFilterHiGain
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| 50 | //
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| 51 | Float_t MExtralgoDigitalFilter::GetChisq(const Int_t maxp, const Int_t frac, const Float_t sum) const
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| 52 | {
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| 53 | /*
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| 54 | TMatrix g (windowh,1);
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| 55 | TMatrix gt(windowh,1);
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| 56 | TMatrix y (windowh,1);
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| 57 |
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| 58 | const Float_t etau = fFineAdjustHi*sumhi;
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| 59 | const Float_t t_fine = TMath::Abs(fFineAdjustHi)< 1./fBinningResolutionHiGain ? -fFineAdjustHi : 0.;
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| 60 |
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| 61 | // if (t_fine==0.)
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| 62 | // return -1.;
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| 63 |
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| 64 | if (fDebug)
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| 65 | gLog << all << " fMaxPHi: " << fMaxPHi << " fIterPHi " << fIterPHi << " t_fine: " << t_fine << endl;
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| 66 |
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| 67 | //
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| 68 | // Slide with a window of size windowh over the sample
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| 69 | // and calculate the arrays by interpolating the pulse shape using the
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| 70 | // fine-tuned time information.
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| 71 | //
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| 72 | for (Int_t sample=0; sample < windowh; sample++)
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| 73 | {
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| 74 | const Int_t idx = fArrBinningResHalfHiGain[sample] + fIterPHi;
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| 75 | const Int_t ids = fMaxPHi + sample;
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| 76 |
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| 77 | y [sample][0] = fHiGainSignalDF[ids];
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| 78 | g [sample][0] = t_fine >= 0
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| 79 | ? (fPulseShapeHiGain[idx] + t_fine*(fPulseShapeHiGain[idx+1] -fPulseShapeHiGain[idx]) )*sumhi
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| 80 | : (fPulseShapeHiGain[idx] + t_fine*(fPulseShapeHiGain[idx] -fPulseShapeHiGain[idx-1]))*sumhi;
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| 81 | gt[sample][0] = t_fine >= 0
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| 82 | ? (fPulseShapeDotHiGain[idx] + t_fine*(fPulseShapeDotHiGain[idx+1]-fPulseShapeDotHiGain[idx]) )*etau
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| 83 | : (fPulseShapeDotHiGain[idx] + t_fine*(fPulseShapeDotHiGain[idx] -fPulseShapeDotHiGain[idx-1]) )*etau;
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| 84 | }
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| 85 |
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| 86 | TMatrix second = y - g - gt;
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| 87 | TMatrix first(TMatrix::kTransposed,second);
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| 88 | TMatrix chisq = first * ((*fBHiInv)*second);
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| 89 |
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| 90 | return chisq[0][0]/(windowh-2);
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| 91 | */
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| 92 | /*
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| 93 |
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| 94 | TMatrix S(fWindowSize, 1); // Signal (start==start of window)
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| 95 | for (int i=0; i<fWindowSize; i++)
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| 96 | S[i][0] = fVal[i+maxp];
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| 97 |
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| 98 | TMatrix g(fWindowSize, 1);
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| 99 | //TMatrix gT(fWindowSize, 1);
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| 100 |
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| 101 | for (int i=0; i<fWindowSize; i++)
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| 102 | {
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| 103 | Int_t idx = fWeightsPerBin*i + frac;
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| 104 |
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| 105 | // FIXME: Maybe we could do an interpolation on time-fineadj?
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| 106 | //Float_t slope = fPulseShapeHiGain[idx+1] -fPulseShapeHiGain[idx];
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| 107 | //Float_t slopet = fPulseShapeDotHiGain[idx+1]-fPulseShapeDotHiGain[idx];
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| 108 |
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| 109 | g[i][0] = fPulseShapeHiGain[idx] *sumhi;
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| 110 | //gT[i][0] = fPulseShapeHiGainDot[idx]*tau;
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| 111 | }
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| 112 |
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| 113 | TMatrix Ainv; // Autocorrelation Matrix (inverted)
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| 114 |
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| 115 | TMatrix m = S - g;// - gT;
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| 116 | TMatrix mT(TMatrix::kTransposed, m);
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| 117 |
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| 118 | TMatrix chisq = mT * (Ainv*m);
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| 119 |
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| 120 | return chisq[0][0]/(fWindowSize-2);
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| 121 | */
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| 122 |
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| 123 | Double_t sumc = 0;
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| 124 |
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| 125 | TMatrix d(fWindowSize, 1); // Signal (start==start of window)
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| 126 | for (int i=0; i<fWindowSize; i++)
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| 127 | {
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| 128 | d[i][0] = fVal[i+maxp]/sum - fPulseShape[fWeightsPerBin*i + frac];
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| 129 | sumc += d[i][0]*d[i][0];
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| 130 | }
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| 131 |
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| 132 | /*
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| 133 | TMatrix Ainv; // Autocorrelation Matrix (inverted)
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| 134 |
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| 135 | TMatrix dT(TMatrix::kTransposed, d);
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| 136 |
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| 137 | TMatrix chisq = dT * (*fAinv*d);
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| 138 | */
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| 139 | return sumc;//chisq[0][0]/(fWindowSize-2);
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| 140 | }
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| 141 |
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| 142 | Int_t MExtralgoDigitalFilter::AlignExtractionWindow(Int_t &maxp, Int_t &frac, const Double_t ampsum)
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| 143 | {
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| 144 | // Align extraction window to signal position
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| 145 |
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| 146 | const Double_t timesum = Eval(fWeightsTime, maxp, frac);
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| 147 |
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| 148 | // Because fWeightsPerBin/2 doesn't correspond to the center
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| 149 | // of a bin the time-values extracted are slightly positive.
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| 150 | // They are roughly between -0.45 and 0.55
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| 151 | const Double_t binoffset = TMath::Even(fWeightsPerBin) ? 0.5 : 0;
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| 152 |
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| 153 | // This is the time offset from the extraction position
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| 154 | Double_t tmoffset = (frac+binoffset)/fWeightsPerBin + timesum/ampsum;
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| 155 |
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| 156 | // Convert the residual fraction of one slice into an
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| 157 | // offset position in the extraction weights
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| 158 | const Int_t integ = TMath::FloorNint(tmoffset+0.5);
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| 159 |
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| 160 | /*
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| 161 | if (integ>0)
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| 162 | tmoffset=0.49-0.05;
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| 163 | if (integ<0)
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| 164 | tmoffset=-0.49-0.05;
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| 165 | integ=0;
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| 166 | */
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| 167 |
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| 168 | // move the extractor by an offset number of slices
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| 169 | // determined by the extracted time
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| 170 | maxp -= integ;
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| 171 |
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| 172 | frac = TMath::FloorNint((tmoffset-integ)*fWeightsPerBin);
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| 173 |
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| 174 | // Align maxp into available range (TO BE CHECKED)
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| 175 | AlignIntoLimits(maxp, frac);
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| 176 |
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| 177 | return integ;
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| 178 | }
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| 179 |
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| 180 | void MExtralgoDigitalFilter::Extract(Int_t maxpos)
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| 181 | {
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| 182 | fSignal = 0; // default is: no pulse found
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| 183 | fTime = -2; // default is: out if range (--> random)
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| 184 | fSignalDev = 0; // default is: valid
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| 185 | fTimeDev = 0; // default is: valid
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| 186 |
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| 187 | // FIXME: How to handle saturation?
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| 188 |
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| 189 | Double_t maxamp = -FLT_MAX;
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| 190 | Int_t maxp = -1;
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| 191 |
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| 192 | //
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| 193 | // Calculate the sum of the first fWindowSize slices
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| 194 | //
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| 195 | // For the case of an even number of weights/bin there is
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| 196 | // no central bin.So we create an artificial central bin.
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| 197 | for (Int_t i=0; i<fNum-fWindowSize+1; i++)
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| 198 | {
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| 199 | const Double_t sumamp = Eval(fWeightsAmp, i);
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| 200 | if (sumamp>maxamp)
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| 201 | {
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| 202 | maxamp = sumamp;
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| 203 | maxp = i;
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| 204 | }
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| 205 | }
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| 206 |
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| 207 | /*
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| 208 | // This could be for a fast but less accurate extraction....
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| 209 | maxamp = Eval(fWeightsAmp, maxpos-fWindowSize/2);
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| 210 | maxp = maxpos-fWindowSize/2;
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| 211 | */
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| 212 |
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| 213 | // The number of available slices were smaller than the
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| 214 | // extraction window size of the extractor
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| 215 | if (maxp<0)
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| 216 | {
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| 217 | fSignalDev = -1; // means: is invalid
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| 218 | fTimeDev = -1; // means: is invalid
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| 219 | return;
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| 220 | }
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| 221 |
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| 222 | // For some reason (by chance or because all slices contain 0)
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| 223 | // maxamp is 0. This means the signal is zero and no arrival
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| 224 | // time can be extracted (but both informations are valid)
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| 225 | if (maxamp==0)
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| 226 | return;
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| 227 |
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| 228 | Int_t frac = 0;
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| 229 | const Int_t shift = AlignExtractionWindow(maxp, frac, maxamp);
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| 230 |
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| 231 | // For safety we do another iteration if we have
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| 232 | // shifted the extraction window
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| 233 | if (TMath::Abs(shift)>0)
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| 234 | AlignExtractionWindow(maxp, frac);
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| 235 |
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| 236 | // Now we have found the "final" position: extract time and charge
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| 237 | const Double_t sumamp = Eval(fWeightsAmp, maxp, frac);
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| 238 |
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| 239 | fSignal = sumamp;
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| 240 | if (sumamp == 0)
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| 241 | return;
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| 242 |
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| 243 | const Double_t sumtime = Eval(fWeightsTime, maxp, frac);
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| 244 |
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| 245 | // This is used to align the weights to bins between
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| 246 | // -0.5/fWeightsPerBin and 0.5/fWeightsPerBin instead of
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| 247 | // 0 and 1./fWeightsPerBin
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| 248 | const Double_t binoffset = TMath::Even(fWeightsPerBin) ? 0.5 : 0;
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| 249 |
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| 250 | fTime = maxp /*- 0.5*/ - Double_t(frac+binoffset)/fWeightsPerBin;
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| 251 |
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| 252 | // To let the lowest value which can be safely extracted be>0:
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| 253 | // Take also a possible offset from timefineadjust into account
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| 254 | // Sould it be: fTime += fWindowSize/2; ???
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| 255 |
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| 256 | // HERE we should add the distance from the beginning of the
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| 257 | // extraction window to the leading edge!
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| 258 | fTime += 0.5 + 0.5/fWeightsPerBin;
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| 259 | // Define in each extractor a lowest and highest extracted value!
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| 260 |
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| 261 | const Float_t timefineadjust = sumtime/sumamp;
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| 262 |
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| 263 | //if (TMath::Abs(timefineadjust) < 0.2)
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| 264 | fTime -= timefineadjust;
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| 265 | }
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| 266 |
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| 267 |
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| 268 | #include <TH1.h>
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| 269 | #include <TH2.h>
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| 270 | #include <TMatrixD.h>
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| 271 | #include <TArrayF.h>
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| 272 | #include <iostream>
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| 273 | #include <TSpline.h>
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| 274 | #include <TProfile.h>
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| 275 |
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| 276 | Int_t MExtralgoDigitalFilter::CalculateWeights(TH1 &shape, const TH2 &autocorr, TArrayF &weightsamp, TArrayF &weightstime, Int_t wpb)
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| 277 | {
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| 278 | const Int_t weightsperbin = wpb<=0?shape.GetNbinsX()/autocorr.GetNbinsX():wpb;
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| 279 |
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| 280 | if (wpb<=0 && weightsperbin*autocorr.GetNbinsX()!=shape.GetNbinsX())
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| 281 | {
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| 282 | cout << "ERROR - Number of bins mismatch..." << endl;
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| 283 | cout << " Shape: " << shape.GetNbinsX() << endl;
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| 284 | cout << " ACorr: " << autocorr.GetNbinsX() << endl;
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| 285 | return -1;
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| 286 | }
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| 287 |
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| 288 | const TAxis &axe = *shape.GetXaxis();
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| 289 |
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| 290 | const Int_t first = axe.GetFirst()/weightsperbin;
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| 291 | const Int_t last = axe.GetLast() /weightsperbin;
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| 292 |
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| 293 | const Int_t width = last-first;
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| 294 |
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| 295 | cout << "Range: " << first << " <= bin < " << last << endl;
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| 296 | cout << "Window: " << width << endl;
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| 297 | cout << "W/Bin: " << weightsperbin << endl;
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| 298 |
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| 299 | // ---------------------------------------------
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| 300 |
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| 301 | const Float_t sum = shape.Integral(first*weightsperbin, last*weightsperbin-1)/weightsperbin;
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| 302 | shape.Scale(1./sum);
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| 303 |
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| 304 | cout << "Sum: " << sum << endl;
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| 305 |
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| 306 | // TGraph gr(&shape);
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| 307 | // TSpline5 val("Signal", &gr);
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| 308 |
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| 309 | // FIXME: DELETE!!!
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| 310 | TH1 &derivative = *static_cast<TH1*>(shape.Clone());
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| 311 | derivative.SetDirectory(0);
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| 312 | derivative.Reset();
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| 313 |
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| 314 | for (int i=0; i<derivative.GetNbinsX(); i++)
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| 315 | {
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| 316 | // const Float_t x = derivative.GetBinCenter(i+1);
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| 317 | // derivative.SetBinContent(i+1, val.Derivative(x));
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| 318 |
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| 319 | const Float_t binm = shape.GetBinContent(i+1-1);
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| 320 | const Float_t binp = shape.GetBinContent(i+1+1);
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| 321 |
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| 322 | const Float_t der = (binp-binm)/2./shape.GetBinWidth(1);
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| 323 |
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| 324 | derivative.SetBinContent(i+1, der);
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| 325 |
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| 326 | if (derivative.InheritsFrom(TProfile::Class()))
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| 327 | static_cast<TProfile&>(derivative).SetBinEntries(i+1,1);
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| 328 | }
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| 329 |
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| 330 | // ---------------------------------------------
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| 331 |
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| 332 | TMatrixD B(width, width);
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| 333 | for (Int_t i=0; i<width; i++)
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| 334 | for (Int_t j=0; j<width; j++)
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| 335 | B[i][j]=autocorr.GetBinContent(i+1/*first*/, j+1/*first*/);
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| 336 |
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| 337 | const TMatrixD Binv(TMatrixD::kInverted, B);
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| 338 |
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| 339 | // ---------------------------------------------
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| 340 |
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| 341 | weightsamp.Set(width*weightsperbin);
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| 342 | weightstime.Set(width*weightsperbin);
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| 343 |
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| 344 | for (Int_t i=0; i<weightsperbin; i++)
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| 345 | {
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| 346 | TMatrixD g(width, 1);
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| 347 | TMatrixD d(width, 1);
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| 348 |
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| 349 | for (Int_t bin=0; bin<width; bin++)
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| 350 | {
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| 351 | const Int_t idx = weightsperbin*(bin+first) + i;
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| 352 |
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| 353 | g[bin][0]=shape.GetBinContent(idx+1);
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| 354 | d[bin][0]=derivative.GetBinContent(idx+1);
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| 355 | }
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| 356 |
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| 357 | const TMatrixD gT(TMatrixD::kTransposed, g);
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| 358 | const TMatrixD dT(TMatrixD::kTransposed, d);
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| 359 |
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| 360 | const TMatrixD denom = (gT*(Binv*g))*(dT*(Binv*d)) - (dT*(Binv*g))*(dT*(Binv*g));
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| 361 |
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| 362 | if (denom[0][0]==0)
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| 363 | {
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| 364 | cout << "ERROR - Division by zero: denom[0][0]==0 for i=" << i << "." << endl;
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| 365 | return -1;
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| 366 | }
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| 367 |
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| 368 | const TMatrixD w_amp = (dT*(Binv*d))*(gT*Binv) - (gT*(Binv*d))*(dT*Binv);
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| 369 | const TMatrixD w_time = (gT*(Binv*g))*(dT*Binv) - (gT*(Binv*d))*(gT*Binv);
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| 370 |
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| 371 | for (Int_t bin=0; bin<width; bin++)
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| 372 | {
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| 373 | const Int_t idx = weightsperbin*bin + i;
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| 374 |
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| 375 | weightsamp[idx] = w_amp [0][bin]/denom[0][0];
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| 376 | weightstime[idx] = w_time[0][bin]/denom[0][0];
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| 377 | }
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| 378 | }
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| 379 |
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| 380 | return first*weightsperbin;
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| 381 | }
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| 382 |
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| 383 | Int_t MExtralgoDigitalFilter::CalculateWeights2(TH1 &shape, const TH2 &autocorr, TArrayF &weightsamp, TArrayF &weightstime, Int_t wpb)
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| 384 | {
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| 385 | const Int_t weightsperbin = wpb<=0?shape.GetNbinsX()/autocorr.GetNbinsX():wpb;
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| 386 |
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| 387 | if (wpb<=0 && weightsperbin*autocorr.GetNbinsX()!=shape.GetNbinsX())
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| 388 | {
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| 389 | cout << "ERROR - Number of bins mismatch..." << endl;
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| 390 | cout << " Shape: " << shape.GetNbinsX() << endl;
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| 391 | cout << " ACorr: " << autocorr.GetNbinsX() << endl;
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| 392 | return -1;
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| 393 | }
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| 394 |
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| 395 | const TAxis &axe = *shape.GetXaxis();
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| 396 |
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| 397 | const Int_t first = axe.GetFirst()/weightsperbin;
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| 398 | const Int_t last = axe.GetLast() /weightsperbin;
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| 399 |
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| 400 | const Int_t width = last-first;
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| 401 |
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| 402 | cout << "Range: " << first << " <= bin < " << last << endl;
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| 403 | cout << "Window: " << width << endl;
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| 404 | cout << "W/Bin: " << weightsperbin << endl;
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| 405 |
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| 406 | // ---------------------------------------------
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| 407 |
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| 408 | const Float_t sum = shape.Integral(first*weightsperbin, last*weightsperbin-1)/weightsperbin;
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| 409 | shape.Scale(1./sum);
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| 410 |
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| 411 | TGraph gr(&shape);
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| 412 | TSpline5 val("Signal", &gr);
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| 413 |
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| 414 | // FIXME: DELETE!!!
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| 415 | TH1 &derivative = *static_cast<TH1*>(shape.Clone());
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| 416 | derivative.SetDirectory(0);
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| 417 | derivative.Reset();
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| 418 |
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| 419 | for (int i=0; i<derivative.GetNbinsX(); i++)
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| 420 | {
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| 421 | const Float_t x = derivative.GetBinCenter(i+1);
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| 422 | derivative.SetBinContent(i+1, val.Derivative(x));
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| 423 |
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| 424 | /*
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| 425 | const Float_t binm = shape.GetBinContent(i+1-1);
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| 426 | const Float_t binp = shape.GetBinContent(i+1+1);
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| 427 |
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| 428 | const Float_t der = (binp-binm)/2./shape.GetBinWidth(1);
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| 429 |
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| 430 | derivative.SetBinContent(i+1, der);
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| 431 | */
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| 432 | }
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| 433 |
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| 434 | // ---------------------------------------------
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| 435 |
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| 436 | TMatrixD B(width, width);
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| 437 | for (Int_t i=0; i<width; i++)
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| 438 | for (Int_t j=0; j<width; j++)
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| 439 | B[i][j]=autocorr.GetBinContent(i+first, j+first);
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| 440 | B.Invert();
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| 441 |
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| 442 | // ---------------------------------------------
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| 443 |
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| 444 | weightsamp.Set(width*weightsperbin);
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| 445 | weightstime.Set(width*weightsperbin);
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| 446 |
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| 447 | for (Int_t i=0; i<weightsperbin; i++)
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| 448 | {
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| 449 | TMatrixD g(width, 1);
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| 450 | TMatrixD d(width, 1);
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| 451 |
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| 452 | for (Int_t bin=0; bin<width; bin++)
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| 453 | {
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| 454 | const Int_t idx = weightsperbin*(bin+first) + i;
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| 455 |
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| 456 | g[bin][0]=shape.GetBinContent(idx+1);
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| 457 | d[bin][0]=derivative.GetBinContent(idx+1);
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| 458 | }
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| 459 |
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| 460 | const TMatrixD gT(TMatrixD::kTransposed, g);
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| 461 | const TMatrixD dT(TMatrixD::kTransposed, d);
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| 462 |
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| 463 | const TMatrixD denom = (gT*(B*g))*(dT*(B*d)) - (dT*(B*g))*(dT*(B*g));
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| 464 |
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| 465 | if (denom[0][0]==0)
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| 466 | {
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| 467 | cout << "ERROR - Division by zero: denom[0][0]==0 for i=" << i << "." << endl;
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| 468 | return -1;
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| 469 | }
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| 470 |
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| 471 | const TMatrixD w_amp = (dT*(B*d))*(gT*B) - (gT*(B*d))*(dT*B);
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| 472 | const TMatrixD w_time = (gT*(B*g))*(dT*B) - (gT*(B*d))*(gT*B);
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| 473 |
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| 474 | for (Int_t bin=0; bin<width; bin++)
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| 475 | {
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| 476 | const Int_t idx = weightsperbin*bin + i;
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| 477 |
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| 478 | weightsamp[idx] = w_amp [0][bin]/denom[0][0];
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| 479 | weightstime[idx] = w_time[0][bin]/denom[0][0];
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| 480 | }
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| 481 | }
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| 482 | return first*weightsperbin;
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| 483 | }
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