11 class TLandauMean: public TObject {
13 void Init(Int_t n, Float_t mean, Float_t sigma); // initial parameters
14 void Gener(); // gener sample
18 Int_t fNSample; // number of samples
19 Float_t fLMean; // landau mean
20 Float_t fLSigma; // landau sigma
22 Float_t fTM_0_6[3]; // truncated method - first 3 momenta
23 Float_t fTM_0_7[3]; // truncated method - first 3 momenta
24 Float_t fTM_0_8[3]; // truncated method - first 3 momenta
25 Float_t fTM_0_10[3]; // truncated method - first 3 momenta
27 Float_t fLM_0_6[3]; // truncated log. method - first 3 momenta
28 Float_t fLM_0_7[3]; // truncated log. method - first 3 momenta
29 Float_t fLM_0_8[3]; // truncated log. method - first 3 momenta
30 Float_t fLM_0_10[3]; // truncated log. method - first 3 momenta
32 Float_t fMedian3; // median 3 value
34 Float_t Moment3(Float_t sum1, Float_t sum2, Float_t sum3, Int_t n, Float_t m[3]);
35 ClassDef(TLandauMean,1)
40 void TLandauMean::Init(Int_t n, Float_t mean, Float_t sigma)
49 Float_t TLandauMean::Moment3(Float_t sumi1, Float_t sumi2, Float_t sumi3, Int_t sum, Float_t m[3])
53 // m3 = (sumi3-3*pos*sumi2+3*pos*pos*sumi-pos*pos*pos*sum)/sum;
54 Float_t pos = sumi1/sum;
56 m[1] = sumi2/sum-pos*pos;
58 printf("pici pici\n");
61 m[1] = TMath::Sqrt(m[1]);
62 m3 = (sumi3-3*pos*sumi2+3*pos*pos*sumi1-pos*pos*pos*sum)/sum;
63 Float_t sign = m3/TMath::Abs(m3);
64 m3 = TMath::Power(sign*m3,1/3.);
71 void TLandauMean::Gener()
75 Float_t * buffer = new Float_t[fNSample];
77 for (Int_t i=0;i<fNSample;i++) {
78 buffer[i] = gRandom->Landau(fLMean,fLSigma);
79 if (buffer[i]>1000) buffer[i]=1000;
82 Int_t *index = new Int_t[fNSample];
83 TMath::Sort(fNSample,buffer,index,kFALSE);
86 Float_t median = buffer[index[fNSample/3]];
88 Float_t sum06[4] = {0.,0.,0.,0.};
89 Float_t sum07[4] = {0.,0.,0.,0.};
90 Float_t sum08[4] = {0.,0.,0.,0.};
91 Float_t sum010[4] = {0.,0.,0.,0.};
93 Float_t suml06[4] = {0.,0.,0.,0.};
94 Float_t suml07[4] = {0.,0.,0.,0.};
95 Float_t suml08[4] = {0.,0.,0.,0.};
96 Float_t suml010[4] = {0.,0.,0.,0.};
99 for (Int_t i =0; i<fNSample; i++){
100 Float_t amp = buffer[index[i]];
101 Float_t lamp = median*TMath::Log(1.+amp/median);
105 sum06[2]+= amp*amp*amp;
108 suml06[1]+= lamp*lamp;
109 suml06[2]+= lamp*lamp*lamp;
116 sum07[2]+= amp*amp*amp;
119 suml07[1]+= lamp*lamp;
120 suml07[2]+= lamp*lamp*lamp;
126 sum08[2]+= amp*amp*amp;
129 suml08[1]+= lamp*lamp;
130 suml08[2]+= lamp*lamp*lamp;
136 sum010[2]+= amp*amp*amp;
139 suml010[1]+= lamp*lamp;
140 suml010[2]+= lamp*lamp*lamp;
148 Moment3(sum06[0],sum06[1],sum06[2],sum06[3],fTM_0_6);
149 Moment3(sum07[0],sum07[1],sum07[2],sum07[3],fTM_0_7);
150 Moment3(sum08[0],sum08[1],sum08[2],sum08[3],fTM_0_8);
151 Moment3(sum010[0],sum010[1],sum010[2],sum010[3],fTM_0_10);
154 Moment3(suml06[0],suml06[1],suml06[2],suml06[3],fLM_0_6);
155 Moment3(suml07[0],suml07[1],suml07[2],suml07[3],fLM_0_7);
156 Moment3(suml08[0],suml08[1],suml08[2],suml08[3],fLM_0_8);
157 Moment3(suml010[0],suml010[1],suml010[2],suml010[3],fLM_0_10);
159 fLM_0_6[0] = (TMath::Exp(fLM_0_6[0]/median)-1.)*median;
160 fLM_0_7[0] = (TMath::Exp(fLM_0_7[0]/median)-1.)*median;
161 fLM_0_8[0] = (TMath::Exp(fLM_0_8[0]/median)-1.)*median;
162 fLM_0_10[0] = (TMath::Exp(fLM_0_10[0]/median)-1.)*median;
168 void GenerLandau(Int_t nsamples)
170 TLandauMean * landau = new TLandauMean;
171 TFile f("Landau.root","recreate");
172 TTree * tree = new TTree("Landau","Landau");
173 tree->Branch("Landau","TLandauMean",&landau);
175 for (Int_t i=0;i<nsamples;i++){
176 Int_t n = 20 + Int_t(gRandom->Rndm()*150);
177 Float_t mean = 40. +gRandom->Rndm()*50.;
178 Float_t sigma = 5. +gRandom->Rndm()*15.;
179 landau->Init(n, mean, sigma);
192 TH1F * LandauTest(Float_t meano, Float_t sigma, Float_t meanlog0, Int_t n,Float_t ratio)
195 // test for different approach of de dx resolution
196 // meano, sigma - mean value of Landau distribution and sigma
197 // meanlog0 - scaling factor for logarithmic mean value
198 // n - number of used layers
199 // ratio - ratio of used amplitudes for truncated mean
203 TCanvas * pad = new TCanvas("Landau test");
205 TH1F * h1 = new TH1F("h1","Logarithmic mean",300,0,4*meano);
206 TH1F * h2 = new TH1F("h2","Logarithmic amplitudes",300,0,8*meano);
207 TH1F * h3 = new TH1F("h3","Mean",300,0,4*meano);
208 TH1F * h4 = new TH1F("h4","Amplitudes",300,0,8*meano);
210 for(Int_t j=0;j<10000;j++){
211 //generate sample and sort it
212 Float_t * buffer = new Float_t[n];
213 Float_t * buffer2= new Float_t[n];
215 for (Int_t i=0;i<n;i++) {
216 buffer[i] = gRandom->Landau(meano,sigma);
217 buffer2[i] = buffer[i];
220 for (Int_t i=1;i<n-1;i++) {
221 buffer[i] = buffer2[i]*1.0+ buffer2[i-1]*0.0+ buffer2[i+1]*0.0;
222 buffer[i] = TMath::Min(buffer[i],1000.);
224 Int_t *index = new Int_t[n];
225 TMath::Sort(n,buffer,index,kFALSE);
232 for (Int_t i=0;i<n*ratio;i++) {
233 if (buffer[index[i]]<1000.){
234 Float_t amp = meanlog0*TMath::Log(1+buffer[index[i]]/meanlog0);
244 Float_t meanlog =meanlog0;
245 for (Int_t i=0;i<n*ratio;i++) {
246 if (buffer[index[i]]<1000.){
247 Float_t amp = meanlog*TMath::Log(1.+buffer[index[i]]/(meanlog));
249 sum2+=buffer[index[i]];
252 h4->Fill(buffer[index[i]]);
256 mean = (TMath::Exp(mean/meanlog)-1)*meanlog;
257 Float_t mean2 = sum2/used;
258 //mean2 = (mean+mean2)/2.;