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 39.8942 6
created -9.46 39.8942 6
created -9.1 33.2452 5
created -8.74 66.4904 10
created -8.38 13.2981 2
created -8.02 53.1923 8
created -7.66 59.8413 9
created -7.3 6.64904 1
created -6.94 46.5433 7
created -6.58 46.5433 7
created -6.22 46.5433 7
created -5.86 6.64904 1
created -5.5 46.5433 7
created -5.14 26.5962 4
created -4.78 46.5433 7
created -4.42 33.2452 5
created -4.06 33.2452 5
created -3.7 6.64904 1
created -3.34 19.9471 3
created -2.98 53.1923 8
created -2.62 13.2981 2
created -2.26 39.8942 6
created -1.9 66.4904 10
created -1.54 33.2452 5
created -1.18 59.8413 9
created -0.82 39.8942 6
created -0.46 13.2981 2
created -0.1 19.9471 3
created 0.26 13.2981 2
created 0.62 46.5433 7
created 0.98 46.5433 7
created 1.34 33.2452 5
created 1.7 6.64904 1
created 2.06 26.5962 4
created 2.42 19.9471 3
created 2.78 19.9471 3
created 3.14 33.2452 5
created 3.5 66.4904 10
created 3.86 33.2452 5
created 4.22 26.5962 4
created 4.58 53.1923 8
created 4.94 19.9471 3
created 5.3 26.5962 4
created 5.66 6.64904 1
created 6.02 6.64904 1
created 6.38 6.64904 1
created 6.74 53.1923 8
created 7.1 53.1923 8
created 7.46 13.2981 2
created 7.82 59.8413 9
created 8.18 13.2981 2
created 8.54 19.9471 3
created 8.9 66.4904 10
created 9.26 33.2452 5
created 9.62 13.2981 2
the total number of created peaks = 55 with sigma = 0.06
the total number of found peaks = 55 with sigma = 0.0600004 (+-7.91202e-06)
fit chi^2 = 7.91302e-07
found -8.74 (+-7.20289e-05) 66.4902 (+-0.0789598) 10 (+-0.00039829)
found -1.9 (+-7.22473e-05) 66.4904 (+-0.0789876) 10.0001 (+-0.00039843)
found 3.5 (+-7.22045e-05) 66.4904 (+-0.078982) 10.0001 (+-0.000398402)
found 8.9 (+-7.2099e-05) 66.4903 (+-0.0789684) 10.0001 (+-0.000398334)
found -7.66 (+-7.59894e-05) 59.8413 (+-0.0749173) 9.00006 (+-0.000377899)
found -1.18 (+-7.62087e-05) 59.8414 (+-0.0749406) 9.00007 (+-0.000378016)
found 7.82 (+-7.57773e-05) 59.8411 (+-0.0748909) 9.00003 (+-0.000377765)
found 7.1 (+-8.07717e-05) 53.1924 (+-0.0706497) 8.00007 (+-0.000356372)
found -8.02 (+-8.08109e-05) 53.1924 (+-0.0706541) 8.00007 (+-0.000356394)
found -2.98 (+-8.05035e-05) 53.1921 (+-0.0706207) 8.00003 (+-0.000356226)
found 4.58 (+-8.06579e-05) 53.1922 (+-0.0706364) 8.00005 (+-0.000356305)
found 6.74 (+-8.06532e-05) 53.1923 (+-0.0706384) 8.00006 (+-0.000356315)
found -6.94 (+-8.62436e-05) 46.5433 (+-0.066078) 7.00005 (+-0.000333311)
found -6.58 (+-8.67312e-05) 46.5436 (+-0.0661219) 7.00009 (+-0.000333533)
found -6.22 (+-8.62436e-05) 46.5433 (+-0.066078) 7.00005 (+-0.000333311)
found -5.5 (+-8.6068e-05) 46.5432 (+-0.066061) 7.00003 (+-0.000333226)
found -4.78 (+-8.64416e-05) 46.5433 (+-0.0660942) 7.00006 (+-0.000333393)
found 0.62 (+-8.63773e-05) 46.5433 (+-0.0660892) 7.00006 (+-0.000333368)
found 0.98 (+-8.66195e-05) 46.5435 (+-0.0661111) 7.00008 (+-0.000333479)
found -0.820001 (+-9.35007e-05) 39.8944 (+-0.0612037) 6.00007 (+-0.000308725)
found -9.82 (+-9.34459e-05) 39.8942 (+-0.0611928) 6.00004 (+-0.00030867)
found -9.46 (+-9.36132e-05) 39.8944 (+-0.0612114) 6.00007 (+-0.000308763)
found -2.26 (+-9.35475e-05) 39.8945 (+-0.0612079) 6.00008 (+-0.000308745)
found -1.54 (+-0.000103226) 33.2458 (+-0.0559265) 5.00013 (+-0.000282105)
found 3.86 (+-0.00010286) 33.2456 (+-0.0559007) 5.00009 (+-0.000281975)
found 9.26 (+-0.000102622) 33.2455 (+-0.0558851) 5.00008 (+-0.000281897)
found -9.1 (+-0.00010303) 33.2457 (+-0.0559124) 5.00011 (+-0.000282034)
found -4.42 (+-0.000102771) 33.2455 (+-0.0558938) 5.00008 (+-0.00028194)
found -4.06 (+-0.000102116) 33.2452 (+-0.0558503) 5.00004 (+-0.000281721)
found 1.34 (+-0.000102263) 33.2453 (+-0.0558608) 5.00005 (+-0.000281774)
found 3.14 (+-0.000102754) 33.2455 (+-0.0558936) 5.00009 (+-0.000281939)
found -5.14 (+-0.000115315) 26.5966 (+-0.0500166) 4.00009 (+-0.000252295)
found 4.22 (+-0.000115211) 26.5965 (+-0.0500108) 4.00009 (+-0.000252265)
found 2.06 (+-0.000114103) 26.5961 (+-0.0499499) 4.00003 (+-0.000251958)
found 5.3 (+-0.000114103) 26.5961 (+-0.0499499) 4.00003 (+-0.000251958)
found 2.42 (+-0.000132648) 19.9473 (+-0.0432939) 3.00005 (+-0.000218383)
found 4.94 (+-0.000133282) 19.9475 (+-0.0433217) 3.00008 (+-0.000218524)
found -3.34 (+-0.000132622) 19.9474 (+-0.0432953) 3.00006 (+-0.000218391)
found -0.1 (+-0.000132079) 19.9472 (+-0.0432702) 3.00003 (+-0.000218264)
found 2.78 (+-0.000132786) 19.9473 (+-0.0432999) 3.00005 (+-0.000218414)
found 8.54 (+-0.000133085) 19.9475 (+-0.0433146) 3.00008 (+-0.000218488)
found -8.38 (+-0.000164887) 13.2988 (+-0.0354223) 2.00012 (+-0.000178678)
found 8.18 (+-0.000163857) 13.2985 (+-0.0353913) 2.00008 (+-0.000178521)
found -2.62 (+-0.00016434) 13.2986 (+-0.0354052) 2.00009 (+-0.000178591)
found -0.460001 (+-0.000163438) 13.2984 (+-0.035378) 2.00006 (+-0.000178454)
found 7.46 (+-0.000164767) 13.2987 (+-0.0354185) 2.00011 (+-0.000178658)
found 0.260001 (+-0.000163591) 13.2984 (+-0.0353828) 2.00007 (+-0.000178478)
found 9.62 (+-0.000161368) 13.2983 (+-0.0353277) 2.00005 (+-0.0001782)
found -7.3 (+-0.000235195) 6.64971 (+-0.0250801) 1.00011 (+-0.000126509)
found -5.86 (+-0.000234713) 6.64962 (+-0.025072) 1.00009 (+-0.000126469)
found -3.7 (+-0.000232764) 6.64935 (+-0.0250409) 1.00005 (+-0.000126311)
found 1.7 (+-0.000233186) 6.6494 (+-0.0250474) 1.00006 (+-0.000126344)
found 5.66 (+-0.000231133) 6.64922 (+-0.0250167) 1.00003 (+-0.00012619)
found 6.38 (+-0.00023229) 6.6494 (+-0.0250359) 1.00006 (+-0.000126287)
found 6.02 (+-0.000229469) 6.64908 (+-0.0249917) 1.00001 (+-0.000126063)

 
#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.