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Reference Guide
FitAwmi.C File Reference
Tutorials » Spectrum tutorials

Detailed Description

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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 -9.88 9.97356 1
created -9.64 99.7356 10
created -9.4 49.8678 5
created -9.16 99.7356 10
created -8.92 9.97356 1
created -8.68 59.8413 6
created -8.44 39.8942 4
created -8.2 19.9471 2
created -7.96 79.7885 8
created -7.72 49.8678 5
created -7.48 99.7356 10
created -7.24 49.8678 5
created -7 49.8678 5
created -6.76 69.8149 7
created -6.52 99.7356 10
created -6.28 99.7356 10
created -6.04 49.8678 5
created -5.8 9.97356 1
created -5.56 69.8149 7
created -5.32 79.7885 8
created -5.08 69.8149 7
created -4.84 19.9471 2
created -4.6 19.9471 2
created -4.36 89.762 9
created -4.12 29.9207 3
created -3.88 99.7356 10
created -3.64 69.8149 7
created -3.4 89.762 9
created -3.16 69.8149 7
created -2.92 99.7356 10
created -2.68 19.9471 2
created -2.44 39.8942 4
created -2.2 49.8678 5
created -1.96 19.9471 2
created -1.72 19.9471 2
created -1.48 39.8942 4
created -1.24 29.9207 3
created -1 79.7885 8
created -0.76 49.8678 5
created -0.52 99.7356 10
created -0.28 79.7885 8
created -0.04 19.9471 2
created 0.2 89.762 9
created 0.44 49.8678 5
created 0.68 19.9471 2
created 0.92 89.762 9
created 1.16 69.8149 7
created 1.4 59.8413 6
created 1.64 9.97356 1
created 1.88 59.8413 6
created 2.12 19.9471 2
created 2.36 19.9471 2
created 2.6 29.9207 3
created 2.84 19.9471 2
created 3.08 9.97356 1
created 3.32 39.8942 4
created 3.56 49.8678 5
created 3.8 89.762 9
created 4.04 29.9207 3
created 4.28 79.7885 8
created 4.52 79.7885 8
created 4.76 39.8942 4
created 5 29.9207 3
created 5.24 59.8413 6
created 5.48 49.8678 5
created 5.72 69.8149 7
created 5.96 79.7885 8
created 6.2 49.8678 5
created 6.44 29.9207 3
created 6.68 79.7885 8
created 6.92 69.8149 7
created 7.16 89.762 9
created 7.4 29.9207 3
created 7.64 19.9471 2
created 7.88 49.8678 5
created 8.12 29.9207 3
created 8.36 39.8942 4
created 8.6 9.97356 1
created 8.84 9.97356 1
created 9.08 39.8942 4
created 9.32 49.8678 5
created 9.56 9.97356 1
created 9.8 9.97356 1
the total number of created peaks = 83 with sigma = 0.04
the total number of found peaks = 83 with sigma = 0.0400021 (+-7.42016e-06)
fit chi^2 = 2.59904e-06
found -6.52 (+-8.47418e-05) 99.7349 (+-0.20792) 10.0004 (+-0.000722346)
found -6.28 (+-8.46494e-05) 99.7344 (+-0.207892) 10.0004 (+-0.00072225)
found -2.92 (+-8.43348e-05) 99.7328 (+-0.207799) 10.0002 (+-0.000721928)
found -9.64 (+-8.41284e-05) 99.7319 (+-0.207741) 10.0002 (+-0.000721727)
found -9.16 (+-8.41283e-05) 99.732 (+-0.207741) 10.0002 (+-0.000721727)
found -7.48 (+-8.44464e-05) 99.7331 (+-0.207829) 10.0003 (+-0.000722031)
found -3.88 (+-8.44173e-05) 99.7331 (+-0.207822) 10.0003 (+-0.000722007)
found -0.519999 (+-8.45779e-05) 99.7339 (+-0.207869) 10.0003 (+-0.000722171)
found -3.4 (+-8.92741e-05) 89.7611 (+-0.197235) 9.00037 (+-0.000685226)
found 7.16 (+-8.9041e-05) 89.76 (+-0.197173) 9.00026 (+-0.000685009)
found -4.36 (+-8.87203e-05) 89.7587 (+-0.197088) 9.00013 (+-0.000684715)
found 0.200001 (+-8.88509e-05) 89.7592 (+-0.197122) 9.00018 (+-0.000684835)
found 0.920001 (+-8.89509e-05) 89.7597 (+-0.19715) 9.00024 (+-0.000684931)
found 3.8 (+-8.89407e-05) 89.7595 (+-0.197145) 9.00021 (+-0.000684913)
found -5.32 (+-9.47715e-05) 79.788 (+-0.185976) 8.00037 (+-0.000646109)
found -0.280002 (+-9.45493e-05) 79.7875 (+-0.185926) 8.00032 (+-0.000645937)
found 4.52 (+-9.46409e-05) 79.7875 (+-0.185944) 8.00032 (+-0.000646)
found 5.96 (+-9.46592e-05) 79.7875 (+-0.185948) 8.00032 (+-0.000646012)
found -7.96 (+-9.43026e-05) 79.7862 (+-0.185863) 8.00018 (+-0.000645719)
found -1 (+-9.44017e-05) 79.7865 (+-0.185886) 8.00021 (+-0.000645796)
found 4.28 (+-9.45617e-05) 79.7873 (+-0.185926) 8.00029 (+-0.000645936)
found 6.68 (+-9.45132e-05) 79.787 (+-0.185913) 8.00027 (+-0.000645893)
found -5.08 (+-0.000101073) 69.8139 (+-0.173916) 7.00026 (+-0.000604211)
found -3.64 (+-0.000101682) 69.8163 (+-0.174047) 7.0005 (+-0.000604667)
found -3.16 (+-0.000101682) 69.8163 (+-0.174047) 7.0005 (+-0.000604667)
found 1.16 (+-0.000101466) 69.8153 (+-0.173998) 7.0004 (+-0.000604498)
found 6.92 (+-0.000101582) 69.8158 (+-0.174024) 7.00045 (+-0.000604588)
found -6.76 (+-0.000101448) 69.8153 (+-0.173995) 7.0004 (+-0.000604486)
found -5.56 (+-0.000100914) 69.8137 (+-0.173886) 7.00024 (+-0.000604108)
found 5.72 (+-0.000101348) 69.8147 (+-0.173972) 7.00035 (+-0.000604407)
found 1.4 (+-0.000109043) 59.8404 (+-0.160994) 6.00021 (+-0.00055932)
found 5.24 (+-0.000109206) 59.8404 (+-0.161018) 6.00021 (+-0.000559402)
found -8.68 (+-0.000108814) 59.8396 (+-0.16095) 6.00013 (+-0.000559168)
found 1.88 (+-0.000108591) 59.839 (+-0.16091) 6.00008 (+-0.000559029)
found -9.4 (+-0.000120773) 49.8705 (+-0.147173) 5.00053 (+-0.000511302)
found -7.24 (+-0.000120385) 49.8692 (+-0.147109) 5.0004 (+-0.000511082)
found -6.04 (+-0.000119802) 49.8682 (+-0.147024) 5.0003 (+-0.000510786)
found 0.439997 (+-0.000119949) 49.8682 (+-0.147042) 5.00029 (+-0.000510849)
found -7.72 (+-0.000120636) 49.87 (+-0.14715) 5.00048 (+-0.000511222)
found -7 (+-0.000120174) 49.8684 (+-0.147074) 5.00032 (+-0.000510959)
found -2.2 (+-0.000119533) 49.8668 (+-0.146974) 5.00016 (+-0.000510612)
found -0.759999 (+-0.000120636) 49.87 (+-0.14715) 5.00048 (+-0.000511222)
found 3.56 (+-0.000120217) 49.8687 (+-0.147082) 5.00035 (+-0.000510988)
found 5.48 (+-0.000120265) 49.8687 (+-0.147089) 5.00035 (+-0.00051101)
found 6.2 (+-0.000120028) 49.8682 (+-0.147052) 5.00029 (+-0.000510884)
found 9.32 (+-0.000119323) 49.8665 (+-0.146945) 5.00013 (+-0.000510511)
found 7.88 (+-0.000119415) 49.8665 (+-0.146956) 5.00013 (+-0.000510549)
found -8.44 (+-0.000134077) 39.8943 (+-0.131513) 4.00021 (+-0.000456897)
found 4.76 (+-0.000134449) 39.8951 (+-0.13156) 4.00029 (+-0.000457062)
found 8.36 (+-0.000133447) 39.8932 (+-0.131435) 4.00011 (+-0.000456628)
found -2.44 (+-0.000133966) 39.894 (+-0.131498) 4.00019 (+-0.000456847)
found -1.48 (+-0.000133699) 39.8935 (+-0.131464) 4.00013 (+-0.000456727)
found 3.32 (+-0.000133713) 39.8938 (+-0.13147) 4.00016 (+-0.000456747)
found 9.08 (+-0.000133713) 39.8937 (+-0.13147) 4.00016 (+-0.000456747)
found -4.12 (+-0.000156745) 29.9242 (+-0.114084) 3.00051 (+-0.000396347)
found 4.04 (+-0.000156531) 29.9237 (+-0.114062) 3.00045 (+-0.00039627)
found 7.4 (+-0.000155541) 29.9221 (+-0.113966) 3.0003 (+-0.000395936)
found 6.44 (+-0.000156022) 29.9226 (+-0.114011) 3.00035 (+-0.000396091)
found 8.12 (+-0.000155462) 29.9215 (+-0.113954) 3.00024 (+-0.000395895)
found -1.24 (+-0.000155857) 29.9223 (+-0.113994) 3.00032 (+-0.000396035)
found 2.6 (+-0.000154462) 29.9202 (+-0.113858) 3.00011 (+-0.000395562)
found 5 (+-0.000155607) 29.9218 (+-0.113969) 3.00027 (+-0.000395946)
found -2.68001 (+-0.000192045) 19.9498 (+-0.0931564) 2.00038 (+-0.00032364)
found -0.0399991 (+-0.000192711) 19.9506 (+-0.0932013) 2.00045 (+-0.000323796)
found -4.84 (+-0.000190967) 19.9485 (+-0.0930833) 2.00024 (+-0.000323386)
found -1.96 (+-0.000190579) 19.948 (+-0.0930562) 2.00019 (+-0.000323292)
found 0.680004 (+-0.000192144) 19.9498 (+-0.0931622) 2.00038 (+-0.00032366)
found 2.12 (+-0.000190785) 19.9482 (+-0.0930704) 2.00021 (+-0.000323342)
found -8.2 (+-0.000191753) 19.9493 (+-0.0931352) 2.00032 (+-0.000323567)
found -4.59999 (+-0.000191284) 19.949 (+-0.0931061) 2.0003 (+-0.000323466)
found -1.72 (+-0.000190346) 19.9477 (+-0.0930402) 2.00016 (+-0.000323237)
found 2.36 (+-0.000190073) 19.9474 (+-0.0930219) 2.00013 (+-0.000323173)
found 2.84 (+-0.000189613) 19.9472 (+-0.0929937) 2.00011 (+-0.000323075)
found 7.64 (+-0.000190917) 19.9482 (+-0.0930779) 2.00021 (+-0.000323367)
found -8.92001 (+-0.000274974) 9.97731 (+-0.0659936) 1.00043 (+-0.000229272)
found 1.64 (+-0.000273878) 9.97624 (+-0.0659518) 1.00032 (+-0.000229127)
found -5.8 (+-0.000273832) 9.97625 (+-0.0659504) 1.00032 (+-0.000229122)
found 8.59999 (+-0.000270302) 9.97439 (+-0.0658282) 1.00013 (+-0.000228698)
found 9.55999 (+-0.000270712) 9.97465 (+-0.0658432) 1.00016 (+-0.00022875)
found 3.08 (+-0.000271179) 9.97465 (+-0.0658566) 1.00016 (+-0.000228796)
found 8.84001 (+-0.000270302) 9.97439 (+-0.0658282) 1.00014 (+-0.000228698)
found 9.8 (+-0.000265727) 9.97358 (+-0.0656931) 1.00005 (+-0.000228228)
found -9.87998 (+-0.000271377) 9.97576 (+-0.0658702) 1.00027 (+-0.000228843)
#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;
}
d
#define d(i)
Definition: RSha256.hxx:102
f
#define f(i)
Definition: RSha256.hxx:104
h
#define h(i)
Definition: RSha256.hxx:106
x1
static const double x1[5]
Definition: RooGaussKronrodIntegrator1D.cxx:346
Int_t
int Int_t
Definition: RtypesCore.h:43
kFALSE
const Bool_t kFALSE
Definition: RtypesCore.h:90
Bool_t
bool Bool_t
Definition: RtypesCore.h:61
Double_t
double Double_t
Definition: RtypesCore.h:57
kRed
@ kRed
Definition: Rtypes.h:64
xmin
float xmin
Definition: THbookFile.cxx:93
xmax
float xmax
Definition: THbookFile.cxx:93
gROOT
#define gROOT
Definition: TROOT.h:406
gRandom
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
TAttMarker::SetMarkerColor
virtual void SetMarkerColor(Color_t mcolor=1)
Set the marker color.
Definition: TAttMarker.h:38
TAttMarker::SetMarkerStyle
virtual void SetMarkerStyle(Style_t mstyle=1)
Set the marker style.
Definition: TAttMarker.h:40
TAttMarker::SetMarkerSize
virtual void SetMarkerSize(Size_t msize=1)
Set the marker size.
Definition: TAttMarker.h:41
TCanvas
The Canvas class.
Definition: TCanvas.h:27
TCanvas::Clear
void Clear(Option_t *option="")
Remove all primitives from the canvas.
Definition: TCanvas.cxx:720
TF1
1-Dim function class
Definition: TF1.h:210
TH1F
1-D histogram with a float per channel (see TH1 documentation)}
Definition: TH1.h:571
TPolyMarker
A PolyMarker is defined by an array on N points in a 2-D space.
Definition: TPolyMarker.h:31
TRandom::SetSeed
virtual void SetSeed(ULong_t seed=0)
Set the random generator seed.
Definition: TRandom.cxx:597
TRandom::Uniform
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition: TRandom.cxx:635
TSpectrumFit
Advanced 1-dimensional spectra fitting functions.
Definition: TSpectrumFit.h:18
TSpectrumFit::GetChi
Double_t GetChi() const
Definition: TSpectrumFit.h:121
TSpectrumFit::SetPeakParameters
void SetPeakParameters(Double_t sigma, Bool_t fixSigma, const Double_t *positionInit, const Bool_t *fixPosition, const Double_t *ampInit, const Bool_t *fixAmp)
This function sets the following fitting parameters of peaks:
Definition: TSpectrumFit.cxx:2656
TSpectrumFit::GetAmplitudesErrors
Double_t * GetAmplitudesErrors() const
Definition: TSpectrumFit.h:117
TSpectrumFit::FitAwmi
void FitAwmi(Double_t *source)
This function fits the source spectrum.
Definition: TSpectrumFit.cxx:820
TSpectrumFit::GetAreasErrors
Double_t * GetAreasErrors() const
Definition: TSpectrumFit.h:119
TSpectrumFit::GetSigma
void GetSigma(Double_t &sigma, Double_t &sigmaErr)
This function gets the sigma parameter and its error.
Definition: TSpectrumFit.cxx:2725
TSpectrumFit::kFitTaylorOrderFirst
@ kFitTaylorOrderFirst
Definition: TSpectrumFit.h:82
TSpectrumFit::GetAreas
Double_t * GetAreas() const
Definition: TSpectrumFit.h:118
TSpectrumFit::GetAmplitudes
Double_t * GetAmplitudes() const
Definition: TSpectrumFit.h:116
TSpectrumFit::SetFitParameters
void SetFitParameters(Int_t xmin, Int_t xmax, Int_t numberIterations, Double_t alpha, Int_t statisticType, Int_t alphaOptim, Int_t power, Int_t fitTaylor)
This function sets the following fitting parameters:
Definition: TSpectrumFit.cxx:2608
TSpectrumFit::GetPositionsErrors
Double_t * GetPositionsErrors() const
Definition: TSpectrumFit.h:123
TSpectrumFit::GetPositions
Double_t * GetPositions() const
Definition: TSpectrumFit.h:122
TSpectrum
Advanced Spectra Processing.
Definition: TSpectrum.h:18
sigma
const Double_t sigma
Definition: h1analysisProxy.h:11
TGeant4Unit::s
static constexpr double s
Definition: TGeant4SystemOfUnits.h:162
TMath::Sqrt2
constexpr Double_t Sqrt2()
Definition: TMath.h:89
TMath::Sqrt
Double_t Sqrt(Double_t x)
Definition: TMath.h:681
TMath::TwoPi
constexpr Double_t TwoPi()
Definition: TMath.h:45
dest
#define dest(otri, vertexptr)
Definition: triangle.c:1040
Author

Definition in file FitAwmi.C.