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FitAwmi.C File Reference
Tutorials » Legacy tutorials » Spectrum tutorials

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 -9.7 15.9577 4
created -9.1 23.9365 6
created -8.5 35.9048 9
created -7.9 7.97885 2
created -7.3 11.9683 3
created -6.7 3.98942 1
created -6.1 7.97885 2
created -5.5 31.9154 8
created -4.9 15.9577 4
created -4.3 39.8942 10
created -3.7 15.9577 4
created -3.1 19.9471 5
created -2.5 39.8942 10
created -1.9 27.926 7
created -1.3 27.926 7
created -0.7 39.8942 10
created -0.1 3.98942 1
created 0.5 3.98942 1
created 1.1 11.9683 3
created 1.7 15.9577 4
created 2.3 31.9154 8
created 2.9 23.9365 6
created 3.5 31.9154 8
created 4.1 39.8942 10
created 4.7 23.9365 6
created 5.3 15.9577 4
created 5.9 39.8942 10
created 6.5 11.9683 3
created 7.1 39.8942 10
created 7.7 39.8942 10
created 8.3 19.9471 5
created 8.9 3.98942 1
created 9.5 31.9154 8
the total number of created peaks = 33 with sigma = 0.1
the total number of found peaks = 33 with sigma = 0.100002 (+-4.30368e-05)
fit chi^2 = 5.54738e-06
found -4.3 (+-0.000325978) 39.8939 (+-0.128519) 10.0001 (+-0.00105469)
found -2.5 (+-0.000326785) 39.8941 (+-0.128557) 10.0002 (+-0.001055)
found -0.700001 (+-0.000325555) 39.8939 (+-0.128503) 10.0001 (+-0.00105456)
found 4.1 (+-0.000327139) 39.8942 (+-0.128574) 10.0002 (+-0.00105514)
found 5.9 (+-0.000325722) 39.8938 (+-0.128507) 10.0001 (+-0.00105459)
found 7.1 (+-0.000326748) 39.8941 (+-0.128557) 10.0002 (+-0.001055)
found 7.7 (+-0.000327228) 39.8942 (+-0.128579) 10.0002 (+-0.00105518)
found -8.5 (+-0.000343646) 35.9045 (+-0.121927) 9.0001 (+-0.00100059)
found -5.5 (+-0.000364247) 31.9151 (+-0.114944) 8.00008 (+-0.000943284)
found 2.3 (+-0.000365448) 31.9153 (+-0.114989) 8.00013 (+-0.000943653)
found 3.5 (+-0.000366704) 31.9156 (+-0.115038) 8.00021 (+-0.00094406)
found 9.50001 (+-0.000361094) 31.9152 (+-0.114841) 8.00011 (+-0.000942445)
found -1.9 (+-0.000392696) 27.9263 (+-0.107632) 7.00022 (+-0.000883282)
found -1.3 (+-0.000392696) 27.9263 (+-0.107632) 7.00022 (+-0.000883282)
found 4.7 (+-0.000423815) 23.9368 (+-0.0996385) 6.00018 (+-0.000817682)
found -9.1 (+-0.000423603) 23.9368 (+-0.0996318) 6.00017 (+-0.000817627)
found 2.9 (+-0.00042455) 23.9369 (+-0.0996598) 6.00021 (+-0.000817857)
found 8.3 (+-0.000463101) 19.9473 (+-0.0909323) 5.00014 (+-0.000746235)
found -3.1 (+-0.000464999) 19.9475 (+-0.0909759) 5.00018 (+-0.000746593)
found -4.9 (+-0.00052264) 15.9583 (+-0.0814284) 4.00023 (+-0.000668241)
found -3.7 (+-0.000521459) 15.9582 (+-0.0814039) 4.0002 (+-0.00066804)
found 5.3 (+-0.000521895) 15.9582 (+-0.0814128) 4.00021 (+-0.000668113)
found -9.7 (+-0.000518375) 15.9577 (+-0.0813342) 4.00008 (+-0.000667468)
found 1.7 (+-0.000519759) 15.958 (+-0.0813689) 4.00014 (+-0.000667753)
found 6.5 (+-0.000606269) 11.9691 (+-0.0705648) 3.00026 (+-0.000579089)
found -7.3 (+-0.000595816) 11.9682 (+-0.0704024) 3.00004 (+-0.000577756)
found 1.1 (+-0.000597455) 11.9683 (+-0.0704272) 3.00006 (+-0.00057796)
found -7.90001 (+-0.000740737) 7.97932 (+-0.0575977) 2.00016 (+-0.000472675)
found -6.09999 (+-0.000736966) 7.97916 (+-0.0575598) 2.00012 (+-0.000472364)
found -0.10002 (+-0.00105201) 3.98993 (+-0.0407571) 1.00015 (+-0.000334473)
found 8.90001 (+-0.00105947) 3.99003 (+-0.0407949) 1.00017 (+-0.000334783)
found -6.7 (+-0.00104638) 3.98961 (+-0.0407203) 1.00007 (+-0.00033417)
found 0.500004 (+-0.00104301) 3.98956 (+-0.040703) 1.00005 (+-0.000334029)
#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
Int_t
int Int_t
Signed integer 4 bytes (int).
Definition RtypesCore.h:59
Bool_t
bool Bool_t
Boolean (0=false, 1=true) (bool).
Definition RtypesCore.h:77
kFALSE
constexpr Bool_t kFALSE
Definition RtypesCore.h:108
Double_t
double Double_t
Double 8 bytes.
Definition RtypesCore.h:73
kRed
@ kRed
Definition Rtypes.h:67
xmin
float xmin
Definition THbookFile.cxx:95
xmax
float xmax
Definition THbookFile.cxx:95
gROOT
#define gROOT
Definition TROOT.h:417
gRandom
externTRandom * gRandom
Definition TRandom.h:62
TAttMarker::SetMarkerColor
virtual void SetMarkerColor(Color_t mcolor=1)
Set the marker color.
Definition TAttMarker.h:41
TAttMarker::SetMarkerStyle
virtual void SetMarkerStyle(Style_t mstyle=1)
Set the marker style.
Definition TAttMarker.h:43
TAttMarker::SetMarkerSize
virtual void SetMarkerSize(Size_t msize=1)
Set the marker size.
Definition TAttMarker.h:48
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:734
TF1
Definition TF1.h:182
TH1F
1-D histogram with a float per channel (see TH1 documentation)
Definition TH1.h:878
TPolyMarker
A PolyMarker is defined by an array on N points in a 2-D space.
Definition TPolyMarker.h:31
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:2657
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:821
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:2726
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:2609
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)
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:89
TMath::Sqrt
Double_t Sqrt(Double_t x)
Returns the square root of x.
Definition TMath.h:673
TMath::TwoPi
constexpr Double_t TwoPi()
Definition TMath.h:47
hist015_TH1_read_and_draw_uhi.dx
dx
Definition hist015_TH1_read_and_draw_uhi.py:58
Author

Definition in file FitAwmi.C.