| 1 | #include "toimanager.h" | 
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| 2 | #include "correl.h" | 
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| 3 | #include "wienerdecor.h" | 
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| 4 | extern "C" { | 
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| 5 | #include "nrutil.h" | 
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| 6 | } | 
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| 7 | extern "C" void dtoeplz(double r[], double x[], double y[], int n); | 
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| 8 |  | 
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| 9 | WienerDecorrelator::WienerDecorrelator(int n, int l) { | 
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| 10 | nsamples = n; | 
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| 11 | lcorr = l; | 
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| 12 | } | 
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| 13 |  | 
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| 14 | void WienerDecorrelator::init() { | 
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| 15 | declareInput("signal"); | 
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| 16 | declareInput("probe"); | 
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| 17 | declareOutput("signal"); | 
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| 18 | declareOutput("noiseestim"); | 
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| 19 | name="WienerDecorrelator"; | 
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| 20 | setNeededHistory(nsamples+lcorr+1); | 
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| 21 | lowExtra = lcorr; | 
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| 22 | } | 
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| 23 |  | 
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| 24 | void WienerDecorrelator::run() { | 
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| 25 | int snb = getMinIn(); | 
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| 26 | int sne = getMaxIn(); | 
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| 27 |  | 
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| 28 | //  cout << "Wiener " << snb << " - " << sne << endl; | 
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| 29 |  | 
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| 30 | CorrelEstimator corr(lcorr, nsamples), autocorr(lcorr, nsamples); | 
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| 31 |  | 
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| 32 | double* r = new double[2*lcorr];  // autocorr toeplitz matrix | 
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| 33 | double* w = new double[lcorr+1];  // filter | 
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| 34 | double* y = new double[lcorr+1];  // corr vector | 
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| 35 | double* window = new double[lcorr]; | 
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| 36 | double* filter = new double[lcorr]; | 
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| 37 | for (int i=0; i<lcorr; i++) filter[i]=0; | 
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| 38 |  | 
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| 39 | int sn = snb; | 
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| 40 | int snstartcorr = -1; | 
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| 41 |  | 
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| 42 | while (sn < sne) { | 
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| 43 | if (snstartcorr < 0 || | 
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| 44 | (snstartcorr + nsamples < sn && sn+nsamples < sne)) { | 
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| 45 | // let's (re)compute the correlation | 
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| 46 | snstartcorr = sn; | 
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| 47 | corr.reset(); | 
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| 48 | autocorr.reset(); | 
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| 49 | int i; | 
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| 50 | for (i=sn; i<sn+nsamples; i++) { | 
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| 51 | double sig = getData(0, i); | 
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| 52 | double prb = getData(1, i); | 
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| 53 | corr.push(i, sig, prb); | 
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| 54 | autocorr.push(i, prb); | 
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| 55 | } | 
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| 56 | // correlation is recomputed, let's recompute the wiener filter from wiener equations | 
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| 57 | for (i=0; i<lcorr; i++) { | 
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| 58 | r[lcorr+i] = r[lcorr-i] = autocorr.correl(i); | 
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| 59 | y[i+1] = corr.correl(i); | 
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| 60 | } | 
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| 61 | dtoeplz(r,w,y,lcorr); | 
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| 62 | if (!isnan(w[1])) { | 
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| 63 | for (int i=0; i<lcorr; i++) { | 
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| 64 | filter[i] = w[i+1]; | 
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| 65 | } | 
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| 66 | } else { | 
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| 67 | cout << "Bad inversion, keeping previous filter\n"; | 
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| 68 | } | 
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| 69 | cout << "Wiener filter : " << sn << "\n "; | 
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| 70 | for (i=0; i<lcorr; i++) { | 
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| 71 | cout << filter[i] << " "; | 
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| 72 | } | 
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| 73 | cout << endl; | 
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| 74 | } | 
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| 75 |  | 
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| 76 | if (sn >= snb+lcorr-1) { | 
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| 77 | getData(1, sn-lcorr+1, lcorr, window); | 
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| 78 | double outSig = 0; | 
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| 79 | for (int i=0; i<lcorr; i++) { | 
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| 80 | outSig += filter[i] * window[lcorr-1 - i]; | 
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| 81 | } | 
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| 82 | putData(0, sn, getData(0, sn) - outSig); | 
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| 83 | putData(1, sn, outSig); | 
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| 84 | } | 
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| 85 | sn++; | 
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| 86 | } | 
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| 87 |  | 
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| 88 | delete[] y; | 
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| 89 | delete[] w; | 
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| 90 | delete[] r; | 
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| 91 | delete[] filter; | 
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| 92 | } | 
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