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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 35.9048 9
created -9.1 23.9365 6
created -8.5 15.9577 4
created -7.9 7.97885 2
created -7.3 31.9154 8
created -6.7 3.98942 1
created -6.1 27.926 7
created -5.5 3.98942 1
created -4.9 19.9471 5
created -4.3 7.97885 2
created -3.7 35.9048 9
created -3.1 11.9683 3
created -2.5 15.9577 4
created -1.9 15.9577 4
created -1.3 15.9577 4
created -0.7 27.926 7
created -0.1 11.9683 3
created 0.5 23.9365 6
created 1.1 27.926 7
created 1.7 23.9365 6
created 2.3 39.8942 10
created 2.9 11.9683 3
created 3.5 27.926 7
created 4.1 19.9471 5
created 4.7 3.98942 1
created 5.3 27.926 7
created 5.9 39.8942 10
created 6.5 27.926 7
created 7.1 11.9683 3
created 7.7 11.9683 3
created 8.3 19.9471 5
created 8.9 15.9577 4
created 9.5 11.9683 3
the total number of created peaks = 33 with sigma = 0.1
the total number of found peaks = 33 with sigma = 0.100002 (+-2.86803e-05)
fit chi^2 = 2.14895e-06
found 2.3 (+-0.000202985) 39.8939 (+-0.0799949) 10.0001 (+-0.000656478)
found 5.9 (+-0.000203621) 39.8942 (+-0.0800249) 10.0002 (+-0.000656724)
found -9.7 (+-0.000214384) 35.9044 (+-0.0759012) 9.00008 (+-0.000622882)
found -3.7 (+-0.000213431) 35.9044 (+-0.0758676) 9.00006 (+-0.000622607)
found -7.3 (+-0.000225946) 31.9149 (+-0.0715135) 8.00004 (+-0.000586875)
found 6.5 (+-0.000243687) 27.9261 (+-0.0669656) 7.00017 (+-0.000549553)
found -6.1 (+-0.000241316) 27.9255 (+-0.0668877) 7.00002 (+-0.000548913)
found -0.7 (+-0.000242815) 27.9258 (+-0.0669349) 7.00009 (+-0.000549301)
found 1.1 (+-0.000243739) 27.926 (+-0.0669662) 7.00015 (+-0.000549558)
found 3.5 (+-0.000243001) 27.9258 (+-0.0669413) 7.0001 (+-0.000549353)
found 5.3 (+-0.000243036) 27.926 (+-0.0669456) 7.00014 (+-0.000549388)
found -9.1 (+-0.00026365) 23.9367 (+-0.0620107) 6.00017 (+-0.00050889)
found 0.500001 (+-0.000263101) 23.9366 (+-0.0619943) 6.00013 (+-0.000508755)
found 1.7 (+-0.00026436) 23.937 (+-0.062032) 6.00022 (+-0.000509065)
found -4.9 (+-0.000286424) 19.9469 (+-0.0565502) 5.00004 (+-0.000464079)
found 4.1 (+-0.000287739) 19.9471 (+-0.0565829) 5.0001 (+-0.000464347)
found 8.3 (+-0.000287949) 19.9471 (+-0.0565859) 5.00009 (+-0.000464371)
found -8.5 (+-0.000322593) 15.9578 (+-0.0506256) 4.0001 (+-0.000415459)
found 8.9 (+-0.000322774) 15.9578 (+-0.0506286) 4.0001 (+-0.000415483)
found -2.5 (+-0.000322471) 15.9578 (+-0.0506224) 4.00009 (+-0.000415433)
found -1.9 (+-0.000322829) 15.9578 (+-0.0506296) 4.0001 (+-0.000415491)
found -1.3 (+-0.000323642) 15.958 (+-0.0506464) 4.00014 (+-0.000415629)
found -3.1 (+-0.000375266) 11.9687 (+-0.0438859) 3.00017 (+-0.00036015)
found -0.100001 (+-0.00037547) 11.9687 (+-0.0438887) 3.00017 (+-0.000360172)
found 2.9 (+-0.000376558) 11.9689 (+-0.0439065) 3.00022 (+-0.000360319)
found 7.1 (+-0.000374266) 11.9686 (+-0.0438701) 3.00013 (+-0.000360019)
found 7.7 (+-0.00037362) 11.9685 (+-0.0438596) 3.0001 (+-0.000359933)
found 9.5 (+-0.000369576) 11.9684 (+-0.0438078) 3.00009 (+-0.000359509)
found -7.9 (+-0.000461337) 7.97932 (+-0.0358515) 2.00016 (+-0.000294215)
found -4.3 (+-0.000462258) 7.97942 (+-0.0358616) 2.00018 (+-0.000294298)
found -6.7 (+-0.000661072) 3.99013 (+-0.0254004) 1.0002 (+-0.000208448)
found -5.5 (+-0.000658718) 3.98997 (+-0.0253865) 1.00016 (+-0.000208334)
found 4.7 (+-0.000658717) 3.98997 (+-0.0253865) 1.00016 (+-0.000208334)
#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.