| 1 |
#include <iostream> |
| 2 |
#include <fstream> |
| 3 |
#include <stdio.h> |
| 4 |
#include <math.h> |
| 5 |
#include <TH1F.h> |
| 6 |
#include <TH2F.h> |
| 7 |
#include <TH1D.h> |
| 8 |
#include <TH2D.h> |
| 9 |
#include <TFile.h> |
| 10 |
#include <TROOT.h> |
| 11 |
#include <TList.h> |
| 12 |
#include <TString.h> |
| 13 |
//#include <TObjectString.h> |
| 14 |
#include <TGraphAsymmErrors.h> |
| 15 |
#include <TGraphErrors.h> |
| 16 |
#include <TChain.h> |
| 17 |
#include <TCutG.h> |
| 18 |
#include <TF1.h> |
| 19 |
#include <TCanvas.h> |
| 20 |
#include <TObjString.h> |
| 21 |
#include <TMath.h> |
| 22 |
|
| 23 |
#include <PamUnfold.h> |
| 24 |
|
| 25 |
using namespace std; |
| 26 |
|
| 27 |
ClassImp(PamUnfold); |
| 28 |
|
| 29 |
|
| 30 |
PamUnfold::PamUnfold(TString name, TString title) : TNamed(name, title){ |
| 31 |
|
| 32 |
cout << "WARNING:: entering PamUnfold::PamUnfold(TString name, TString title)" << endl; |
| 33 |
cout << " empty constructor be sure to initialize measured and smearing" << endl; |
| 34 |
|
| 35 |
_measured = NULL; |
| 36 |
_smearing = NULL; |
| 37 |
_prior = NULL; |
| 38 |
|
| 39 |
} |
| 40 |
|
| 41 |
PamUnfold::~PamUnfold(){ |
| 42 |
} |
| 43 |
|
| 44 |
PamUnfold::PamUnfold(TString name, TString title, TH1D* measured, TH2D* smearing) : TNamed(name, title){ |
| 45 |
|
| 46 |
_measured = measured; |
| 47 |
_smearing = smearing; |
| 48 |
_prior = NULL; |
| 49 |
|
| 50 |
if( !IsBinningOK() ) |
| 51 |
cerr << " -- ERROR in PamUnfold::PamUnfold(TString name, TString title, TH1D* measured, TH2D* smearing)" << endl; |
| 52 |
|
| 53 |
if( !IsSmNormalized() ){ |
| 54 |
cerr << " -- WARNING in PamUnfold::PamUnfold(TString name, TString title, TH1D* measured, TH2D* smearing)" << endl; |
| 55 |
cerr << " ---- Remember to provide the normalization histogram for the smearing matrix" << endl; |
| 56 |
} |
| 57 |
|
| 58 |
Init(); |
| 59 |
|
| 60 |
_is_improved = kFALSE; |
| 61 |
_smooth = kFALSE; |
| 62 |
_smooth_opt = "ROOT"; |
| 63 |
|
| 64 |
_nsamples = 500; |
| 65 |
_max_steps = 50; |
| 66 |
_min_chi2 = 1.; |
| 67 |
|
| 68 |
} |
| 69 |
|
| 70 |
void PamUnfold::AddExcludedBin(Int_t bin){ |
| 71 |
_excluded_bins.push_back(bin); |
| 72 |
} |
| 73 |
|
| 74 |
TH1D* PamUnfold::GetMeasured(){ |
| 75 |
return _measured; |
| 76 |
} |
| 77 |
|
| 78 |
TH2D* PamUnfold::GetSmearing(){ |
| 79 |
return _smearing; |
| 80 |
} |
| 81 |
|
| 82 |
TH1D* PamUnfold::GetUnfolded(){ |
| 83 |
TH1D* __unfolded = (TH1D*) _unfolded->Clone( Form("%s_%s_unf", _measured->GetName(), this->GetName()) ); |
| 84 |
return __unfolded; |
| 85 |
} |
| 86 |
|
| 87 |
TList* PamUnfold::GetBinHistList(){ |
| 88 |
return _bin_hist_list; |
| 89 |
} |
| 90 |
|
| 91 |
void PamUnfold::SetMeasured(TH1D* measured){ |
| 92 |
_measured = measured; |
| 93 |
} |
| 94 |
|
| 95 |
void PamUnfold::SetSmearing(TH2D* smearing){ |
| 96 |
|
| 97 |
_smearing = smearing; |
| 98 |
|
| 99 |
if( !IsBinningOK() ) |
| 100 |
cerr << " -- ERROR in PamUnfold::SetSmearing(TH2D* smearing)" << endl; |
| 101 |
|
| 102 |
Init(); |
| 103 |
|
| 104 |
} |
| 105 |
|
| 106 |
void PamUnfold::SetPrior(TH1D* prior){ |
| 107 |
|
| 108 |
_prior = (TH1D*) prior->Clone( Form("_prior_%s", this->GetName()) ); |
| 109 |
|
| 110 |
if( !IsBinningOK() ) |
| 111 |
cerr << " -- ERROR in PamUnfold::SetPrior(TH1D* prior)" << endl; |
| 112 |
|
| 113 |
} |
| 114 |
|
| 115 |
void PamUnfold::SetNormalization(TH1D* norm){ |
| 116 |
_norm = norm; |
| 117 |
|
| 118 |
//If the matrix is not normalized it is normalized now. |
| 119 |
if( !IsSmNormalized() ){ |
| 120 |
cout << " Normalizing smearing matrix" << endl; |
| 121 |
|
| 122 |
try{ if(!_norm) throw 1; } |
| 123 |
catch(int e){ |
| 124 |
if(e==1){ |
| 125 |
cerr << " -- ERROR in PamUnfold::Init()" << endl; |
| 126 |
cerr << " ---- Normalization histogram is NULL" << endl; |
| 127 |
cerr << " execution is likely to crash." << endl; |
| 128 |
} |
| 129 |
} |
| 130 |
|
| 131 |
NormalizeMatrix(); |
| 132 |
|
| 133 |
} |
| 134 |
|
| 135 |
} |
| 136 |
|
| 137 |
void PamUnfold::SetImproved(Bool_t improv){ |
| 138 |
_is_improved = improv; |
| 139 |
} |
| 140 |
|
| 141 |
void PamUnfold::SetSmoothing(Bool_t smooth, TString smooth_opt){ |
| 142 |
|
| 143 |
_smooth = smooth; |
| 144 |
_smooth_opt = smooth_opt; |
| 145 |
|
| 146 |
if(!_smooth_opt.CompareTo("")) |
| 147 |
_smooth_opt = "ROOT"; |
| 148 |
|
| 149 |
} |
| 150 |
|
| 151 |
void PamUnfold::SetNsamples(UInt_t nsamples){ |
| 152 |
_nsamples = nsamples; |
| 153 |
} |
| 154 |
|
| 155 |
void PamUnfold::SetMaxSteps(UInt_t max_steps){ |
| 156 |
_max_steps = max_steps; |
| 157 |
} |
| 158 |
|
| 159 |
void PamUnfold::SetMinChi2(Double_t min_chi2){ |
| 160 |
_min_chi2 = min_chi2; |
| 161 |
} |
| 162 |
|
| 163 |
|
| 164 |
Bool_t PamUnfold::IsSmNormalized(){ |
| 165 |
|
| 166 |
Double_t sum = 0; |
| 167 |
for(UInt_t i=0; i<_smearing->GetNbinsX(); i++){ |
| 168 |
sum = 0; |
| 169 |
for(UInt_t j=0; j<_smearing->GetNbinsY(); j++) |
| 170 |
sum += _smearing->GetBinContent(_smearing->GetBin(i+1,j+1)); |
| 171 |
if(sum>1.0000001){ |
| 172 |
cout << "Bin: " << i+1 << " sum=" << sum << endl; |
| 173 |
return kFALSE; |
| 174 |
} |
| 175 |
} |
| 176 |
|
| 177 |
return kTRUE; |
| 178 |
|
| 179 |
} |
| 180 |
|
| 181 |
void PamUnfold::WMovAvSmooth(TH1D* input, vector<Int_t>&excl){ |
| 182 |
|
| 183 |
Double_t* xarr = new Double_t [input->GetNbinsX()]; |
| 184 |
|
| 185 |
for(UInt_t ib=0; ib<input->GetNbinsX(); ib++) |
| 186 |
xarr[ib] = (Double_t) input->GetBinContent(ib+1); |
| 187 |
|
| 188 |
Bool_t excluding; |
| 189 |
for(UInt_t ib=1; ib<input->GetNbinsX()-1; ib++){ |
| 190 |
|
| 191 |
excluding = kFALSE; |
| 192 |
for(UInt_t iex=0; iex<excl.size(); iex++) |
| 193 |
if( |
| 194 |
ib == excl[iex] || |
| 195 |
ib+1 == excl[iex] || |
| 196 |
ib+2 == excl[iex] |
| 197 |
) excluding = kTRUE; |
| 198 |
if(excluding) continue; |
| 199 |
|
| 200 |
Double_t xc = xarr[ib]; |
| 201 |
Double_t xl = xarr[ib-1]; |
| 202 |
Double_t xh = xarr[ib+1]; |
| 203 |
Double_t x = 0.25*(xh+xl) + 0.5*xc; |
| 204 |
input->SetBinContent(ib+1, (Float_t) x); |
| 205 |
} |
| 206 |
|
| 207 |
delete xarr; |
| 208 |
|
| 209 |
return; |
| 210 |
|
| 211 |
} |
| 212 |
|
| 213 |
Double_t PamUnfold::GetChi2H( TH1D* h1, TH1D* h2 ){ |
| 214 |
|
| 215 |
if(h1->GetNbinsX() != h2->GetNbinsX()){ |
| 216 |
cout << " -- Warning in PamUnfold::GetChi2H(TH1D*, TH1D*) : Histograms have different number of bins" << endl; |
| 217 |
return -1; |
| 218 |
} |
| 219 |
|
| 220 |
const Double_t* x_1 = h1->GetXaxis()->GetXbins()->GetArray(); |
| 221 |
const Double_t* x_2 = h2->GetXaxis()->GetXbins()->GetArray(); |
| 222 |
|
| 223 |
for(Int_t ib=0; ib < h1->GetNbinsX()+1; ib++){ |
| 224 |
if(x_1[ib] != x_2[ib]){ |
| 225 |
cout << " -- Warning in PamUnfold::GetChi2H(TH1D*, TH1D*) : Histograms have different number of bins" << endl; |
| 226 |
return -1; |
| 227 |
} |
| 228 |
else |
| 229 |
continue; |
| 230 |
} |
| 231 |
|
| 232 |
|
| 233 |
|
| 234 |
Double_t chi2 = 0; |
| 235 |
for(UInt_t i=0; i<h1->GetNbinsX(); i++){ |
| 236 |
if(h1->GetBinContent(i+1) + h2->GetBinContent(i+2) > 1) |
| 237 |
chi2 += pow(h1->GetBinContent(i+1) - h2->GetBinContent(i+1),2)/(h1->GetBinContent(i+1) + h2->GetBinContent(i+2)); |
| 238 |
else |
| 239 |
chi2 += pow(h1->GetBinContent(i+1) - h2->GetBinContent(i+1),2); |
| 240 |
} |
| 241 |
|
| 242 |
return chi2; |
| 243 |
} |
| 244 |
|
| 245 |
void PamUnfold::Unfold(){ |
| 246 |
|
| 247 |
|
| 248 |
//Smoothing is applied to the spectrum, not to the counts histogram!!! |
| 249 |
// ------------------------------------------------------ |
| 250 |
// Prior initialization |
| 251 |
// ------------------------------------------------------ |
| 252 |
|
| 253 |
for(Int_t i=0; i<_prior->GetNbinsX(); i++) |
| 254 |
_prior->SetBinContent(i+1, _prior->GetBinContent(i+1)/_prior->GetBinWidth(i+1) ); |
| 255 |
|
| 256 |
if(_smooth){ |
| 257 |
if(_smooth_opt.Contains("WMA")){ |
| 258 |
cout << " --- Using Weighted Moving Average smoothing\n"; |
| 259 |
WMovAvSmooth(_prior, _excluded_bins); |
| 260 |
} |
| 261 |
else if(_smooth_opt.Contains("ROOT")){ |
| 262 |
cout << " --- Using standard ROOT smoothing\n"; |
| 263 |
_prior->Smooth(); |
| 264 |
} |
| 265 |
else |
| 266 |
cout << " --- WARNING: No valid smoothing option specified" << endl; |
| 267 |
} |
| 268 |
|
| 269 |
for(Int_t i=0; i<_prior->GetNbinsX(); i++) |
| 270 |
_prior->SetBinContent(i+1, _prior->GetBinContent(i+1)*_prior->GetBinWidth(i+1) ); |
| 271 |
|
| 272 |
_prior->Scale(1./_prior->GetSumOfWeights()); //The prior is a 'probability' so it has to be normalized at the very last step |
| 273 |
|
| 274 |
// ------------------------------------------------------ |
| 275 |
// Unfolding |
| 276 |
// ------------------------------------------------------ |
| 277 |
|
| 278 |
cout << " --- UNFOLDING!!" << endl; |
| 279 |
|
| 280 |
TH2D* theta = (TH2D*) _smearing->Clone("theta"); |
| 281 |
theta->Reset(); |
| 282 |
|
| 283 |
for(Int_t i=0; i<theta->GetNbinsY(); i++){ |
| 284 |
for(Int_t j=0; j<theta->GetNbinsX(); j++){ |
| 285 |
|
| 286 |
Double_t s = _smearing->GetBinContent(_smearing->GetBin(i+1,j+1))*_prior->GetBinContent(i+1); |
| 287 |
Double_t ls = 0; |
| 288 |
for(Int_t k=0; k<_smearing->GetNbinsX(); k++) |
| 289 |
ls+=_smearing->GetBinContent(_smearing->GetBin(k+1,j+1))*_prior->GetBinContent(k+1); |
| 290 |
|
| 291 |
if(ls) |
| 292 |
theta->SetBinContent(theta->GetBin(j+1,i+1),s/ls); |
| 293 |
} |
| 294 |
} |
| 295 |
|
| 296 |
_unfolded->Reset(); |
| 297 |
|
| 298 |
for(Int_t i=0; i<_unfolded->GetNbinsX(); i++){ |
| 299 |
Double_t num = 0; |
| 300 |
Double_t den = 0; |
| 301 |
Double_t err = 0; |
| 302 |
for(Int_t j=0; j<theta->GetNbinsX(); j++){ |
| 303 |
|
| 304 |
num+=theta->GetBinContent( theta->GetBin(j+1,i+1) )*_measured->GetBinContent(j+1); |
| 305 |
den+=_smearing->GetBinContent(_smearing->GetBin(i+1,j+1)); |
| 306 |
err+=pow( theta->GetBinContent(theta->GetBin(j+1,i+1))*_measured->GetBinError(j+1), 1 ); |
| 307 |
// err+=pow( theta->GetBinContent(theta->GetBin(j+1,i+1))*sp->GetBinError(j+1), 2 ); |
| 308 |
|
| 309 |
} |
| 310 |
|
| 311 |
if(den){ |
| 312 |
_unfolded->SetBinContent(i+1, num/den); |
| 313 |
_unfolded->SetBinError(i+1, fabs(err)/den); |
| 314 |
// _unfolded->SetBinError(i+1,sqrt(err)/den); |
| 315 |
} |
| 316 |
} |
| 317 |
|
| 318 |
} |
| 319 |
|
| 320 |
|
| 321 |
void PamUnfold::ImprovedUnfold(){ |
| 322 |
|
| 323 |
|
| 324 |
vector<Int_t> mu(_measured->GetNbinsX()); |
| 325 |
|
| 326 |
//Smoothing is applied to the spectrum, not to the counts histogram!!! |
| 327 |
// ------------------------------------------------------ |
| 328 |
// Prior initialization |
| 329 |
// ------------------------------------------------------ |
| 330 |
|
| 331 |
for(Int_t i=0; i<_prior->GetNbinsX(); i++) |
| 332 |
_prior->SetBinContent(i+1, _prior->GetBinContent(i+1)/_prior->GetBinWidth(i+1) ); |
| 333 |
|
| 334 |
if(_smooth){ |
| 335 |
if(_smooth_opt.Contains("WMA")){ |
| 336 |
cout << " --- Using Weighted Moving Average smoothing\n"; |
| 337 |
WMovAvSmooth(_prior, _excluded_bins); |
| 338 |
} |
| 339 |
else if(_smooth_opt.Contains("ROOT")){ |
| 340 |
cout << " --- Using standard ROOT smoothing\n"; |
| 341 |
_prior->Smooth(); |
| 342 |
} |
| 343 |
else |
| 344 |
cout << " --- WARNING: No valid smoothing option specified" << endl; |
| 345 |
} |
| 346 |
|
| 347 |
for(Int_t i=0; i<_prior->GetNbinsX(); i++) |
| 348 |
_prior->SetBinContent(i+1, _prior->GetBinContent(i+1)*_prior->GetBinWidth(i+1) ); |
| 349 |
|
| 350 |
_prior->Scale(1./_prior->GetSumOfWeights()); //The prior is a 'probability' so it has to be normalized at the very last step |
| 351 |
|
| 352 |
// ------------------------------------------------------ |
| 353 |
// Unfolding |
| 354 |
// ------------------------------------------------------ |
| 355 |
|
| 356 |
cout << " --- UNFOLDING!!" << endl; |
| 357 |
|
| 358 |
_bin_list->Clear(); |
| 359 |
|
| 360 |
TMVA::Timer* timer = new TMVA::Timer(_nsamples, "unf"); |
| 361 |
for(UInt_t sample=0; sample<_nsamples; sample++){ |
| 362 |
|
| 363 |
cout << " ---- Sampling... " << timer->GetLeftTime(sample) << " left..." << endl << flush <<"\33[1A"; |
| 364 |
|
| 365 |
SampleMatrix(); |
| 366 |
|
| 367 |
TH2D* theta = (TH2D*) _smearing_sample->Clone("theta"); |
| 368 |
theta->Reset(); |
| 369 |
|
| 370 |
for(Int_t i=0; i<theta->GetNbinsY(); i++){ |
| 371 |
for(Int_t j=0; j<theta->GetNbinsX(); j++){ |
| 372 |
|
| 373 |
Double_t s = _smearing_sample->GetBinContent(_smearing_sample->GetBin(i+1,j+1))*_prior->GetBinContent(i+1); |
| 374 |
Double_t ls = 0; |
| 375 |
for(Int_t k=0; k<_smearing_sample->GetNbinsX(); k++) |
| 376 |
ls+=_smearing_sample->GetBinContent(_smearing_sample->GetBin(k+1,j+1))*_prior->GetBinContent(k+1); |
| 377 |
|
| 378 |
if(ls) |
| 379 |
theta->SetBinContent(theta->GetBin(j+1,i+1),s/ls); |
| 380 |
|
| 381 |
} |
| 382 |
} |
| 383 |
|
| 384 |
TVectorD* result = new TVectorD(_unfolded->GetNbinsX()); |
| 385 |
|
| 386 |
//Sampling mu_j and rounding to nearest integer |
| 387 |
for(Int_t j=0; j<_measured->GetNbinsX(); j++){ |
| 388 |
mu[j] = TMath::Nint( rangen->Gamma( 1 + _measured->GetBinContent(j+1), 1 ) ); |
| 389 |
|
| 390 |
vector<Double_t> theta_vec_j(_unfolded->GetNbinsX()); |
| 391 |
for(Int_t i=0; i<_unfolded->GetNbinsX(); i++){ |
| 392 |
theta_vec_j[i] = theta->GetBinContent( theta->GetBin(j+1,i+1) ); |
| 393 |
// cout << theta_vec_j[i] << " "; |
| 394 |
} |
| 395 |
// cout << endl; |
| 396 |
|
| 397 |
vector<Int_t> res_partial = rangen->Multinomial(mu[j], theta_vec_j); |
| 398 |
for(Int_t i=0; i<_unfolded->GetNbinsX(); i++){ |
| 399 |
// cout << res_partial[i] << " "; |
| 400 |
(*result)[i] += res_partial[i]; |
| 401 |
} |
| 402 |
// cout << endl; |
| 403 |
// cout << _measured->GetBinContent(j+1) << " " << mu[j] << " " << res_partial[17] << " " << (*result)[17] << endl; |
| 404 |
|
| 405 |
} |
| 406 |
|
| 407 |
|
| 408 |
for(Int_t i=0; i<_unfolded->GetNbinsX(); i++){ |
| 409 |
Double_t den = 0; |
| 410 |
for(Int_t j=0; j<_measured->GetNbinsX(); j++) |
| 411 |
den+=_smearing_sample->GetBinContent(_smearing_sample->GetBin(i+1,j+1)); |
| 412 |
|
| 413 |
(*result)[i] /= den; |
| 414 |
} |
| 415 |
|
| 416 |
_bin_list->Add(result); |
| 417 |
|
| 418 |
} |
| 419 |
|
| 420 |
BuildFlux(); |
| 421 |
|
| 422 |
} |
| 423 |
|
| 424 |
|
| 425 |
Bool_t PamUnfold::IsBinningOK(){ |
| 426 |
|
| 427 |
Int_t n_meas = _measured->GetNbinsX(); |
| 428 |
Int_t n_smy = _smearing->GetNbinsY(); |
| 429 |
|
| 430 |
|
| 431 |
if(n_meas != n_smy){ |
| 432 |
cerr << " --- Different binning between measured and smearing" << endl; |
| 433 |
cerr << " ---- measured: " << n_meas << " bins; smearing:" << n_smy << " bins on Y-axis" << endl; |
| 434 |
return kFALSE; |
| 435 |
} |
| 436 |
|
| 437 |
const Double_t* x_meas = _measured->GetXaxis()->GetXbins()->GetArray(); |
| 438 |
const Double_t* y_sm = _smearing->GetYaxis()->GetXbins()->GetArray(); |
| 439 |
|
| 440 |
for(Int_t ib=0; ib < n_meas+1; ib++){ |
| 441 |
if( fabs(x_meas[ib] - y_sm[ib])/x_meas[ib] > 1e-4 ){ |
| 442 |
cerr << " --- Different binning between measured and smearing" << endl; |
| 443 |
cerr << " ---- x_meas[" << ib << "] = " << x_meas[ib] << ";" |
| 444 |
<<" y_sm[" << ib << "] = " << y_sm[ib] << ";" << endl; |
| 445 |
return kFALSE; |
| 446 |
} |
| 447 |
else |
| 448 |
continue; |
| 449 |
} |
| 450 |
|
| 451 |
|
| 452 |
|
| 453 |
if(_prior){ |
| 454 |
|
| 455 |
Int_t n_prior = _prior->GetNbinsX(); |
| 456 |
Int_t n_smx = _smearing->GetNbinsX(); |
| 457 |
|
| 458 |
if(n_prior != n_smx){ |
| 459 |
cerr << " --- Different binning between prior and smearing" << endl; |
| 460 |
return kFALSE; |
| 461 |
} |
| 462 |
|
| 463 |
const Double_t* x_prior = _prior->GetXaxis()->GetXbins()->GetArray(); |
| 464 |
const Double_t* x_sm = _smearing->GetXaxis()->GetXbins()->GetArray(); |
| 465 |
|
| 466 |
for(Int_t ib=0; ib < n_prior+1; ib++){ |
| 467 |
if( fabs(x_prior[ib] - x_sm[ib])/x_sm[ib] > 1e-4 ){ |
| 468 |
cerr << " --- Different binning between prior and smearing" << endl; |
| 469 |
return kFALSE; |
| 470 |
} |
| 471 |
else |
| 472 |
continue; |
| 473 |
} |
| 474 |
} |
| 475 |
|
| 476 |
|
| 477 |
return kTRUE; |
| 478 |
|
| 479 |
} |
| 480 |
|
| 481 |
void PamUnfold::IterativeUnfolding(UInt_t niter, TList* list){ |
| 482 |
|
| 483 |
cout << " -- PamUnfold object " << this->GetName() << endl |
| 484 |
<< " Starting unfolding"; |
| 485 |
|
| 486 |
if(!niter) |
| 487 |
cout << " with chi2 convergence check"; |
| 488 |
else |
| 489 |
cout << " with " << niter << " iterations"; |
| 490 |
|
| 491 |
if(_is_improved) |
| 492 |
cout << " and improved algorithm (may take a while...)"; |
| 493 |
else |
| 494 |
cout << " and standard algorithm"; |
| 495 |
|
| 496 |
cout << endl; |
| 497 |
|
| 498 |
if(list) |
| 499 |
cout << " Saving iterations to TList object at " << list << endl; |
| 500 |
|
| 501 |
|
| 502 |
UInt_t iiter = 0; |
| 503 |
Double_t chi2 = 1e6; |
| 504 |
Bool_t kFlag = kTRUE; |
| 505 |
|
| 506 |
while( kFlag ){ |
| 507 |
|
| 508 |
if(iiter > 0) |
| 509 |
SetPrior(_old_unfolded); |
| 510 |
|
| 511 |
if(_is_improved) |
| 512 |
ImprovedUnfold(); |
| 513 |
else |
| 514 |
Unfold(); |
| 515 |
|
| 516 |
if(iiter > 0){ |
| 517 |
chi2 = GetChi2H( _unfolded, _old_unfolded ); |
| 518 |
cout << " Chi2 of change from iteration " << iiter-1 << " to " << iiter << " = " << chi2 << endl; |
| 519 |
} |
| 520 |
|
| 521 |
if(!niter) |
| 522 |
kFlag = chi2 < _min_chi2 ? kFALSE : kTRUE; |
| 523 |
else |
| 524 |
kFlag = iiter == niter ? kFALSE : kTRUE; |
| 525 |
|
| 526 |
if(iiter >= _max_steps){ |
| 527 |
kFlag = kFALSE; |
| 528 |
cerr << "WARNING: Unfolding procedure did not converge in less than " << _max_steps << " steps\n"; |
| 529 |
} |
| 530 |
|
| 531 |
_old_unfolded = GetUnfolded(); |
| 532 |
|
| 533 |
_old_unfolded->SetName( Form("%s_%03i", _old_unfolded->GetName(), iiter) ); |
| 534 |
if(list){ |
| 535 |
list->Add( _old_unfolded ); |
| 536 |
} |
| 537 |
iiter++; |
| 538 |
|
| 539 |
} |
| 540 |
|
| 541 |
cout << " Unfolding converged" << endl; |
| 542 |
|
| 543 |
} |
| 544 |
|
| 545 |
void PamUnfold::Init(){ |
| 546 |
|
| 547 |
cout << " -- PamUnfold object " << this->GetName() << endl |
| 548 |
<< " Initializing unfolded histogram" << endl; |
| 549 |
|
| 550 |
_unfolded = new TH1D( Form("%s_%s_u", _measured->GetName(), this->GetName()), "", _smearing->GetNbinsX(), _smearing->GetXaxis()->GetXbins()->GetArray()); |
| 551 |
_unfolded->Reset(); |
| 552 |
|
| 553 |
_prior = (TH1D*) _unfolded->Clone( Form("_prior_%s",this->GetName()) ); |
| 554 |
_prior->Reset(); |
| 555 |
|
| 556 |
cout << " Initializing flat Prior" << endl; |
| 557 |
//Initializing flat prior |
| 558 |
for(UInt_t ibin=0; ibin<_prior->GetNbinsX(); ibin++){ |
| 559 |
_prior->SetBinContent(ibin+1, _prior->GetBinWidth(ibin+1)/(_prior->GetBinLowEdge(_prior->GetNbinsX()+1)-_prior->GetBinLowEdge(1)) ); |
| 560 |
} |
| 561 |
|
| 562 |
cout << " Initializing Random number generator" << endl; |
| 563 |
rangen = new RanGen(); |
| 564 |
|
| 565 |
_bin_list = new TList(); |
| 566 |
_bin_hist_list = new TList(); |
| 567 |
_smearing_sample = (TH2D*) _smearing->Clone( Form("%s_sample", _smearing->GetName()) ); |
| 568 |
|
| 569 |
cout << " Initialization done" << endl; |
| 570 |
|
| 571 |
} |
| 572 |
|
| 573 |
|
| 574 |
void PamUnfold::NormalizeMatrix(){ |
| 575 |
|
| 576 |
for(UInt_t ibiny=0; ibiny<_smearing->GetNbinsY(); ibiny++){ |
| 577 |
for(UInt_t ibinx=0; ibinx<_smearing->GetNbinsX(); ibinx++){ |
| 578 |
Int_t globalbin = _smearing->GetBin(ibinx+1, ibiny+1); |
| 579 |
if(_norm->GetBinContent(ibinx+1)) |
| 580 |
_smearing->SetBinContent( globalbin, _smearing->GetBinContent(globalbin)/_norm->GetBinContent(ibinx+1) ); |
| 581 |
} |
| 582 |
} |
| 583 |
|
| 584 |
} |
| 585 |
|
| 586 |
void PamUnfold::SampleMatrix(){ |
| 587 |
|
| 588 |
_smearing_sample->Reset(); |
| 589 |
|
| 590 |
vector<Int_t> alpha(_smearing->GetNbinsY()+1); |
| 591 |
vector<Double_t> sampled; |
| 592 |
|
| 593 |
for(UInt_t ibinx=0; ibinx<_smearing->GetNbinsX(); ibinx++){ |
| 594 |
|
| 595 |
// cout << _norm->GetBinContent(ibinx+1) << endl; |
| 596 |
Double_t snorm=0; |
| 597 |
for(UInt_t ibiny=0; ibiny<_smearing->GetNbinsY(); ibiny++){ |
| 598 |
Int_t globalbin = _smearing->GetBin(ibinx+1, ibiny+1); |
| 599 |
snorm += _smearing->GetBinContent(globalbin); |
| 600 |
alpha[ibiny] = TMath::Nint( _smearing->GetBinContent(globalbin) * _norm->GetBinContent(ibinx+1) ); |
| 601 |
} |
| 602 |
alpha[_smearing->GetNbinsY()] = TMath::Nint( (1 - snorm) * _norm->GetBinContent(ibinx+1) ); |
| 603 |
//cout << "bin: " << ibinx << " " << alpha[_smearing->GetNbinsY()] << endl; |
| 604 |
|
| 605 |
sampled = rangen->Dirichlet(_smearing->GetNbinsY() + 1, alpha); |
| 606 |
|
| 607 |
for(UInt_t ibiny=0; ibiny<_smearing_sample->GetNbinsY(); ibiny++){ |
| 608 |
Int_t globalbin = _smearing_sample->GetBin(ibinx+1, ibiny+1); |
| 609 |
// cout << sampled[ibiny] << " "; |
| 610 |
_smearing_sample->SetBinContent(globalbin, sampled[ibiny]); |
| 611 |
} |
| 612 |
// cout << endl; |
| 613 |
} |
| 614 |
// cout << endl; |
| 615 |
|
| 616 |
} |
| 617 |
|
| 618 |
|
| 619 |
void PamUnfold::BuildFlux(){ |
| 620 |
|
| 621 |
_unfolded->Reset(); |
| 622 |
_bin_hist_list->Delete(); |
| 623 |
|
| 624 |
for(Int_t j=0; j<_unfolded->GetNbinsX(); j++){ |
| 625 |
Double_t min=1e9; |
| 626 |
Double_t max=0; |
| 627 |
Double_t check=0; |
| 628 |
|
| 629 |
for(Int_t i=0; i<_bin_list->GetEntries(); i++){ |
| 630 |
TVectorD* vv = (TVectorD*) _bin_list->At(i); |
| 631 |
check = (*vv)(j); |
| 632 |
if(check<min) min=check; |
| 633 |
if(check>max) max=check; |
| 634 |
} |
| 635 |
|
| 636 |
_bin_hist_list->Add( new TH1D( Form("hh_%03i", j), ";Events", 150, min-20, max+20 ) ); |
| 637 |
} |
| 638 |
|
| 639 |
for(Int_t i=0; i<_bin_list->GetEntries(); i++){ |
| 640 |
TVectorD* vv = (TVectorD*) _bin_list->At(i); |
| 641 |
//cout << "Bin " << i << " "; |
| 642 |
for(Int_t j=0; j<vv->GetNoElements(); j++){ |
| 643 |
//cout << (*vv)(j) << " "; |
| 644 |
((TH1D*) _bin_hist_list->At(j))->Fill( (*vv)(j) ); |
| 645 |
} |
| 646 |
// cout << endl; |
| 647 |
} |
| 648 |
|
| 649 |
Double_t qq = 0.682689492137; |
| 650 |
Double_t yq[2], xq[2]; |
| 651 |
xq[0] = (1-qq)/2; xq[1] = xq[0] + qq; |
| 652 |
|
| 653 |
|
| 654 |
for(Int_t j=0; j<_unfolded->GetNbinsX(); j++){ |
| 655 |
TH1D* mt = ((TH1D*) _bin_hist_list->At(j)); |
| 656 |
mt->GetQuantiles(2, yq, xq); |
| 657 |
|
| 658 |
double mean = 0.5*(yq[0] + yq[1]); |
| 659 |
double err = 0.5*(yq[1] - yq[0]); |
| 660 |
if(mt->ComputeIntegral()){ |
| 661 |
_unfolded->SetBinContent(j+1, mean); |
| 662 |
_unfolded->SetBinError(j+1, err); |
| 663 |
} |
| 664 |
else{ |
| 665 |
_unfolded->SetBinContent(j+1, 0); |
| 666 |
_unfolded->SetBinError(j+1, 0); |
| 667 |
} |
| 668 |
|
| 669 |
} |
| 670 |
|
| 671 |
} |
| 672 |
|
| 673 |
void PamUnfold::Draw(TString path){ |
| 674 |
|
| 675 |
Int_t nx, ny; |
| 676 |
FindSplitting(_unfolded->GetNbinsX() , nx, ny); |
| 677 |
canv = dynamic_cast<TCanvas*>(gDirectory->FindObject( Form("canv_%s", this->GetName()) )); |
| 678 |
if(!canv) canv = new TCanvas(Form("canv_%s", this->GetName()), "Bin Distributions", 0, 0, 4 + 500*nx, 28 + 500*ny); |
| 679 |
canv->Divide(nx, ny); |
| 680 |
|
| 681 |
for(Int_t ip=0; ip<_unfolded->GetNbinsX(); ip++){ |
| 682 |
canv->cd(ip+1); |
| 683 |
|
| 684 |
TH1D* mt = ((TH1D*) _bin_hist_list->At(ip)); |
| 685 |
mt->Draw(); |
| 686 |
|
| 687 |
Double_t mean = _unfolded->GetBinContent(ip+1); |
| 688 |
Double_t err = _unfolded->GetBinError(ip+1); |
| 689 |
|
| 690 |
TLine* line1 = new TLine(mean-err, 0, mean-err, mt->GetMaximum()); |
| 691 |
TLine* line2 = new TLine(mean+err, 0, mean+err, mt->GetMaximum()); |
| 692 |
TLine* line3 = new TLine(mean, 0, mean, mt->GetMaximum()); |
| 693 |
|
| 694 |
line1->SetLineWidth(2); |
| 695 |
line1->SetLineColor(2); |
| 696 |
line2->SetLineWidth(2); |
| 697 |
line2->SetLineColor(2); |
| 698 |
line3->SetLineWidth(2); |
| 699 |
line3->SetLineColor(4); |
| 700 |
|
| 701 |
line1->Draw("same"); |
| 702 |
line2->Draw("same"); |
| 703 |
line3->Draw("same"); |
| 704 |
|
| 705 |
} |
| 706 |
|
| 707 |
if(path) canv->Print(path); |
| 708 |
|
| 709 |
} |
| 710 |
|
| 711 |
void PamUnfold::FindSplitting(Int_t n, Int_t &nx, Int_t &ny){ |
| 712 |
|
| 713 |
Int_t x = TMath::Nint( sqrt(n) ); |
| 714 |
if(x*x == n){ nx=ny=x; return; } |
| 715 |
|
| 716 |
x = floor( sqrt(n) ) + 1; |
| 717 |
for(Int_t y=0; y<=x; y++){ |
| 718 |
if(y*x>=n){ ny = y; break;} |
| 719 |
} |
| 720 |
nx = x; |
| 721 |
|
| 722 |
if(ny>nx){ nx=ny; ny=x;} |
| 723 |
|
| 724 |
} |
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