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FitAwmi.C File Reference
Tutorials » Spectrum tutorials

Detailed Description

View in nbviewer Open in SWAN 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 -9.76 49.8678 10
created -9.28 34.9074 7
created -8.8 19.9471 4
created -8.32 39.8942 8
created -7.84 4.98678 1
created -7.36 49.8678 10
created -6.88 39.8942 8
created -6.4 49.8678 10
created -5.92 4.98678 1
created -5.44 39.8942 8
created -4.96 19.9471 4
created -4.48 19.9471 4
created -4 29.9207 6
created -3.52 19.9471 4
created -3.04 29.9207 6
created -2.56 34.9074 7
created -2.08 49.8678 10
created -1.6 44.881 9
created -1.12 39.8942 8
created -0.64 44.881 9
created -0.16 24.9339 5
created 0.32 39.8942 8
created 0.8 4.98678 1
created 1.28 29.9207 6
created 1.76 34.9074 7
created 2.24 4.98678 1
created 2.72 24.9339 5
created 3.2 29.9207 6
created 3.68 49.8678 10
created 4.16 9.97356 2
created 4.64 29.9207 6
created 5.12 34.9074 7
created 5.6 34.9074 7
created 6.08 49.8678 10
created 6.56 29.9207 6
created 7.04 44.881 9
created 7.52 4.98678 1
created 8 34.9074 7
created 8.48 4.98678 1
created 8.96 9.97356 2
created 9.44 14.9603 3
the total number of created peaks = 41 with sigma = 0.08
the total number of found peaks = 41 with sigma = 0.0800011 (+-1.70199e-05)
fit chi^2 = 1.76989e-06
found -9.76 (+-0.000146408) 49.8675 (+-0.0899809) 10.0001 (+-0.00059587)
found -7.36 (+-0.000145914) 49.8676 (+-0.0899549) 10.0001 (+-0.000595698)
found -6.4 (+-0.000145914) 49.8676 (+-0.0899549) 10.0001 (+-0.000595698)
found -2.08 (+-0.000146698) 49.8679 (+-0.0900104) 10.0002 (+-0.000596065)
found 3.68 (+-0.000145961) 49.8675 (+-0.0899563) 10.0001 (+-0.000595707)
found 6.08 (+-0.000146482) 49.8678 (+-0.0899939) 10.0001 (+-0.000595956)
found -1.6 (+-0.000154904) 44.8813 (+-0.0854103) 9.00018 (+-0.000565602)
found -0.64 (+-0.000154503) 44.8811 (+-0.0853826) 9.00013 (+-0.000565419)
found 7.04 (+-0.000153734) 44.8808 (+-0.0853333) 9.00007 (+-0.000565093)
found -8.32 (+-0.000162939) 39.8939 (+-0.0804454) 8.00005 (+-0.000532724)
found -6.88 (+-0.000164617) 39.8947 (+-0.0805456) 8.0002 (+-0.000533387)
found -5.44 (+-0.000162939) 39.8939 (+-0.0804454) 8.00005 (+-0.000532724)
found -1.12 (+-0.000164467) 39.8946 (+-0.080536) 8.00018 (+-0.000533324)
found 0.319999 (+-0.000163058) 39.894 (+-0.0804526) 8.00006 (+-0.000532771)
found -9.28 (+-0.000175559) 34.9077 (+-0.0753209) 7.00014 (+-0.000498788)
found -2.56 (+-0.000175815) 34.9078 (+-0.0753344) 7.00016 (+-0.000498878)
found 1.76 (+-0.000174558) 34.9073 (+-0.0752692) 7.00007 (+-0.000498446)
found 5.12 (+-0.000175543) 34.9076 (+-0.0753192) 7.00013 (+-0.000498777)
found 5.6 (+-0.000175922) 34.9078 (+-0.0753402) 7.00017 (+-0.000498917)
found 8 (+-0.000173692) 34.9071 (+-0.0752251) 7.00002 (+-0.000498154)
found 6.56 (+-0.000190495) 29.9212 (+-0.0697745) 6.00019 (+-0.00046206)
found -4 (+-0.000189143) 29.9207 (+-0.0697106) 6.00008 (+-0.000461636)
found -3.04 (+-0.000189555) 29.9208 (+-0.0697298) 6.00011 (+-0.000461763)
found 1.28 (+-0.000188836) 29.9207 (+-0.0696992) 6.00008 (+-0.000461561)
found 3.2 (+-0.000190019) 29.921 (+-0.069752) 6.00015 (+-0.00046191)
found 4.64 (+-0.000189148) 29.9207 (+-0.069712) 6.00009 (+-0.000461645)
found -0.16 (+-0.000208821) 24.9344 (+-0.063701) 5.00017 (+-0.00042184)
found 2.72 (+-0.000206966) 24.9339 (+-0.0636301) 5.00007 (+-0.00042137)
found -8.8 (+-0.000233697) 19.9476 (+-0.0569835) 4.00015 (+-0.000377355)
found -4.96 (+-0.000233106) 19.9475 (+-0.0569645) 4.00012 (+-0.000377229)
found -3.52 (+-0.000233191) 19.9475 (+-0.0569668) 4.00012 (+-0.000377245)
found -4.48 (+-0.000232776) 19.9474 (+-0.0569536) 4.0001 (+-0.000377157)
found 9.44 (+-0.000265289) 14.9604 (+-0.049251) 3.00005 (+-0.000326149)
found 4.16 (+-0.00033332) 9.97424 (+-0.0403421) 2.00016 (+-0.000267153)
found 8.96 (+-0.000328372) 9.97363 (+-0.0402598) 2.00004 (+-0.000266608)
found -7.84 (+-0.000477246) 4.98763 (+-0.0285798) 1.00018 (+-0.000189261)
found -5.92 (+-0.000477246) 4.98763 (+-0.0285798) 1.00018 (+-0.000189261)
found 7.52 (+-0.000476304) 4.98753 (+-0.0285709) 1.00016 (+-0.000189202)
found 0.799997 (+-0.000475276) 4.98743 (+-0.0285613) 1.00014 (+-0.000189138)
found 2.24 (+-0.00047414) 4.98733 (+-0.0285509) 1.00012 (+-0.000189069)
found 8.47999 (+-0.000471475) 4.98717 (+-0.028528) 1.00009 (+-0.000188918)
#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:45
kFALSE
const Bool_t kFALSE
Definition RtypesCore.h:92
Bool_t
bool Bool_t
Definition RtypesCore.h:63
Double_t
double Double_t
Definition RtypesCore.h:59
kRed
@ kRed
Definition Rtypes.h:66
xmin
float xmin
Definition THbookFile.cxx:95
xmax
float xmax
Definition THbookFile.cxx:95
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:23
TCanvas::Clear
void Clear(Option_t *option="") override
Remove all primitives from the canvas.
Definition TCanvas.cxx:727
TF1
1-Dim function class
Definition TF1.h:213
TH1F
1-D histogram with a float per channel (see TH1 documentation)}
Definition TH1.h:575
TH1::FindObject
virtual TObject * FindObject(const char *name) const
Search object named name in the list of functions.
Definition TH1.cxx:3865
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:608
TRandom::Uniform
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition TRandom.cxx:672
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::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
TSpectrum::SearchHighRes
Int_t SearchHighRes(Double_t *source, Double_t *destVector, Int_t ssize, Double_t sigma, Double_t threshold, bool backgroundRemove, Int_t deconIterations, bool markov, Int_t averWindow)
One-dimensional high-resolution peak search function.
Definition TSpectrum.cxx:2127
TSpectrum::GetPositionX
Double_t * GetPositionX() const
Definition TSpectrum.h:58
sigma
const Double_t sigma
Definition h1analysisProxy.h:11
TMath::Sqrt2
constexpr Double_t Sqrt2()
Definition TMath.h:88
TMath::Sqrt
Double_t Sqrt(Double_t x)
Definition TMath.h:691
TMath::TwoPi
constexpr Double_t TwoPi()
Definition TMath.h:44
dest
#define dest(otri, vertexptr)
Definition triangle.c:1040
Author

Definition in file FitAwmi.C.