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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 19.9471 5
created -9.1 11.9683 3
created -8.5 15.9577 4
created -7.9 35.9048 9
created -7.3 3.98942 1
created -6.7 27.926 7
created -6.1 19.9471 5
created -5.5 11.9683 3
created -4.9 27.926 7
created -4.3 31.9154 8
created -3.7 3.98942 1
created -3.1 23.9365 6
created -2.5 19.9471 5
created -1.9 35.9048 9
created -1.3 27.926 7
created -0.7 27.926 7
created -0.1 23.9365 6
created 0.5 15.9577 4
created 1.1 27.926 7
created 1.7 39.8942 10
created 2.3 3.98942 1
created 2.9 11.9683 3
created 3.5 35.9048 9
created 4.1 11.9683 3
created 4.7 35.9048 9
created 5.3 15.9577 4
created 5.9 39.8942 10
created 6.5 31.9154 8
created 7.1 7.97885 2
created 7.7 23.9365 6
created 8.3 15.9577 4
created 8.9 7.97885 2
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 (+-4.39221e-05)
fit chi^2 = 5.56434e-06
found 1.7 (+-0.000326052) 39.8939 (+-0.128699) 10.0001 (+-0.00105617)
found 5.9 (+-0.000327223) 39.8941 (+-0.128751) 10.0002 (+-0.00105659)
found -7.9 (+-0.000343243) 35.9044 (+-0.122075) 9.00006 (+-0.00100181)
found -1.9 (+-0.000345237) 35.9047 (+-0.122157) 9.00015 (+-0.00100248)
found 3.5 (+-0.000343786) 35.9044 (+-0.122096) 9.00008 (+-0.00100198)
found 4.7 (+-0.000344068) 35.9045 (+-0.122107) 9.00009 (+-0.00100207)
found 6.5 (+-0.000366049) 31.9154 (+-0.115169) 8.00015 (+-0.000945132)
found -4.3 (+-0.000364979) 31.9152 (+-0.115129) 8.0001 (+-0.000944802)
found 9.50001 (+-0.000362165) 31.9153 (+-0.115035) 8.00012 (+-0.000944033)
found -1.3 (+-0.000393108) 27.9263 (+-0.10779) 7.00021 (+-0.000884575)
found -6.7 (+-0.000389984) 27.9257 (+-0.107686) 7.00008 (+-0.000883721)
found -4.9 (+-0.000391741) 27.926 (+-0.107743) 7.00014 (+-0.000884192)
found -0.7 (+-0.000392449) 27.9261 (+-0.107766) 7.00017 (+-0.000884383)
found 1.1 (+-0.000392483) 27.9262 (+-0.107769) 7.00018 (+-0.000884403)
found -3.1 (+-0.000421599) 23.9364 (+-0.0997079) 6.00008 (+-0.000818252)
found -0.100001 (+-0.000423773) 23.9367 (+-0.0997691) 6.00014 (+-0.000818754)
found 7.7 (+-0.000421949) 23.9364 (+-0.0997161) 6.00008 (+-0.000818319)
found -9.7 (+-0.000462664) 19.9469 (+-0.0910305) 5.00004 (+-0.000747041)
found -6.1 (+-0.000464425) 19.9473 (+-0.0910819) 5.00013 (+-0.000747463)
found -2.5 (+-0.000466227) 19.9475 (+-0.0911273) 5.00019 (+-0.000747835)
found 0.500001 (+-0.000521712) 15.9581 (+-0.081516) 4.00017 (+-0.00066896)
found 5.3 (+-0.000523766) 15.9584 (+-0.0815598) 4.00025 (+-0.000669319)
found 8.3 (+-0.000519097) 15.9578 (+-0.0814637) 4.0001 (+-0.000668531)
found -8.5 (+-0.000520875) 15.958 (+-0.0815001) 4.00016 (+-0.00066883)
found -9.1 (+-0.00060195) 11.9685 (+-0.0705876) 3.00012 (+-0.000579276)
found -5.5 (+-0.000603628) 11.9687 (+-0.0706142) 3.00016 (+-0.000579495)
found 4.1 (+-0.00060642) 11.969 (+-0.0706596) 3.00023 (+-0.000579867)
found 2.90001 (+-0.000600863) 11.9686 (+-0.0705756) 3.00013 (+-0.000579178)
found 7.1 (+-0.000744043) 7.97942 (+-0.0577083) 2.00018 (+-0.000473582)
found 8.9 (+-0.000742355) 7.97932 (+-0.0576901) 2.00016 (+-0.000473433)
found -7.3 (+-0.00106479) 3.99018 (+-0.0408791) 1.00021 (+-0.000335474)
found -3.7 (+-0.0010625) 3.99008 (+-0.0408654) 1.00018 (+-0.000335361)
found 2.29998 (+-0.00105951) 3.99003 (+-0.0408496) 1.00017 (+-0.000335232)
#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
Bool_t
bool Bool_t
Boolean (0=false, 1=true) (bool)
Definition RtypesCore.h:77
Int_t
int Int_t
Signed integer 4 bytes (int)
Definition RtypesCore.h:59
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
TRangeDynCast
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Definition TCollection.h:359
dest
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t dest
Definition TGWin32VirtualXProxy.cxx:164
x1
Option_t Option_t TPoint TPoint const char x1
Definition TGWin32VirtualXProxy.cxx:70
xmin
float xmin
Definition THbookFile.cxx:95
xmax
float xmax
Definition THbookFile.cxx:95
gROOT
#define gROOT
Definition TROOT.h:411
gRandom
R__EXTERN TRandom * gRandom
Definition TRandom.h:62
TCanvas
The Canvas class.
Definition TCanvas.h:23
TF1
1-Dim function class
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
TRandom::SetSeed
virtual void SetSeed(ULong_t seed=0)
Set the random generator seed.
Definition TRandom.cxx:614
TRandom::Uniform
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition TRandom.cxx:681
TSpectrumFit
Advanced 1-dimensional spectra fitting functions.
Definition TSpectrumFit.h:18
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:2118
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
Author

Definition in file FitAwmi.C.