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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 39.8942 4
created -9.64 49.8678 5
created -9.4 99.7356 10
created -9.16 79.7885 8
created -8.92 9.97356 1
created -8.68 39.8942 4
created -8.44 99.7356 10
created -8.2 19.9471 2
created -7.96 9.97356 1
created -7.72 29.9207 3
created -7.48 49.8678 5
created -7.24 49.8678 5
created -7 59.8413 6
created -6.76 19.9471 2
created -6.52 79.7885 8
created -6.28 49.8678 5
created -6.04 99.7356 10
created -5.8 19.9471 2
created -5.56 49.8678 5
created -5.32 89.762 9
created -5.08 89.762 9
created -4.84 39.8942 4
created -4.6 19.9471 2
created -4.36 39.8942 4
created -4.12 59.8413 6
created -3.88 29.9207 3
created -3.64 69.8149 7
created -3.4 39.8942 4
created -3.16 49.8678 5
created -2.92 59.8413 6
created -2.68 59.8413 6
created -2.44 49.8678 5
created -2.2 39.8942 4
created -1.96 69.8149 7
created -1.72 39.8942 4
created -1.48 79.7885 8
created -1.24 49.8678 5
created -1 19.9471 2
created -0.76 19.9471 2
created -0.52 89.762 9
created -0.28 39.8942 4
created -0.04 69.8149 7
created 0.2 79.7885 8
created 0.44 29.9207 3
created 0.68 59.8413 6
created 0.92 69.8149 7
created 1.16 99.7356 10
created 1.4 99.7356 10
created 1.64 79.7885 8
created 1.88 49.8678 5
created 2.12 59.8413 6
created 2.36 69.8149 7
created 2.6 59.8413 6
created 2.84 79.7885 8
created 3.08 39.8942 4
created 3.32 49.8678 5
created 3.56 79.7885 8
created 3.8 39.8942 4
created 4.04 59.8413 6
created 4.28 49.8678 5
created 4.52 89.762 9
created 4.76 69.8149 7
created 5 29.9207 3
created 5.24 49.8678 5
created 5.48 39.8942 4
created 5.72 19.9471 2
created 5.96 99.7356 10
created 6.2 39.8942 4
created 6.44 79.7885 8
created 6.68 89.762 9
created 6.92 79.7885 8
created 7.16 9.97356 1
created 7.4 29.9207 3
created 7.64 99.7356 10
created 7.88 49.8678 5
created 8.12 29.9207 3
created 8.36 19.9471 2
created 8.6 69.8149 7
created 8.84 29.9207 3
created 9.08 99.7356 10
created 9.32 89.762 9
created 9.56 39.8942 4
created 9.8 99.7356 10
the total number of created peaks = 83 with sigma = 0.04
the total number of found peaks = 83 with sigma = 0.040002 (+-1.798e-05)
fit chi^2 = 1.67531e-05
found 1.16 (+-0.000215149) 99.735 (+-0.527883) 10.0005 (+-0.00183395)
found 1.4 (+-0.000215251) 99.7353 (+-0.527914) 10.0005 (+-0.00183406)
found -9.4 (+-0.000214733) 99.7339 (+-0.527754) 10.0003 (+-0.0018335)
found -8.44 (+-0.000213745) 99.732 (+-0.527466) 10.0002 (+-0.0018325)
found -6.04 (+-0.000213884) 99.7323 (+-0.527507) 10.0002 (+-0.00183264)
found 5.96 (+-0.000213745) 99.7321 (+-0.527466) 10.0002 (+-0.0018325)
found 7.64 (+-0.000214093) 99.7326 (+-0.527564) 10.0002 (+-0.00183284)
found 9.08 (+-0.000214519) 99.7337 (+-0.527696) 10.0003 (+-0.0018333)
found 9.8 (+-0.000212701) 99.7342 (+-0.527226) 10.0004 (+-0.00183166)
found -5.08 (+-0.00022646) 89.7609 (+-0.500705) 9.00034 (+-0.00173953)
found 6.68 (+-0.000226879) 89.7617 (+-0.500819) 9.00042 (+-0.00173992)
found 9.32 (+-0.000226556) 89.7612 (+-0.500733) 9.00037 (+-0.00173963)
found -5.32 (+-0.000226614) 89.7611 (+-0.500746) 9.00037 (+-0.00173967)
found -0.52 (+-0.00022543) 89.759 (+-0.500429) 9.00016 (+-0.00173857)
found 4.52 (+-0.000226399) 89.7606 (+-0.500685) 9.00032 (+-0.00173946)
found -9.16 (+-0.000239689) 79.7873 (+-0.471968) 8.00029 (+-0.00163969)
found 0.199999 (+-0.000239957) 79.787 (+-0.472011) 8.00026 (+-0.00163984)
found 1.64 (+-0.000240675) 79.7884 (+-0.472188) 8.0004 (+-0.00164046)
found 2.84 (+-0.000240023) 79.7871 (+-0.472024) 8.00026 (+-0.00163989)
found 6.92 (+-0.000239582) 79.787 (+-0.47194) 8.00026 (+-0.00163959)
found -6.52 (+-0.000239423) 79.7863 (+-0.471884) 8.00019 (+-0.0016394)
found -1.48 (+-0.000239874) 79.7868 (+-0.471987) 8.00024 (+-0.00163976)
found 3.56 (+-0.000239874) 79.7868 (+-0.471987) 8.00024 (+-0.00163976)
found 6.44 (+-0.000240396) 79.7879 (+-0.472119) 8.00035 (+-0.00164022)
found 0.920001 (+-0.000257733) 69.8156 (+-0.441789) 7.00043 (+-0.00153484)
found 2.36 (+-0.000257186) 69.8145 (+-0.441665) 7.00032 (+-0.00153441)
found 4.76 (+-0.000257023) 69.8145 (+-0.441636) 7.00032 (+-0.00153431)
found -3.64 (+-0.000256245) 69.8132 (+-0.441464) 7.00019 (+-0.00153371)
found -1.96 (+-0.000256469) 69.8135 (+-0.44151) 7.00021 (+-0.00153388)
found -0.039999 (+-0.000257119) 69.8145 (+-0.441653) 7.00032 (+-0.00153437)
found 8.6 (+-0.000255742) 69.8127 (+-0.441361) 7.00013 (+-0.00153336)
found -7 (+-0.00027694) 59.8402 (+-0.408749) 6.00019 (+-0.00142006)
found -4.12 (+-0.000277042) 59.8402 (+-0.408764) 6.00019 (+-0.00142011)
found -2.92 (+-0.000277929) 59.8412 (+-0.408928) 6.00029 (+-0.00142068)
found -2.68 (+-0.000277929) 59.8412 (+-0.408928) 6.00029 (+-0.00142068)
found 0.680001 (+-0.000277628) 59.841 (+-0.408875) 6.00027 (+-0.0014205)
found 2.12 (+-0.000278105) 59.8415 (+-0.408962) 6.00032 (+-0.0014208)
found 2.6 (+-0.000278639) 59.8423 (+-0.409065) 6.0004 (+-0.00142116)
found 4.04 (+-0.000277516) 59.8407 (+-0.408851) 6.00024 (+-0.00142041)
found 7.88 (+-0.000305078) 49.8687 (+-0.373406) 5.00035 (+-0.00129727)
found -9.64 (+-0.000305382) 49.869 (+-0.373452) 5.00037 (+-0.00129743)
found -7.48 (+-0.000304109) 49.8674 (+-0.373246) 5.00021 (+-0.00129671)
found -7.24 (+-0.000304899) 49.8682 (+-0.373369) 5.00029 (+-0.00129714)
found -6.28 (+-0.000306279) 49.87 (+-0.373596) 5.00048 (+-0.00129793)
found -3.16 (+-0.000304639) 49.8679 (+-0.373329) 5.00027 (+-0.001297)
found -2.44 (+-0.000304639) 49.8679 (+-0.373329) 5.00027 (+-0.001297)
found -1.24 (+-0.00030436) 49.8679 (+-0.373293) 5.00027 (+-0.00129688)
found 1.88 (+-0.00030553) 49.869 (+-0.373472) 5.00037 (+-0.0012975)
found 3.32 (+-0.000305039) 49.8684 (+-0.373394) 5.00032 (+-0.00129723)
found 4.28 (+-0.000305708) 49.8692 (+-0.373502) 5.0004 (+-0.0012976)
found 5.24 (+-0.000303852) 49.8671 (+-0.373205) 5.00019 (+-0.00129657)
found -5.56 (+-0.000304536) 49.8682 (+-0.373323) 5.0003 (+-0.00129698)
found -4.84 (+-0.000341106) 39.8951 (+-0.333991) 4.00029 (+-0.00116034)
found -0.280001 (+-0.000342801) 39.8965 (+-0.334204) 4.00043 (+-0.00116108)
found 6.2 (+-0.000343242) 39.897 (+-0.334263) 4.00048 (+-0.00116128)
found 9.56 (+-0.000343462) 39.8973 (+-0.334293) 4.00051 (+-0.00116139)
found -3.4 (+-0.000341804) 39.8954 (+-0.334072) 4.00032 (+-0.00116062)
found -2.2 (+-0.000341804) 39.8954 (+-0.334072) 4.00032 (+-0.00116062)
found -1.72 (+-0.000342582) 39.8962 (+-0.334174) 4.0004 (+-0.00116097)
found 3.08 (+-0.000342039) 39.8957 (+-0.334103) 4.00035 (+-0.00116073)
found 3.8 (+-0.000342324) 39.8959 (+-0.33414) 4.00037 (+-0.00116086)
found 5.48 (+-0.000340124) 39.8941 (+-0.333858) 4.00019 (+-0.00115988)
found -9.88 (+-0.000340028) 39.8936 (+-0.333818) 4.00014 (+-0.00115974)
found -8.68 (+-0.000340657) 39.8952 (+-0.333945) 4.0003 (+-0.00116018)
found -4.36 (+-0.000340404) 39.8943 (+-0.333895) 4.00021 (+-0.00116001)
found 0.439999 (+-0.000396491) 29.9229 (+-0.289496) 3.00037 (+-0.00100575)
found -3.88 (+-0.000396187) 29.9226 (+-0.289465) 3.00035 (+-0.00100565)
found 5 (+-0.000395816) 29.9224 (+-0.289428) 3.00032 (+-0.00100552)
found 8.12 (+-0.000393628) 29.921 (+-0.289215) 3.00019 (+-0.00100478)
found 8.84 (+-0.000397367) 29.9237 (+-0.289586) 3.00045 (+-0.00100607)
found -7.72 (+-0.000392806) 29.9208 (+-0.289143) 3.00016 (+-0.00100453)
found 7.40001 (+-0.000394323) 29.9221 (+-0.289301) 3.0003 (+-0.00100508)
found -8.20001 (+-0.000484807) 19.9491 (+-0.236339) 2.0003 (+-0.00082108)
found -5.8 (+-0.000488187) 19.9501 (+-0.236553) 2.0004 (+-0.000821824)
found -6.76 (+-0.000487974) 19.9498 (+-0.236536) 2.00037 (+-0.000821763)
found -1 (+-0.000483857) 19.948 (+-0.236258) 2.00019 (+-0.000820798)
found -4.6 (+-0.000484819) 19.9482 (+-0.236319) 2.00021 (+-0.00082101)
found -0.759993 (+-0.000485646) 19.9491 (+-0.236385) 2.0003 (+-0.000821239)
found 5.72001 (+-0.000487579) 19.9498 (+-0.236513) 2.00037 (+-0.000821682)
found 8.36 (+-0.000485706) 19.9488 (+-0.236382) 2.00027 (+-0.00082123)
found -8.92001 (+-0.000694867) 9.97627 (+-0.167429) 1.00032 (+-0.000581676)
found 7.15999 (+-0.000693571) 9.97601 (+-0.167385) 1.0003 (+-0.000581521)
found -7.96 (+-0.000687227) 9.9744 (+-0.167157) 1.00014 (+-0.000580731)
#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
Definition RtypesCore.h:63
Int_t
int Int_t
Definition RtypesCore.h:45
kFALSE
constexpr Bool_t kFALSE
Definition RtypesCore.h:101
Double_t
double Double_t
Definition RtypesCore.h:59
kRed
@ kRed
Definition Rtypes.h:66
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: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:45
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
1-Dim function class
Definition TF1.h:233
TH1F
1-D histogram with a float per channel (see TH1 documentation)
Definition TH1.h:621
TH1::FindObject
TObject * FindObject(const char *name) const override
Search object named name in the list of functions.
Definition TH1.cxx:3857
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:615
TRandom::Uniform
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition TRandom.cxx:682
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:2658
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:822
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:2727
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:2610
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:2129
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:86
TMath::Sqrt
Double_t Sqrt(Double_t x)
Returns the square root of x.
Definition TMath.h:662
TMath::TwoPi
constexpr Double_t TwoPi()
Definition TMath.h:44
Author

Definition in file FitAwmi.C.