Introduction of Cascade ESD task from Antonin Maire (Antonin.Maire@cern.ch)
[u/mrichter/AliRoot.git] / TPC / AliTPCCalibViewer.cxx
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39bcd65d 1/**************************************************************************
2 * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
3 * *
4 * Author: The ALICE Off-line Project. *
5 * Contributors are mentioned in the code where appropriate. *
6 * *
7 * Permission to use, copy, modify and distribute this software and its *
8 * documentation strictly for non-commercial purposes is hereby granted *
9 * without fee, provided that the above copyright notice appears in all *
10 * copies and that both the copyright notice and this permission notice *
11 * appear in the supporting documentation. The authors make no claims *
12 * about the suitability of this software for any purpose. It is *
13 * provided "as is" without express or implied warranty. *
14 **************************************************************************/
15
16
17///////////////////////////////////////////////////////////////////////////////
18// //
19// Class for viewing/visualizing TPC calibration data //
20// base on TTree functionality for visualization //
72d0ab7e 21// //
22// Create a list of AliTPCCalPads, arrange them in an TObjArray. //
23// Pass this TObjArray to MakeTree and create the calibration Tree //
24// While craating this tree some statistical information are calculated //
25// Open the viewer with this Tree: AliTPCCalibViewer v("CalibTree.root") //
26// Have fun! //
27// EasyDraw("CETmean~-CETmean_mean", "A", "(CETmean~-CETmean_mean)>0") //
28// //
29// If you like to click, we recommand you the //
30// AliTPCCalibViewerGUI //
31// //
32// THE DOCUMENTATION IS STILL NOT COMPLETED !!!! //
33// //
39bcd65d 34///////////////////////////////////////////////////////////////////////////////
35
36//
37// ROOT includes
38//
39#include <iostream>
4f3934a1 40#include <fstream>
39bcd65d 41#include <TString.h>
42#include <TRandom.h>
43#include <TLegend.h>
44#include <TLine.h>
45#include <TCanvas.h>
46#include <TROOT.h>
47#include <TStyle.h>
72d0ab7e 48#include <TH1.h>
39bcd65d 49#include <TH1F.h>
50#include <THashTable.h>
51#include <TObjString.h>
52#include "TTreeStream.h"
53#include "TFile.h"
54#include "TKey.h"
4f3934a1 55#include "TGraph.h"
832bb12c 56#include "TDirectory.h"
4f3934a1 57#include "AliTPCCalibPulser.h"
58#include "AliTPCCalibPedestal.h"
59#include "AliTPCCalibCE.h"
832bb12c 60#include "TFriendElement.h"
4f3934a1 61// #include "TObjArray.h"
62// #include "TObjString.h"
63// #include "TString.h"
64// #include "AliTPCCalPad.h"
39bcd65d 65
66
67//
68// AliRoot includes
69//
70#include "AliTPCCalibViewer.h"
71
72ClassImp(AliTPCCalibViewer)
73
832bb12c 74
39bcd65d 75AliTPCCalibViewer::AliTPCCalibViewer()
76 :TObject(),
77 fTree(0),
78 fFile(0),
a6d2bd0c 79 fListOfObjectsToBeDeleted(0),
832bb12c 80 fTreeMustBeDeleted(0),
81 fAbbreviation(0),
82 fAppendString(0)
39bcd65d 83{
84 //
85 // Default constructor
86 //
87
88}
89
90//_____________________________________________________________________________
91AliTPCCalibViewer::AliTPCCalibViewer(const AliTPCCalibViewer &c)
92 :TObject(c),
93 fTree(0),
94 fFile(0),
a6d2bd0c 95 fListOfObjectsToBeDeleted(0),
832bb12c 96 fTreeMustBeDeleted(0),
97 fAbbreviation(0),
98 fAppendString(0)
39bcd65d 99{
100 //
101 // dummy AliTPCCalibViewer copy constructor
102 // not yet working!!!
103 //
104 fTree = c.fTree;
a6d2bd0c 105 fTreeMustBeDeleted = c.fTreeMustBeDeleted;
39bcd65d 106 //fFile = new TFile(*(c.fFile));
107 fListOfObjectsToBeDeleted = c.fListOfObjectsToBeDeleted;
832bb12c 108 fAbbreviation = c.fAbbreviation;
109 fAppendString = c.fAppendString;
39bcd65d 110}
111
112//_____________________________________________________________________________
113AliTPCCalibViewer::AliTPCCalibViewer(TTree* tree)
114 :TObject(),
115 fTree(0),
116 fFile(0),
a6d2bd0c 117 fListOfObjectsToBeDeleted(0),
832bb12c 118 fTreeMustBeDeleted(0),
119 fAbbreviation(0),
120 fAppendString(0)
39bcd65d 121{
122 //
123 // Constructor that initializes the calibration viewer
124 //
125 fTree = tree;
a6d2bd0c 126 fTreeMustBeDeleted = kFALSE;
39bcd65d 127 fListOfObjectsToBeDeleted = new TObjArray();
832bb12c 128 fAbbreviation = "~";
129 fAppendString = ".fElements";
39bcd65d 130}
131
132//_____________________________________________________________________________
133AliTPCCalibViewer::AliTPCCalibViewer(char* fileName, char* treeName)
134 :TObject(),
135 fTree(0),
136 fFile(0),
a6d2bd0c 137 fListOfObjectsToBeDeleted(0),
832bb12c 138 fTreeMustBeDeleted(0),
139 fAbbreviation(0),
140 fAppendString(0)
141
39bcd65d 142{
143 //
144 // Constructor to initialize the calibration viewer
145 // the file 'fileName' contains the tree 'treeName'
146 //
147 fFile = new TFile(fileName, "read");
148 fTree = (TTree*) fFile->Get(treeName);
a6d2bd0c 149 fTreeMustBeDeleted = kTRUE;
39bcd65d 150 fListOfObjectsToBeDeleted = new TObjArray();
832bb12c 151 fAbbreviation = "~";
152 fAppendString = ".fElements";
39bcd65d 153}
154
155//____________________________________________________________________________
156AliTPCCalibViewer & AliTPCCalibViewer::operator =(const AliTPCCalibViewer & param)
157{
158 //
159 // assignment operator - dummy
160 // not yet working!!!
161 //
162 fTree = param.fTree;
a6d2bd0c 163 fTreeMustBeDeleted = param.fTreeMustBeDeleted;
39bcd65d 164 //fFile = new TFile(*(param.fFile));
165 fListOfObjectsToBeDeleted = param.fListOfObjectsToBeDeleted;
832bb12c 166 fAbbreviation = param.fAbbreviation;
167 fAppendString = param.fAppendString;
39bcd65d 168 return (*this);
169}
170
171//_____________________________________________________________________________
172AliTPCCalibViewer::~AliTPCCalibViewer()
173{
174 //
175 // AliTPCCalibViewer destructor
a6d2bd0c 176 // all objects will be deleted, the file will be closed, the pictures will disappear
39bcd65d 177 //
a6d2bd0c 178 if (fTree && fTreeMustBeDeleted) {
179 fTree->SetCacheSize(0);
180 fTree->Delete();
181 //delete fTree;
182 }
39bcd65d 183 if (fFile) {
184 fFile->Close();
185 fFile = 0;
186 }
187
188 for (Int_t i = fListOfObjectsToBeDeleted->GetEntriesFast()-1; i >= 0; i--) {
189 //cout << "Index " << i << " trying to delete the following object: " << fListOfObjectsToBeDeleted->At(i)->GetName() << "..."<< endl;
190 delete fListOfObjectsToBeDeleted->At(i);
191 }
192 delete fListOfObjectsToBeDeleted;
193}
194
195//_____________________________________________________________________________
a6d2bd0c 196void AliTPCCalibViewer::Delete(Option_t* option) {
197 //
198 // Should be called from AliTPCCalibViewerGUI class only.
199 // If you use Delete() do not call the destructor.
200 // All objects (except those contained in fListOfObjectsToBeDeleted) will be deleted, the file will be closed.
201 //
202
203 option = option; // to avoid warnings on compiling
204 if (fTree && fTreeMustBeDeleted) {
205 fTree->SetCacheSize(0);
206 fTree->Delete();
207 }
208 if (fFile)
209 delete fFile;
210 delete fListOfObjectsToBeDeleted;
211}
212
8192627b 213
214const char* AliTPCCalibViewer::AddAbbreviations(char* c, Bool_t printDrawCommand){
215 // Replace all "<variable>" with "<variable><fAbbreviation>" (Adds forgotten "~")
216 // but take care on the statistical information, like "CEQmean_Mean"
217 // and also take care on correct given variables, like "CEQmean~"
218 //
219 // For each variable out of "listOfVariables":
220 // - 'Save' correct items:
221 // - form <replaceString>, take <variable>'s first char, add <removeString>, add rest of <variable>, e.g. "C!#EQmean" (<removeString> = "!#")
222 // - For each statistical information in "listOfNormalizationVariables":
223 // - ReplaceAll <variable><statistical_Information> with <replaceString><statistical_Information>
224 // - ReplaceAll <variable><abbreviation> with <replaceString><abbreviation>, e.g. "CEQmean~" -> "C!#EQmean~"
225 // - ReplaceAll <variable><appendStr> with <replaceString><appendStr>, e.g. "CEQmean.fElements" -> "C!#EQmean.fElements"
226 //
227 // - Do actual replacing:
228 // - ReplaceAll <variable> with <variable><fAbbreviation>, e.g. "CEQmean" -> "CEQmean~"
229 //
230 // - Undo saving:
231 // - For each statistical information in "listOfNormalizationVariables":
232 // - ReplaceAll <replaceString><statistical_Information> with <variable><statistical_Information>
233 // - ReplaceAll <replaceString><abbreviation> with <variable><abbreviation>, e.g. "C!#EQmean~" -> "CEQmean~"
234 // - ReplaceAll <replaceString><appendStr> with <variable><appendStr>, e.g. "C!#EQmean.fElements" -> "CEQmean.fElements"
235 //
236 // Now all the missing "~" should be added.
237
238 TString str(c);
239 TString removeString = "!#"; // very unpropable combination of chars
240 TString replaceString = "";
241 TString searchString = "";
242 TString normString = "";
243 TObjArray *listOfVariables = GetListOfVariables();
244 listOfVariables->Add(new TObjString("channel"));
245 listOfVariables->Add(new TObjString("gx"));
246 listOfVariables->Add(new TObjString("gy"));
247 listOfVariables->Add(new TObjString("lx"));
248 listOfVariables->Add(new TObjString("ly"));
249 listOfVariables->Add(new TObjString("pad"));
250 listOfVariables->Add(new TObjString("row"));
251 listOfVariables->Add(new TObjString("rpad"));
252 listOfVariables->Add(new TObjString("sector"));
253 TObjArray *listOfNormalizationVariables = GetListOfNormalizationVariables();
254 Int_t nVariables = listOfVariables->GetEntriesFast();
255 Int_t nNorm = listOfNormalizationVariables->GetEntriesFast();
256
257 Int_t *varLengths = new Int_t[nVariables];
258 for (Int_t i = 0; i < nVariables; i++) {
259 varLengths[i] = ((TObjString*)listOfVariables->At(i))->String().Length();
260 }
261 Int_t *normLengths = new Int_t[nNorm];
262 for (Int_t i = 0; i < nNorm; i++) {
263 normLengths[i] = ((TObjString*)listOfNormalizationVariables->At(i))->String().Length();
264 // printf("normLengths[%i] (%s) = %i \n", i,((TObjString*)listOfNormalizationVariables->At(i))->String().Data(), normLengths[i]);
265 }
266 Int_t *varSort = new Int_t[nVariables];
267 TMath::Sort(nVariables, varLengths, varSort, kTRUE);
268 Int_t *normSort = new Int_t[nNorm];
269 TMath::Sort(nNorm, normLengths, normSort, kTRUE);
270 // for (Int_t i = 0; i<nNorm; i++) printf("normLengths: %i\n", normLengths[normSort[i]]);
271 // for (Int_t i = 0; i<nVariables; i++) printf("varLengths: %i\n", varLengths[varSort[i]]);
272
273 for (Int_t ivar = 0; ivar < nVariables; ivar++) {
274 // ***** save correct tokens *****
275 // first get the next variable:
276 searchString = ((TObjString*)listOfVariables->At(varSort[ivar]))->String();
277 // printf("searchString: %s ++++++++++++++\n", searchString.Data());
278 // form replaceString:
279 replaceString = "";
280 for (Int_t i = 0; i < searchString.Length(); i++) {
281 replaceString.Append(searchString[i]);
282 if (i == 0) replaceString.Append(removeString);
283 }
284 // go through normalization:
285 // printf("go through normalization\n");
286 for (Int_t inorm = 0; inorm < nNorm; inorm++) {
287 // printf(" inorm=%i, nNorm=%i, normSort[inorm]=%i \n", inorm, nNorm, normSort[inorm]);
288 normString = ((TObjString*)listOfNormalizationVariables->At(normSort[inorm]))->String();
289 // printf(" walking in normalization, i=%i, normString=%s \n", inorm, normString.Data());
290 str.ReplaceAll(searchString + normString, replaceString + normString);
291 // like: str.ReplaceAll("CEQmean_Mean", "C!EQmean_Mean");
292 }
293 str.ReplaceAll(searchString + fAbbreviation, replaceString + fAbbreviation);
294 // like: str.ReplaceAll("CEQmean~", "C!EQmean~");
295 str.ReplaceAll(searchString + fAppendString, replaceString + fAppendString);
296 // like: str.ReplaceAll("CEQmean.fElements", "C!EQmean.fElements");
297
298 // ***** add missing extensions *****
299 str.ReplaceAll(searchString, replaceString + fAbbreviation);
300 // like: str.ReplaceAll("CEQmean", "C!EQmean~");
301 }
302
303 // ***** undo saving *****
304 str.ReplaceAll(removeString, "");
305
306 if (printDrawCommand) std::cout << "The string looks now like: " << str.Data() << std::endl;
307 delete varSort;
308 delete normSort;
309 return str.Data();
310}
311
312
313
314
a6d2bd0c 315//_____________________________________________________________________________
39bcd65d 316Int_t AliTPCCalibViewer::EasyDraw(const char* drawCommand, const char* sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
317 //
318 // easy drawing of data, use '~' for abbreviation of '.fElements'
319 // example: EasyDraw("CETmean~-CETmean_mean", "A", "(CETmean~-CETmean_mean)>0")
320 // sector: sector-number - only the specified sector will be drwawn
321 // 'A'/'C' or 'a'/'c' - side A/C will be drawn
322 // 'ALL' - whole TPC will be drawn, projected on one side
323 // cuts: specifies cuts
324 // drawOptions: draw options like 'same'
325 // writeDrawCommand: write the command, that is passed to TTree::Draw
326 //
72d0ab7e 327
39bcd65d 328 TString drawStr(drawCommand);
329 TString sectorStr(sector);
330 sectorStr.ToUpper();
331 TString cutStr("");
72d0ab7e 332 //TString drawOptionsStr("profcolz ");
8192627b 333 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
334 if (dangerousToDraw) {
c4607f01 335 Warning("EasyDraw", "The draw string must not contain ':' or '>>'. Using only first variable for drawing!");
336// return -1;
337// drawStr.Resize(drawStr.First(">"));
338 drawStr.Resize(drawStr.First(":"));
8192627b 339 }
c4607f01 340
72d0ab7e 341 TString drawOptionsStr("");
39bcd65d 342 TRandom rnd(0);
343 Int_t rndNumber = rnd.Integer(10000);
72d0ab7e 344
345 if (drawOptions && strcmp(drawOptions, "") != 0)
39bcd65d 346 drawOptionsStr += drawOptions;
72d0ab7e 347 else
348 drawOptionsStr += "profcolz";
39bcd65d 349
350 if (sectorStr == "A") {
832bb12c 351 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 352 drawStr += rndNumber;
353 drawStr += "(330,-250,250,330,-250,250)";
354 cutStr += "(sector/18)%2==0 ";
355 }
356 else if (sectorStr == "C") {
832bb12c 357 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 358 drawStr += rndNumber;
359 drawStr += "(330,-250,250,330,-250,250)";
360 cutStr += "(sector/18)%2==1 ";
361 }
362 else if (sectorStr == "ALL") {
832bb12c 363 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 364 drawStr += rndNumber;
365 drawStr += "(330,-250,250,330,-250,250)";
366 }
c4607f01 367 else if (sectorStr.Contains("S")) {
368 drawStr += Form(":rpad%s:row%s+(sector>35)*63>>prof", fAppendString.Data(), fAppendString.Data());
369 drawStr += rndNumber;
370 drawStr += "(159,0,159,140,-70,70)";
371 TString sec=sectorStr;
372 sec.Remove(0,1);
373 cutStr += "sector%36=="+sec+" ";
374 }
39bcd65d 375 else if (sectorStr.IsDigit()) {
376 Int_t isec = sectorStr.Atoi();
832bb12c 377 drawStr += Form(":rpad%s:row%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 378 drawStr += rndNumber;
379 if (isec < 36 && isec >= 0)
380 drawStr += "(63,0,63,108,-54,54)";
381 else if (isec < 72 && isec >= 36)
382 drawStr += "(96,0,96,140,-70,70)";
383 else {
384 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
385 return -1;
386 }
387 cutStr += "(sector==";
388 cutStr += isec;
389 cutStr += ") ";
390 }
391
392 if (cuts && cuts[0] != 0) {
393 if (cutStr.Length() != 0) cutStr += "&& ";
394 cutStr += "(";
395 cutStr += cuts;
396 cutStr += ")";
397 }
832bb12c 398 drawStr.ReplaceAll(fAbbreviation, fAppendString);
399 cutStr.ReplaceAll(fAbbreviation, fAppendString);
39bcd65d 400 if (writeDrawCommand) std::cout << "fTree->Draw(\"" << drawStr << "\", \"" << cutStr << "\", \"" << drawOptionsStr << "\");" << std::endl;
832bb12c 401 Int_t returnValue = fTree->Draw(drawStr.Data(), cutStr.Data(), drawOptionsStr.Data());
402 TString profName("prof");
403 profName += rndNumber;
404 TObject *obj = gDirectory->Get(profName.Data());
405 if (obj && obj->InheritsFrom("TH1")) FormatHistoLabels((TH1*)obj);
406 return returnValue;
39bcd65d 407}
408
72d0ab7e 409
39bcd65d 410Int_t AliTPCCalibViewer::EasyDraw(const char* drawCommand, Int_t sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
411 //
412 // easy drawing of data, use '~' for abbreviation of '.fElements'
413 // example: EasyDraw("CETmean~-CETmean_mean", 34, "(CETmean~-CETmean_mean)>0")
414 // sector: sector-number - only the specified sector will be drwawn
415 // cuts: specifies cuts
416 // drawOptions: draw options like 'same'
417 // writeDrawCommand: write the command, that is passed to TTree::Draw
418 //
419 if (sector >= 0 && sector < 72) {
420 char sectorChr[3];
421 sprintf(sectorChr, "%i", sector);
422 return EasyDraw(drawCommand, sectorChr, cuts, drawOptions, writeDrawCommand);
423 }
424 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
425 return -1;
426}
427
72d0ab7e 428
39bcd65d 429//_____________________________________________________________________________
430Int_t AliTPCCalibViewer::EasyDraw1D(const char* drawCommand, const char* sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
431 //
432 // easy drawing of data, use '~' for abbreviation of '.fElements'
433 // example: EasyDraw("CETmean~-CETmean_mean", "A", "(CETmean~-CETmean_mean)>0")
434 // sector: sector-number - the specified sector will be drwawn
435 // 'A'/'C' or 'a'/'c' - side A/C will be drawn
436 // 'ALL' - whole TPC will be drawn, projected on one side
437 // cuts: specifies cuts
438 // drawOptions: draw options like 'same'
439 // writeDrawCommand: write the command, that is passed to TTree::Draw
440 //
441
442 TString drawStr(drawCommand);
443 TString sectorStr(sector);
444 TString drawOptionsStr(drawOptions);
445 sectorStr.ToUpper();
446 TString cutStr("");
447
448 if (sectorStr == "A")
449 cutStr += "(sector/18)%2==0 ";
450 else if (sectorStr == "C")
451 cutStr += "(sector/18)%2==1 ";
452 else if (sectorStr.IsDigit()) {
453 Int_t isec = sectorStr.Atoi();
454 if (isec < 0 || isec > 71) {
455 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
456 return -1;
457 }
458 cutStr += "(sector==";
459 cutStr += isec;
460 cutStr += ") ";
461 }
c4607f01 462 else if (sectorStr.Contains("S")) {
463 TString sec=sectorStr;
464 sec.Remove(0,1);
465 cutStr += "sector%36=="+sec+" ";
466 }
39bcd65d 467
468 if (cuts && cuts[0] != 0) {
469 if (cutStr.Length() != 0) cutStr += "&& ";
470 cutStr += "(";
471 cutStr += cuts;
472 cutStr += ")";
473 }
474
832bb12c 475 drawStr.ReplaceAll(fAbbreviation, fAppendString);
476 cutStr.ReplaceAll(fAbbreviation, fAppendString);
39bcd65d 477 if (writeDrawCommand) std::cout << "fTree->Draw(\"" << drawStr << "\", \"" << cutStr << "\", \"" << drawOptionsStr << "\");" << std::endl;
832bb12c 478 Int_t returnValue = fTree->Draw(drawStr.Data(), cutStr.Data(), drawOptionsStr.Data());
8192627b 479 if (returnValue == -1) return -1;
832bb12c 480
8192627b 481 TObject *obj = (gPad) ? gPad->GetPrimitive("htemp") : 0;
832bb12c 482 if (!obj) obj = (TH1F*)gDirectory->Get("htemp");
483 if (!obj) obj = gPad->GetPrimitive("tempHist");
484 if (!obj) obj = (TH1F*)gDirectory->Get("tempHist");
485 if (!obj) obj = gPad->GetPrimitive("Graph");
486 if (!obj) obj = (TH1F*)gDirectory->Get("Graph");
487 if (obj && obj->InheritsFrom("TH1")) FormatHistoLabels((TH1*)obj);
488 return returnValue;
39bcd65d 489}
490
72d0ab7e 491
39bcd65d 492Int_t AliTPCCalibViewer::EasyDraw1D(const char* drawCommand, Int_t sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
493 //
494 // easy drawing of data, use '~' for abbreviation of '.fElements'
495 // example: EasyDraw("CETmean~-CETmean_mean", 34, "(CETmean~-CETmean_mean)>0")
496 // sector: sector-number - the specified sector will be drwawn
497 // cuts: specifies cuts
498 // drawOptions: draw options like 'same'
499 // writeDrawCommand: write the command, that is passed to TTree::Draw
500 //
501
502 if (sector >= 0 && sector < 72) {
503 char sectorChr[3];
504 sprintf(sectorChr, "%i", sector);
505 return EasyDraw1D(drawCommand, sectorChr, cuts, drawOptions, writeDrawCommand);
506 }
507 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
508 return -1;
509}
510
39bcd65d 511
832bb12c 512void AliTPCCalibViewer::FormatHistoLabels(TH1 *histo) const {
513 //
514 // formats title and axis labels of histo
515 // removes '.fElements'
516 //
517 if (!histo) return;
518 TString replaceString(fAppendString.Data());
519 TString *str = new TString(histo->GetTitle());
520 str->ReplaceAll(replaceString, "");
521 histo->SetTitle(str->Data());
522 delete str;
523 if (histo->GetXaxis()) {
524 str = new TString(histo->GetXaxis()->GetTitle());
525 str->ReplaceAll(replaceString, "");
526 histo->GetXaxis()->SetTitle(str->Data());
527 delete str;
528 }
529 if (histo->GetYaxis()) {
530 str = new TString(histo->GetYaxis()->GetTitle());
531 str->ReplaceAll(replaceString, "");
532 histo->GetYaxis()->SetTitle(str->Data());
533 delete str;
534 }
535 if (histo->GetZaxis()) {
536 str = new TString(histo->GetZaxis()->GetTitle());
537 str->ReplaceAll(replaceString, "");
538 histo->GetZaxis()->SetTitle(str->Data());
539 delete str;
540 }
541}
542
543
72d0ab7e 544Int_t AliTPCCalibViewer::DrawHisto1D(const char* drawCommand, Int_t sector, const char* cuts, const char *sigmas, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM) const {
545 //
546 // Easy drawing of data, in principle the same as EasyDraw1D
547 // Difference: A line for the mean / median / LTM is drawn
548 // in 'sigmas' you can specify in which distance to the mean/median/LTM you want to see a line in sigma-units, separated by ';'
549 // example: sigmas = "2; 4; 6;" at Begin_Latex 2 #sigma End_Latex, Begin_Latex 4 #sigma End_Latex and Begin_Latex 6 #sigma End_Latex a line is drawn.
550 // "plotMean", "plotMedian" and "plotLTM": what kind of lines do you want to see?
551 //
552 if (sector >= 0 && sector < 72) {
553 char sectorChr[3];
554 sprintf(sectorChr, "%i", sector);
555 return DrawHisto1D(drawCommand, sectorChr, cuts, sigmas, plotMean, plotMedian, plotLTM);
556 }
557 Error("DrawHisto1D","The TPC contains only sectors between 0 and 71.");
558 return -1;
559}
39bcd65d 560
72d0ab7e 561
562Int_t AliTPCCalibViewer::DrawHisto1D(const char* drawCommand, const char* sector, const char* cuts, const char *sigmas, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM) const {
563 //
564 // Easy drawing of data, in principle the same as EasyDraw1D
565 // Difference: A line for the mean / median / LTM is drawn
566 // in 'sigmas' you can specify in which distance to the mean/median/LTM you want to see a line in sigma-units, separated by ';'
567 // example: sigmas = "2; 4; 6;" at Begin_Latex 2 #sigma End_Latex, Begin_Latex 4 #sigma End_Latex and Begin_Latex 6 #sigma End_Latex a line is drawn.
568 // "plotMean", "plotMedian" and "plotLTM": what kind of lines do you want to see?
569 //
39bcd65d 570 Int_t oldOptStat = gStyle->GetOptStat();
571 gStyle->SetOptStat(0000000);
72d0ab7e 572 Double_t ltmFraction = 0.8;
573
574 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
575 TVectorF nsigma(sigmasTokens->GetEntriesFast());
576 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
577 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
578 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
579 nsigma[i] = sig;
39bcd65d 580 }
581
72d0ab7e 582 TString drawStr(drawCommand);
832bb12c 583 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
584 if (dangerousToDraw) {
585 Warning("DrawHisto1D", "The draw string must not contain ':' or '>>'.");
586 return -1;
587 }
72d0ab7e 588 drawStr += " >> tempHist";
589 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts);
590 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
591 // FIXME is this histogram deleted automatically?
592 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
593
594 Double_t mean = TMath::Mean(entries, values);
595 Double_t median = TMath::Median(entries, values);
596 Double_t sigma = TMath::RMS(entries, values);
597 Double_t maxY = htemp->GetMaximum();
598
39bcd65d 599 char c[500];
72d0ab7e 600 TLegend * legend = new TLegend(.7,.7, .99, .99, "Statistical information");
601// sprintf(c, "%s, sector: %i", type, sector);
832bb12c 602 //fListOfObjectsToBeDeleted->Add(legend);
39bcd65d 603
39bcd65d 604 if (plotMean) {
72d0ab7e 605 // draw Mean
606 TLine* line = new TLine(mean, 0, mean, maxY);
832bb12c 607 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 608 line->SetLineColor(kRed);
609 line->SetLineWidth(2);
610 line->SetLineStyle(1);
611 line->Draw();
72d0ab7e 612 sprintf(c, "Mean: %f", mean);
39bcd65d 613 legend->AddEntry(line, c, "l");
72d0ab7e 614 // draw sigma lines
39bcd65d 615 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 616 TLine* linePlusSigma = new TLine(mean + nsigma[i] * sigma, 0, mean + nsigma[i] * sigma, maxY);
832bb12c 617 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 618 linePlusSigma->SetLineColor(kRed);
72d0ab7e 619 linePlusSigma->SetLineStyle(2 + i);
39bcd65d 620 linePlusSigma->Draw();
72d0ab7e 621 TLine* lineMinusSigma = new TLine(mean - nsigma[i] * sigma, 0, mean - nsigma[i] * sigma, maxY);
832bb12c 622 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 623 lineMinusSigma->SetLineColor(kRed);
72d0ab7e 624 lineMinusSigma->SetLineStyle(2 + i);
39bcd65d 625 lineMinusSigma->Draw();
72d0ab7e 626 sprintf(c, "%i #sigma = %f",(Int_t)(nsigma[i]), (Float_t)(nsigma[i] * sigma));
39bcd65d 627 legend->AddEntry(lineMinusSigma, c, "l");
628 }
629 }
39bcd65d 630 if (plotMedian) {
72d0ab7e 631 // draw median
632 TLine* line = new TLine(median, 0, median, maxY);
832bb12c 633 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 634 line->SetLineColor(kBlue);
635 line->SetLineWidth(2);
636 line->SetLineStyle(1);
637 line->Draw();
72d0ab7e 638 sprintf(c, "Median: %f", median);
39bcd65d 639 legend->AddEntry(line, c, "l");
72d0ab7e 640 // draw sigma lines
39bcd65d 641 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 642 TLine* linePlusSigma = new TLine(median + nsigma[i] * sigma, 0, median + nsigma[i]*sigma, maxY);
832bb12c 643 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 644 linePlusSigma->SetLineColor(kBlue);
72d0ab7e 645 linePlusSigma->SetLineStyle(2 + i);
39bcd65d 646 linePlusSigma->Draw();
72d0ab7e 647 TLine* lineMinusSigma = new TLine(median - nsigma[i] * sigma, 0, median - nsigma[i]*sigma, maxY);
832bb12c 648 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 649 lineMinusSigma->SetLineColor(kBlue);
72d0ab7e 650 lineMinusSigma->SetLineStyle(2 + i);
39bcd65d 651 lineMinusSigma->Draw();
72d0ab7e 652 sprintf(c, "%i #sigma = %f",(Int_t)(nsigma[i]), (Float_t)(nsigma[i] * sigma));
39bcd65d 653 legend->AddEntry(lineMinusSigma, c, "l");
654 }
655 }
39bcd65d 656 if (plotLTM) {
72d0ab7e 657 // draw LTM
658 Double_t ltmRms = 0;
659 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
660 TLine* line = new TLine(ltm, 0, ltm, maxY);
832bb12c 661 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 662 line->SetLineColor(kGreen+2);
663 line->SetLineWidth(2);
664 line->SetLineStyle(1);
665 line->Draw();
72d0ab7e 666 sprintf(c, "LTM: %f", ltm);
39bcd65d 667 legend->AddEntry(line, c, "l");
72d0ab7e 668 // draw sigma lines
39bcd65d 669 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 670 TLine* linePlusSigma = new TLine(ltm + nsigma[i] * ltmRms, 0, ltm + nsigma[i] * ltmRms, maxY);
832bb12c 671 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 672 linePlusSigma->SetLineColor(kGreen+2);
673 linePlusSigma->SetLineStyle(2+i);
674 linePlusSigma->Draw();
675
72d0ab7e 676 TLine* lineMinusSigma = new TLine(ltm - nsigma[i] * ltmRms, 0, ltm - nsigma[i] * ltmRms, maxY);
832bb12c 677 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 678 lineMinusSigma->SetLineColor(kGreen+2);
679 lineMinusSigma->SetLineStyle(2+i);
680 lineMinusSigma->Draw();
72d0ab7e 681 sprintf(c, "%i #sigma = %f", (Int_t)(nsigma[i]), (Float_t)(nsigma[i] * ltmRms));
39bcd65d 682 legend->AddEntry(lineMinusSigma, c, "l");
683 }
684 }
72d0ab7e 685 if (!plotMean && !plotMedian && !plotLTM) return -1;
39bcd65d 686 legend->Draw();
687 gStyle->SetOptStat(oldOptStat);
72d0ab7e 688 return 1;
39bcd65d 689}
690
39bcd65d 691
72d0ab7e 692Int_t AliTPCCalibViewer::SigmaCut(const char* drawCommand, Int_t sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, Bool_t pm, const char *sigmas, Float_t sigmaStep) const {
693 //
694 // Creates a histogram Begin_Latex S(t, #mu, #sigma) End_Latex, where you can see, how much of the data are inside sigma-intervals around the mean value
695 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'array', 'n' specifies the length of the array
696 // 'mean' and 'sigma' are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in 'array', to be specified by the user
697 // 'nbins': number of bins, 'binLow': first bin, 'binUp': last bin
698 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
699 // sigmaStep: the binsize of the generated histogram
700 // Begin_Latex
701 // f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{#mu}^{#mu + t #sigma} f(x, #mu, #sigma) dx + #int_{#mu}^{#mu - t #sigma} f(x, #mu, #sigma) dx }{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
702 // End_Latex
703 //
704 //
705 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
706 // around the mean/median/LTM
707 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
708 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
709 // sigmaStep: the binsize of the generated histogram
710 // plotMean/plotMedian/plotLTM: specifies where to put the center
711 //
712 if (sector >= 0 && sector < 72) {
713 char sectorChr[3];
714 sprintf(sectorChr, "%i", sector);
715 return SigmaCut(drawCommand, sectorChr, cuts, sigmaMax, plotMean, plotMedian, plotLTM, pm, sigmas, sigmaStep);
716 }
717 Error("SigmaCut","The TPC contains only sectors between 0 and 71.");
718 return -1;
719}
720
721
722Int_t AliTPCCalibViewer::SigmaCut(const char* drawCommand, const char* sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, Bool_t pm, const char *sigmas, Float_t sigmaStep) const {
723 //
724 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
725 // around the mean/median/LTM
726 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
727 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
728 // sigmaStep: the binsize of the generated histogram
729 // plotMean/plotMedian/plotLTM: specifies where to put the center
730 //
731
732 Double_t ltmFraction = 0.8;
733
734 TString drawStr(drawCommand);
832bb12c 735 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
736 if (dangerousToDraw) {
737 Warning("SigmaCut", "The draw string must not contain ':' or '>>'.");
738 return -1;
739 }
72d0ab7e 740 drawStr += " >> tempHist";
741
742 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
743 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
744 // FIXME is this histogram deleted automatically?
745 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
746
747 Double_t mean = TMath::Mean(entries, values);
748 Double_t median = TMath::Median(entries, values);
749 Double_t sigma = TMath::RMS(entries, values);
750
751 TLegend * legend = new TLegend(.7,.7, .99, .99, "Cumulative");
832bb12c 752 //fListOfObjectsToBeDeleted->Add(legend);
72d0ab7e 753 TH1F *cutHistoMean = 0;
754 TH1F *cutHistoMedian = 0;
755 TH1F *cutHistoLTM = 0;
756
757 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
758 TVectorF nsigma(sigmasTokens->GetEntriesFast());
759 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
760 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
761 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
762 nsigma[i] = sig;
763 }
764
765 if (plotMean) {
766 cutHistoMean = AliTPCCalibViewer::SigmaCut(htemp, mean, sigma, sigmaMax, sigmaStep, pm);
767 if (cutHistoMean) {
832bb12c 768 //fListOfObjectsToBeDeleted->Add(cutHistoMean);
72d0ab7e 769 cutHistoMean->SetLineColor(kRed);
770 legend->AddEntry(cutHistoMean, "Mean", "l");
771 cutHistoMean->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
772 cutHistoMean->Draw();
773 DrawLines(cutHistoMean, nsigma, legend, kRed, pm);
774 } // if (cutHistoMean)
775
776 }
777 if (plotMedian) {
778 cutHistoMedian = AliTPCCalibViewer::SigmaCut(htemp, median, sigma, sigmaMax, sigmaStep, pm);
779 if (cutHistoMedian) {
832bb12c 780 //fListOfObjectsToBeDeleted->Add(cutHistoMedian);
72d0ab7e 781 cutHistoMedian->SetLineColor(kBlue);
782 legend->AddEntry(cutHistoMedian, "Median", "l");
783 cutHistoMedian->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
784 if (plotMean && cutHistoMean) cutHistoMedian->Draw("same");
785 else cutHistoMedian->Draw();
786 DrawLines(cutHistoMedian, nsigma, legend, kBlue, pm);
787 } // if (cutHistoMedian)
788 }
789 if (plotLTM) {
790 Double_t ltmRms = 0;
791 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
792 cutHistoLTM = AliTPCCalibViewer::SigmaCut(htemp, ltm, ltmRms, sigmaMax, sigmaStep, pm);
793 if (cutHistoLTM) {
832bb12c 794 //fListOfObjectsToBeDeleted->Add(cutHistoLTM);
72d0ab7e 795 cutHistoLTM->SetLineColor(kGreen+2);
796 legend->AddEntry(cutHistoLTM, "LTM", "l");
797 cutHistoLTM->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
798 if (plotMean && cutHistoMean || plotMedian && cutHistoMedian) cutHistoLTM->Draw("same");
799 else cutHistoLTM->Draw();
800 DrawLines(cutHistoLTM, nsigma, legend, kGreen+2, pm);
801 }
802 }
803 if (!plotMean && !plotMedian && !plotLTM) return -1;
804 legend->Draw();
805 return 1;
806}
807
832bb12c 808
4f3934a1 809Int_t AliTPCCalibViewer::SigmaCutNew(const char* drawCommand, const char* sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, Bool_t pm, const char *sigmas, Float_t sigmaStep) const {
810 //
811 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
812 // around the mean/median/LTM
813 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
814 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
815 // sigmaStep: the binsize of the generated histogram
816 // plotMean/plotMedian/plotLTM: specifies where to put the center
817 //
818
819 // Double_t ltmFraction = 0.8; //unused
820 // avoid compiler warnings:
821 sigmaMax = sigmaMax;
822 pm = pm;
823 sigmaStep = sigmaStep;
824
825 TString drawStr(drawCommand);
826 drawStr += " >> tempHist";
827
828 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
829 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
830 TGraph *cutGraphMean = 0;
831 // TGraph *cutGraphMedian = 0;
832 // TGraph *cutGraphLTM = 0;
833 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
834 Int_t *index = new Int_t[entries];
835 Float_t *xarray = new Float_t[entries];
836 Float_t *yarray = new Float_t[entries];
837 TMath::Sort(entries, values, index, kFALSE);
838
839 Double_t mean = TMath::Mean(entries, values);
840 // Double_t median = TMath::Median(entries, values);
841 Double_t sigma = TMath::RMS(entries, values);
842
843 TLegend * legend = new TLegend(.7,.7, .99, .99, "Cumulative");
832bb12c 844 //fListOfObjectsToBeDeleted->Add(legend);
4f3934a1 845
846 // parse sigmas string
847 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
848 TVectorF nsigma(sigmasTokens->GetEntriesFast());
849 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
850 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
851 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
852 nsigma[i] = sig;
853 }
854
855 if (plotMean) {
856 for (Int_t i = 0; i < entries; i++) {
857 xarray[i] = TMath::Abs(values[index[i]] - mean) / sigma;
858 yarray[i] = float(i) / float(entries);
859 }
860 cutGraphMean = new TGraph(entries, xarray, yarray);
861 if (cutGraphMean) {
832bb12c 862 //fListOfObjectsToBeDeleted->Add(cutGraphMean);
4f3934a1 863 cutGraphMean->SetLineColor(kRed);
864 legend->AddEntry(cutGraphMean, "Mean", "l");
865 cutGraphMean->SetTitle(Form("%s, Cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
866 cutGraphMean->Draw("alu");
867 DrawLines(cutGraphMean, nsigma, legend, kRed, kTRUE);
868 }
869 }
870 /*
871 if (plotMedian) {
872 cutHistoMedian = AliTPCCalibViewer::SigmaCut(htemp, median, sigma, sigmaMax, sigmaStep, pm);
873 if (cutHistoMedian) {
874 fListOfObjectsToBeDeleted->Add(cutHistoMedian);
875 cutHistoMedian->SetLineColor(kBlue);
876 legend->AddEntry(cutHistoMedian, "Median", "l");
877 cutHistoMedian->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
878 if (plotMean && cutHistoMean) cutHistoMedian->Draw("same");
879 else cutHistoMedian->Draw();
880 DrawLines(cutHistoMedian, nsigma, legend, kBlue, pm);
881 } // if (cutHistoMedian)
882 }
883 if (plotLTM) {
884 Double_t ltmRms = 0;
885 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
886 cutHistoLTM = AliTPCCalibViewer::SigmaCut(htemp, ltm, ltmRms, sigmaMax, sigmaStep, pm);
887 if (cutHistoLTM) {
888 fListOfObjectsToBeDeleted->Add(cutHistoLTM);
889 cutHistoLTM->SetLineColor(kGreen+2);
890 legend->AddEntry(cutHistoLTM, "LTM", "l");
891 cutHistoLTM->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
892 if (plotMean && cutHistoMean || plotMedian && cutHistoMedian) cutHistoLTM->Draw("same");
893 else cutHistoLTM->Draw();
894 DrawLines(cutHistoLTM, nsigma, legend, kGreen+2, pm);
895 }
896 }*/
897 if (!plotMean && !plotMedian && !plotLTM) return -1;
898 legend->Draw();
899 return 1;
900}
901
72d0ab7e 902
72d0ab7e 903Int_t AliTPCCalibViewer::Integrate(const char* drawCommand, Int_t sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, const char *sigmas, Float_t sigmaStep) const {
904 //
905 // Creates an integrated histogram Begin_Latex S(t, #mu, #sigma) End_Latex, out of the input distribution distribution Begin_Latex f(x, #mu, #sigma) End_Latex, given in "histogram"
906 // "mean" and "sigma" are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in "histogram", to be specified by the user
907 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
908 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
909 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
910 // The actual work is done on the array.
911 /* Begin_Latex
912 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{-#infty}^{#mu + t #sigma} f(x, #mu, #sigma) dx}{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
913 End_Latex
914 */
915 if (sector >= 0 && sector < 72) {
916 char sectorChr[3];
917 sprintf(sectorChr, "%i", sector);
918 return Integrate(drawCommand, sectorChr, cuts, sigmaMax, plotMean, plotMedian, plotLTM, sigmas, sigmaStep);
919 }
920 Error("Integrate","The TPC contains only sectors between 0 and 71.");
921 return -1;
922
923}
924
925
4f3934a1 926Int_t AliTPCCalibViewer::IntegrateOld(const char* drawCommand, const char* sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, const char *sigmas, Float_t sigmaStep) const {
72d0ab7e 927 //
928 // Creates an integrated histogram Begin_Latex S(t, #mu, #sigma) End_Latex, out of the input distribution distribution Begin_Latex f(x, #mu, #sigma) End_Latex, given in "histogram"
929 // "mean" and "sigma" are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in "histogram", to be specified by the user
930 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
931 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
932 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
933 // The actual work is done on the array.
934 /* Begin_Latex
935 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{-#infty}^{#mu + t #sigma} f(x, #mu, #sigma) dx}{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
936 End_Latex
937 */
938
939 Double_t ltmFraction = 0.8;
940
941 TString drawStr(drawCommand);
942 drawStr += " >> tempHist";
943
944 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
945 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
946 // FIXME is this histogram deleted automatically?
947 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
948
949 Double_t mean = TMath::Mean(entries, values);
950 Double_t median = TMath::Median(entries, values);
951 Double_t sigma = TMath::RMS(entries, values);
952
953 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
954 TVectorF nsigma(sigmasTokens->GetEntriesFast());
955 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
956 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
957 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
958 nsigma[i] = sig;
959 }
960
961 TLegend * legend = new TLegend(.7,.7, .99, .99, "Integrated histogram");
832bb12c 962 //fListOfObjectsToBeDeleted->Add(legend);
72d0ab7e 963 TH1F *integralHistoMean = 0;
964 TH1F *integralHistoMedian = 0;
965 TH1F *integralHistoLTM = 0;
966
967 if (plotMean) {
968 integralHistoMean = AliTPCCalibViewer::Integrate(htemp, mean, sigma, sigmaMax, sigmaStep);
969 if (integralHistoMean) {
832bb12c 970 //fListOfObjectsToBeDeleted->Add(integralHistoMean);
72d0ab7e 971 integralHistoMean->SetLineColor(kRed);
972 legend->AddEntry(integralHistoMean, "Mean", "l");
973 integralHistoMean->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
974 integralHistoMean->Draw();
975 DrawLines(integralHistoMean, nsigma, legend, kRed, kTRUE);
39bcd65d 976 }
72d0ab7e 977 }
978 if (plotMedian) {
979 integralHistoMedian = AliTPCCalibViewer::Integrate(htemp, median, sigma, sigmaMax, sigmaStep);
980 if (integralHistoMedian) {
832bb12c 981 //fListOfObjectsToBeDeleted->Add(integralHistoMedian);
72d0ab7e 982 integralHistoMedian->SetLineColor(kBlue);
983 legend->AddEntry(integralHistoMedian, "Median", "l");
984 integralHistoMedian->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
985 if (plotMean && integralHistoMean) integralHistoMedian->Draw("same");
986 else integralHistoMedian->Draw();
987 DrawLines(integralHistoMedian, nsigma, legend, kBlue, kTRUE);
39bcd65d 988 }
72d0ab7e 989 }
990 if (plotLTM) {
991 Double_t ltmRms = 0;
992 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
993 integralHistoLTM = AliTPCCalibViewer::Integrate(htemp, ltm, ltmRms, sigmaMax, sigmaStep);
994 if (integralHistoLTM) {
832bb12c 995 //fListOfObjectsToBeDeleted->Add(integralHistoLTM);
72d0ab7e 996 integralHistoLTM->SetLineColor(kGreen+2);
997 legend->AddEntry(integralHistoLTM, "LTM", "l");
998 integralHistoLTM->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
999 if (plotMean && integralHistoMean || plotMedian && integralHistoMedian) integralHistoLTM->Draw("same");
1000 else integralHistoLTM->Draw();
1001 DrawLines(integralHistoLTM, nsigma, legend, kGreen+2, kTRUE);
39bcd65d 1002 }
1003 }
72d0ab7e 1004 if (!plotMean && !plotMedian && !plotLTM) return -1;
1005 legend->Draw();
1006 return 1;
1007}
1008
1009
4f3934a1 1010Int_t AliTPCCalibViewer::Integrate(const char* drawCommand, const char* sector, const char* cuts, Float_t sigmaMax, Bool_t plotMean, Bool_t plotMedian, Bool_t plotLTM, const char *sigmas, Float_t sigmaStep) const {
1011 //
1012 // Creates an integrated histogram Begin_Latex S(t, #mu, #sigma) End_Latex, out of the input distribution distribution Begin_Latex f(x, #mu, #sigma) End_Latex, given in "histogram"
1013 // "mean" and "sigma" are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in "histogram", to be specified by the user
1014 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1015 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1016 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1017 // The actual work is done on the array.
1018 /* Begin_Latex
1019 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{-#infty}^{#mu + t #sigma} f(x, #mu, #sigma) dx}{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
1020 End_Latex
1021 */
1022
1023 Double_t ltmFraction = 0.8;
1024 // avoid compiler warnings:
1025 sigmaMax = sigmaMax;
1026 sigmaStep = sigmaStep;
1027
1028 TString drawStr(drawCommand);
832bb12c 1029 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
1030 if (dangerousToDraw) {
1031 Warning("Integrate", "The draw string must not contain ':' or '>>'.");
1032 return -1;
1033 }
4f3934a1 1034 drawStr += " >> tempHist";
1035
1036 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
1037 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
1038 TGraph *integralGraphMean = 0;
1039 TGraph *integralGraphMedian = 0;
1040 TGraph *integralGraphLTM = 0;
1041 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
1042 Int_t *index = new Int_t[entries];
1043 Float_t *xarray = new Float_t[entries];
1044 Float_t *yarray = new Float_t[entries];
1045 TMath::Sort(entries, values, index, kFALSE);
1046
1047 Double_t mean = TMath::Mean(entries, values);
1048 Double_t median = TMath::Median(entries, values);
1049 Double_t sigma = TMath::RMS(entries, values);
1050
1051 // parse sigmas string
1052 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
1053 TVectorF nsigma(sigmasTokens->GetEntriesFast());
1054 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
1055 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
1056 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
1057 nsigma[i] = sig;
1058 }
1059
1060 TLegend * legend = new TLegend(.7,.7, .99, .99, "Integrated histogram");
832bb12c 1061 //fListOfObjectsToBeDeleted->Add(legend);
4f3934a1 1062
1063 if (plotMean) {
1064 for (Int_t i = 0; i < entries; i++) {
1065 xarray[i] = (values[index[i]] - mean) / sigma;
1066 yarray[i] = float(i) / float(entries);
1067 }
1068 integralGraphMean = new TGraph(entries, xarray, yarray);
1069 if (integralGraphMean) {
832bb12c 1070 //fListOfObjectsToBeDeleted->Add(integralGraphMean);
4f3934a1 1071 integralGraphMean->SetLineColor(kRed);
1072 legend->AddEntry(integralGraphMean, "Mean", "l");
1073 integralGraphMean->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
1074 integralGraphMean->Draw("alu");
1075 DrawLines(integralGraphMean, nsigma, legend, kRed, kTRUE);
1076 }
1077 }
1078 if (plotMedian) {
1079 for (Int_t i = 0; i < entries; i++) {
1080 xarray[i] = (values[index[i]] - median) / sigma;
1081 yarray[i] = float(i) / float(entries);
1082 }
1083 integralGraphMedian = new TGraph(entries, xarray, yarray);
1084 if (integralGraphMedian) {
832bb12c 1085 //fListOfObjectsToBeDeleted->Add(integralGraphMedian);
4f3934a1 1086 integralGraphMedian->SetLineColor(kBlue);
1087 legend->AddEntry(integralGraphMedian, "Median", "l");
1088 integralGraphMedian->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
1089 if (plotMean && integralGraphMean) integralGraphMedian->Draw("samelu");
1090 else integralGraphMedian->Draw("alu");
1091 DrawLines(integralGraphMedian, nsigma, legend, kBlue, kTRUE);
1092 }
1093 }
1094 if (plotLTM) {
1095 Double_t ltmRms = 0;
1096 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
1097 for (Int_t i = 0; i < entries; i++) {
1098 xarray[i] = (values[index[i]] - ltm) / ltmRms;
1099 yarray[i] = float(i) / float(entries);
1100 }
1101 integralGraphLTM = new TGraph(entries, xarray, yarray);
1102 if (integralGraphLTM) {
832bb12c 1103 //fListOfObjectsToBeDeleted->Add(integralGraphLTM);
4f3934a1 1104 integralGraphLTM->SetLineColor(kGreen+2);
1105 legend->AddEntry(integralGraphLTM, "LTM", "l");
1106 integralGraphLTM->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
1107 if (plotMean && integralGraphMean || plotMedian && integralGraphMedian) integralGraphLTM->Draw("samelu");
1108 else integralGraphLTM->Draw("alu");
1109 DrawLines(integralGraphLTM, nsigma, legend, kGreen+2, kTRUE);
1110 }
1111 }
1112 if (!plotMean && !plotMedian && !plotLTM) return -1;
1113 legend->Draw();
1114 return entries;
1115}
1116
1117
72d0ab7e 1118void AliTPCCalibViewer::DrawLines(TH1F *histogram, TVectorF nsigma, TLegend *legend, Int_t color, Bool_t pm) const {
1119 //
1120 // Private function for SigmaCut(...) and Integrate(...)
1121 // Draws lines into the given histogram, specified by "nsigma", the lines are addeed to the legend
1122 //
39bcd65d 1123
72d0ab7e 1124 // start to draw the lines, loop over requested sigmas
39bcd65d 1125 char c[500];
72d0ab7e 1126 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
1127 if (!pm) {
1128 Int_t bin = histogram->GetXaxis()->FindBin(nsigma[i]);
1129 TLine* lineUp = new TLine(nsigma[i], 0, nsigma[i], histogram->GetBinContent(bin));
832bb12c 1130 //fListOfObjectsToBeDeleted->Add(lineUp);
72d0ab7e 1131 lineUp->SetLineColor(color);
1132 lineUp->SetLineStyle(2 + i);
1133 lineUp->Draw();
1134 TLine* lineLeft = new TLine(nsigma[i], histogram->GetBinContent(bin), 0, histogram->GetBinContent(bin));
832bb12c 1135 //fListOfObjectsToBeDeleted->Add(lineLeft);
72d0ab7e 1136 lineLeft->SetLineColor(color);
1137 lineLeft->SetLineStyle(2 + i);
1138 lineLeft->Draw();
1139 sprintf(c, "Fraction(%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1140 legend->AddEntry(lineLeft, c, "l");
1141 }
1142 else { // if (pm)
1143 Int_t bin = histogram->GetXaxis()->FindBin(nsigma[i]);
1144 TLine* lineUp1 = new TLine(nsigma[i], 0, nsigma[i], histogram->GetBinContent(bin));
832bb12c 1145 //fListOfObjectsToBeDeleted->Add(lineUp1);
72d0ab7e 1146 lineUp1->SetLineColor(color);
1147 lineUp1->SetLineStyle(2 + i);
1148 lineUp1->Draw();
1149 TLine* lineLeft1 = new TLine(nsigma[i], histogram->GetBinContent(bin), histogram->GetBinLowEdge(0)+histogram->GetBinWidth(0), histogram->GetBinContent(bin));
832bb12c 1150 //fListOfObjectsToBeDeleted->Add(lineLeft1);
72d0ab7e 1151 lineLeft1->SetLineColor(color);
1152 lineLeft1->SetLineStyle(2 + i);
1153 lineLeft1->Draw();
1154 sprintf(c, "Fraction(+%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1155 legend->AddEntry(lineLeft1, c, "l");
1156 bin = histogram->GetXaxis()->FindBin(-nsigma[i]);
1157 TLine* lineUp2 = new TLine(-nsigma[i], 0, -nsigma[i], histogram->GetBinContent(bin));
832bb12c 1158 //fListOfObjectsToBeDeleted->Add(lineUp2);
72d0ab7e 1159 lineUp2->SetLineColor(color);
1160 lineUp2->SetLineStyle(2 + i);
1161 lineUp2->Draw();
1162 TLine* lineLeft2 = new TLine(-nsigma[i], histogram->GetBinContent(bin), histogram->GetBinLowEdge(0)+histogram->GetBinWidth(0), histogram->GetBinContent(bin));
832bb12c 1163 //fListOfObjectsToBeDeleted->Add(lineLeft2);
72d0ab7e 1164 lineLeft2->SetLineColor(color);
1165 lineLeft2->SetLineStyle(2 + i);
1166 lineLeft2->Draw();
1167 sprintf(c, "Fraction(-%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1168 legend->AddEntry(lineLeft2, c, "l");
1169 }
1170 } // for (Int_t i = 0; i < nsigma.GetNoElements(); i++)
1171}
1172
1173
4f3934a1 1174void AliTPCCalibViewer::DrawLines(TGraph *graph, TVectorF nsigma, TLegend *legend, Int_t color, Bool_t pm) const {
1175 //
1176 // Private function for SigmaCut(...) and Integrate(...)
1177 // Draws lines into the given histogram, specified by "nsigma", the lines are addeed to the legend
1178 //
1179
1180 // start to draw the lines, loop over requested sigmas
1181 char c[500];
1182 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
1183 if (!pm) {
1184 TLine* lineUp = new TLine(nsigma[i], 0, nsigma[i], graph->Eval(nsigma[i]));
832bb12c 1185 //fListOfObjectsToBeDeleted->Add(lineUp);
4f3934a1 1186 lineUp->SetLineColor(color);
1187 lineUp->SetLineStyle(2 + i);
1188 lineUp->Draw();
1189 TLine* lineLeft = new TLine(nsigma[i], graph->Eval(nsigma[i]), 0, graph->Eval(nsigma[i]));
832bb12c 1190 //fListOfObjectsToBeDeleted->Add(lineLeft);
4f3934a1 1191 lineLeft->SetLineColor(color);
1192 lineLeft->SetLineStyle(2 + i);
1193 lineLeft->Draw();
1194 sprintf(c, "Fraction(%f #sigma) = %f",nsigma[i], graph->Eval(nsigma[i]));
1195 legend->AddEntry(lineLeft, c, "l");
1196 }
1197 else { // if (pm)
1198 TLine* lineUp1 = new TLine(nsigma[i], 0, nsigma[i], graph->Eval(nsigma[i]));
832bb12c 1199 //fListOfObjectsToBeDeleted->Add(lineUp1);
4f3934a1 1200 lineUp1->SetLineColor(color);
1201 lineUp1->SetLineStyle(2 + i);
1202 lineUp1->Draw();
1203 TLine* lineLeft1 = new TLine(nsigma[i], graph->Eval(nsigma[i]), graph->GetHistogram()->GetXaxis()->GetBinLowEdge(0), graph->Eval(nsigma[i]));
832bb12c 1204 //fListOfObjectsToBeDeleted->Add(lineLeft1);
4f3934a1 1205 lineLeft1->SetLineColor(color);
1206 lineLeft1->SetLineStyle(2 + i);
1207 lineLeft1->Draw();
1208 sprintf(c, "Fraction(+%f #sigma) = %f",nsigma[i], graph->Eval(nsigma[i]));
1209 legend->AddEntry(lineLeft1, c, "l");
1210 TLine* lineUp2 = new TLine(-nsigma[i], 0, -nsigma[i], graph->Eval(-nsigma[i]));
832bb12c 1211 //fListOfObjectsToBeDeleted->Add(lineUp2);
4f3934a1 1212 lineUp2->SetLineColor(color);
1213 lineUp2->SetLineStyle(2 + i);
1214 lineUp2->Draw();
1215 TLine* lineLeft2 = new TLine(-nsigma[i], graph->Eval(-nsigma[i]), graph->GetHistogram()->GetXaxis()->GetBinLowEdge(0), graph->Eval(-nsigma[i]));
832bb12c 1216 //fListOfObjectsToBeDeleted->Add(lineLeft2);
4f3934a1 1217 lineLeft2->SetLineColor(color);
1218 lineLeft2->SetLineStyle(2 + i);
1219 lineLeft2->Draw();
1220 sprintf(c, "Fraction(-%f #sigma) = %f",nsigma[i], graph->Eval(-nsigma[i]));
1221 legend->AddEntry(lineLeft2, c, "l");
1222 }
1223 } // for (Int_t i = 0; i < nsigma.GetNoElements(); i++)
1224}
1225
72d0ab7e 1226
1227
1228
1229
1230/////////////////
1231// Array tools //
1232/////////////////
1233
1234
1235Int_t AliTPCCalibViewer::GetBin(Float_t value, Int_t nbins, Double_t binLow, Double_t binUp){
1236 // Returns the 'bin' for 'value'
1237 // The interval between 'binLow' and 'binUp' is divided into 'nbins' equidistant bins
1238 // avoid index out of bounds error: 'if (bin < binLow) bin = binLow' and vice versa
1239 /* Begin_Latex
1240 GetBin(value) = #frac{nbins - 1}{binUp - binLow} #upoint (value - binLow) +1
1241 End_Latex
1242 */
1243
1244 Int_t bin = TMath::Nint( (Float_t)(value - binLow) / (Float_t)(binUp - binLow) * (nbins-1) ) + 1;
1245 // avoid index out of bounds:
1246 if (value < binLow) bin = 0;
1247 if (value > binUp) bin = nbins + 1;
1248 return bin;
39bcd65d 1249
72d0ab7e 1250}
39bcd65d 1251
72d0ab7e 1252
1253Double_t AliTPCCalibViewer::GetLTM(Int_t n, Double_t *array, Double_t *sigma, Double_t fraction){
1254 //
1255 // returns the LTM and sigma
1256 //
1257 Double_t *ddata = new Double_t[n];
1258 Double_t mean = 0, lsigma = 0;
1259 UInt_t nPoints = 0;
1260 for (UInt_t i = 0; i < (UInt_t)n; i++) {
1261 ddata[nPoints]= array[nPoints];
1262 nPoints++;
1263 }
1264 Int_t hh = TMath::Min(TMath::Nint(fraction * nPoints), Int_t(n));
1265 AliMathBase::EvaluateUni(nPoints, ddata, mean, lsigma, hh);
1266 if (sigma) *sigma = lsigma;
1267 delete [] ddata;
1268 return mean;
39bcd65d 1269}
1270
1271
72d0ab7e 1272TH1F* AliTPCCalibViewer::SigmaCut(TH1F *histogram, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep, Bool_t pm) {
1273 //
1274 // Creates a cumulative histogram Begin_Latex S(t, #mu, #sigma) End_Latex, where you can see, how much of the data are inside sigma-intervals around the mean value
1275 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'histogram'
1276 // 'mean' and 'sigma' are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in 'histogram', to be specified by the user
1277 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
1278 // sigmaStep: the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1279 // pm: Decide weather Begin_Latex t > 0 End_Latex (first case) or Begin_Latex t End_Latex arbitrary (secound case)
1280 // The actual work is done on the array.
1281 /* Begin_Latex
1282 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{#mu}^{#mu + t #sigma} f(x, #mu, #sigma) dx + #int_{#mu}^{#mu - t #sigma} f(x, #mu, #sigma) dx }{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx } , for t > 0
1283 or
1284 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{#mu}^{#mu + t #sigma} f(x, #mu, #sigma) dx}{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
1285 End_Latex
1286 begin_macro(source)
1287 {
1288 Float_t mean = 0;
1289 Float_t sigma = 1.5;
1290 Float_t sigmaMax = 4;
1291 gROOT->SetStyle("Plain");
5547c0ab 1292 TH1F *distribution = new TH1F("Distribution1", "Distribution f(x, #mu, #sigma)", 1000,-5,5);
72d0ab7e 1293 TRandom rand(23);
1294 for (Int_t i = 0; i <50000;i++) distribution->Fill(rand.Gaus(mean, sigma));
1295 Float_t *ar = distribution->GetArray();
1296
5547c0ab 1297 TCanvas* macro_example_canvas = new TCanvas("macro_example_canvas_SigmaCut", "", 350, 350);
72d0ab7e 1298 macro_example_canvas->Divide(0,3);
1299 TVirtualPad *pad1 = macro_example_canvas->cd(1);
1300 pad1->SetGridy();
1301 pad1->SetGridx();
1302 distribution->Draw();
1303 TVirtualPad *pad2 = macro_example_canvas->cd(2);
1304 pad2->SetGridy();
1305 pad2->SetGridx();
1306
1307 TH1F *shist = AliTPCCalibViewer::SigmaCut(distribution, mean, sigma, sigmaMax);
1308 shist->SetNameTitle("Cumulative","Cumulative S(t, #mu, #sigma)");
1309 shist->Draw();
1310 TVirtualPad *pad3 = macro_example_canvas->cd(3);
1311 pad3->SetGridy();
1312 pad3->SetGridx();
1313 TH1F *shistPM = AliTPCCalibViewer::SigmaCut(distribution, mean, sigma, sigmaMax, -1, kTRUE);
1314 shistPM->Draw();
1315 return macro_example_canvas;
1316 }
1317 end_macro
1318 */
1319
1320 Float_t *array = histogram->GetArray();
1321 Int_t nbins = histogram->GetXaxis()->GetNbins();
1322 Float_t binLow = histogram->GetXaxis()->GetXmin();
1323 Float_t binUp = histogram->GetXaxis()->GetXmax();
1324 return AliTPCCalibViewer::SigmaCut(nbins, array, mean, sigma, nbins, binLow, binUp, sigmaMax, sigmaStep, pm);
1325}
1326
1327
72d0ab7e 1328TH1F* AliTPCCalibViewer::SigmaCut(Int_t n, Float_t *array, Float_t mean, Float_t sigma, Int_t nbins, Float_t binLow, Float_t binUp, Float_t sigmaMax, Float_t sigmaStep, Bool_t pm){
1329 //
1330 // Creates a histogram Begin_Latex S(t, #mu, #sigma) End_Latex, where you can see, how much of the data are inside sigma-intervals around the mean value
1331 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'array', 'n' specifies the length of the array
1332 // 'mean' and 'sigma' are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in 'array', to be specified by the user
1333 // 'nbins': number of bins, 'binLow': first bin, 'binUp': last bin
1334 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
1335 // sigmaStep: the binsize of the generated histogram
1336 // Here the actual work is done.
1337
1338 if (sigma == 0) return 0;
1339 Float_t binWidth = (binUp-binLow)/(nbins - 1);
1340 if (sigmaStep <= 0) sigmaStep = binWidth;
1341 Int_t kbins = (Int_t)(sigmaMax * sigma / sigmaStep) + 1; // + 1 due to overflow bin in histograms
1342 if (pm) kbins = 2 * (Int_t)(sigmaMax * sigma / sigmaStep) + 1;
1343 Float_t kbinLow = !pm ? 0 : -sigmaMax;
1344 Float_t kbinUp = sigmaMax;
1345 TH1F *hist = new TH1F("sigmaCutHisto","Cumulative; Multiples of #sigma; Fraction of included data", kbins, kbinLow, kbinUp);
1346 hist->SetDirectory(0);
1347 hist->Reset();
1348
1349 // calculate normalization
1350 Double_t normalization = 0;
1351 for (Int_t i = 0; i <= n; i++) {
1352 normalization += array[i];
1353 }
1354
1355 // given units: units from given histogram
1356 // sigma units: in units of sigma
1357 // iDelta: integrate in interval (mean +- iDelta), given units
1358 // x: ofset from mean for integration, given units
1359 // hist: needs
1360
1361// printf("nbins: %i, binLow: %f, binUp: %f \n", nbins, binLow, binUp);
1362 // fill histogram
1363 for (Float_t iDelta = 0; iDelta <= sigmaMax * sigma; iDelta += sigmaStep) {
1364 // integrate array
1365 Double_t valueP = array[GetBin(mean, nbins, binLow, binUp)];
1366 Double_t valueM = array[GetBin(mean-binWidth, nbins, binLow, binUp)];
1367 // add bin of mean value only once to the histogram
1368// printf("++ adding bins: ");
1369 for (Float_t x = binWidth; x <= iDelta; x += binWidth) {
1370 valueP += (mean + x <= binUp) ? array[GetBin(mean + x, nbins, binLow, binUp)] : 0;
1371 valueM += (mean-binWidth - x >= binLow) ? array[GetBin(mean-binWidth - x, nbins, binLow, binUp)] : 0;
1372// printf("%i, ", GetBin(mean + x, nbins, binLow, binUp));
1373 }
1374// printf("\n");
1375 if (valueP / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", valueP, normalization);
1376 if (valueP / normalization > 100) return hist;
1377 if (valueM / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", valueM, normalization);
1378 if (valueM / normalization > 100) return hist;
1379 valueP = (valueP / normalization);
1380 valueM = (valueM / normalization);
1381 if (pm) {
1382 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1383 hist->SetBinContent(bin, valueP);
1384 bin = GetBin(-iDelta/sigma, kbins, kbinLow, kbinUp);
1385 hist->SetBinContent(bin, valueM);
1386 }
1387 else { // if (!pm)
1388 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1389 hist->SetBinContent(bin, valueP + valueM);
1390// printf(" first integration bin: %i, last integration bin in + direction: %i \n", GetBin(mean+binWidth, nbins, binLow, binUp), GetBin(iDelta, nbins, binLow, binUp));
1391// printf(" first integration bin: %i, last integration bin in - direction: %i \n", GetBin(mean+binWidth, nbins, binLow, binUp), GetBin(-iDelta, nbins, binLow, binUp));
1392// printf(" value: %f, normalization: %f, iDelta: %f, Bin: %i \n", valueP+valueM, normalization, iDelta, bin);
1393 }
1394 }
1395 //hist->SetMaximum(0.7);
1396 if (!pm) hist->SetMaximum(1.2);
1397 return hist;
1398}
1399
1400
1401TH1F* AliTPCCalibViewer::SigmaCut(Int_t n, Double_t *array, Double_t mean, Double_t sigma, Int_t nbins, Double_t *xbins, Double_t sigmaMax){
1402 //
1403 // SigmaCut for variable binsize
1404 // NOT YET IMPLEMENTED !!!
1405 //
1406 printf("SigmaCut with variable binsize, Not yet implemented\n");
1407 // avoid compiler warnings:
1408 n=n;
1409 mean=mean;
1410 sigma=sigma;
1411 nbins=nbins;
1412 sigmaMax=sigmaMax;
1413 array=array;
1414 xbins=xbins;
1415
1416 return 0;
1417}
1418
1419
1420TH1F* AliTPCCalibViewer::Integrate(TH1F *histogram, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep){
1421 //
1422 // Creates an integrated histogram Begin_Latex S(t, #mu, #sigma) End_Latex, out of the input distribution distribution Begin_Latex f(x, #mu, #sigma) End_Latex, given in "histogram"
1423 // "mean" and "sigma" are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in "histogram", to be specified by the user
1424 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1425 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1426 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1427 // The actual work is done on the array.
1428 /* Begin_Latex
1429 f(x, #mu, #sigma) #Rightarrow S(t, #mu, #sigma) = #frac{#int_{-#infty}^{#mu + t #sigma} f(x, #mu, #sigma) dx}{ #int_{-#infty}^{+#infty} f(x, #mu, #sigma) dx }
1430 End_Latex
1431 begin_macro(source)
1432 {
1433 Float_t mean = 0;
1434 Float_t sigma = 1.5;
1435 Float_t sigmaMax = 4;
1436 gROOT->SetStyle("Plain");
5547c0ab 1437 TH1F *distribution = new TH1F("Distribution2", "Distribution f(x, #mu, #sigma)", 1000,-5,5);
72d0ab7e 1438 TRandom rand(23);
1439 for (Int_t i = 0; i <50000;i++) distribution->Fill(rand.Gaus(mean, sigma));
1440 Float_t *ar = distribution->GetArray();
1441
5547c0ab 1442 TCanvas* macro_example_canvas = new TCanvas("macro_example_canvas_Integrate", "", 350, 350);
72d0ab7e 1443 macro_example_canvas->Divide(0,2);
1444 TVirtualPad *pad1 = macro_example_canvas->cd(1);
1445 pad1->SetGridy();
1446 pad1->SetGridx();
1447 distribution->Draw();
1448 TVirtualPad *pad2 = macro_example_canvas->cd(2);
1449 pad2->SetGridy();
1450 pad2->SetGridx();
1451 TH1F *shist = AliTPCCalibViewer::Integrate(distribution, mean, sigma, sigmaMax);
1452 shist->SetNameTitle("Cumulative","Cumulative S(t, #mu, #sigma)");
1453 shist->Draw();
1454
7072d276 1455 return macro_example_canvas_Integrate;
72d0ab7e 1456 }
1457 end_macro
1458 */
1459
1460
1461 Float_t *array = histogram->GetArray();
1462 Int_t nbins = histogram->GetXaxis()->GetNbins();
1463 Float_t binLow = histogram->GetXaxis()->GetXmin();
1464 Float_t binUp = histogram->GetXaxis()->GetXmax();
1465 return AliTPCCalibViewer::Integrate(nbins, array, nbins, binLow, binUp, mean, sigma, sigmaMax, sigmaStep);
1466}
1467
1468
1469TH1F* AliTPCCalibViewer::Integrate(Int_t n, Float_t *array, Int_t nbins, Float_t binLow, Float_t binUp, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep){
1470 // Creates an integrated histogram Begin_Latex S(t, #mu, #sigma) End_Latex, out of the input distribution distribution Begin_Latex f(x, #mu, #sigma) End_Latex, given in "histogram"
1471 // "mean" and "sigma" are Begin_Latex #mu End_Latex and Begin_Latex #sigma End_Latex of the distribution in "histogram", to be specified by the user
1472 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1473 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1474 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1475 // Here the actual work is done.
1476
1477 Bool_t givenUnits = kTRUE;
1478 if (sigma != 0 && sigmaMax != 0) givenUnits = kFALSE;
1479 if (givenUnits) {
1480 sigma = 1;
1481 sigmaMax = (binUp - binLow) / 2.;
1482 }
1483
1484 Float_t binWidth = (binUp-binLow)/(nbins - 1);
1485 if (sigmaStep <= 0) sigmaStep = binWidth;
1486 Int_t kbins = (Int_t)(sigmaMax * sigma / sigmaStep) + 1; // + 1 due to overflow bin in histograms
1487 Float_t kbinLow = givenUnits ? binLow : -sigmaMax;
1488 Float_t kbinUp = givenUnits ? binUp : sigmaMax;
1489 TH1F *hist = 0;
1490 if (givenUnits) hist = new TH1F("integratedHisto","Integrated Histogram; Given x; Fraction of included data", kbins, kbinLow, kbinUp);
1491 if (!givenUnits) hist = new TH1F("integratedHisto","Integrated Histogram; Multiples of #sigma; Fraction of included data", kbins, kbinLow, kbinUp);
1492 hist->SetDirectory(0);
1493 hist->Reset();
1494
1495 // calculate normalization
1496 // printf("calculating normalization, integrating from bin 1 to %i \n", n);
1497 Double_t normalization = 0;
1498 for (Int_t i = 1; i <= n; i++) {
1499 normalization += array[i];
1500 }
1501 // printf("normalization: %f \n", normalization);
1502
1503 // given units: units from given histogram
1504 // sigma units: in units of sigma
1505 // iDelta: integrate in interval (mean +- iDelta), given units
1506 // x: ofset from mean for integration, given units
1507 // hist: needs
1508
1509 // fill histogram
1510 for (Float_t iDelta = mean - sigmaMax * sigma; iDelta <= mean + sigmaMax * sigma; iDelta += sigmaStep) {
1511 // integrate array
1512 Double_t value = 0;
1513 for (Float_t x = mean - sigmaMax * sigma; x <= iDelta; x += binWidth) {
1514 value += (x <= binUp && x >= binLow) ? array[GetBin(x, nbins, binLow, binUp)] : 0;
1515 }
1516 if (value / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", value, normalization);
1517 if (value / normalization > 100) return hist;
1518 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1519 // printf("first integration bin: %i, last integration bin: %i \n", GetBin(mean - sigmaMax * sigma, nbins, binLow, binUp), GetBin(iDelta, nbins, binLow, binUp));
1520 // printf("value: %f, normalization: %f, normalized value: %f, iDelta: %f, Bin: %i \n", value, normalization, value/normalization, iDelta, bin);
1521 value = (value / normalization);
1522 hist->SetBinContent(bin, value);
1523 }
1524 return hist;
1525}
1526
1527
1528
1529
1530
1531////////////////////////
1532// end of Array tools //
1533////////////////////////
1534
1535
1536
39bcd65d 1537//_____________________________________________________________________________
ac7becc3 1538AliTPCCalPad* AliTPCCalibViewer::GetCalPadOld(const char* desiredData, char* cuts, char* calPadName) const {
39bcd65d 1539 //
1540 // creates a AliTPCCalPad out of the 'desiredData'
1541 // the functionality of EasyDraw1D is used
1542 // calPadName specifies the name of the created AliTPCCalPad
1543 // - this takes a while -
1544 //
1545 TString drawStr(desiredData);
832bb12c 1546 drawStr.Append(":channel");
1547 drawStr.Append(fAbbreviation);
39bcd65d 1548 AliTPCCalPad * createdCalPad = new AliTPCCalPad(calPadName, calPadName);
1549 Int_t entries = 0;
1550 for (Int_t sec = 0; sec < 72; sec++) {
ac7becc3 1551 AliTPCCalROC * roc = createdCalPad->GetCalROC(sec);
39bcd65d 1552 entries = EasyDraw1D(drawStr.Data(), (Int_t)sec, cuts, "goff");
a6d2bd0c 1553 if (entries == -1) return 0;
ac7becc3 1554 const Double_t *pchannel = fTree->GetV2();
1555 const Double_t *pvalue = fTree->GetV1();
39bcd65d 1556 for (Int_t i = 0; i < entries; i++)
ac7becc3 1557 roc->SetValue((UInt_t)(pchannel[i]), (Float_t)(pvalue[i]));
1558 }
1559 return createdCalPad;
1560}
1561
1562
1563//_____________________________________________________________________________
1564AliTPCCalPad* AliTPCCalibViewer::GetCalPad(const char* desiredData, char* cuts, char* calPadName) const {
1565 //
1566 // creates a AliTPCCalPad out of the 'desiredData'
1567 // the functionality of EasyDraw1D is used
1568 // calPadName specifies the name of the created AliTPCCalPad
1569 // - this takes a while -
1570 //
1571 TString drawStr(desiredData);
1572 drawStr.Append(":channel.fElements:sector");
1573 AliTPCCalPad * createdCalPad = new AliTPCCalPad(calPadName, calPadName);
1574 //
1575 Int_t entries = fTree->Draw(drawStr, cuts,"goff");
1576 const Double_t *pvalue = fTree->GetV1();
1577 const Double_t *pchannel = fTree->GetV2();
1578 const Double_t *psector = fTree->GetV3();
1579
1580 for (Int_t ientry=0; ientry<entries; ientry++){
1581 Int_t sector= TMath::Nint(psector[ientry]);
1582 AliTPCCalROC * roc = createdCalPad->GetCalROC(sector);
1583 if (roc) roc->SetValue((UInt_t)(pchannel[ientry]), (Float_t)(pvalue[ientry]));
39bcd65d 1584 }
ac7becc3 1585
1586 // for (Int_t sec = 0; sec < 72; sec++) {
1587// AliTPCCalROC * roc = createdCalPad->GetCalROC(sec);
1588// entries = EasyDraw1D(drawStr.Data(), (Int_t)sec, cuts, "goff");
1589// if (entries == -1) return 0;
1590// for (Int_t i = 0; i < entries; i++)
1591// roc->SetValue((UInt_t)(pchannel[i]), (Float_t)(pvalue[i]));
1592// }
39bcd65d 1593 return createdCalPad;
1594}
1595
1596//_____________________________________________________________________________
1597AliTPCCalROC* AliTPCCalibViewer::GetCalROC(const char* desiredData, UInt_t sector, char* cuts) const {
1598 //
1599 // creates a AliTPCCalROC out of the desiredData
1600 // the functionality of EasyDraw1D is used
1601 // sector specifies the sector of the created AliTPCCalROC
1602 //
1603 TString drawStr(desiredData);
8192627b 1604 drawStr.Append(":channel");
1605 drawStr.Append(fAbbreviation);
39bcd65d 1606 Int_t entries = EasyDraw1D(drawStr.Data(), (Int_t)sector, cuts, "goff");
a6d2bd0c 1607 if (entries == -1) return 0;
39bcd65d 1608 AliTPCCalROC * createdROC = new AliTPCCalROC(sector);
1609 for (Int_t i = 0; i < entries; i++)
1610 createdROC->SetValue((UInt_t)(fTree->GetV2()[i]), fTree->GetV1()[i]);
1611 return createdROC;
1612}
1613
1614
1615TObjArray* AliTPCCalibViewer::GetListOfVariables(Bool_t printList) {
1616 //
1617 // scan the tree - produces a list of available variables in the tree
1618 // printList: print the list to the screen, after the scan is done
1619 //
1620 TObjArray* arr = new TObjArray();
1621 TObjString* str = 0;
596afefb 1622 if (!fTree) return 0;
39bcd65d 1623 Int_t nentries = fTree->GetListOfBranches()->GetEntries();
1624 for (Int_t i = 0; i < nentries; i++) {
1625 str = new TObjString(fTree->GetListOfBranches()->At(i)->GetName());
1626 str->String().ReplaceAll("_Median", "");
1627 str->String().ReplaceAll("_Mean", "");
1628 str->String().ReplaceAll("_RMS", "");
1629 str->String().ReplaceAll("_LTM", "");
1630 str->String().ReplaceAll("_OutlierCutted", "");
1631 str->String().ReplaceAll(".", "");
1632 if (!arr->FindObject(str) &&
1633 !(str->String() == "channel" || str->String() == "gx" || str->String() == "gy" ||
1634 str->String() == "lx" || str->String() == "ly" || str->String() == "pad" ||
1635 str->String() == "row" || str->String() == "rpad" || str->String() == "sector" ))
1636 arr->Add(str);
1637 }
832bb12c 1638
1639 // loop over all friends (if there are some) and add them to the list
1640 if (fTree->GetListOfFriends()) {
1641 for (Int_t ifriend = 0; ifriend < fTree->GetListOfFriends()->GetEntries(); ifriend++){
1642 // printf("iterating through friendlist, currently at %i\n", ifriend);
1643 // printf("working with %s\n", fTree->GetListOfFriends()->At(ifriend)->ClassName());
1644 if (TString(fTree->GetListOfFriends()->At(ifriend)->ClassName()) != "TFriendElement") continue; // no friendElement found
1645 TFriendElement *friendElement = (TFriendElement*)fTree->GetListOfFriends()->At(ifriend);
1646 if (friendElement->GetTree() == 0) continue; // no tree found in friendElement
1647 // printf("friend found \n");
1648 for (Int_t i = 0; i < friendElement->GetTree()->GetListOfBranches()->GetEntries(); i++) {
1649 // printf("iterating through friendelement entries, currently at %i\n", i);
1650 str = new TObjString(friendElement->GetTree()->GetListOfBranches()->At(i)->GetName());
1651 str->String().ReplaceAll("_Median", "");
1652 str->String().ReplaceAll("_Mean", "");
1653 str->String().ReplaceAll("_RMS", "");
1654 str->String().ReplaceAll("_LTM", "");
1655 str->String().ReplaceAll("_OutlierCutted", "");
1656 str->String().ReplaceAll(".", "");
1657 if (!(str->String() == "channel" || str->String() == "gx" || str->String() == "gy" ||
1658 str->String() == "lx" || str->String() == "ly" || str->String() == "pad" ||
1659 str->String() == "row" || str->String() == "rpad" || str->String() == "sector" )){
1660 // insert "<friendName>." at the beginning: (<friendName> is per default "R")
1661 str->String().Insert(0, ".");
1662 str->String().Insert(0, friendElement->GetName());
1663 if (!arr->FindObject(str)) arr->Add(str);
1664 // printf("added string %s \n", str->String().Data());
1665 }
1666 }
1667 }
1668 } // if (fTree->GetListOfFriends())
1669
39bcd65d 1670 arr->Sort();
832bb12c 1671// ((TFriendElement*)gui->GetViewer()->GetTree()->GetListOfFriends()->At(0))->GetTree()->GetListOfBranches()->At(0)->GetName()
1672// ((TFriendElement*)gui->GetViewer()->GetTree()->GetListOfFriends()->At(0))->GetTree()->GetListOfBranches()
1673
39bcd65d 1674
1675 if (printList) {
1676 TIterator* iter = arr->MakeIterator();
1677 iter->Reset();
1678 TObjString* currentStr = 0;
1679 while ( (currentStr = (TObjString*)(iter->Next())) ) {
1680 std::cout << currentStr->GetString().Data() << std::endl;
1681 }
1682 delete iter;
1683 }
1684 return arr;
1685}
1686
1687
72d0ab7e 1688TObjArray* AliTPCCalibViewer::GetListOfNormalizationVariables(Bool_t printList) const{
39bcd65d 1689 //
1690 // produces a list of available variables for normalization in the tree
1691 // printList: print the list to the screen, after the scan is done
1692 //
1693 TObjArray* arr = new TObjArray();
1694 arr->Add(new TObjString("_Mean"));
1695 arr->Add(new TObjString("_Mean_OutlierCutted"));
1696 arr->Add(new TObjString("_Median"));
1697 arr->Add(new TObjString("_Median_OutlierCutted"));
1698 arr->Add(new TObjString("_LTM"));
1699 arr->Add(new TObjString("_LTM_OutlierCutted"));
832bb12c 1700 arr->Add(new TObjString(Form("LFitIntern_4_8%s", fAppendString.Data())));
1701 arr->Add(new TObjString(Form("GFitIntern_Lin%s", fAppendString.Data())));
1702 arr->Add(new TObjString(Form("GFitIntern_Par%s", fAppendString.Data())));
a6d2bd0c 1703 arr->Add(new TObjString("FitLinLocal"));
1704 arr->Add(new TObjString("FitLinGlobal"));
72d0ab7e 1705 arr->Add(new TObjString("FitParLocal"));
1706 arr->Add(new TObjString("FitParGlobal"));
39bcd65d 1707
1708 if (printList) {
1709 TIterator* iter = arr->MakeIterator();
1710 iter->Reset();
1711 TObjString* currentStr = 0;
1712 while ((currentStr = (TObjString*)(iter->Next()))) {
1713 std::cout << currentStr->GetString().Data() << std::endl;
1714 }
1715 delete iter;
1716 }
1717 return arr;
1718}
1719
1720
1721TFriendElement* AliTPCCalibViewer::AddReferenceTree(const char* filename, const char* treename, const char* refname){
1722 //
1723 // add a reference tree to the current tree
1724 // by default the treename is 'calPads' and the reference treename is 'R'
1725 //
1726 TFile *file = new TFile(filename);
1727 fListOfObjectsToBeDeleted->Add(file);
1728 TTree * tree = (TTree*)file->Get(treename);
1729 return AddFriend(tree, refname);
1730}
1731
1732
1733TObjArray* AliTPCCalibViewer::GetArrayOfCalPads(){
1734 //
1735 // Returns a TObjArray with all AliTPCCalPads that are stored in the tree
1736 // - this takes a while -
1737 //
1738 TObjArray *listOfCalPads = GetListOfVariables();
1739 TObjArray *calPadsArray = new TObjArray();
1740 Int_t numberOfCalPads = listOfCalPads->GetEntries();
1741 for (Int_t i = 0; i < numberOfCalPads; i++) {
832bb12c 1742 std::cout << "Creating calPad " << (i+1) << " of " << numberOfCalPads << "\r" << std::flush;
39bcd65d 1743 char* calPadName = (char*)((TObjString*)(listOfCalPads->At(i)))->GetString().Data();
1744 TString drawCommand = ((TObjString*)(listOfCalPads->At(i)))->GetString();
832bb12c 1745 drawCommand.Append(fAbbreviation.Data());
39bcd65d 1746 AliTPCCalPad* calPad = GetCalPad(drawCommand.Data(), "", calPadName);
1747 calPadsArray->Add(calPad);
1748 }
1749 std::cout << std::endl;
1750 listOfCalPads->Delete();
1751 delete listOfCalPads;
1752 return calPadsArray;
1753}
1754
1755
a6d2bd0c 1756TString* AliTPCCalibViewer::Fit(const char* drawCommand, const char* formula, const char* cuts, Double_t & chi2, TVectorD &fitParam, TMatrixD &covMatrix){
1757 //
1758 // fit an arbitrary function, specified by formula into the data, specified by drawCommand and cuts
1759 // returns chi2, fitParam and covMatrix
1760 // returns TString with fitted formula
1761 //
1762
1763 TString formulaStr(formula);
1764 TString drawStr(drawCommand);
1765 TString cutStr(cuts);
1766
1767 // abbreviations:
832bb12c 1768 drawStr.ReplaceAll(fAbbreviation, fAppendString);
1769 cutStr.ReplaceAll(fAbbreviation, fAppendString);
1770 formulaStr.ReplaceAll(fAbbreviation, fAppendString);
a6d2bd0c 1771
832bb12c 1772 formulaStr.ReplaceAll("++", fAbbreviation);
1773 TObjArray* formulaTokens = formulaStr.Tokenize(fAbbreviation.Data());
a6d2bd0c 1774 Int_t dim = formulaTokens->GetEntriesFast();
1775
1776 fitParam.ResizeTo(dim);
1777 covMatrix.ResizeTo(dim,dim);
1778
1779 TLinearFitter* fitter = new TLinearFitter(dim+1, Form("hyp%d",dim));
1780 fitter->StoreData(kTRUE);
1781 fitter->ClearPoints();
1782
1783 Int_t entries = Draw(drawStr.Data(), cutStr.Data(), "goff");
1784 if (entries == -1) return new TString("An ERROR has occured during fitting!");
1785 Double_t **values = new Double_t*[dim+1] ;
1786
1787 for (Int_t i = 0; i < dim + 1; i++){
1788 Int_t centries = 0;
1789 if (i < dim) centries = fTree->Draw(((TObjString*)formulaTokens->At(i))->GetName(), cutStr.Data(), "goff");
1790 else centries = fTree->Draw(drawStr.Data(), cutStr.Data(), "goff");
1791
1792 if (entries != centries) return new TString("An ERROR has occured during fitting!");
1793 values[i] = new Double_t[entries];
1794 memcpy(values[i], fTree->GetV1(), entries*sizeof(Double_t));
1795 }
1796
1797 // add points to the fitter
1798 for (Int_t i = 0; i < entries; i++){
1799 Double_t x[1000];
1800 for (Int_t j=0; j<dim;j++) x[j]=values[j][i];
1801 fitter->AddPoint(x, values[dim][i], 1);
1802 }
1803
1804 fitter->Eval();
1805 fitter->GetParameters(fitParam);
1806 fitter->GetCovarianceMatrix(covMatrix);
1807 chi2 = fitter->GetChisquare();
1808 chi2 = chi2;
1809
1810 TString *preturnFormula = new TString(Form("( %f+",fitParam[0])), &returnFormula = *preturnFormula;
1811
1812 for (Int_t iparam = 0; iparam < dim; iparam++) {
1813 returnFormula.Append(Form("%s*(%f)",((TObjString*)formulaTokens->At(iparam))->GetName(),fitParam[iparam+1]));
1814 if (iparam < dim-1) returnFormula.Append("+");
1815 }
1816 returnFormula.Append(" )");
1817 delete formulaTokens;
1818 delete fitter;
1819 delete[] values;
1820 return preturnFormula;
1821}
1822
1823
39bcd65d 1824void AliTPCCalibViewer::MakeTreeWithObjects(const char * fileName, TObjArray * array, const char * mapFileName) {
1825 //
1826 // Write tree with all available information
1827 // im mapFileName is speciefied, the Map information are also written to the tree
1828 // AliTPCCalPad-Objects are written directly to the tree, so that they can be accessd later on
1829 // (does not work!!!)
1830 //
1831 AliTPCROC* tpcROCinstance = AliTPCROC::Instance();
1832
1833 TObjArray* mapIROCs = 0;
1834 TObjArray* mapOROCs = 0;
1835 TVectorF *mapIROCArray = 0;
1836 TVectorF *mapOROCArray = 0;
1837 Int_t mapEntries = 0;
1838 TString* mapNames = 0;
1839
1840 if (mapFileName) {
1841 TFile mapFile(mapFileName, "read");
1842
1843 TList* listOfROCs = mapFile.GetListOfKeys();
1844 mapEntries = listOfROCs->GetEntries()/2;
1845 mapIROCs = new TObjArray(mapEntries*2);
1846 mapOROCs = new TObjArray(mapEntries*2);
1847 mapIROCArray = new TVectorF[mapEntries];
1848 mapOROCArray = new TVectorF[mapEntries];
1849
1850 mapNames = new TString[mapEntries];
1851 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
72d0ab7e 1852 TString rocName(((TKey*)(listOfROCs->At(ivalue*2)))->GetName());
1853 rocName.Remove(rocName.Length()-4, 4);
1854 mapIROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "IROC").Data()), ivalue);
1855 mapOROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "OROC").Data()), ivalue);
1856 mapNames[ivalue].Append(rocName);
39bcd65d 1857 }
1858
1859 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
1860 mapIROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(0));
1861 mapOROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(36));
1862
1863 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(0); ichannel++)
1864 (mapIROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapIROCs->At(ivalue)))->GetValue(ichannel);
1865 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(36); ichannel++)
1866 (mapOROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapOROCs->At(ivalue)))->GetValue(ichannel);
1867 }
1868
1869 } // if (mapFileName)
1870
1871 TTreeSRedirector cstream(fileName);
1872 Int_t arrayEntries = array->GetEntries();
1873
1874 // Read names of AliTPCCalPads and save them in names[]
1875 TString* names = new TString[arrayEntries];
1876 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
1877 names[ivalue].Append(((AliTPCCalPad*)array->At(ivalue))->GetName());
1878
1879 for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++) {
1880
1881 TVectorF *vectorArray = new TVectorF[arrayEntries];
1882 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
1883 vectorArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
1884
1885
1886 //
1887 // fill vectors of variable per pad
1888 //
1889 TVectorF *posArray = new TVectorF[8];
1890 for (Int_t ivalue = 0; ivalue < 8; ivalue++)
1891 posArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
1892
1893 Float_t posG[3] = {0};
1894 Float_t posL[3] = {0};
1895 Int_t ichannel = 0;
1896 for (UInt_t irow = 0; irow < tpcROCinstance->GetNRows(isector); irow++) {
1897 for (UInt_t ipad = 0; ipad < tpcROCinstance->GetNPads(isector, irow); ipad++) {
1898 tpcROCinstance->GetPositionLocal(isector, irow, ipad, posL);
1899 tpcROCinstance->GetPositionGlobal(isector, irow, ipad, posG);
1900 posArray[0][ichannel] = irow;
1901 posArray[1][ichannel] = ipad;
1902 posArray[2][ichannel] = posL[0];
1903 posArray[3][ichannel] = posL[1];
1904 posArray[4][ichannel] = posG[0];
1905 posArray[5][ichannel] = posG[1];
1906 posArray[6][ichannel] = (Int_t)(ipad - (Double_t)(tpcROCinstance->GetNPads(isector, irow))/2);
1907 posArray[7][ichannel] = ichannel;
1908
1909 // loop over array containing AliTPCCalPads
1910 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
1911 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
1912 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
1913 if (calROC)
1914 (vectorArray[ivalue])[ichannel] = calROC->GetValue(irow, ipad);
1915 else
1916 (vectorArray[ivalue])[ichannel] = 0;
1917 }
1918 ichannel++;
1919 }
1920 }
1921 AliTPCCalROC dummyROC(0);
1922 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
1923 AliTPCCalROC *roc = ((AliTPCCalPad*)array->At(ivalue))->GetCalROC(isector);
1924 if (!roc) roc = &dummyROC;
1925 cstream << "calPads" <<
1926 (Char_t*)((names[ivalue] + ".=").Data()) << &vectorArray[ivalue];
1927 cstream << "calPads" <<
1928 (Char_t*)((names[ivalue] + "Pad.=").Data()) << roc;
1929 }
1930
1931 if (mapFileName) {
1932 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
1933 if (isector < 36)
1934 cstream << "calPads" <<
1935 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapIROCArray[ivalue];
1936 else
1937 cstream << "calPads" <<
1938 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapOROCArray[ivalue];
1939 }
1940 }
1941
1942 cstream << "calPads" <<
1943 "sector=" << isector;
1944
1945 cstream << "calPads" <<
1946 "row.=" << &posArray[0] <<
1947 "pad.=" << &posArray[1] <<
1948 "lx.=" << &posArray[2] <<
1949 "ly.=" << &posArray[3] <<
1950 "gx.=" << &posArray[4] <<
1951 "gy.=" << &posArray[5] <<
1952 "rpad.=" << &posArray[6] <<
1953 "channel.=" << &posArray[7];
1954
1955 cstream << "calPads" <<
1956 "\n";
1957
1958 delete[] posArray;
1959 delete[] vectorArray;
1960 } //for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++)
1961
1962 delete[] names;
1963 if (mapFileName) {
1964 delete mapIROCs;
1965 delete mapOROCs;
1966 delete[] mapIROCArray;
1967 delete[] mapOROCArray;
1968 delete[] mapNames;
1969 }
1970}
1971
72d0ab7e 1972
39bcd65d 1973void AliTPCCalibViewer::MakeTree(const char * fileName, TObjArray * array, const char * mapFileName, AliTPCCalPad* outlierPad, Float_t ltmFraction) {
1974 //
1975 // Write a tree with all available information
72d0ab7e 1976 // if mapFileName is speciefied, the Map information are also written to the tree
39bcd65d 1977 // pads specified in outlierPad are not used for calculating statistics
72d0ab7e 1978 // The following statistical information on the basis of a ROC are calculated:
1979 // "_Median", "_Mean", "_LTM", "_RMS_LTM"
1980 // "_Median_OutlierCutted", "_Mean_OutlierCutted", "_RMS_OutlierCutted", "_LTM_OutlierCutted", "_RMS_LTM_OutlierCutted"
1981 // The following position variables are available:
1982 // "row", "pad", "lx", "ly", "gx", "gy", "rpad", "channel"
1983 //
1984 // The tree out of this function is the basis for the AliTPCCalibViewer and the AliTPCCalibViewerGUI.
1985
39bcd65d 1986 AliTPCROC* tpcROCinstance = AliTPCROC::Instance();
1987
1988 TObjArray* mapIROCs = 0;
1989 TObjArray* mapOROCs = 0;
1990 TVectorF *mapIROCArray = 0;
1991 TVectorF *mapOROCArray = 0;
1992 Int_t mapEntries = 0;
1993 TString* mapNames = 0;
1994
1995 if (mapFileName) {
1996 TFile mapFile(mapFileName, "read");
1997
1998 TList* listOfROCs = mapFile.GetListOfKeys();
1999 mapEntries = listOfROCs->GetEntries()/2;
2000 mapIROCs = new TObjArray(mapEntries*2);
2001 mapOROCs = new TObjArray(mapEntries*2);
2002 mapIROCArray = new TVectorF[mapEntries];
2003 mapOROCArray = new TVectorF[mapEntries];
2004
2005 mapNames = new TString[mapEntries];
2006 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
72d0ab7e 2007 TString rocName(((TKey*)(listOfROCs->At(ivalue*2)))->GetName());
2008 rocName.Remove(rocName.Length()-4, 4);
2009 mapIROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "IROC").Data()), ivalue);
2010 mapOROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "OROC").Data()), ivalue);
2011 mapNames[ivalue].Append(rocName);
39bcd65d 2012 }
2013
2014 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
2015 mapIROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(0));
2016 mapOROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(36));
2017
2018 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(0); ichannel++)
2019 (mapIROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapIROCs->At(ivalue)))->GetValue(ichannel);
2020 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(36); ichannel++)
2021 (mapOROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapOROCs->At(ivalue)))->GetValue(ichannel);
2022 }
2023
2024 } // if (mapFileName)
2025
2026 TTreeSRedirector cstream(fileName);
72d0ab7e 2027 Int_t arrayEntries = 0;
2028 if (array) arrayEntries = array->GetEntries();
39bcd65d 2029
2030 TString* names = new TString[arrayEntries];
2031 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
2032 names[ivalue].Append(((AliTPCCalPad*)array->At(ivalue))->GetName());
2033
2034 for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++) {
2035 //
2036 // get statistic for given sector
2037 //
2038 TVectorF median(arrayEntries);
2039 TVectorF mean(arrayEntries);
2040 TVectorF rms(arrayEntries);
2041 TVectorF ltm(arrayEntries);
2042 TVectorF ltmrms(arrayEntries);
2043 TVectorF medianWithOut(arrayEntries);
2044 TVectorF meanWithOut(arrayEntries);
2045 TVectorF rmsWithOut(arrayEntries);
2046 TVectorF ltmWithOut(arrayEntries);
2047 TVectorF ltmrmsWithOut(arrayEntries);
2048
2049 TVectorF *vectorArray = new TVectorF[arrayEntries];
2050 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
2051 vectorArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
2052
2053 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2054 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
2055 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
2056 AliTPCCalROC* outlierROC = 0;
2057 if (outlierPad) outlierROC = outlierPad->GetCalROC(isector);
2058 if (calROC) {
2059 median[ivalue] = calROC->GetMedian();
2060 mean[ivalue] = calROC->GetMean();
2061 rms[ivalue] = calROC->GetRMS();
2062 Double_t ltmrmsValue = 0;
2063 ltm[ivalue] = calROC->GetLTM(&ltmrmsValue, ltmFraction);
2064 ltmrms[ivalue] = ltmrmsValue;
2065 if (outlierROC) {
2066 medianWithOut[ivalue] = calROC->GetMedian(outlierROC);
2067 meanWithOut[ivalue] = calROC->GetMean(outlierROC);
2068 rmsWithOut[ivalue] = calROC->GetRMS(outlierROC);
2069 ltmrmsValue = 0;
2070 ltmWithOut[ivalue] = calROC->GetLTM(&ltmrmsValue, ltmFraction, outlierROC);
2071 ltmrmsWithOut[ivalue] = ltmrmsValue;
2072 }
2073 }
2074 else {
2075 median[ivalue] = 0.;
2076 mean[ivalue] = 0.;
2077 rms[ivalue] = 0.;
2078 ltm[ivalue] = 0.;
2079 ltmrms[ivalue] = 0.;
2080 medianWithOut[ivalue] = 0.;
2081 meanWithOut[ivalue] = 0.;
2082 rmsWithOut[ivalue] = 0.;
2083 ltmWithOut[ivalue] = 0.;
2084 ltmrmsWithOut[ivalue] = 0.;
2085 }
2086 }
2087
2088 //
2089 // fill vectors of variable per pad
2090 //
2091 TVectorF *posArray = new TVectorF[8];
2092 for (Int_t ivalue = 0; ivalue < 8; ivalue++)
2093 posArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
2094
2095 Float_t posG[3] = {0};
2096 Float_t posL[3] = {0};
2097 Int_t ichannel = 0;
2098 for (UInt_t irow = 0; irow < tpcROCinstance->GetNRows(isector); irow++) {
2099 for (UInt_t ipad = 0; ipad < tpcROCinstance->GetNPads(isector, irow); ipad++) {
2100 tpcROCinstance->GetPositionLocal(isector, irow, ipad, posL);
2101 tpcROCinstance->GetPositionGlobal(isector, irow, ipad, posG);
2102 posArray[0][ichannel] = irow;
2103 posArray[1][ichannel] = ipad;
2104 posArray[2][ichannel] = posL[0];
2105 posArray[3][ichannel] = posL[1];
2106 posArray[4][ichannel] = posG[0];
2107 posArray[5][ichannel] = posG[1];
2108 posArray[6][ichannel] = (Int_t)(ipad - (Double_t)(tpcROCinstance->GetNPads(isector, irow))/2);
2109 posArray[7][ichannel] = ichannel;
2110
2111 // loop over array containing AliTPCCalPads
2112 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2113 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
2114 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
2115 if (calROC)
2116 (vectorArray[ivalue])[ichannel] = calROC->GetValue(irow, ipad);
2117 else
2118 (vectorArray[ivalue])[ichannel] = 0;
2119 }
2120 ichannel++;
2121 }
2122 }
2123
2124 cstream << "calPads" <<
2125 "sector=" << isector;
2126
2127 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2128 cstream << "calPads" <<
2129 (Char_t*)((names[ivalue] + "_Median=").Data()) << median[ivalue] <<
2130 (Char_t*)((names[ivalue] + "_Mean=").Data()) << mean[ivalue] <<
2131 (Char_t*)((names[ivalue] + "_RMS=").Data()) << rms[ivalue] <<
2132 (Char_t*)((names[ivalue] + "_LTM=").Data()) << ltm[ivalue] <<
2133 (Char_t*)((names[ivalue] + "_RMS_LTM=").Data()) << ltmrms[ivalue];
2134 if (outlierPad) {
2135 cstream << "calPads" <<
2136 (Char_t*)((names[ivalue] + "_Median_OutlierCutted=").Data()) << medianWithOut[ivalue] <<
2137 (Char_t*)((names[ivalue] + "_Mean_OutlierCutted=").Data()) << meanWithOut[ivalue] <<
2138 (Char_t*)((names[ivalue] + "_RMS_OutlierCutted=").Data()) << rmsWithOut[ivalue] <<
2139 (Char_t*)((names[ivalue] + "_LTM_OutlierCutted=").Data()) << ltmWithOut[ivalue] <<
2140 (Char_t*)((names[ivalue] + "_RMS_LTM_OutlierCutted=").Data()) << ltmrmsWithOut[ivalue];
2141 }
2142 }
2143
2144 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2145 cstream << "calPads" <<
2146 (Char_t*)((names[ivalue] + ".=").Data()) << &vectorArray[ivalue];
2147 }
2148
2149 if (mapFileName) {
2150 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
2151 if (isector < 36)
2152 cstream << "calPads" <<
2153 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapIROCArray[ivalue];
2154 else
2155 cstream << "calPads" <<
2156 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapOROCArray[ivalue];
2157 }
2158 }
2159
2160 cstream << "calPads" <<
2161 "row.=" << &posArray[0] <<
2162 "pad.=" << &posArray[1] <<
2163 "lx.=" << &posArray[2] <<
2164 "ly.=" << &posArray[3] <<
2165 "gx.=" << &posArray[4] <<
2166 "gy.=" << &posArray[5] <<
2167 "rpad.=" << &posArray[6] <<
2168 "channel.=" << &posArray[7];
2169
2170 cstream << "calPads" <<
2171 "\n";
2172
2173 delete[] posArray;
2174 delete[] vectorArray;
2175 }
2176
2177
2178 delete[] names;
2179 if (mapFileName) {
2180 delete mapIROCs;
2181 delete mapOROCs;
2182 delete[] mapIROCArray;
2183 delete[] mapOROCArray;
2184 delete[] mapNames;
2185 }
2186}
2187
4f3934a1 2188
2189void AliTPCCalibViewer::MakeTree(const char *outPutFileName, const Char_t *inputFileName, AliTPCCalPad *outlierPad, Float_t ltmFraction, const char *mapFileName ){
2190 //
2191 // Function to create a calibration Tree with all available information.
2192 // See also documentation to MakeTree
2193 // the file "inputFileName" must be in the following format (see also CreateObjectList):
2194 // (each colum separated by tabs, "dependingOnType" can have 2 or 3 colums)
2195 //
2196 // type path dependingOnType
2197 //
2198 // type == "CE":
2199 // dependingOnType = CETmean CEQmean CETrms
2200 //
2201 // type == "Pulser":
2202 // dependingOnType = PulserTmean PulsterQmean PulserTrms
2203 //
2204 // type == "Pedestals":
2205 // dependingOnType = Pedestals Noise
2206 //
2207 // type == "CalPad":
2208 // dependingOnType = NameInFile NameToWriteToFile
2209 //
2210 //
2211 TObjArray objArray;
2212 CreateObjectList(inputFileName, &objArray);
2213 MakeTree(outPutFileName, &objArray, mapFileName, outlierPad, ltmFraction);
2214}
2215
832bb12c 2216
4f3934a1 2217void AliTPCCalibViewer::CreateObjectList(const Char_t *filename, TObjArray *calibObjects){
2218 //
2219 // Function to create a TObjArray out of a given file
2220 // the file must be in the following format:
2221 // (each colum separated by tabs, "dependingOnType" can have 2 or 3 colums)
2222 //
2223 //
2224 // type path dependingOnType
2225 //
2226 // type == "CE":
2227 // dependingOnType = CETmean CEQmean CETrms
2228 //
2229 // type == "Pulser":
2230 // dependingOnType = PulserTmean PulsterQmean PulserTrms
2231 //
2232 // type == "Pedestals":
2233 // dependingOnType = Pedestals Noise
2234 //
2235 // type == "CalPad":
2236 // dependingOnType = NameInFile NameToWriteToFile
2237 //
2238 //
2239 //
2240 if ( calibObjects == 0x0 ) return;
2241 ifstream in;
2242 in.open(filename);
2243 if ( !in.is_open() ){
2244 fprintf(stderr,"Error: cannot open list file '%s'", filename);
2245 return;
2246 }
2247
2248 AliTPCCalPad *calPad=0x0;
2249
2250 TString sFile;
2251 sFile.ReadFile(in);
2252 in.close();
2253
2254 TObjArray *arrFileLine = sFile.Tokenize("\n");
2255 TIter nextLine(arrFileLine);
2256
2257 TObjString *sObjLine = 0x0;
2258 while ( (sObjLine = (TObjString*)nextLine()) ){
2259 TString sLine(sObjLine->GetString());
2260
2261 TObjArray *arrCol = sLine.Tokenize("\t");
2262 Int_t nCols = arrCol->GetEntriesFast();
2263
2264 TObjString *sObjType = (TObjString*)(arrCol->At(0));
2265 TObjString *sObjFileName = (TObjString*)(arrCol->At(1));
2266 TObjString *sObjName = 0x0;
2267
2268 if ( !sObjType || !sObjFileName ) continue;
2269 TString sType(sObjType->GetString());
2270 TString sFileName(sObjFileName->GetString());
2271 printf("Type %s, opening %s \n", sType.Data(), sFileName.Data());
2272 TFile *fIn = TFile::Open(sFileName);
2273 if ( !fIn ){
2274 fprintf(stderr,"File not found: '%s'", sFileName.Data());
2275 continue;
2276 }
2277
2278 if ( sType == "CE" ){ // next three colums are the names for CETmean, CEQmean and CETrms
2279 AliTPCCalibCE *ce = (AliTPCCalibCE*)fIn->Get("AliTPCCalibCE");
2280 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadT0());
2281 if (nCols > 2) { // check, if the name is provided
2282 sObjName = (TObjString*)(arrCol->At(2));
2283 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2284 }
2285 else calPad->SetNameTitle("CETmean","CETmean");
2286 calibObjects->Add(calPad);
2287
2288 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadQ());
2289 if (nCols > 3) { // check, if the name is provided
2290 sObjName = (TObjString*)(arrCol->At(3));
2291 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2292 }
2293 else calPad->SetNameTitle("CEQmean","CEQmean");
2294 calibObjects->Add(calPad);
2295
2296 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadRMS());
2297 if (nCols > 4) { // check, if the name is provided
2298 sObjName = (TObjString*)(arrCol->At(4));
2299 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2300 }
2301 else calPad->SetNameTitle("CETrms","CETrms");
2302 calibObjects->Add(calPad);
2303
2304 } else if ( sType == "Pulser") {
2305 AliTPCCalibPulser *sig = (AliTPCCalibPulser*)fIn->Get("AliTPCCalibPulser");
2306
2307 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadT0());
2308 if (nCols > 2) {
2309 sObjName = (TObjString*)(arrCol->At(2));
2310 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2311 }
2312 else calPad->SetNameTitle("PulserTmean","PulserTmean");
2313 calibObjects->Add(calPad);
2314
2315 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadQ());
2316 if (nCols > 3) {
2317 sObjName = (TObjString*)(arrCol->At(3));
2318 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2319 }
2320 else calPad->SetNameTitle("PulserQmean","PulserQmean");
2321 calibObjects->Add(calPad);
2322
2323 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadRMS());
2324 if (nCols > 4) {
2325 sObjName = (TObjString*)(arrCol->At(4));
2326 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2327 }
2328 else calPad->SetNameTitle("PulserTrms","PulserTrms");
2329 calibObjects->Add(calPad);
2330
2331 } else if ( sType == "Pedestals") {
2332 AliTPCCalibPedestal *ped = (AliTPCCalibPedestal*)fIn->Get("AliTPCCalibPedestal");
2333
2334 calPad = new AliTPCCalPad((TObjArray*)ped->GetCalPadPedestal());
2335 if (nCols > 2) {
2336 sObjName = (TObjString*)(arrCol->At(2));
2337 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2338 }
2339 else calPad->SetNameTitle("Pedestals","Pedestals");
2340 calibObjects->Add(calPad);
2341
2342 calPad = new AliTPCCalPad((TObjArray*)ped->GetCalPadRMS());
2343 if (nCols > 3) {
2344 sObjName = (TObjString*)(arrCol->At(3));
2345 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2346 }
2347 else calPad->SetNameTitle("Noise","Noise");
2348 calibObjects->Add(calPad);
2349
2350 } else if ( sType == "CalPad") {
2351 if (nCols > 2) sObjName = (TObjString*)(arrCol->At(2));
2352 else continue;
2353 calPad = new AliTPCCalPad(*(AliTPCCalPad*)fIn->Get(sObjName->GetString().Data()));
2354 if (nCols > 3) {
2355 sObjName = (TObjString*)(arrCol->At(3));
2356 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2357 }
2358 calibObjects->Add(calPad);
2359 } else {
2360 fprintf(stderr,"Undefined Type: '%s'",sType.Data());
2361 }
2362 delete fIn;
2363 }
2364}
2365
2366
2367