FitAwmi.C File Reference

Detailed Description

This macro fits the source spectrum using the AWMI algorithm from the "TSpectrumFit" class ("TSpectrum" class is used to find peaks).

To try this macro, in a ROOT (5 or 6) prompt, do:

root > .x FitAwmi.C

or:

root > .x FitAwmi.C++
root > FitAwmi(); // re-run with another random set of peaks

 
created -9.82 26.5962 4
created -9.46 33.2452 5
created -9.1 33.2452 5
created -8.74 26.5962 4
created -8.38 59.8413 9
created -8.02 6.64904 1
created -7.66 39.8942 6
created -7.3 19.9471 3
created -6.94 13.2981 2
created -6.58 59.8413 9
created -6.22 66.4904 10
created -5.86 33.2452 5
created -5.5 13.2981 2
created -5.14 33.2452 5
created -4.78 26.5962 4
created -4.42 19.9471 3
created -4.06 66.4904 10
created -3.7 33.2452 5
created -3.34 33.2452 5
created -2.98 19.9471 3
created -2.62 13.2981 2
created -2.26 26.5962 4
created -1.9 66.4904 10
created -1.54 6.64904 1
created -1.18 39.8942 6
created -0.82 26.5962 4
created -0.46 13.2981 2
created -0.1 66.4904 10
created 0.26 39.8942 6
created 0.62 46.5433 7
created 0.98 53.1923 8
created 1.34 13.2981 2
created 1.7 19.9471 3
created 2.06 53.1923 8
created 2.42 66.4904 10
created 2.78 26.5962 4
created 3.14 6.64904 1
created 3.5 19.9471 3
created 3.86 6.64904 1
created 4.22 13.2981 2
created 4.58 59.8413 9
created 4.94 59.8413 9
created 5.3 26.5962 4
created 5.66 66.4904 10
created 6.02 59.8413 9
created 6.38 59.8413 9
created 6.74 33.2452 5
created 7.1 13.2981 2
created 7.46 26.5962 4
created 7.82 66.4904 10
created 8.18 6.64904 1
created 8.54 66.4904 10
created 8.9 66.4904 10
created 9.26 53.1923 8
created 9.62 26.5962 4
the total number of created peaks = 55 with sigma = 0.06
the total number of found peaks = 55 with sigma = 0.0600004 (+-1.06339e-05)
fit chi^2 = 1.54959e-06
found -6.22 (+-0.00010125) 66.4905 (+-0.110554) 10.0001 (+-0.000557659)
found -4.06 (+-0.000100894) 66.4903 (+-0.110507) 10.0001 (+-0.000557421)
found -1.9 (+-0.000100595) 66.4901 (+-0.110471) 10 (+-0.000557237)
found -0.0999998 (+-0.000100856) 66.4903 (+-0.110503) 10.0001 (+-0.000557401)
found 2.42 (+-0.000101137) 66.4904 (+-0.110539) 10.0001 (+-0.000557583)
found 5.66 (+-0.000101182) 66.4905 (+-0.110545) 10.0001 (+-0.000557614)
found 7.82 (+-0.000100595) 66.4901 (+-0.110471) 10 (+-0.000557237)
found 8.54 (+-0.00010091) 66.4904 (+-0.110513) 10.0001 (+-0.000557453)
found 8.9 (+-0.000101457) 66.4907 (+-0.110582) 10.0001 (+-0.0005578)
found 4.94 (+-0.000106733) 59.8415 (+-0.104882) 9.00009 (+-0.000529047)
found 6.02 (+-0.000107085) 59.8418 (+-0.104925) 9.00013 (+-0.000529263)
found 6.38 (+-0.000106808) 59.8415 (+-0.104891) 9.00009 (+-0.000529092)
found -8.38 (+-0.000106088) 59.8411 (+-0.104807) 9.00003 (+-0.000528671)
found -6.58 (+-0.000106583) 59.8415 (+-0.104866) 9.00008 (+-0.000528966)
found 4.58 (+-0.000106536) 59.8414 (+-0.10486) 9.00007 (+-0.000528936)
found 9.26 (+-0.000113355) 53.1926 (+-0.0989001) 8.00009 (+-0.000498873)
found 0.98 (+-0.000112971) 53.1923 (+-0.0988593) 8.00006 (+-0.000498667)
found 2.06 (+-0.000113257) 53.1925 (+-0.0988901) 8.00009 (+-0.000498823)
found 0.62 (+-0.000121364) 46.5436 (+-0.0925293) 7.00009 (+-0.000466737)
found 0.26 (+-0.000131479) 39.8947 (+-0.0856988) 6.00011 (+-0.000432283)
found -7.66 (+-0.000130077) 39.8941 (+-0.0855855) 6.00003 (+-0.000431712)
found -1.18 (+-0.0001302) 39.8942 (+-0.0855955) 6.00003 (+-0.000431762)
found -5.86 (+-0.000143608) 33.2455 (+-0.0782048) 5.00008 (+-0.000394481)
found -3.7 (+-0.000144067) 33.2456 (+-0.0782352) 5.0001 (+-0.000394635)
found 6.74 (+-0.000143531) 33.2455 (+-0.078199) 5.00007 (+-0.000394452)
found -9.46 (+-0.000143482) 33.2454 (+-0.0781933) 5.00006 (+-0.000394424)
found -9.1 (+-0.000143482) 33.2454 (+-0.0781933) 5.00006 (+-0.000394424)
found -5.14 (+-0.000143029) 33.2452 (+-0.078163) 5.00004 (+-0.000394271)
found -3.34 (+-0.000143335) 33.2453 (+-0.0781835) 5.00005 (+-0.000394374)
found -8.74 (+-0.000161325) 26.5966 (+-0.0699903) 4.00009 (+-0.000353046)
found -4.78 (+-0.000160531) 26.5963 (+-0.0699447) 4.00005 (+-0.000352816)
found -0.820001 (+-0.000160441) 26.5963 (+-0.0699406) 4.00005 (+-0.000352795)
found 2.78 (+-0.000160547) 26.5965 (+-0.0699501) 4.00007 (+-0.000352843)
found 5.3 (+-0.000161887) 26.5968 (+-0.0700231) 4.00013 (+-0.000353211)
found 9.62 (+-0.000159489) 26.5965 (+-0.0699028) 4.00008 (+-0.000352605)
found -9.82 (+-0.000160306) 26.5962 (+-0.069927) 4.00003 (+-0.000352726)
found -2.26 (+-0.00016086) 26.5965 (+-0.0699657) 4.00008 (+-0.000352922)
found 7.46 (+-0.00016086) 26.5965 (+-0.0699657) 4.00008 (+-0.000352922)
found -7.3 (+-0.000185702) 19.9473 (+-0.060589) 3.00005 (+-0.000305624)
found -4.42 (+-0.000186759) 19.9476 (+-0.0606351) 3.00009 (+-0.000305856)
found -2.98 (+-0.000185533) 19.9473 (+-0.0605815) 3.00005 (+-0.000305586)
found 1.7 (+-0.000185992) 19.9474 (+-0.0606022) 3.00007 (+-0.000305691)
found 3.5 (+-0.000184041) 19.9471 (+-0.0605208) 3.00001 (+-0.00030528)
found 1.34 (+-0.000229121) 13.2985 (+-0.0495202) 2.00007 (+-0.000249791)
found -6.94 (+-0.000229299) 13.2985 (+-0.049526) 2.00008 (+-0.000249819)
found -5.5 (+-0.000229077) 13.2984 (+-0.0495178) 2.00007 (+-0.000249778)
found -2.62 (+-0.000228197) 13.2983 (+-0.0494918) 2.00005 (+-0.000249647)
found -0.459998 (+-0.000229797) 13.2986 (+-0.0495409) 2.00009 (+-0.000249895)
found 7.1 (+-0.000228799) 13.2984 (+-0.0495096) 2.00006 (+-0.000249737)
found 4.22 (+-0.000228307) 13.2984 (+-0.0494991) 2.00007 (+-0.000249684)
found 8.18 (+-0.000330407) 6.64989 (+-0.0351181) 1.00014 (+-0.000177143)
found -1.54 (+-0.000329035) 6.64971 (+-0.0350954) 1.00011 (+-0.000177029)
found -8.02 (+-0.000328737) 6.64967 (+-0.0350903) 1.0001 (+-0.000177003)
found 3.14 (+-0.000325234) 6.64931 (+-0.0350339) 1.00005 (+-0.000176718)
found 3.86 (+-0.000323912) 6.64922 (+-0.0350138) 1.00003 (+-0.000176617)

 
#include "TROOT.h"
#include "TMath.h"
#include "TRandom.h"
#include "TH1.h"
#include "TF1.h"
#include "TCanvas.h"
#include "TSpectrum.h"
#include "TSpectrumFit.h"
#include "TPolyMarker.h"
#include "TList.h"
 
#include <iostream>
 
TH1F *FitAwmi_Create_Spectrum(void) {
   Int_t nbins = 1000;
   Double_t xmin = -10., xmax = 10.;
   delete gROOT->FindObject("h"); // prevent "memory leak"
   TH1F *h = new TH1F("h", "simulated spectrum", nbins, xmin, xmax);
   h->SetStats(kFALSE);
   TF1 f("f", "TMath::Gaus(x, [0], [1], 1)", xmin, xmax);
   // f.SetParNames("mean", "sigma");
   gRandom->SetSeed(0); // make it really random
   // create well separated peaks with exactly known means and areas
   // note: TSpectrumFit assumes that all peaks have the same sigma
   Double_t sigma = (xmax - xmin) / Double_t(nbins) * Int_t(gRandom->Uniform(2., 6.));
   Int_t npeaks = 0;
   while (xmax > (xmin + 6. * sigma)) {
      npeaks++;
      xmin += 3. * sigma; // "mean"
      f.SetParameters(xmin, sigma);
      Double_t area = 1. * Int_t(gRandom->Uniform(1., 11.));
      h->Add(&f, area, ""); // "" ... or ... "I"
      std::cout << "created "
                << xmin << " "
                << (area / sigma / TMath::Sqrt(TMath::TwoPi())) << " "
                << area << std::endl;
      xmin += 3. * sigma;
   }
   std::cout << "the total number of created peaks = " << npeaks
             << " with sigma = " << sigma << std::endl;
   return h;
}
 
void FitAwmi(void) {
 
   TH1F *h = FitAwmi_Create_Spectrum();
 
   TCanvas *cFit = ((TCanvas *)(gROOT->GetListOfCanvases()->FindObject("cFit")));
   if (!cFit) cFit = new TCanvas("cFit", "cFit", 10, 10, 1000, 700);
   else cFit->Clear();
   h->Draw("L");
   Int_t i, nfound, bin;
   Int_t nbins = h->GetNbinsX();
 
   Double_t *source = new Double_t[nbins];
   Double_t *dest = new Double_t[nbins];
 
   for (i = 0; i < nbins; i++) source[i] = h->GetBinContent(i + 1);
   TSpectrum *s = new TSpectrum(); // note: default maxpositions = 100
   // searching for candidate peaks positions
   nfound = s->SearchHighRes(source, dest, nbins, 2., 2., kFALSE, 10000, kFALSE, 0);
   // filling in the initial estimates of the input parameters
   Bool_t *FixPos = new Bool_t[nfound];
   Bool_t *FixAmp = new Bool_t[nfound];
   for(i = 0; i < nfound; i++) FixAmp[i] = FixPos[i] = kFALSE;
 
   Double_t *Pos, *Amp = new Double_t[nfound]; // ROOT 6
 
   Pos = s->GetPositionX(); // 0 ... (nbins - 1)
   for (i = 0; i < nfound; i++) {
      bin = 1 + Int_t(Pos[i] + 0.5); // the "nearest" bin
      Amp[i] = h->GetBinContent(bin);
   }
   TSpectrumFit *pfit = new TSpectrumFit(nfound);
   pfit->SetFitParameters(0, (nbins - 1), 1000, 0.1, pfit->kFitOptimChiCounts,
                          pfit->kFitAlphaHalving, pfit->kFitPower2,
                          pfit->kFitTaylorOrderFirst);
   pfit->SetPeakParameters(2., kFALSE, Pos, FixPos, Amp, FixAmp);
   // pfit->SetBackgroundParameters(source[0], kFALSE, 0., kFALSE, 0., kFALSE);
   pfit->FitAwmi(source);
   Double_t *Positions = pfit->GetPositions();
   Double_t *PositionsErrors = pfit->GetPositionsErrors();
   Double_t *Amplitudes = pfit->GetAmplitudes();
   Double_t *AmplitudesErrors = pfit->GetAmplitudesErrors();
   Double_t *Areas = pfit->GetAreas();
   Double_t *AreasErrors = pfit->GetAreasErrors();
   delete gROOT->FindObject("d"); // prevent "memory leak"
   TH1F *d = new TH1F(*h); d->SetNameTitle("d", ""); d->Reset("M");
   for (i = 0; i < nbins; i++) d->SetBinContent(i + 1, source[i]);
   Double_t x1 = d->GetBinCenter(1), dx = d->GetBinWidth(1);
   Double_t sigma, sigmaErr;
   pfit->GetSigma(sigma, sigmaErr);
 
   // current TSpectrumFit needs a sqrt(2) correction factor for sigma
   sigma /= TMath::Sqrt2(); sigmaErr /= TMath::Sqrt2();
   // convert "bin numbers" into "x-axis values"
   sigma *= dx; sigmaErr *= dx;
 
   std::cout << "the total number of found peaks = " << nfound
             << " with sigma = " << sigma << " (+-" << sigmaErr << ")"
             << std::endl;
   std::cout << "fit chi^2 = " << pfit->GetChi() << std::endl;
   for (i = 0; i < nfound; i++) {
      bin = 1 + Int_t(Positions[i] + 0.5); // the "nearest" bin
      Pos[i] = d->GetBinCenter(bin);
      Amp[i] = d->GetBinContent(bin);
 
      // convert "bin numbers" into "x-axis values"
      Positions[i] = x1 + Positions[i] * dx;
      PositionsErrors[i] *= dx;
      Areas[i] *= dx;
      AreasErrors[i] *= dx;
 
      std::cout << "found "
                << Positions[i] << " (+-" << PositionsErrors[i] << ") "
                << Amplitudes[i] << " (+-" << AmplitudesErrors[i] << ") "
                << Areas[i] << " (+-" << AreasErrors[i] << ")"
                << std::endl;
   }
   d->SetLineColor(kRed); d->SetLineWidth(1);
   d->Draw("SAME L");
   TPolyMarker *pm = ((TPolyMarker*)(h->GetListOfFunctions()->FindObject("TPolyMarker")));
   if (pm) {
      h->GetListOfFunctions()->Remove(pm);
      delete pm;
   }
   pm = new TPolyMarker(nfound, Pos, Amp);
   h->GetListOfFunctions()->Add(pm);
   pm->SetMarkerStyle(23);
   pm->SetMarkerColor(kRed);
   pm->SetMarkerSize(1);
   // cleanup
   delete pfit;
   delete [] Amp;
   delete [] FixAmp;
   delete [] FixPos;
   delete s;
   delete [] dest;
   delete [] source;
   return;
}

Author

Definition in file FitAwmi.C.