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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//
2811495d 39
4f3934a1 40#include <fstream>
2811495d 41#include <iostream>
42
43#include <TFile.h>
44#include <TFriendElement.h>
45#include <TGraph.h>
46#include <TKey.h>
47#include <TPad.h>
48//#include <TCanvas.h>
72d0ab7e 49#include <TH1.h>
39bcd65d 50#include <TH1F.h>
2811495d 51#include <TLegend.h>
52#include <TLine.h>
53#include <TMath.h>
39bcd65d 54#include <TObjString.h>
2811495d 55//#include <TROOT.h>
56#include <TRandom.h>
57#include <TString.h>
58#include <TStyle.h>
59#include <TTreeStream.h>
39bcd65d 60
2811495d 61#include "AliTPCCalibCE.h"
62#include "AliMathBase.h"
63#include "AliTPCCalPad.h"
64#include "AliTPCCalROC.h"
65#include "AliTPCCalibPedestal.h"
66#include "AliTPCCalibPulser.h"
39bcd65d 67
68//
69// AliRoot includes
70//
71#include "AliTPCCalibViewer.h"
72
73ClassImp(AliTPCCalibViewer)
74
832bb12c 75
39bcd65d 76AliTPCCalibViewer::AliTPCCalibViewer()
77 :TObject(),
78 fTree(0),
79 fFile(0),
a6d2bd0c 80 fListOfObjectsToBeDeleted(0),
832bb12c 81 fTreeMustBeDeleted(0),
82 fAbbreviation(0),
83 fAppendString(0)
39bcd65d 84{
85 //
86 // Default constructor
87 //
88
89}
90
91//_____________________________________________________________________________
92AliTPCCalibViewer::AliTPCCalibViewer(const AliTPCCalibViewer &c)
93 :TObject(c),
94 fTree(0),
95 fFile(0),
a6d2bd0c 96 fListOfObjectsToBeDeleted(0),
832bb12c 97 fTreeMustBeDeleted(0),
98 fAbbreviation(0),
99 fAppendString(0)
39bcd65d 100{
101 //
102 // dummy AliTPCCalibViewer copy constructor
103 // not yet working!!!
104 //
105 fTree = c.fTree;
a6d2bd0c 106 fTreeMustBeDeleted = c.fTreeMustBeDeleted;
39bcd65d 107 //fFile = new TFile(*(c.fFile));
108 fListOfObjectsToBeDeleted = c.fListOfObjectsToBeDeleted;
832bb12c 109 fAbbreviation = c.fAbbreviation;
110 fAppendString = c.fAppendString;
39bcd65d 111}
112
113//_____________________________________________________________________________
2811495d 114AliTPCCalibViewer::AliTPCCalibViewer(TTree *const tree)
39bcd65d 115 :TObject(),
116 fTree(0),
117 fFile(0),
a6d2bd0c 118 fListOfObjectsToBeDeleted(0),
832bb12c 119 fTreeMustBeDeleted(0),
120 fAbbreviation(0),
121 fAppendString(0)
39bcd65d 122{
123 //
124 // Constructor that initializes the calibration viewer
125 //
126 fTree = tree;
a6d2bd0c 127 fTreeMustBeDeleted = kFALSE;
39bcd65d 128 fListOfObjectsToBeDeleted = new TObjArray();
832bb12c 129 fAbbreviation = "~";
130 fAppendString = ".fElements";
39bcd65d 131}
132
133//_____________________________________________________________________________
a6e0ebfe 134AliTPCCalibViewer::AliTPCCalibViewer(const char* fileName, const char* treeName)
39bcd65d 135 :TObject(),
136 fTree(0),
137 fFile(0),
a6d2bd0c 138 fListOfObjectsToBeDeleted(0),
832bb12c 139 fTreeMustBeDeleted(0),
140 fAbbreviation(0),
141 fAppendString(0)
142
39bcd65d 143{
144 //
145 // Constructor to initialize the calibration viewer
146 // the file 'fileName' contains the tree 'treeName'
147 //
148 fFile = new TFile(fileName, "read");
149 fTree = (TTree*) fFile->Get(treeName);
a6d2bd0c 150 fTreeMustBeDeleted = kTRUE;
39bcd65d 151 fListOfObjectsToBeDeleted = new TObjArray();
832bb12c 152 fAbbreviation = "~";
153 fAppendString = ".fElements";
39bcd65d 154}
155
156//____________________________________________________________________________
157AliTPCCalibViewer & AliTPCCalibViewer::operator =(const AliTPCCalibViewer & param)
158{
159 //
160 // assignment operator - dummy
161 // not yet working!!!
162 //
163 fTree = param.fTree;
a6d2bd0c 164 fTreeMustBeDeleted = param.fTreeMustBeDeleted;
39bcd65d 165 //fFile = new TFile(*(param.fFile));
166 fListOfObjectsToBeDeleted = param.fListOfObjectsToBeDeleted;
832bb12c 167 fAbbreviation = param.fAbbreviation;
168 fAppendString = param.fAppendString;
39bcd65d 169 return (*this);
170}
171
172//_____________________________________________________________________________
173AliTPCCalibViewer::~AliTPCCalibViewer()
174{
175 //
176 // AliTPCCalibViewer destructor
a6d2bd0c 177 // all objects will be deleted, the file will be closed, the pictures will disappear
39bcd65d 178 //
a6d2bd0c 179 if (fTree && fTreeMustBeDeleted) {
180 fTree->SetCacheSize(0);
181 fTree->Delete();
182 //delete fTree;
183 }
39bcd65d 184 if (fFile) {
185 fFile->Close();
186 fFile = 0;
187 }
188
189 for (Int_t i = fListOfObjectsToBeDeleted->GetEntriesFast()-1; i >= 0; i--) {
190 //cout << "Index " << i << " trying to delete the following object: " << fListOfObjectsToBeDeleted->At(i)->GetName() << "..."<< endl;
191 delete fListOfObjectsToBeDeleted->At(i);
192 }
193 delete fListOfObjectsToBeDeleted;
194}
195
a6d2bd0c 196//_____________________________________________________________________________
197void AliTPCCalibViewer::Delete(Option_t* option) {
198 //
199 // Should be called from AliTPCCalibViewerGUI class only.
200 // If you use Delete() do not call the destructor.
201 // All objects (except those contained in fListOfObjectsToBeDeleted) will be deleted, the file will be closed.
202 //
203
204 option = option; // to avoid warnings on compiling
205 if (fTree && fTreeMustBeDeleted) {
206 fTree->SetCacheSize(0);
207 fTree->Delete();
208 }
209 if (fFile)
210 delete fFile;
211 delete fListOfObjectsToBeDeleted;
212}
213
8192627b 214
2811495d 215const char* AliTPCCalibViewer::AddAbbreviations(const Char_t *c, Bool_t printDrawCommand){
8192627b 216 // Replace all "<variable>" with "<variable><fAbbreviation>" (Adds forgotten "~")
217 // but take care on the statistical information, like "CEQmean_Mean"
218 // and also take care on correct given variables, like "CEQmean~"
219 //
220 // For each variable out of "listOfVariables":
221 // - 'Save' correct items:
222 // - form <replaceString>, take <variable>'s first char, add <removeString>, add rest of <variable>, e.g. "C!#EQmean" (<removeString> = "!#")
223 // - For each statistical information in "listOfNormalizationVariables":
224 // - ReplaceAll <variable><statistical_Information> with <replaceString><statistical_Information>
225 // - ReplaceAll <variable><abbreviation> with <replaceString><abbreviation>, e.g. "CEQmean~" -> "C!#EQmean~"
226 // - ReplaceAll <variable><appendStr> with <replaceString><appendStr>, e.g. "CEQmean.fElements" -> "C!#EQmean.fElements"
227 //
228 // - Do actual replacing:
229 // - ReplaceAll <variable> with <variable><fAbbreviation>, e.g. "CEQmean" -> "CEQmean~"
230 //
231 // - Undo saving:
232 // - For each statistical information in "listOfNormalizationVariables":
233 // - ReplaceAll <replaceString><statistical_Information> with <variable><statistical_Information>
234 // - ReplaceAll <replaceString><abbreviation> with <variable><abbreviation>, e.g. "C!#EQmean~" -> "CEQmean~"
235 // - ReplaceAll <replaceString><appendStr> with <variable><appendStr>, e.g. "C!#EQmean.fElements" -> "CEQmean.fElements"
236 //
237 // Now all the missing "~" should be added.
238
239 TString str(c);
240 TString removeString = "!#"; // very unpropable combination of chars
241 TString replaceString = "";
242 TString searchString = "";
243 TString normString = "";
244 TObjArray *listOfVariables = GetListOfVariables();
245 listOfVariables->Add(new TObjString("channel"));
246 listOfVariables->Add(new TObjString("gx"));
247 listOfVariables->Add(new TObjString("gy"));
248 listOfVariables->Add(new TObjString("lx"));
249 listOfVariables->Add(new TObjString("ly"));
250 listOfVariables->Add(new TObjString("pad"));
251 listOfVariables->Add(new TObjString("row"));
252 listOfVariables->Add(new TObjString("rpad"));
253 listOfVariables->Add(new TObjString("sector"));
254 TObjArray *listOfNormalizationVariables = GetListOfNormalizationVariables();
255 Int_t nVariables = listOfVariables->GetEntriesFast();
256 Int_t nNorm = listOfNormalizationVariables->GetEntriesFast();
257
258 Int_t *varLengths = new Int_t[nVariables];
259 for (Int_t i = 0; i < nVariables; i++) {
260 varLengths[i] = ((TObjString*)listOfVariables->At(i))->String().Length();
261 }
262 Int_t *normLengths = new Int_t[nNorm];
263 for (Int_t i = 0; i < nNorm; i++) {
264 normLengths[i] = ((TObjString*)listOfNormalizationVariables->At(i))->String().Length();
265 // printf("normLengths[%i] (%s) = %i \n", i,((TObjString*)listOfNormalizationVariables->At(i))->String().Data(), normLengths[i]);
266 }
267 Int_t *varSort = new Int_t[nVariables];
268 TMath::Sort(nVariables, varLengths, varSort, kTRUE);
269 Int_t *normSort = new Int_t[nNorm];
270 TMath::Sort(nNorm, normLengths, normSort, kTRUE);
271 // for (Int_t i = 0; i<nNorm; i++) printf("normLengths: %i\n", normLengths[normSort[i]]);
272 // for (Int_t i = 0; i<nVariables; i++) printf("varLengths: %i\n", varLengths[varSort[i]]);
273
274 for (Int_t ivar = 0; ivar < nVariables; ivar++) {
275 // ***** save correct tokens *****
276 // first get the next variable:
277 searchString = ((TObjString*)listOfVariables->At(varSort[ivar]))->String();
278 // printf("searchString: %s ++++++++++++++\n", searchString.Data());
279 // form replaceString:
280 replaceString = "";
281 for (Int_t i = 0; i < searchString.Length(); i++) {
282 replaceString.Append(searchString[i]);
283 if (i == 0) replaceString.Append(removeString);
284 }
285 // go through normalization:
286 // printf("go through normalization\n");
287 for (Int_t inorm = 0; inorm < nNorm; inorm++) {
288 // printf(" inorm=%i, nNorm=%i, normSort[inorm]=%i \n", inorm, nNorm, normSort[inorm]);
289 normString = ((TObjString*)listOfNormalizationVariables->At(normSort[inorm]))->String();
290 // printf(" walking in normalization, i=%i, normString=%s \n", inorm, normString.Data());
291 str.ReplaceAll(searchString + normString, replaceString + normString);
292 // like: str.ReplaceAll("CEQmean_Mean", "C!EQmean_Mean");
293 }
294 str.ReplaceAll(searchString + fAbbreviation, replaceString + fAbbreviation);
295 // like: str.ReplaceAll("CEQmean~", "C!EQmean~");
296 str.ReplaceAll(searchString + fAppendString, replaceString + fAppendString);
297 // like: str.ReplaceAll("CEQmean.fElements", "C!EQmean.fElements");
298
299 // ***** add missing extensions *****
300 str.ReplaceAll(searchString, replaceString + fAbbreviation);
301 // like: str.ReplaceAll("CEQmean", "C!EQmean~");
302 }
303
304 // ***** undo saving *****
305 str.ReplaceAll(removeString, "");
306
307 if (printDrawCommand) std::cout << "The string looks now like: " << str.Data() << std::endl;
6fefa5ce 308 delete [] varLengths;
309 delete [] normLengths;
4ce766eb 310 delete [] varSort;
311 delete [] normSort;
8192627b 312 return str.Data();
313}
314
315
316
317
39bcd65d 318//_____________________________________________________________________________
319Int_t AliTPCCalibViewer::EasyDraw(const char* drawCommand, const char* sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
320 //
321 // easy drawing of data, use '~' for abbreviation of '.fElements'
322 // example: EasyDraw("CETmean~-CETmean_mean", "A", "(CETmean~-CETmean_mean)>0")
323 // sector: sector-number - only the specified sector will be drwawn
324 // 'A'/'C' or 'a'/'c' - side A/C will be drawn
325 // 'ALL' - whole TPC will be drawn, projected on one side
326 // cuts: specifies cuts
327 // drawOptions: draw options like 'same'
328 // writeDrawCommand: write the command, that is passed to TTree::Draw
329 //
72d0ab7e 330
39bcd65d 331 TString drawStr(drawCommand);
332 TString sectorStr(sector);
333 sectorStr.ToUpper();
334 TString cutStr("");
72d0ab7e 335 //TString drawOptionsStr("profcolz ");
8192627b 336 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
337 if (dangerousToDraw) {
c4607f01 338 Warning("EasyDraw", "The draw string must not contain ':' or '>>'. Using only first variable for drawing!");
339// return -1;
340// drawStr.Resize(drawStr.First(">"));
341 drawStr.Resize(drawStr.First(":"));
8192627b 342 }
c4607f01 343
72d0ab7e 344 TString drawOptionsStr("");
39bcd65d 345 TRandom rnd(0);
346 Int_t rndNumber = rnd.Integer(10000);
72d0ab7e 347
348 if (drawOptions && strcmp(drawOptions, "") != 0)
39bcd65d 349 drawOptionsStr += drawOptions;
72d0ab7e 350 else
351 drawOptionsStr += "profcolz";
39bcd65d 352
353 if (sectorStr == "A") {
832bb12c 354 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 355 drawStr += rndNumber;
356 drawStr += "(330,-250,250,330,-250,250)";
357 cutStr += "(sector/18)%2==0 ";
358 }
359 else if (sectorStr == "C") {
832bb12c 360 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 361 drawStr += rndNumber;
362 drawStr += "(330,-250,250,330,-250,250)";
363 cutStr += "(sector/18)%2==1 ";
364 }
365 else if (sectorStr == "ALL") {
832bb12c 366 drawStr += Form(":gy%s:gx%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 367 drawStr += rndNumber;
368 drawStr += "(330,-250,250,330,-250,250)";
369 }
c4607f01 370 else if (sectorStr.Contains("S")) {
371 drawStr += Form(":rpad%s:row%s+(sector>35)*63>>prof", fAppendString.Data(), fAppendString.Data());
372 drawStr += rndNumber;
373 drawStr += "(159,0,159,140,-70,70)";
374 TString sec=sectorStr;
375 sec.Remove(0,1);
376 cutStr += "sector%36=="+sec+" ";
377 }
39bcd65d 378 else if (sectorStr.IsDigit()) {
379 Int_t isec = sectorStr.Atoi();
832bb12c 380 drawStr += Form(":rpad%s:row%s>>prof", fAppendString.Data(), fAppendString.Data());
39bcd65d 381 drawStr += rndNumber;
382 if (isec < 36 && isec >= 0)
383 drawStr += "(63,0,63,108,-54,54)";
384 else if (isec < 72 && isec >= 36)
385 drawStr += "(96,0,96,140,-70,70)";
386 else {
387 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
388 return -1;
389 }
390 cutStr += "(sector==";
391 cutStr += isec;
392 cutStr += ") ";
393 }
394
395 if (cuts && cuts[0] != 0) {
396 if (cutStr.Length() != 0) cutStr += "&& ";
397 cutStr += "(";
398 cutStr += cuts;
399 cutStr += ")";
400 }
832bb12c 401 drawStr.ReplaceAll(fAbbreviation, fAppendString);
402 cutStr.ReplaceAll(fAbbreviation, fAppendString);
39bcd65d 403 if (writeDrawCommand) std::cout << "fTree->Draw(\"" << drawStr << "\", \"" << cutStr << "\", \"" << drawOptionsStr << "\");" << std::endl;
832bb12c 404 Int_t returnValue = fTree->Draw(drawStr.Data(), cutStr.Data(), drawOptionsStr.Data());
405 TString profName("prof");
406 profName += rndNumber;
407 TObject *obj = gDirectory->Get(profName.Data());
408 if (obj && obj->InheritsFrom("TH1")) FormatHistoLabels((TH1*)obj);
409 return returnValue;
39bcd65d 410}
411
72d0ab7e 412
39bcd65d 413Int_t AliTPCCalibViewer::EasyDraw(const char* drawCommand, Int_t sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
414 //
415 // easy drawing of data, use '~' for abbreviation of '.fElements'
416 // example: EasyDraw("CETmean~-CETmean_mean", 34, "(CETmean~-CETmean_mean)>0")
417 // sector: sector-number - only the specified sector will be drwawn
418 // cuts: specifies cuts
419 // drawOptions: draw options like 'same'
420 // writeDrawCommand: write the command, that is passed to TTree::Draw
421 //
422 if (sector >= 0 && sector < 72) {
423 char sectorChr[3];
424 sprintf(sectorChr, "%i", sector);
425 return EasyDraw(drawCommand, sectorChr, cuts, drawOptions, writeDrawCommand);
426 }
427 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
428 return -1;
429}
430
72d0ab7e 431
39bcd65d 432//_____________________________________________________________________________
433Int_t AliTPCCalibViewer::EasyDraw1D(const char* drawCommand, const char* sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
434 //
435 // easy drawing of data, use '~' for abbreviation of '.fElements'
436 // example: EasyDraw("CETmean~-CETmean_mean", "A", "(CETmean~-CETmean_mean)>0")
437 // sector: sector-number - the specified sector will be drwawn
438 // 'A'/'C' or 'a'/'c' - side A/C will be drawn
439 // 'ALL' - whole TPC will be drawn, projected on one side
440 // cuts: specifies cuts
441 // drawOptions: draw options like 'same'
442 // writeDrawCommand: write the command, that is passed to TTree::Draw
443 //
444
445 TString drawStr(drawCommand);
446 TString sectorStr(sector);
447 TString drawOptionsStr(drawOptions);
448 sectorStr.ToUpper();
449 TString cutStr("");
450
451 if (sectorStr == "A")
452 cutStr += "(sector/18)%2==0 ";
453 else if (sectorStr == "C")
454 cutStr += "(sector/18)%2==1 ";
455 else if (sectorStr.IsDigit()) {
456 Int_t isec = sectorStr.Atoi();
457 if (isec < 0 || isec > 71) {
458 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
459 return -1;
460 }
461 cutStr += "(sector==";
462 cutStr += isec;
463 cutStr += ") ";
464 }
c4607f01 465 else if (sectorStr.Contains("S")) {
466 TString sec=sectorStr;
467 sec.Remove(0,1);
468 cutStr += "sector%36=="+sec+" ";
469 }
39bcd65d 470
471 if (cuts && cuts[0] != 0) {
472 if (cutStr.Length() != 0) cutStr += "&& ";
473 cutStr += "(";
474 cutStr += cuts;
475 cutStr += ")";
476 }
477
832bb12c 478 drawStr.ReplaceAll(fAbbreviation, fAppendString);
479 cutStr.ReplaceAll(fAbbreviation, fAppendString);
39bcd65d 480 if (writeDrawCommand) std::cout << "fTree->Draw(\"" << drawStr << "\", \"" << cutStr << "\", \"" << drawOptionsStr << "\");" << std::endl;
832bb12c 481 Int_t returnValue = fTree->Draw(drawStr.Data(), cutStr.Data(), drawOptionsStr.Data());
8192627b 482 if (returnValue == -1) return -1;
832bb12c 483
8192627b 484 TObject *obj = (gPad) ? gPad->GetPrimitive("htemp") : 0;
832bb12c 485 if (!obj) obj = (TH1F*)gDirectory->Get("htemp");
486 if (!obj) obj = gPad->GetPrimitive("tempHist");
487 if (!obj) obj = (TH1F*)gDirectory->Get("tempHist");
488 if (!obj) obj = gPad->GetPrimitive("Graph");
489 if (!obj) obj = (TH1F*)gDirectory->Get("Graph");
490 if (obj && obj->InheritsFrom("TH1")) FormatHistoLabels((TH1*)obj);
491 return returnValue;
39bcd65d 492}
493
72d0ab7e 494
39bcd65d 495Int_t AliTPCCalibViewer::EasyDraw1D(const char* drawCommand, Int_t sector, const char* cuts, const char* drawOptions, Bool_t writeDrawCommand) const {
496 //
497 // easy drawing of data, use '~' for abbreviation of '.fElements'
498 // example: EasyDraw("CETmean~-CETmean_mean", 34, "(CETmean~-CETmean_mean)>0")
499 // sector: sector-number - the specified sector will be drwawn
500 // cuts: specifies cuts
501 // drawOptions: draw options like 'same'
502 // writeDrawCommand: write the command, that is passed to TTree::Draw
503 //
504
505 if (sector >= 0 && sector < 72) {
506 char sectorChr[3];
507 sprintf(sectorChr, "%i", sector);
508 return EasyDraw1D(drawCommand, sectorChr, cuts, drawOptions, writeDrawCommand);
509 }
510 Error("EasyDraw","The TPC contains only sectors between 0 and 71.");
511 return -1;
512}
513
39bcd65d 514
832bb12c 515void AliTPCCalibViewer::FormatHistoLabels(TH1 *histo) const {
516 //
517 // formats title and axis labels of histo
518 // removes '.fElements'
519 //
520 if (!histo) return;
521 TString replaceString(fAppendString.Data());
522 TString *str = new TString(histo->GetTitle());
523 str->ReplaceAll(replaceString, "");
524 histo->SetTitle(str->Data());
525 delete str;
526 if (histo->GetXaxis()) {
527 str = new TString(histo->GetXaxis()->GetTitle());
528 str->ReplaceAll(replaceString, "");
529 histo->GetXaxis()->SetTitle(str->Data());
530 delete str;
531 }
532 if (histo->GetYaxis()) {
533 str = new TString(histo->GetYaxis()->GetTitle());
534 str->ReplaceAll(replaceString, "");
535 histo->GetYaxis()->SetTitle(str->Data());
536 delete str;
537 }
538 if (histo->GetZaxis()) {
539 str = new TString(histo->GetZaxis()->GetTitle());
540 str->ReplaceAll(replaceString, "");
541 histo->GetZaxis()->SetTitle(str->Data());
542 delete str;
543 }
544}
545
546
72d0ab7e 547Int_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 {
548 //
549 // Easy drawing of data, in principle the same as EasyDraw1D
550 // Difference: A line for the mean / median / LTM is drawn
551 // in 'sigmas' you can specify in which distance to the mean/median/LTM you want to see a line in sigma-units, separated by ';'
552 // 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.
553 // "plotMean", "plotMedian" and "plotLTM": what kind of lines do you want to see?
554 //
555 if (sector >= 0 && sector < 72) {
556 char sectorChr[3];
557 sprintf(sectorChr, "%i", sector);
558 return DrawHisto1D(drawCommand, sectorChr, cuts, sigmas, plotMean, plotMedian, plotLTM);
559 }
560 Error("DrawHisto1D","The TPC contains only sectors between 0 and 71.");
561 return -1;
562}
39bcd65d 563
72d0ab7e 564
565Int_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 {
566 //
567 // Easy drawing of data, in principle the same as EasyDraw1D
568 // Difference: A line for the mean / median / LTM is drawn
569 // in 'sigmas' you can specify in which distance to the mean/median/LTM you want to see a line in sigma-units, separated by ';'
570 // 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.
571 // "plotMean", "plotMedian" and "plotLTM": what kind of lines do you want to see?
572 //
39bcd65d 573 Int_t oldOptStat = gStyle->GetOptStat();
574 gStyle->SetOptStat(0000000);
72d0ab7e 575 Double_t ltmFraction = 0.8;
576
577 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
578 TVectorF nsigma(sigmasTokens->GetEntriesFast());
579 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
580 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
581 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
582 nsigma[i] = sig;
39bcd65d 583 }
584
72d0ab7e 585 TString drawStr(drawCommand);
832bb12c 586 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
587 if (dangerousToDraw) {
588 Warning("DrawHisto1D", "The draw string must not contain ':' or '>>'.");
589 return -1;
590 }
72d0ab7e 591 drawStr += " >> tempHist";
592 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts);
593 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
594 // FIXME is this histogram deleted automatically?
595 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
596
597 Double_t mean = TMath::Mean(entries, values);
598 Double_t median = TMath::Median(entries, values);
599 Double_t sigma = TMath::RMS(entries, values);
600 Double_t maxY = htemp->GetMaximum();
601
39bcd65d 602 char c[500];
72d0ab7e 603 TLegend * legend = new TLegend(.7,.7, .99, .99, "Statistical information");
604// sprintf(c, "%s, sector: %i", type, sector);
832bb12c 605 //fListOfObjectsToBeDeleted->Add(legend);
39bcd65d 606
39bcd65d 607 if (plotMean) {
72d0ab7e 608 // draw Mean
609 TLine* line = new TLine(mean, 0, mean, maxY);
832bb12c 610 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 611 line->SetLineColor(kRed);
612 line->SetLineWidth(2);
613 line->SetLineStyle(1);
614 line->Draw();
72d0ab7e 615 sprintf(c, "Mean: %f", mean);
39bcd65d 616 legend->AddEntry(line, c, "l");
72d0ab7e 617 // draw sigma lines
39bcd65d 618 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 619 TLine* linePlusSigma = new TLine(mean + nsigma[i] * sigma, 0, mean + nsigma[i] * sigma, maxY);
832bb12c 620 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 621 linePlusSigma->SetLineColor(kRed);
72d0ab7e 622 linePlusSigma->SetLineStyle(2 + i);
39bcd65d 623 linePlusSigma->Draw();
72d0ab7e 624 TLine* lineMinusSigma = new TLine(mean - nsigma[i] * sigma, 0, mean - nsigma[i] * sigma, maxY);
832bb12c 625 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 626 lineMinusSigma->SetLineColor(kRed);
72d0ab7e 627 lineMinusSigma->SetLineStyle(2 + i);
39bcd65d 628 lineMinusSigma->Draw();
72d0ab7e 629 sprintf(c, "%i #sigma = %f",(Int_t)(nsigma[i]), (Float_t)(nsigma[i] * sigma));
39bcd65d 630 legend->AddEntry(lineMinusSigma, c, "l");
631 }
632 }
39bcd65d 633 if (plotMedian) {
72d0ab7e 634 // draw median
635 TLine* line = new TLine(median, 0, median, maxY);
832bb12c 636 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 637 line->SetLineColor(kBlue);
638 line->SetLineWidth(2);
639 line->SetLineStyle(1);
640 line->Draw();
72d0ab7e 641 sprintf(c, "Median: %f", median);
39bcd65d 642 legend->AddEntry(line, c, "l");
72d0ab7e 643 // draw sigma lines
39bcd65d 644 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 645 TLine* linePlusSigma = new TLine(median + nsigma[i] * sigma, 0, median + nsigma[i]*sigma, maxY);
832bb12c 646 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 647 linePlusSigma->SetLineColor(kBlue);
72d0ab7e 648 linePlusSigma->SetLineStyle(2 + i);
39bcd65d 649 linePlusSigma->Draw();
72d0ab7e 650 TLine* lineMinusSigma = new TLine(median - nsigma[i] * sigma, 0, median - nsigma[i]*sigma, maxY);
832bb12c 651 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 652 lineMinusSigma->SetLineColor(kBlue);
72d0ab7e 653 lineMinusSigma->SetLineStyle(2 + i);
39bcd65d 654 lineMinusSigma->Draw();
72d0ab7e 655 sprintf(c, "%i #sigma = %f",(Int_t)(nsigma[i]), (Float_t)(nsigma[i] * sigma));
39bcd65d 656 legend->AddEntry(lineMinusSigma, c, "l");
657 }
658 }
39bcd65d 659 if (plotLTM) {
72d0ab7e 660 // draw LTM
661 Double_t ltmRms = 0;
662 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
663 TLine* line = new TLine(ltm, 0, ltm, maxY);
832bb12c 664 //fListOfObjectsToBeDeleted->Add(line);
39bcd65d 665 line->SetLineColor(kGreen+2);
666 line->SetLineWidth(2);
667 line->SetLineStyle(1);
668 line->Draw();
72d0ab7e 669 sprintf(c, "LTM: %f", ltm);
39bcd65d 670 legend->AddEntry(line, c, "l");
72d0ab7e 671 // draw sigma lines
39bcd65d 672 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
72d0ab7e 673 TLine* linePlusSigma = new TLine(ltm + nsigma[i] * ltmRms, 0, ltm + nsigma[i] * ltmRms, maxY);
832bb12c 674 //fListOfObjectsToBeDeleted->Add(linePlusSigma);
39bcd65d 675 linePlusSigma->SetLineColor(kGreen+2);
676 linePlusSigma->SetLineStyle(2+i);
677 linePlusSigma->Draw();
678
72d0ab7e 679 TLine* lineMinusSigma = new TLine(ltm - nsigma[i] * ltmRms, 0, ltm - nsigma[i] * ltmRms, maxY);
832bb12c 680 //fListOfObjectsToBeDeleted->Add(lineMinusSigma);
39bcd65d 681 lineMinusSigma->SetLineColor(kGreen+2);
682 lineMinusSigma->SetLineStyle(2+i);
683 lineMinusSigma->Draw();
72d0ab7e 684 sprintf(c, "%i #sigma = %f", (Int_t)(nsigma[i]), (Float_t)(nsigma[i] * ltmRms));
39bcd65d 685 legend->AddEntry(lineMinusSigma, c, "l");
686 }
687 }
72d0ab7e 688 if (!plotMean && !plotMedian && !plotLTM) return -1;
39bcd65d 689 legend->Draw();
690 gStyle->SetOptStat(oldOptStat);
72d0ab7e 691 return 1;
39bcd65d 692}
693
39bcd65d 694
72d0ab7e 695Int_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 {
696 //
697 // 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
698 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'array', 'n' specifies the length of the array
699 // '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
700 // 'nbins': number of bins, 'binLow': first bin, 'binUp': last bin
701 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
702 // sigmaStep: the binsize of the generated histogram
703 // Begin_Latex
704 // 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 }
705 // End_Latex
706 //
707 //
708 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
709 // around the mean/median/LTM
710 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
711 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
712 // sigmaStep: the binsize of the generated histogram
713 // plotMean/plotMedian/plotLTM: specifies where to put the center
714 //
715 if (sector >= 0 && sector < 72) {
716 char sectorChr[3];
717 sprintf(sectorChr, "%i", sector);
718 return SigmaCut(drawCommand, sectorChr, cuts, sigmaMax, plotMean, plotMedian, plotLTM, pm, sigmas, sigmaStep);
719 }
720 Error("SigmaCut","The TPC contains only sectors between 0 and 71.");
721 return -1;
722}
723
724
725Int_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 {
726 //
727 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
728 // around the mean/median/LTM
729 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
730 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
731 // sigmaStep: the binsize of the generated histogram
732 // plotMean/plotMedian/plotLTM: specifies where to put the center
733 //
734
735 Double_t ltmFraction = 0.8;
736
737 TString drawStr(drawCommand);
832bb12c 738 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
739 if (dangerousToDraw) {
740 Warning("SigmaCut", "The draw string must not contain ':' or '>>'.");
741 return -1;
742 }
72d0ab7e 743 drawStr += " >> tempHist";
744
745 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
746 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
747 // FIXME is this histogram deleted automatically?
748 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
749
750 Double_t mean = TMath::Mean(entries, values);
751 Double_t median = TMath::Median(entries, values);
752 Double_t sigma = TMath::RMS(entries, values);
753
754 TLegend * legend = new TLegend(.7,.7, .99, .99, "Cumulative");
832bb12c 755 //fListOfObjectsToBeDeleted->Add(legend);
72d0ab7e 756 TH1F *cutHistoMean = 0;
757 TH1F *cutHistoMedian = 0;
758 TH1F *cutHistoLTM = 0;
759
760 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
761 TVectorF nsigma(sigmasTokens->GetEntriesFast());
762 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
763 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
764 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
765 nsigma[i] = sig;
766 }
767
768 if (plotMean) {
769 cutHistoMean = AliTPCCalibViewer::SigmaCut(htemp, mean, sigma, sigmaMax, sigmaStep, pm);
770 if (cutHistoMean) {
832bb12c 771 //fListOfObjectsToBeDeleted->Add(cutHistoMean);
72d0ab7e 772 cutHistoMean->SetLineColor(kRed);
773 legend->AddEntry(cutHistoMean, "Mean", "l");
774 cutHistoMean->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
775 cutHistoMean->Draw();
776 DrawLines(cutHistoMean, nsigma, legend, kRed, pm);
777 } // if (cutHistoMean)
778
779 }
780 if (plotMedian) {
781 cutHistoMedian = AliTPCCalibViewer::SigmaCut(htemp, median, sigma, sigmaMax, sigmaStep, pm);
782 if (cutHistoMedian) {
832bb12c 783 //fListOfObjectsToBeDeleted->Add(cutHistoMedian);
72d0ab7e 784 cutHistoMedian->SetLineColor(kBlue);
785 legend->AddEntry(cutHistoMedian, "Median", "l");
786 cutHistoMedian->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
787 if (plotMean && cutHistoMean) cutHistoMedian->Draw("same");
788 else cutHistoMedian->Draw();
789 DrawLines(cutHistoMedian, nsigma, legend, kBlue, pm);
790 } // if (cutHistoMedian)
791 }
792 if (plotLTM) {
793 Double_t ltmRms = 0;
794 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
795 cutHistoLTM = AliTPCCalibViewer::SigmaCut(htemp, ltm, ltmRms, sigmaMax, sigmaStep, pm);
796 if (cutHistoLTM) {
832bb12c 797 //fListOfObjectsToBeDeleted->Add(cutHistoLTM);
72d0ab7e 798 cutHistoLTM->SetLineColor(kGreen+2);
799 legend->AddEntry(cutHistoLTM, "LTM", "l");
800 cutHistoLTM->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
94bf739c 801 if ((plotMean && cutHistoMean) || (plotMedian && cutHistoMedian)) cutHistoLTM->Draw("same");
72d0ab7e 802 else cutHistoLTM->Draw();
803 DrawLines(cutHistoLTM, nsigma, legend, kGreen+2, pm);
804 }
805 }
806 if (!plotMean && !plotMedian && !plotLTM) return -1;
807 legend->Draw();
808 return 1;
809}
810
832bb12c 811
4f3934a1 812Int_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 {
813 //
814 // Creates a histogram, where you can see, how much of the data are inside sigma-intervals
815 // around the mean/median/LTM
816 // with drawCommand, sector and cuts you specify your input data, see EasyDraw
817 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma)
818 // sigmaStep: the binsize of the generated histogram
819 // plotMean/plotMedian/plotLTM: specifies where to put the center
820 //
821
822 // Double_t ltmFraction = 0.8; //unused
823 // avoid compiler warnings:
824 sigmaMax = sigmaMax;
825 pm = pm;
826 sigmaStep = sigmaStep;
827
828 TString drawStr(drawCommand);
829 drawStr += " >> tempHist";
830
831 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
832 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
833 TGraph *cutGraphMean = 0;
834 // TGraph *cutGraphMedian = 0;
835 // TGraph *cutGraphLTM = 0;
836 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
837 Int_t *index = new Int_t[entries];
838 Float_t *xarray = new Float_t[entries];
839 Float_t *yarray = new Float_t[entries];
840 TMath::Sort(entries, values, index, kFALSE);
841
842 Double_t mean = TMath::Mean(entries, values);
843 // Double_t median = TMath::Median(entries, values);
844 Double_t sigma = TMath::RMS(entries, values);
845
846 TLegend * legend = new TLegend(.7,.7, .99, .99, "Cumulative");
832bb12c 847 //fListOfObjectsToBeDeleted->Add(legend);
4f3934a1 848
849 // parse sigmas string
850 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
851 TVectorF nsigma(sigmasTokens->GetEntriesFast());
852 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
853 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
854 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
855 nsigma[i] = sig;
856 }
857
858 if (plotMean) {
859 for (Int_t i = 0; i < entries; i++) {
860 xarray[i] = TMath::Abs(values[index[i]] - mean) / sigma;
861 yarray[i] = float(i) / float(entries);
862 }
863 cutGraphMean = new TGraph(entries, xarray, yarray);
864 if (cutGraphMean) {
832bb12c 865 //fListOfObjectsToBeDeleted->Add(cutGraphMean);
4f3934a1 866 cutGraphMean->SetLineColor(kRed);
867 legend->AddEntry(cutGraphMean, "Mean", "l");
868 cutGraphMean->SetTitle(Form("%s, Cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
869 cutGraphMean->Draw("alu");
870 DrawLines(cutGraphMean, nsigma, legend, kRed, kTRUE);
871 }
872 }
873 /*
874 if (plotMedian) {
875 cutHistoMedian = AliTPCCalibViewer::SigmaCut(htemp, median, sigma, sigmaMax, sigmaStep, pm);
876 if (cutHistoMedian) {
877 fListOfObjectsToBeDeleted->Add(cutHistoMedian);
878 cutHistoMedian->SetLineColor(kBlue);
879 legend->AddEntry(cutHistoMedian, "Median", "l");
880 cutHistoMedian->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
881 if (plotMean && cutHistoMean) cutHistoMedian->Draw("same");
882 else cutHistoMedian->Draw();
883 DrawLines(cutHistoMedian, nsigma, legend, kBlue, pm);
884 } // if (cutHistoMedian)
885 }
886 if (plotLTM) {
887 Double_t ltmRms = 0;
888 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
889 cutHistoLTM = AliTPCCalibViewer::SigmaCut(htemp, ltm, ltmRms, sigmaMax, sigmaStep, pm);
890 if (cutHistoLTM) {
891 fListOfObjectsToBeDeleted->Add(cutHistoLTM);
892 cutHistoLTM->SetLineColor(kGreen+2);
893 legend->AddEntry(cutHistoLTM, "LTM", "l");
894 cutHistoLTM->SetTitle(Form("%s, cumulative; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
895 if (plotMean && cutHistoMean || plotMedian && cutHistoMedian) cutHistoLTM->Draw("same");
896 else cutHistoLTM->Draw();
897 DrawLines(cutHistoLTM, nsigma, legend, kGreen+2, pm);
898 }
899 }*/
900 if (!plotMean && !plotMedian && !plotLTM) return -1;
901 legend->Draw();
902 return 1;
903}
904
72d0ab7e 905
72d0ab7e 906Int_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 {
907 //
908 // 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"
909 // "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
910 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
911 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
912 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
913 // The actual work is done on the array.
914 /* Begin_Latex
915 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 }
916 End_Latex
917 */
918 if (sector >= 0 && sector < 72) {
919 char sectorChr[3];
920 sprintf(sectorChr, "%i", sector);
921 return Integrate(drawCommand, sectorChr, cuts, sigmaMax, plotMean, plotMedian, plotLTM, sigmas, sigmaStep);
922 }
923 Error("Integrate","The TPC contains only sectors between 0 and 71.");
924 return -1;
925
926}
927
928
4f3934a1 929Int_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 930 //
931 // 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"
932 // "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
933 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
934 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
935 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
936 // The actual work is done on the array.
937 /* Begin_Latex
938 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 }
939 End_Latex
940 */
941
942 Double_t ltmFraction = 0.8;
943
944 TString drawStr(drawCommand);
945 drawStr += " >> tempHist";
946
947 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
948 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
949 // FIXME is this histogram deleted automatically?
950 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
951
952 Double_t mean = TMath::Mean(entries, values);
953 Double_t median = TMath::Median(entries, values);
954 Double_t sigma = TMath::RMS(entries, values);
955
956 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
957 TVectorF nsigma(sigmasTokens->GetEntriesFast());
958 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
959 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
960 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
961 nsigma[i] = sig;
962 }
963
964 TLegend * legend = new TLegend(.7,.7, .99, .99, "Integrated histogram");
832bb12c 965 //fListOfObjectsToBeDeleted->Add(legend);
72d0ab7e 966 TH1F *integralHistoMean = 0;
967 TH1F *integralHistoMedian = 0;
968 TH1F *integralHistoLTM = 0;
969
970 if (plotMean) {
971 integralHistoMean = AliTPCCalibViewer::Integrate(htemp, mean, sigma, sigmaMax, sigmaStep);
972 if (integralHistoMean) {
832bb12c 973 //fListOfObjectsToBeDeleted->Add(integralHistoMean);
72d0ab7e 974 integralHistoMean->SetLineColor(kRed);
975 legend->AddEntry(integralHistoMean, "Mean", "l");
976 integralHistoMean->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
977 integralHistoMean->Draw();
978 DrawLines(integralHistoMean, nsigma, legend, kRed, kTRUE);
39bcd65d 979 }
72d0ab7e 980 }
981 if (plotMedian) {
982 integralHistoMedian = AliTPCCalibViewer::Integrate(htemp, median, sigma, sigmaMax, sigmaStep);
983 if (integralHistoMedian) {
832bb12c 984 //fListOfObjectsToBeDeleted->Add(integralHistoMedian);
72d0ab7e 985 integralHistoMedian->SetLineColor(kBlue);
986 legend->AddEntry(integralHistoMedian, "Median", "l");
987 integralHistoMedian->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
988 if (plotMean && integralHistoMean) integralHistoMedian->Draw("same");
989 else integralHistoMedian->Draw();
990 DrawLines(integralHistoMedian, nsigma, legend, kBlue, kTRUE);
39bcd65d 991 }
72d0ab7e 992 }
993 if (plotLTM) {
994 Double_t ltmRms = 0;
995 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
996 integralHistoLTM = AliTPCCalibViewer::Integrate(htemp, ltm, ltmRms, sigmaMax, sigmaStep);
997 if (integralHistoLTM) {
832bb12c 998 //fListOfObjectsToBeDeleted->Add(integralHistoLTM);
72d0ab7e 999 integralHistoLTM->SetLineColor(kGreen+2);
1000 legend->AddEntry(integralHistoLTM, "LTM", "l");
1001 integralHistoLTM->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
94bf739c 1002 if ((plotMean && integralHistoMean) || (plotMedian && integralHistoMedian)) integralHistoLTM->Draw("same");
72d0ab7e 1003 else integralHistoLTM->Draw();
1004 DrawLines(integralHistoLTM, nsigma, legend, kGreen+2, kTRUE);
39bcd65d 1005 }
1006 }
72d0ab7e 1007 if (!plotMean && !plotMedian && !plotLTM) return -1;
1008 legend->Draw();
1009 return 1;
1010}
1011
1012
4f3934a1 1013Int_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 {
1014 //
1015 // 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"
1016 // "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
1017 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1018 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1019 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1020 // The actual work is done on the array.
1021 /* Begin_Latex
1022 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 }
1023 End_Latex
1024 */
1025
1026 Double_t ltmFraction = 0.8;
1027 // avoid compiler warnings:
1028 sigmaMax = sigmaMax;
1029 sigmaStep = sigmaStep;
1030
1031 TString drawStr(drawCommand);
832bb12c 1032 Bool_t dangerousToDraw = drawStr.Contains(":") || drawStr.Contains(">>");
1033 if (dangerousToDraw) {
1034 Warning("Integrate", "The draw string must not contain ':' or '>>'.");
1035 return -1;
1036 }
4f3934a1 1037 drawStr += " >> tempHist";
1038
1039 Int_t entries = EasyDraw1D(drawStr.Data(), sector, cuts, "goff");
1040 TH1F *htemp = (TH1F*)gDirectory->Get("tempHist");
1041 TGraph *integralGraphMean = 0;
1042 TGraph *integralGraphMedian = 0;
1043 TGraph *integralGraphLTM = 0;
1044 Double_t *values = fTree->GetV1(); // value is the array containing 'entries' numbers
1045 Int_t *index = new Int_t[entries];
1046 Float_t *xarray = new Float_t[entries];
1047 Float_t *yarray = new Float_t[entries];
1048 TMath::Sort(entries, values, index, kFALSE);
1049
1050 Double_t mean = TMath::Mean(entries, values);
1051 Double_t median = TMath::Median(entries, values);
1052 Double_t sigma = TMath::RMS(entries, values);
1053
1054 // parse sigmas string
1055 TObjArray *sigmasTokens = TString(sigmas).Tokenize(";");
1056 TVectorF nsigma(sigmasTokens->GetEntriesFast());
1057 for (Int_t i = 0; i < sigmasTokens->GetEntriesFast(); i++) {
1058 TString str(((TObjString*)sigmasTokens->At(i))->GetString());
1059 Double_t sig = (str.IsFloat()) ? str.Atof() : 0;
1060 nsigma[i] = sig;
1061 }
1062
1063 TLegend * legend = new TLegend(.7,.7, .99, .99, "Integrated histogram");
832bb12c 1064 //fListOfObjectsToBeDeleted->Add(legend);
4f3934a1 1065
1066 if (plotMean) {
1067 for (Int_t i = 0; i < entries; i++) {
1068 xarray[i] = (values[index[i]] - mean) / sigma;
1069 yarray[i] = float(i) / float(entries);
1070 }
1071 integralGraphMean = new TGraph(entries, xarray, yarray);
1072 if (integralGraphMean) {
832bb12c 1073 //fListOfObjectsToBeDeleted->Add(integralGraphMean);
4f3934a1 1074 integralGraphMean->SetLineColor(kRed);
1075 legend->AddEntry(integralGraphMean, "Mean", "l");
1076 integralGraphMean->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
1077 integralGraphMean->Draw("alu");
1078 DrawLines(integralGraphMean, nsigma, legend, kRed, kTRUE);
1079 }
1080 }
1081 if (plotMedian) {
1082 for (Int_t i = 0; i < entries; i++) {
1083 xarray[i] = (values[index[i]] - median) / sigma;
1084 yarray[i] = float(i) / float(entries);
1085 }
1086 integralGraphMedian = new TGraph(entries, xarray, yarray);
1087 if (integralGraphMedian) {
832bb12c 1088 //fListOfObjectsToBeDeleted->Add(integralGraphMedian);
4f3934a1 1089 integralGraphMedian->SetLineColor(kBlue);
1090 legend->AddEntry(integralGraphMedian, "Median", "l");
1091 integralGraphMedian->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
1092 if (plotMean && integralGraphMean) integralGraphMedian->Draw("samelu");
1093 else integralGraphMedian->Draw("alu");
1094 DrawLines(integralGraphMedian, nsigma, legend, kBlue, kTRUE);
1095 }
1096 }
1097 if (plotLTM) {
1098 Double_t ltmRms = 0;
1099 Double_t ltm = GetLTM(entries, values, &ltmRms, ltmFraction);
1100 for (Int_t i = 0; i < entries; i++) {
1101 xarray[i] = (values[index[i]] - ltm) / ltmRms;
1102 yarray[i] = float(i) / float(entries);
1103 }
1104 integralGraphLTM = new TGraph(entries, xarray, yarray);
1105 if (integralGraphLTM) {
832bb12c 1106 //fListOfObjectsToBeDeleted->Add(integralGraphLTM);
4f3934a1 1107 integralGraphLTM->SetLineColor(kGreen+2);
1108 legend->AddEntry(integralGraphLTM, "LTM", "l");
1109 integralGraphLTM->SetTitle(Form("%s, integrated; Multiples of #sigma; Fraction of included data", htemp->GetTitle()));
94bf739c 1110 if ((plotMean && integralGraphMean) || (plotMedian && integralGraphMedian)) integralGraphLTM->Draw("samelu");
4f3934a1 1111 else integralGraphLTM->Draw("alu");
1112 DrawLines(integralGraphLTM, nsigma, legend, kGreen+2, kTRUE);
1113 }
1114 }
1115 if (!plotMean && !plotMedian && !plotLTM) return -1;
1116 legend->Draw();
1117 return entries;
1118}
1119
1120
72d0ab7e 1121void AliTPCCalibViewer::DrawLines(TH1F *histogram, TVectorF nsigma, TLegend *legend, Int_t color, Bool_t pm) const {
1122 //
1123 // Private function for SigmaCut(...) and Integrate(...)
1124 // Draws lines into the given histogram, specified by "nsigma", the lines are addeed to the legend
1125 //
39bcd65d 1126
72d0ab7e 1127 // start to draw the lines, loop over requested sigmas
39bcd65d 1128 char c[500];
72d0ab7e 1129 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
1130 if (!pm) {
1131 Int_t bin = histogram->GetXaxis()->FindBin(nsigma[i]);
1132 TLine* lineUp = new TLine(nsigma[i], 0, nsigma[i], histogram->GetBinContent(bin));
832bb12c 1133 //fListOfObjectsToBeDeleted->Add(lineUp);
72d0ab7e 1134 lineUp->SetLineColor(color);
1135 lineUp->SetLineStyle(2 + i);
1136 lineUp->Draw();
1137 TLine* lineLeft = new TLine(nsigma[i], histogram->GetBinContent(bin), 0, histogram->GetBinContent(bin));
832bb12c 1138 //fListOfObjectsToBeDeleted->Add(lineLeft);
72d0ab7e 1139 lineLeft->SetLineColor(color);
1140 lineLeft->SetLineStyle(2 + i);
1141 lineLeft->Draw();
1142 sprintf(c, "Fraction(%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1143 legend->AddEntry(lineLeft, c, "l");
1144 }
1145 else { // if (pm)
1146 Int_t bin = histogram->GetXaxis()->FindBin(nsigma[i]);
1147 TLine* lineUp1 = new TLine(nsigma[i], 0, nsigma[i], histogram->GetBinContent(bin));
832bb12c 1148 //fListOfObjectsToBeDeleted->Add(lineUp1);
72d0ab7e 1149 lineUp1->SetLineColor(color);
1150 lineUp1->SetLineStyle(2 + i);
1151 lineUp1->Draw();
1152 TLine* lineLeft1 = new TLine(nsigma[i], histogram->GetBinContent(bin), histogram->GetBinLowEdge(0)+histogram->GetBinWidth(0), histogram->GetBinContent(bin));
832bb12c 1153 //fListOfObjectsToBeDeleted->Add(lineLeft1);
72d0ab7e 1154 lineLeft1->SetLineColor(color);
1155 lineLeft1->SetLineStyle(2 + i);
1156 lineLeft1->Draw();
1157 sprintf(c, "Fraction(+%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1158 legend->AddEntry(lineLeft1, c, "l");
1159 bin = histogram->GetXaxis()->FindBin(-nsigma[i]);
1160 TLine* lineUp2 = new TLine(-nsigma[i], 0, -nsigma[i], histogram->GetBinContent(bin));
832bb12c 1161 //fListOfObjectsToBeDeleted->Add(lineUp2);
72d0ab7e 1162 lineUp2->SetLineColor(color);
1163 lineUp2->SetLineStyle(2 + i);
1164 lineUp2->Draw();
1165 TLine* lineLeft2 = new TLine(-nsigma[i], histogram->GetBinContent(bin), histogram->GetBinLowEdge(0)+histogram->GetBinWidth(0), histogram->GetBinContent(bin));
832bb12c 1166 //fListOfObjectsToBeDeleted->Add(lineLeft2);
72d0ab7e 1167 lineLeft2->SetLineColor(color);
1168 lineLeft2->SetLineStyle(2 + i);
1169 lineLeft2->Draw();
1170 sprintf(c, "Fraction(-%f #sigma) = %f",nsigma[i], histogram->GetBinContent(bin));
1171 legend->AddEntry(lineLeft2, c, "l");
1172 }
1173 } // for (Int_t i = 0; i < nsigma.GetNoElements(); i++)
1174}
1175
1176
4f3934a1 1177void AliTPCCalibViewer::DrawLines(TGraph *graph, TVectorF nsigma, TLegend *legend, Int_t color, Bool_t pm) const {
1178 //
1179 // Private function for SigmaCut(...) and Integrate(...)
1180 // Draws lines into the given histogram, specified by "nsigma", the lines are addeed to the legend
1181 //
1182
1183 // start to draw the lines, loop over requested sigmas
1184 char c[500];
1185 for (Int_t i = 0; i < nsigma.GetNoElements(); i++) {
1186 if (!pm) {
1187 TLine* lineUp = new TLine(nsigma[i], 0, nsigma[i], graph->Eval(nsigma[i]));
832bb12c 1188 //fListOfObjectsToBeDeleted->Add(lineUp);
4f3934a1 1189 lineUp->SetLineColor(color);
1190 lineUp->SetLineStyle(2 + i);
1191 lineUp->Draw();
1192 TLine* lineLeft = new TLine(nsigma[i], graph->Eval(nsigma[i]), 0, graph->Eval(nsigma[i]));
832bb12c 1193 //fListOfObjectsToBeDeleted->Add(lineLeft);
4f3934a1 1194 lineLeft->SetLineColor(color);
1195 lineLeft->SetLineStyle(2 + i);
1196 lineLeft->Draw();
1197 sprintf(c, "Fraction(%f #sigma) = %f",nsigma[i], graph->Eval(nsigma[i]));
1198 legend->AddEntry(lineLeft, c, "l");
1199 }
1200 else { // if (pm)
1201 TLine* lineUp1 = new TLine(nsigma[i], 0, nsigma[i], graph->Eval(nsigma[i]));
832bb12c 1202 //fListOfObjectsToBeDeleted->Add(lineUp1);
4f3934a1 1203 lineUp1->SetLineColor(color);
1204 lineUp1->SetLineStyle(2 + i);
1205 lineUp1->Draw();
1206 TLine* lineLeft1 = new TLine(nsigma[i], graph->Eval(nsigma[i]), graph->GetHistogram()->GetXaxis()->GetBinLowEdge(0), graph->Eval(nsigma[i]));
832bb12c 1207 //fListOfObjectsToBeDeleted->Add(lineLeft1);
4f3934a1 1208 lineLeft1->SetLineColor(color);
1209 lineLeft1->SetLineStyle(2 + i);
1210 lineLeft1->Draw();
1211 sprintf(c, "Fraction(+%f #sigma) = %f",nsigma[i], graph->Eval(nsigma[i]));
1212 legend->AddEntry(lineLeft1, c, "l");
1213 TLine* lineUp2 = new TLine(-nsigma[i], 0, -nsigma[i], graph->Eval(-nsigma[i]));
832bb12c 1214 //fListOfObjectsToBeDeleted->Add(lineUp2);
4f3934a1 1215 lineUp2->SetLineColor(color);
1216 lineUp2->SetLineStyle(2 + i);
1217 lineUp2->Draw();
1218 TLine* lineLeft2 = new TLine(-nsigma[i], graph->Eval(-nsigma[i]), graph->GetHistogram()->GetXaxis()->GetBinLowEdge(0), graph->Eval(-nsigma[i]));
832bb12c 1219 //fListOfObjectsToBeDeleted->Add(lineLeft2);
4f3934a1 1220 lineLeft2->SetLineColor(color);
1221 lineLeft2->SetLineStyle(2 + i);
1222 lineLeft2->Draw();
1223 sprintf(c, "Fraction(-%f #sigma) = %f",nsigma[i], graph->Eval(-nsigma[i]));
1224 legend->AddEntry(lineLeft2, c, "l");
1225 }
1226 } // for (Int_t i = 0; i < nsigma.GetNoElements(); i++)
1227}
1228
72d0ab7e 1229
1230
1231
1232
1233/////////////////
1234// Array tools //
1235/////////////////
1236
1237
1238Int_t AliTPCCalibViewer::GetBin(Float_t value, Int_t nbins, Double_t binLow, Double_t binUp){
1239 // Returns the 'bin' for 'value'
1240 // The interval between 'binLow' and 'binUp' is divided into 'nbins' equidistant bins
1241 // avoid index out of bounds error: 'if (bin < binLow) bin = binLow' and vice versa
1242 /* Begin_Latex
1243 GetBin(value) = #frac{nbins - 1}{binUp - binLow} #upoint (value - binLow) +1
1244 End_Latex
1245 */
1246
1247 Int_t bin = TMath::Nint( (Float_t)(value - binLow) / (Float_t)(binUp - binLow) * (nbins-1) ) + 1;
1248 // avoid index out of bounds:
1249 if (value < binLow) bin = 0;
1250 if (value > binUp) bin = nbins + 1;
1251 return bin;
39bcd65d 1252
72d0ab7e 1253}
39bcd65d 1254
72d0ab7e 1255
2811495d 1256Double_t AliTPCCalibViewer::GetLTM(Int_t n, const Double_t *const array, Double_t *const sigma, Double_t fraction){
72d0ab7e 1257 //
1258 // returns the LTM and sigma
1259 //
1260 Double_t *ddata = new Double_t[n];
1261 Double_t mean = 0, lsigma = 0;
1262 UInt_t nPoints = 0;
1263 for (UInt_t i = 0; i < (UInt_t)n; i++) {
1264 ddata[nPoints]= array[nPoints];
1265 nPoints++;
1266 }
1267 Int_t hh = TMath::Min(TMath::Nint(fraction * nPoints), Int_t(n));
1268 AliMathBase::EvaluateUni(nPoints, ddata, mean, lsigma, hh);
1269 if (sigma) *sigma = lsigma;
1270 delete [] ddata;
1271 return mean;
39bcd65d 1272}
1273
1274
2811495d 1275TH1F* AliTPCCalibViewer::SigmaCut(TH1F *const histogram, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep, Bool_t pm) {
72d0ab7e 1276 //
1277 // 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
1278 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'histogram'
1279 // '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
1280 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
1281 // sigmaStep: the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1282 // pm: Decide weather Begin_Latex t > 0 End_Latex (first case) or Begin_Latex t End_Latex arbitrary (secound case)
1283 // The actual work is done on the array.
1284 /* Begin_Latex
1285 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
1286 or
1287 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 }
1288 End_Latex
1289 begin_macro(source)
1290 {
1291 Float_t mean = 0;
1292 Float_t sigma = 1.5;
1293 Float_t sigmaMax = 4;
1294 gROOT->SetStyle("Plain");
5547c0ab 1295 TH1F *distribution = new TH1F("Distribution1", "Distribution f(x, #mu, #sigma)", 1000,-5,5);
72d0ab7e 1296 TRandom rand(23);
1297 for (Int_t i = 0; i <50000;i++) distribution->Fill(rand.Gaus(mean, sigma));
1298 Float_t *ar = distribution->GetArray();
1299
5547c0ab 1300 TCanvas* macro_example_canvas = new TCanvas("macro_example_canvas_SigmaCut", "", 350, 350);
72d0ab7e 1301 macro_example_canvas->Divide(0,3);
1302 TVirtualPad *pad1 = macro_example_canvas->cd(1);
1303 pad1->SetGridy();
1304 pad1->SetGridx();
1305 distribution->Draw();
1306 TVirtualPad *pad2 = macro_example_canvas->cd(2);
1307 pad2->SetGridy();
1308 pad2->SetGridx();
1309
1310 TH1F *shist = AliTPCCalibViewer::SigmaCut(distribution, mean, sigma, sigmaMax);
1311 shist->SetNameTitle("Cumulative","Cumulative S(t, #mu, #sigma)");
1312 shist->Draw();
1313 TVirtualPad *pad3 = macro_example_canvas->cd(3);
1314 pad3->SetGridy();
1315 pad3->SetGridx();
1316 TH1F *shistPM = AliTPCCalibViewer::SigmaCut(distribution, mean, sigma, sigmaMax, -1, kTRUE);
1317 shistPM->Draw();
1318 return macro_example_canvas;
1319 }
1320 end_macro
1321 */
1322
1323 Float_t *array = histogram->GetArray();
1324 Int_t nbins = histogram->GetXaxis()->GetNbins();
1325 Float_t binLow = histogram->GetXaxis()->GetXmin();
1326 Float_t binUp = histogram->GetXaxis()->GetXmax();
1327 return AliTPCCalibViewer::SigmaCut(nbins, array, mean, sigma, nbins, binLow, binUp, sigmaMax, sigmaStep, pm);
1328}
1329
1330
2811495d 1331TH1F* AliTPCCalibViewer::SigmaCut(Int_t n, const 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){
72d0ab7e 1332 //
1333 // 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
1334 // The data of the distribution Begin_Latex f(x, #mu, #sigma) End_Latex are given in 'array', 'n' specifies the length of the array
1335 // '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
1336 // 'nbins': number of bins, 'binLow': first bin, 'binUp': last bin
1337 // sigmaMax: up to which sigma around the mean/median/LTM the histogram is generated (in units of sigma, Begin_Latex t #sigma End_Latex)
1338 // sigmaStep: the binsize of the generated histogram
1339 // Here the actual work is done.
1340
1341 if (sigma == 0) return 0;
1342 Float_t binWidth = (binUp-binLow)/(nbins - 1);
1343 if (sigmaStep <= 0) sigmaStep = binWidth;
1344 Int_t kbins = (Int_t)(sigmaMax * sigma / sigmaStep) + 1; // + 1 due to overflow bin in histograms
1345 if (pm) kbins = 2 * (Int_t)(sigmaMax * sigma / sigmaStep) + 1;
1346 Float_t kbinLow = !pm ? 0 : -sigmaMax;
1347 Float_t kbinUp = sigmaMax;
1348 TH1F *hist = new TH1F("sigmaCutHisto","Cumulative; Multiples of #sigma; Fraction of included data", kbins, kbinLow, kbinUp);
1349 hist->SetDirectory(0);
1350 hist->Reset();
1351
1352 // calculate normalization
1353 Double_t normalization = 0;
1354 for (Int_t i = 0; i <= n; i++) {
1355 normalization += array[i];
1356 }
1357
1358 // given units: units from given histogram
1359 // sigma units: in units of sigma
1360 // iDelta: integrate in interval (mean +- iDelta), given units
1361 // x: ofset from mean for integration, given units
1362 // hist: needs
1363
1364// printf("nbins: %i, binLow: %f, binUp: %f \n", nbins, binLow, binUp);
1365 // fill histogram
1366 for (Float_t iDelta = 0; iDelta <= sigmaMax * sigma; iDelta += sigmaStep) {
1367 // integrate array
1368 Double_t valueP = array[GetBin(mean, nbins, binLow, binUp)];
1369 Double_t valueM = array[GetBin(mean-binWidth, nbins, binLow, binUp)];
1370 // add bin of mean value only once to the histogram
1371// printf("++ adding bins: ");
1372 for (Float_t x = binWidth; x <= iDelta; x += binWidth) {
1373 valueP += (mean + x <= binUp) ? array[GetBin(mean + x, nbins, binLow, binUp)] : 0;
1374 valueM += (mean-binWidth - x >= binLow) ? array[GetBin(mean-binWidth - x, nbins, binLow, binUp)] : 0;
1375// printf("%i, ", GetBin(mean + x, nbins, binLow, binUp));
1376 }
1377// printf("\n");
1378 if (valueP / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", valueP, normalization);
1379 if (valueP / normalization > 100) return hist;
1380 if (valueM / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", valueM, normalization);
1381 if (valueM / normalization > 100) return hist;
1382 valueP = (valueP / normalization);
1383 valueM = (valueM / normalization);
1384 if (pm) {
1385 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1386 hist->SetBinContent(bin, valueP);
1387 bin = GetBin(-iDelta/sigma, kbins, kbinLow, kbinUp);
1388 hist->SetBinContent(bin, valueM);
1389 }
1390 else { // if (!pm)
1391 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1392 hist->SetBinContent(bin, valueP + valueM);
1393// printf(" first integration bin: %i, last integration bin in + direction: %i \n", GetBin(mean+binWidth, nbins, binLow, binUp), GetBin(iDelta, nbins, binLow, binUp));
1394// printf(" first integration bin: %i, last integration bin in - direction: %i \n", GetBin(mean+binWidth, nbins, binLow, binUp), GetBin(-iDelta, nbins, binLow, binUp));
1395// printf(" value: %f, normalization: %f, iDelta: %f, Bin: %i \n", valueP+valueM, normalization, iDelta, bin);
1396 }
1397 }
1398 //hist->SetMaximum(0.7);
1399 if (!pm) hist->SetMaximum(1.2);
1400 return hist;
1401}
1402
1403
2811495d 1404TH1F* AliTPCCalibViewer::SigmaCut(Int_t n, const Double_t *array, Double_t mean, Double_t sigma, Int_t nbins, const Double_t *xbins, Double_t sigmaMax){
72d0ab7e 1405 //
1406 // SigmaCut for variable binsize
1407 // NOT YET IMPLEMENTED !!!
1408 //
1409 printf("SigmaCut with variable binsize, Not yet implemented\n");
1410 // avoid compiler warnings:
1411 n=n;
1412 mean=mean;
1413 sigma=sigma;
1414 nbins=nbins;
1415 sigmaMax=sigmaMax;
1416 array=array;
1417 xbins=xbins;
1418
1419 return 0;
1420}
1421
1422
2811495d 1423TH1F* AliTPCCalibViewer::Integrate(TH1F *const histogram, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep){
72d0ab7e 1424 //
1425 // 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"
1426 // "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
1427 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1428 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1429 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1430 // The actual work is done on the array.
1431 /* Begin_Latex
1432 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 }
1433 End_Latex
1434 begin_macro(source)
1435 {
1436 Float_t mean = 0;
1437 Float_t sigma = 1.5;
1438 Float_t sigmaMax = 4;
1439 gROOT->SetStyle("Plain");
5547c0ab 1440 TH1F *distribution = new TH1F("Distribution2", "Distribution f(x, #mu, #sigma)", 1000,-5,5);
72d0ab7e 1441 TRandom rand(23);
1442 for (Int_t i = 0; i <50000;i++) distribution->Fill(rand.Gaus(mean, sigma));
1443 Float_t *ar = distribution->GetArray();
1444
5547c0ab 1445 TCanvas* macro_example_canvas = new TCanvas("macro_example_canvas_Integrate", "", 350, 350);
72d0ab7e 1446 macro_example_canvas->Divide(0,2);
1447 TVirtualPad *pad1 = macro_example_canvas->cd(1);
1448 pad1->SetGridy();
1449 pad1->SetGridx();
1450 distribution->Draw();
1451 TVirtualPad *pad2 = macro_example_canvas->cd(2);
1452 pad2->SetGridy();
1453 pad2->SetGridx();
1454 TH1F *shist = AliTPCCalibViewer::Integrate(distribution, mean, sigma, sigmaMax);
1455 shist->SetNameTitle("Cumulative","Cumulative S(t, #mu, #sigma)");
1456 shist->Draw();
1457
7072d276 1458 return macro_example_canvas_Integrate;
72d0ab7e 1459 }
1460 end_macro
1461 */
1462
1463
1464 Float_t *array = histogram->GetArray();
1465 Int_t nbins = histogram->GetXaxis()->GetNbins();
1466 Float_t binLow = histogram->GetXaxis()->GetXmin();
1467 Float_t binUp = histogram->GetXaxis()->GetXmax();
1468 return AliTPCCalibViewer::Integrate(nbins, array, nbins, binLow, binUp, mean, sigma, sigmaMax, sigmaStep);
1469}
1470
1471
2811495d 1472TH1F* AliTPCCalibViewer::Integrate(Int_t n, const Float_t *const array, Int_t nbins, Float_t binLow, Float_t binUp, Float_t mean, Float_t sigma, Float_t sigmaMax, Float_t sigmaStep){
72d0ab7e 1473 // 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"
1474 // "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
1475 // sigmaMax: up to which sigma around the mean/median/LTM you want to integrate
1476 // if "igma == 0" and "sigmaMax == 0" the whole histogram is integrated
1477 // "sigmaStep": the binsize of the generated histogram, -1 means, that the maximal reasonable stepsize is used
1478 // Here the actual work is done.
1479
1480 Bool_t givenUnits = kTRUE;
1481 if (sigma != 0 && sigmaMax != 0) givenUnits = kFALSE;
1482 if (givenUnits) {
1483 sigma = 1;
1484 sigmaMax = (binUp - binLow) / 2.;
1485 }
1486
1487 Float_t binWidth = (binUp-binLow)/(nbins - 1);
1488 if (sigmaStep <= 0) sigmaStep = binWidth;
1489 Int_t kbins = (Int_t)(sigmaMax * sigma / sigmaStep) + 1; // + 1 due to overflow bin in histograms
1490 Float_t kbinLow = givenUnits ? binLow : -sigmaMax;
1491 Float_t kbinUp = givenUnits ? binUp : sigmaMax;
1492 TH1F *hist = 0;
1493 if (givenUnits) hist = new TH1F("integratedHisto","Integrated Histogram; Given x; Fraction of included data", kbins, kbinLow, kbinUp);
1494 if (!givenUnits) hist = new TH1F("integratedHisto","Integrated Histogram; Multiples of #sigma; Fraction of included data", kbins, kbinLow, kbinUp);
1495 hist->SetDirectory(0);
1496 hist->Reset();
1497
1498 // calculate normalization
1499 // printf("calculating normalization, integrating from bin 1 to %i \n", n);
1500 Double_t normalization = 0;
1501 for (Int_t i = 1; i <= n; i++) {
1502 normalization += array[i];
1503 }
1504 // printf("normalization: %f \n", normalization);
1505
1506 // given units: units from given histogram
1507 // sigma units: in units of sigma
1508 // iDelta: integrate in interval (mean +- iDelta), given units
1509 // x: ofset from mean for integration, given units
1510 // hist: needs
1511
1512 // fill histogram
1513 for (Float_t iDelta = mean - sigmaMax * sigma; iDelta <= mean + sigmaMax * sigma; iDelta += sigmaStep) {
1514 // integrate array
1515 Double_t value = 0;
1516 for (Float_t x = mean - sigmaMax * sigma; x <= iDelta; x += binWidth) {
1517 value += (x <= binUp && x >= binLow) ? array[GetBin(x, nbins, binLow, binUp)] : 0;
1518 }
1519 if (value / normalization > 100) printf("+++ Error, value to big: %f, normalization with %f will fail +++ \n", value, normalization);
1520 if (value / normalization > 100) return hist;
1521 Int_t bin = GetBin(iDelta/sigma, kbins, kbinLow, kbinUp);
1522 // printf("first integration bin: %i, last integration bin: %i \n", GetBin(mean - sigmaMax * sigma, nbins, binLow, binUp), GetBin(iDelta, nbins, binLow, binUp));
1523 // printf("value: %f, normalization: %f, normalized value: %f, iDelta: %f, Bin: %i \n", value, normalization, value/normalization, iDelta, bin);
1524 value = (value / normalization);
1525 hist->SetBinContent(bin, value);
1526 }
1527 return hist;
1528}
1529
1530
1531
1532
1533
1534////////////////////////
1535// end of Array tools //
1536////////////////////////
1537
1538
1539
39bcd65d 1540//_____________________________________________________________________________
a6e0ebfe 1541AliTPCCalPad* AliTPCCalibViewer::GetCalPadOld(const char* desiredData, const char* cuts, const char* calPadName) const {
39bcd65d 1542 //
1543 // creates a AliTPCCalPad out of the 'desiredData'
1544 // the functionality of EasyDraw1D is used
1545 // calPadName specifies the name of the created AliTPCCalPad
1546 // - this takes a while -
1547 //
1548 TString drawStr(desiredData);
832bb12c 1549 drawStr.Append(":channel");
1550 drawStr.Append(fAbbreviation);
39bcd65d 1551 AliTPCCalPad * createdCalPad = new AliTPCCalPad(calPadName, calPadName);
1552 Int_t entries = 0;
1553 for (Int_t sec = 0; sec < 72; sec++) {
ac7becc3 1554 AliTPCCalROC * roc = createdCalPad->GetCalROC(sec);
39bcd65d 1555 entries = EasyDraw1D(drawStr.Data(), (Int_t)sec, cuts, "goff");
a6d2bd0c 1556 if (entries == -1) return 0;
ac7becc3 1557 const Double_t *pchannel = fTree->GetV2();
1558 const Double_t *pvalue = fTree->GetV1();
39bcd65d 1559 for (Int_t i = 0; i < entries; i++)
ac7becc3 1560 roc->SetValue((UInt_t)(pchannel[i]), (Float_t)(pvalue[i]));
1561 }
1562 return createdCalPad;
1563}
1564
1565
1566//_____________________________________________________________________________
a6e0ebfe 1567AliTPCCalPad* AliTPCCalibViewer::GetCalPad(const char* desiredData, const char* cuts, const char* calPadName) const {
ac7becc3 1568 //
1569 // creates a AliTPCCalPad out of the 'desiredData'
1570 // the functionality of EasyDraw1D is used
1571 // calPadName specifies the name of the created AliTPCCalPad
1572 // - this takes a while -
1573 //
1574 TString drawStr(desiredData);
1575 drawStr.Append(":channel.fElements:sector");
1576 AliTPCCalPad * createdCalPad = new AliTPCCalPad(calPadName, calPadName);
1577 //
1578 Int_t entries = fTree->Draw(drawStr, cuts,"goff");
1579 const Double_t *pvalue = fTree->GetV1();
1580 const Double_t *pchannel = fTree->GetV2();
1581 const Double_t *psector = fTree->GetV3();
1582
1583 for (Int_t ientry=0; ientry<entries; ientry++){
1584 Int_t sector= TMath::Nint(psector[ientry]);
1585 AliTPCCalROC * roc = createdCalPad->GetCalROC(sector);
1586 if (roc) roc->SetValue((UInt_t)(pchannel[ientry]), (Float_t)(pvalue[ientry]));
39bcd65d 1587 }
ac7becc3 1588
1589 // for (Int_t sec = 0; sec < 72; sec++) {
1590// AliTPCCalROC * roc = createdCalPad->GetCalROC(sec);
1591// entries = EasyDraw1D(drawStr.Data(), (Int_t)sec, cuts, "goff");
1592// if (entries == -1) return 0;
1593// for (Int_t i = 0; i < entries; i++)
1594// roc->SetValue((UInt_t)(pchannel[i]), (Float_t)(pvalue[i]));
1595// }
39bcd65d 1596 return createdCalPad;
1597}
1598
1599//_____________________________________________________________________________
f78da5ae 1600AliTPCCalROC* AliTPCCalibViewer::GetCalROC(const char* desiredData, UInt_t sector, const char* cuts) const {
39bcd65d 1601 //
1602 // creates a AliTPCCalROC out of the desiredData
1603 // the functionality of EasyDraw1D is used
1604 // sector specifies the sector of the created AliTPCCalROC
1605 //
1606 TString drawStr(desiredData);
8192627b 1607 drawStr.Append(":channel");
1608 drawStr.Append(fAbbreviation);
39bcd65d 1609 Int_t entries = EasyDraw1D(drawStr.Data(), (Int_t)sector, cuts, "goff");
a6d2bd0c 1610 if (entries == -1) return 0;
39bcd65d 1611 AliTPCCalROC * createdROC = new AliTPCCalROC(sector);
1612 for (Int_t i = 0; i < entries; i++)
1613 createdROC->SetValue((UInt_t)(fTree->GetV2()[i]), fTree->GetV1()[i]);
1614 return createdROC;
1615}
1616
1617
1618TObjArray* AliTPCCalibViewer::GetListOfVariables(Bool_t printList) {
1619 //
1620 // scan the tree - produces a list of available variables in the tree
1621 // printList: print the list to the screen, after the scan is done
1622 //
1623 TObjArray* arr = new TObjArray();
1624 TObjString* str = 0;
596afefb 1625 if (!fTree) return 0;
39bcd65d 1626 Int_t nentries = fTree->GetListOfBranches()->GetEntries();
1627 for (Int_t i = 0; i < nentries; i++) {
1628 str = new TObjString(fTree->GetListOfBranches()->At(i)->GetName());
1629 str->String().ReplaceAll("_Median", "");
1630 str->String().ReplaceAll("_Mean", "");
1631 str->String().ReplaceAll("_RMS", "");
1632 str->String().ReplaceAll("_LTM", "");
1633 str->String().ReplaceAll("_OutlierCutted", "");
1634 str->String().ReplaceAll(".", "");
1635 if (!arr->FindObject(str) &&
1636 !(str->String() == "channel" || str->String() == "gx" || str->String() == "gy" ||
1637 str->String() == "lx" || str->String() == "ly" || str->String() == "pad" ||
1638 str->String() == "row" || str->String() == "rpad" || str->String() == "sector" ))
1639 arr->Add(str);
1640 }
832bb12c 1641
1642 // loop over all friends (if there are some) and add them to the list
1643 if (fTree->GetListOfFriends()) {
1644 for (Int_t ifriend = 0; ifriend < fTree->GetListOfFriends()->GetEntries(); ifriend++){
1645 // printf("iterating through friendlist, currently at %i\n", ifriend);
1646 // printf("working with %s\n", fTree->GetListOfFriends()->At(ifriend)->ClassName());
1647 if (TString(fTree->GetListOfFriends()->At(ifriend)->ClassName()) != "TFriendElement") continue; // no friendElement found
1648 TFriendElement *friendElement = (TFriendElement*)fTree->GetListOfFriends()->At(ifriend);
1649 if (friendElement->GetTree() == 0) continue; // no tree found in friendElement
1650 // printf("friend found \n");
1651 for (Int_t i = 0; i < friendElement->GetTree()->GetListOfBranches()->GetEntries(); i++) {
1652 // printf("iterating through friendelement entries, currently at %i\n", i);
1653 str = new TObjString(friendElement->GetTree()->GetListOfBranches()->At(i)->GetName());
1654 str->String().ReplaceAll("_Median", "");
1655 str->String().ReplaceAll("_Mean", "");
1656 str->String().ReplaceAll("_RMS", "");
1657 str->String().ReplaceAll("_LTM", "");
1658 str->String().ReplaceAll("_OutlierCutted", "");
1659 str->String().ReplaceAll(".", "");
1660 if (!(str->String() == "channel" || str->String() == "gx" || str->String() == "gy" ||
1661 str->String() == "lx" || str->String() == "ly" || str->String() == "pad" ||
1662 str->String() == "row" || str->String() == "rpad" || str->String() == "sector" )){
1663 // insert "<friendName>." at the beginning: (<friendName> is per default "R")
1664 str->String().Insert(0, ".");
1665 str->String().Insert(0, friendElement->GetName());
1666 if (!arr->FindObject(str)) arr->Add(str);
1667 // printf("added string %s \n", str->String().Data());
1668 }
1669 }
1670 }
1671 } // if (fTree->GetListOfFriends())
1672
39bcd65d 1673 arr->Sort();
832bb12c 1674// ((TFriendElement*)gui->GetViewer()->GetTree()->GetListOfFriends()->At(0))->GetTree()->GetListOfBranches()->At(0)->GetName()
1675// ((TFriendElement*)gui->GetViewer()->GetTree()->GetListOfFriends()->At(0))->GetTree()->GetListOfBranches()
1676
39bcd65d 1677
1678 if (printList) {
1679 TIterator* iter = arr->MakeIterator();
1680 iter->Reset();
1681 TObjString* currentStr = 0;
1682 while ( (currentStr = (TObjString*)(iter->Next())) ) {
1683 std::cout << currentStr->GetString().Data() << std::endl;
1684 }
1685 delete iter;
1686 }
1687 return arr;
1688}
1689
1690
72d0ab7e 1691TObjArray* AliTPCCalibViewer::GetListOfNormalizationVariables(Bool_t printList) const{
39bcd65d 1692 //
1693 // produces a list of available variables for normalization in the tree
1694 // printList: print the list to the screen, after the scan is done
1695 //
1696 TObjArray* arr = new TObjArray();
1697 arr->Add(new TObjString("_Mean"));
1698 arr->Add(new TObjString("_Mean_OutlierCutted"));
1699 arr->Add(new TObjString("_Median"));
1700 arr->Add(new TObjString("_Median_OutlierCutted"));
1701 arr->Add(new TObjString("_LTM"));
1702 arr->Add(new TObjString("_LTM_OutlierCutted"));
832bb12c 1703 arr->Add(new TObjString(Form("LFitIntern_4_8%s", fAppendString.Data())));
1704 arr->Add(new TObjString(Form("GFitIntern_Lin%s", fAppendString.Data())));
1705 arr->Add(new TObjString(Form("GFitIntern_Par%s", fAppendString.Data())));
a6d2bd0c 1706 arr->Add(new TObjString("FitLinLocal"));
1707 arr->Add(new TObjString("FitLinGlobal"));
72d0ab7e 1708 arr->Add(new TObjString("FitParLocal"));
1709 arr->Add(new TObjString("FitParGlobal"));
39bcd65d 1710
1711 if (printList) {
1712 TIterator* iter = arr->MakeIterator();
1713 iter->Reset();
1714 TObjString* currentStr = 0;
1715 while ((currentStr = (TObjString*)(iter->Next()))) {
1716 std::cout << currentStr->GetString().Data() << std::endl;
1717 }
1718 delete iter;
1719 }
1720 return arr;
1721}
1722
1723
1724TFriendElement* AliTPCCalibViewer::AddReferenceTree(const char* filename, const char* treename, const char* refname){
1725 //
1726 // add a reference tree to the current tree
1727 // by default the treename is 'calPads' and the reference treename is 'R'
1728 //
1729 TFile *file = new TFile(filename);
1730 fListOfObjectsToBeDeleted->Add(file);
1731 TTree * tree = (TTree*)file->Get(treename);
1732 return AddFriend(tree, refname);
1733}
1734
1735
1736TObjArray* AliTPCCalibViewer::GetArrayOfCalPads(){
1737 //
1738 // Returns a TObjArray with all AliTPCCalPads that are stored in the tree
1739 // - this takes a while -
1740 //
1741 TObjArray *listOfCalPads = GetListOfVariables();
1742 TObjArray *calPadsArray = new TObjArray();
1743 Int_t numberOfCalPads = listOfCalPads->GetEntries();
1744 for (Int_t i = 0; i < numberOfCalPads; i++) {
832bb12c 1745 std::cout << "Creating calPad " << (i+1) << " of " << numberOfCalPads << "\r" << std::flush;
39bcd65d 1746 char* calPadName = (char*)((TObjString*)(listOfCalPads->At(i)))->GetString().Data();
1747 TString drawCommand = ((TObjString*)(listOfCalPads->At(i)))->GetString();
832bb12c 1748 drawCommand.Append(fAbbreviation.Data());
39bcd65d 1749 AliTPCCalPad* calPad = GetCalPad(drawCommand.Data(), "", calPadName);
1750 calPadsArray->Add(calPad);
1751 }
1752 std::cout << std::endl;
1753 listOfCalPads->Delete();
1754 delete listOfCalPads;
1755 return calPadsArray;
1756}
1757
1758
a6d2bd0c 1759TString* AliTPCCalibViewer::Fit(const char* drawCommand, const char* formula, const char* cuts, Double_t & chi2, TVectorD &fitParam, TMatrixD &covMatrix){
1760 //
1761 // fit an arbitrary function, specified by formula into the data, specified by drawCommand and cuts
1762 // returns chi2, fitParam and covMatrix
1763 // returns TString with fitted formula
1764 //
1765
1766 TString formulaStr(formula);
1767 TString drawStr(drawCommand);
1768 TString cutStr(cuts);
1769
1770 // abbreviations:
832bb12c 1771 drawStr.ReplaceAll(fAbbreviation, fAppendString);
1772 cutStr.ReplaceAll(fAbbreviation, fAppendString);
1773 formulaStr.ReplaceAll(fAbbreviation, fAppendString);
a6d2bd0c 1774
832bb12c 1775 formulaStr.ReplaceAll("++", fAbbreviation);
1776 TObjArray* formulaTokens = formulaStr.Tokenize(fAbbreviation.Data());
a6d2bd0c 1777 Int_t dim = formulaTokens->GetEntriesFast();
1778
1779 fitParam.ResizeTo(dim);
1780 covMatrix.ResizeTo(dim,dim);
1781
1782 TLinearFitter* fitter = new TLinearFitter(dim+1, Form("hyp%d",dim));
1783 fitter->StoreData(kTRUE);
1784 fitter->ClearPoints();
1785
1786 Int_t entries = Draw(drawStr.Data(), cutStr.Data(), "goff");
1787 if (entries == -1) return new TString("An ERROR has occured during fitting!");
1788 Double_t **values = new Double_t*[dim+1] ;
1789
1790 for (Int_t i = 0; i < dim + 1; i++){
1791 Int_t centries = 0;
1792 if (i < dim) centries = fTree->Draw(((TObjString*)formulaTokens->At(i))->GetName(), cutStr.Data(), "goff");
1793 else centries = fTree->Draw(drawStr.Data(), cutStr.Data(), "goff");
1794
1795 if (entries != centries) return new TString("An ERROR has occured during fitting!");
1796 values[i] = new Double_t[entries];
1797 memcpy(values[i], fTree->GetV1(), entries*sizeof(Double_t));
1798 }
1799
1800 // add points to the fitter
1801 for (Int_t i = 0; i < entries; i++){
1802 Double_t x[1000];
1803 for (Int_t j=0; j<dim;j++) x[j]=values[j][i];
1804 fitter->AddPoint(x, values[dim][i], 1);
1805 }
1806
1807 fitter->Eval();
1808 fitter->GetParameters(fitParam);
1809 fitter->GetCovarianceMatrix(covMatrix);
1810 chi2 = fitter->GetChisquare();
1811 chi2 = chi2;
1812
7390f655 1813 TString *preturnFormula = new TString(Form("( %e+",fitParam[0])), &returnFormula = *preturnFormula;
a6d2bd0c 1814
1815 for (Int_t iparam = 0; iparam < dim; iparam++) {
7390f655 1816 returnFormula.Append(Form("%s*(%e)",((TObjString*)formulaTokens->At(iparam))->GetName(),fitParam[iparam+1]));
a6d2bd0c 1817 if (iparam < dim-1) returnFormula.Append("+");
1818 }
1819 returnFormula.Append(" )");
1820 delete formulaTokens;
1821 delete fitter;
1822 delete[] values;
1823 return preturnFormula;
1824}
1825
1826
2811495d 1827void AliTPCCalibViewer::MakeTreeWithObjects(const char *fileName, const TObjArray *const array, const char * mapFileName) {
39bcd65d 1828 //
1829 // Write tree with all available information
1830 // im mapFileName is speciefied, the Map information are also written to the tree
1831 // AliTPCCalPad-Objects are written directly to the tree, so that they can be accessd later on
1832 // (does not work!!!)
1833 //
1834 AliTPCROC* tpcROCinstance = AliTPCROC::Instance();
1835
1836 TObjArray* mapIROCs = 0;
1837 TObjArray* mapOROCs = 0;
1838 TVectorF *mapIROCArray = 0;
1839 TVectorF *mapOROCArray = 0;
1840 Int_t mapEntries = 0;
1841 TString* mapNames = 0;
1842
1843 if (mapFileName) {
1844 TFile mapFile(mapFileName, "read");
1845
1846 TList* listOfROCs = mapFile.GetListOfKeys();
1847 mapEntries = listOfROCs->GetEntries()/2;
1848 mapIROCs = new TObjArray(mapEntries*2);
1849 mapOROCs = new TObjArray(mapEntries*2);
1850 mapIROCArray = new TVectorF[mapEntries];
1851 mapOROCArray = new TVectorF[mapEntries];
1852
1853 mapNames = new TString[mapEntries];
1854 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
72d0ab7e 1855 TString rocName(((TKey*)(listOfROCs->At(ivalue*2)))->GetName());
1856 rocName.Remove(rocName.Length()-4, 4);
1857 mapIROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "IROC").Data()), ivalue);
1858 mapOROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "OROC").Data()), ivalue);
1859 mapNames[ivalue].Append(rocName);
39bcd65d 1860 }
1861
1862 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
1863 mapIROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(0));
1864 mapOROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(36));
1865
1866 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(0); ichannel++)
1867 (mapIROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapIROCs->At(ivalue)))->GetValue(ichannel);
1868 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(36); ichannel++)
1869 (mapOROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapOROCs->At(ivalue)))->GetValue(ichannel);
1870 }
1871
1872 } // if (mapFileName)
1873
1874 TTreeSRedirector cstream(fileName);
1875 Int_t arrayEntries = array->GetEntries();
1876
1877 // Read names of AliTPCCalPads and save them in names[]
1878 TString* names = new TString[arrayEntries];
1879 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
1880 names[ivalue].Append(((AliTPCCalPad*)array->At(ivalue))->GetName());
1881
1882 for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++) {
1883
1884 TVectorF *vectorArray = new TVectorF[arrayEntries];
1885 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
1886 vectorArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
1887
1888
1889 //
1890 // fill vectors of variable per pad
1891 //
1892 TVectorF *posArray = new TVectorF[8];
1893 for (Int_t ivalue = 0; ivalue < 8; ivalue++)
1894 posArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
1895
1896 Float_t posG[3] = {0};
1897 Float_t posL[3] = {0};
1898 Int_t ichannel = 0;
1899 for (UInt_t irow = 0; irow < tpcROCinstance->GetNRows(isector); irow++) {
1900 for (UInt_t ipad = 0; ipad < tpcROCinstance->GetNPads(isector, irow); ipad++) {
1901 tpcROCinstance->GetPositionLocal(isector, irow, ipad, posL);
1902 tpcROCinstance->GetPositionGlobal(isector, irow, ipad, posG);
1903 posArray[0][ichannel] = irow;
1904 posArray[1][ichannel] = ipad;
1905 posArray[2][ichannel] = posL[0];
1906 posArray[3][ichannel] = posL[1];
1907 posArray[4][ichannel] = posG[0];
1908 posArray[5][ichannel] = posG[1];
1909 posArray[6][ichannel] = (Int_t)(ipad - (Double_t)(tpcROCinstance->GetNPads(isector, irow))/2);
1910 posArray[7][ichannel] = ichannel;
1911
1912 // loop over array containing AliTPCCalPads
1913 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
1914 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
1915 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
1916 if (calROC)
1917 (vectorArray[ivalue])[ichannel] = calROC->GetValue(irow, ipad);
1918 else
1919 (vectorArray[ivalue])[ichannel] = 0;
1920 }
1921 ichannel++;
1922 }
1923 }
1924 AliTPCCalROC dummyROC(0);
1925 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
1926 AliTPCCalROC *roc = ((AliTPCCalPad*)array->At(ivalue))->GetCalROC(isector);
1927 if (!roc) roc = &dummyROC;
1928 cstream << "calPads" <<
1929 (Char_t*)((names[ivalue] + ".=").Data()) << &vectorArray[ivalue];
1930 cstream << "calPads" <<
1931 (Char_t*)((names[ivalue] + "Pad.=").Data()) << roc;
1932 }
1933
1934 if (mapFileName) {
1935 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
1936 if (isector < 36)
1937 cstream << "calPads" <<
1938 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapIROCArray[ivalue];
1939 else
1940 cstream << "calPads" <<
1941 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapOROCArray[ivalue];
1942 }
1943 }
1944
1945 cstream << "calPads" <<
1946 "sector=" << isector;
1947
1948 cstream << "calPads" <<
1949 "row.=" << &posArray[0] <<
1950 "pad.=" << &posArray[1] <<
1951 "lx.=" << &posArray[2] <<
1952 "ly.=" << &posArray[3] <<
1953 "gx.=" << &posArray[4] <<
1954 "gy.=" << &posArray[5] <<
1955 "rpad.=" << &posArray[6] <<
1956 "channel.=" << &posArray[7];
1957
1958 cstream << "calPads" <<
1959 "\n";
1960
1961 delete[] posArray;
1962 delete[] vectorArray;
1963 } //for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++)
1964
1965 delete[] names;
1966 if (mapFileName) {
1967 delete mapIROCs;
1968 delete mapOROCs;
1969 delete[] mapIROCArray;
1970 delete[] mapOROCArray;
1971 delete[] mapNames;
1972 }
1973}
1974
72d0ab7e 1975
2811495d 1976void AliTPCCalibViewer::MakeTree(const char * fileName, TObjArray * array, const char * mapFileName, AliTPCCalPad *const outlierPad, Float_t ltmFraction) {
39bcd65d 1977 //
1978 // Write a tree with all available information
72d0ab7e 1979 // if mapFileName is speciefied, the Map information are also written to the tree
39bcd65d 1980 // pads specified in outlierPad are not used for calculating statistics
72d0ab7e 1981 // The following statistical information on the basis of a ROC are calculated:
1982 // "_Median", "_Mean", "_LTM", "_RMS_LTM"
1983 // "_Median_OutlierCutted", "_Mean_OutlierCutted", "_RMS_OutlierCutted", "_LTM_OutlierCutted", "_RMS_LTM_OutlierCutted"
1984 // The following position variables are available:
1985 // "row", "pad", "lx", "ly", "gx", "gy", "rpad", "channel"
1986 //
1987 // The tree out of this function is the basis for the AliTPCCalibViewer and the AliTPCCalibViewerGUI.
1988
7390f655 1989 AliTPCROC* tpcROCinstance = AliTPCROC::Instance();
39bcd65d 1990
7390f655 1991 TObjArray* mapIROCs = 0;
1992 TObjArray* mapOROCs = 0;
1993 TVectorF *mapIROCArray = 0;
1994 TVectorF *mapOROCArray = 0;
1995 Int_t mapEntries = 0;
1996 TString* mapNames = 0;
1997
1998 if (mapFileName) {
1999 TFile mapFile(mapFileName, "read");
2000
2001 TList* listOfROCs = mapFile.GetListOfKeys();
2002 mapEntries = listOfROCs->GetEntries()/2;
2003 mapIROCs = new TObjArray(mapEntries*2);
2004 mapOROCs = new TObjArray(mapEntries*2);
2005 mapIROCArray = new TVectorF[mapEntries];
2006 mapOROCArray = new TVectorF[mapEntries];
2007
2008 mapNames = new TString[mapEntries];
2009 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
2010 TString rocName(((TKey*)(listOfROCs->At(ivalue*2)))->GetName());
2011 rocName.Remove(rocName.Length()-4, 4);
2012 mapIROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "IROC").Data()), ivalue);
2013 mapOROCs->AddAt((AliTPCCalROC*)mapFile.Get((rocName + "OROC").Data()), ivalue);
2014 mapNames[ivalue].Append(rocName);
2015 }
2016
2017 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
2018 mapIROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(0));
2019 mapOROCArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(36));
39bcd65d 2020
7390f655 2021 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(0); ichannel++)
2022 (mapIROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapIROCs->At(ivalue)))->GetValue(ichannel);
2023 for (UInt_t ichannel = 0; ichannel < tpcROCinstance->GetNChannels(36); ichannel++)
2024 (mapOROCArray[ivalue])[ichannel] = ((AliTPCCalROC*)(mapOROCs->At(ivalue)))->GetValue(ichannel);
2025 }
2026
2027 } // if (mapFileName)
39bcd65d 2028
7390f655 2029 TTreeSRedirector cstream(fileName);
2030 Int_t arrayEntries = 0;
2031 if (array) arrayEntries = array->GetEntries();
2032
2033 TString* names = new TString[arrayEntries];
2034 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++)
2035 names[ivalue].Append(((AliTPCCalPad*)array->At(ivalue))->GetName());
2036
2037 for (UInt_t isector = 0; isector < tpcROCinstance->GetNSectors(); isector++) {
39bcd65d 2038 //
2039 // get statistic for given sector
2040 //
7390f655 2041 TVectorF median(arrayEntries);
2042 TVectorF mean(arrayEntries);
2043 TVectorF rms(arrayEntries);
2044 TVectorF ltm(arrayEntries);
2045 TVectorF ltmrms(arrayEntries);
2046 TVectorF medianWithOut(arrayEntries);
2047 TVectorF meanWithOut(arrayEntries);
2048 TVectorF rmsWithOut(arrayEntries);
2049 TVectorF ltmWithOut(arrayEntries);
2050 TVectorF ltmrmsWithOut(arrayEntries);
2051
2052 TVectorF *vectorArray = new TVectorF[arrayEntries];
2053 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++){
2054 vectorArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
2055 vectorArray[ivalue].SetUniqueID(array->UncheckedAt(ivalue)->GetUniqueID());
2056// printf("UniqueID: %d\n",vectorArray[ivalue].GetUniqueID());
2057 }
2058
2059 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2060 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
2061 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
2062 AliTPCCalROC* outlierROC = 0;
2063 if (outlierPad) outlierROC = outlierPad->GetCalROC(isector);
2064 if (calROC) {
2065 median[ivalue] = calROC->GetMedian();
2066 mean[ivalue] = calROC->GetMean();
2067 rms[ivalue] = calROC->GetRMS();
2068 Double_t ltmrmsValue = 0;
2069 ltm[ivalue] = calROC->GetLTM(&ltmrmsValue, ltmFraction);
2070 ltmrms[ivalue] = ltmrmsValue;
2071 if (outlierROC) {
2072 medianWithOut[ivalue] = calROC->GetMedian(outlierROC);
2073 meanWithOut[ivalue] = calROC->GetMean(outlierROC);
2074 rmsWithOut[ivalue] = calROC->GetRMS(outlierROC);
2075 ltmrmsValue = 0;
2076 ltmWithOut[ivalue] = calROC->GetLTM(&ltmrmsValue, ltmFraction, outlierROC);
2077 ltmrmsWithOut[ivalue] = ltmrmsValue;
2078 }
39bcd65d 2079 }
7390f655 2080 else {
2081 median[ivalue] = 0.;
2082 mean[ivalue] = 0.;
2083 rms[ivalue] = 0.;
2084 ltm[ivalue] = 0.;
2085 ltmrms[ivalue] = 0.;
2086 medianWithOut[ivalue] = 0.;
2087 meanWithOut[ivalue] = 0.;
2088 rmsWithOut[ivalue] = 0.;
2089 ltmWithOut[ivalue] = 0.;
2090 ltmrmsWithOut[ivalue] = 0.;
2091 }
2092 }
2093
39bcd65d 2094 //
2095 // fill vectors of variable per pad
2096 //
7390f655 2097 TVectorF *posArray = new TVectorF[8];
2098 for (Int_t ivalue = 0; ivalue < 8; ivalue++)
2099 posArray[ivalue].ResizeTo(tpcROCinstance->GetNChannels(isector));
2100
2101 Float_t posG[3] = {0};
2102 Float_t posL[3] = {0};
2103 Int_t ichannel = 0;
2104 for (UInt_t irow = 0; irow < tpcROCinstance->GetNRows(isector); irow++) {
2105 for (UInt_t ipad = 0; ipad < tpcROCinstance->GetNPads(isector, irow); ipad++) {
2106 tpcROCinstance->GetPositionLocal(isector, irow, ipad, posL);
2107 tpcROCinstance->GetPositionGlobal(isector, irow, ipad, posG);
2108 posArray[0][ichannel] = irow;
2109 posArray[1][ichannel] = ipad;
2110 posArray[2][ichannel] = posL[0];
2111 posArray[3][ichannel] = posL[1];
2112 posArray[4][ichannel] = posG[0];
2113 posArray[5][ichannel] = posG[1];
2114 posArray[6][ichannel] = (Int_t)(ipad - (Double_t)(tpcROCinstance->GetNPads(isector, irow))/2);
2115 posArray[7][ichannel] = ichannel;
2116
39bcd65d 2117 // loop over array containing AliTPCCalPads
7390f655 2118 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2119 AliTPCCalPad* calPad = (AliTPCCalPad*) array->At(ivalue);
2120 AliTPCCalROC* calROC = calPad->GetCalROC(isector);
2121 if (calROC)
39bcd65d 2122 (vectorArray[ivalue])[ichannel] = calROC->GetValue(irow, ipad);
7390f655 2123 else
2124 (vectorArray[ivalue])[ichannel] = 0;
2125 }
2126 ichannel++;
39bcd65d 2127 }
7390f655 2128 }
2129
2130 cstream << "calPads" <<
2131 "sector=" << isector;
2132
2133 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
39bcd65d 2134 cstream << "calPads" <<
7390f655 2135 (Char_t*)((names[ivalue] + "_Median=").Data()) << median[ivalue] <<
2136 (Char_t*)((names[ivalue] + "_Mean=").Data()) << mean[ivalue] <<
2137 (Char_t*)((names[ivalue] + "_RMS=").Data()) << rms[ivalue] <<
2138 (Char_t*)((names[ivalue] + "_LTM=").Data()) << ltm[ivalue] <<
2139 (Char_t*)((names[ivalue] + "_RMS_LTM=").Data()) << ltmrms[ivalue];
2140 if (outlierPad) {
2141 cstream << "calPads" <<
2142 (Char_t*)((names[ivalue] + "_Median_OutlierCutted=").Data()) << medianWithOut[ivalue] <<
2143 (Char_t*)((names[ivalue] + "_Mean_OutlierCutted=").Data()) << meanWithOut[ivalue] <<
2144 (Char_t*)((names[ivalue] + "_RMS_OutlierCutted=").Data()) << rmsWithOut[ivalue] <<
2145 (Char_t*)((names[ivalue] + "_LTM_OutlierCutted=").Data()) << ltmWithOut[ivalue] <<
2146 (Char_t*)((names[ivalue] + "_RMS_LTM_OutlierCutted=").Data()) << ltmrmsWithOut[ivalue];
39bcd65d 2147 }
7390f655 2148 //timestamp and run, if given in title
2149/* TString title(((AliTPCCalPad*) array->At(ivalue))->GetTitle());
2150 TObjArray *arrtitle=title.Tokenize(",");
2151 Int_t run=-1;
2152 UInt_t time=0;
2153 TIter next(arrtitle);
2154 TObject *o=0;
2155 while ( (o=next()) ){
2156 TString &entry=((TObjString*)o)->GetString();
2157 entry.Remove(TString::kBoth,' ');
2158 entry.Remove(TString::kBoth,'\t');
2159 if (entry.BeginsWith("Run:")) {
2160 run=entry(4,entry.Length()).Atoi();
2161 } else if (entry.BeginsWith("Time:")) {
2162 time=entry(6,entry.Length()).Atoi();
2163 }
39bcd65d 2164 }
7390f655 2165 delete arrtitle;*/
2166
2167 }
2168
2169 for (Int_t ivalue = 0; ivalue < arrayEntries; ivalue++) {
2170 cstream << "calPads" <<
2171 (Char_t*)((names[ivalue] + ".=").Data()) << &vectorArray[ivalue];
2172 }
2173
2174 if (mapFileName) {
2175 for (Int_t ivalue = 0; ivalue < mapEntries; ivalue++) {
39bcd65d 2176 if (isector < 36)
7390f655 2177 cstream << "calPads" <<
2178 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapIROCArray[ivalue];
39bcd65d 2179 else
7390f655 2180 cstream << "calPads" <<
2181 (Char_t*)((mapNames[ivalue] + ".=").Data()) << &mapOROCArray[ivalue];
39bcd65d 2182 }
7390f655 2183 }
2184
2185 cstream << "calPads" <<
2186 "row.=" << &posArray[0] <<
2187 "pad.=" << &posArray[1] <<
2188 "lx.=" << &posArray[2] <<
2189 "ly.=" << &posArray[3] <<
2190 "gx.=" << &posArray[4] <<
2191 "gy.=" << &posArray[5] <<
2192 "rpad.=" << &posArray[6] <<
2193 "channel.=" << &posArray[7];
2194
2195 cstream << "calPads" <<
2196 "\n";
2197
2198 delete[] posArray;
2199 delete[] vectorArray;
2200 }
2201
2202
2203 delete[] names;
2204 if (mapFileName) {
2205 delete mapIROCs;
2206 delete mapOROCs;
2207 delete[] mapIROCArray;
2208 delete[] mapOROCArray;
2209 delete[] mapNames;
2210 }
39bcd65d 2211}
2212
4f3934a1 2213
2214void AliTPCCalibViewer::MakeTree(const char *outPutFileName, const Char_t *inputFileName, AliTPCCalPad *outlierPad, Float_t ltmFraction, const char *mapFileName ){
2215 //
2216 // Function to create a calibration Tree with all available information.
2217 // See also documentation to MakeTree
2218 // the file "inputFileName" must be in the following format (see also CreateObjectList):
2219 // (each colum separated by tabs, "dependingOnType" can have 2 or 3 colums)
2220 //
2221 // type path dependingOnType
2222 //
2223 // type == "CE":
2224 // dependingOnType = CETmean CEQmean CETrms
2225 //
2226 // type == "Pulser":
2227 // dependingOnType = PulserTmean PulsterQmean PulserTrms
2228 //
2229 // type == "Pedestals":
2230 // dependingOnType = Pedestals Noise
2231 //
2232 // type == "CalPad":
2233 // dependingOnType = NameInFile NameToWriteToFile
2234 //
2235 //
2236 TObjArray objArray;
2237 CreateObjectList(inputFileName, &objArray);
2238 MakeTree(outPutFileName, &objArray, mapFileName, outlierPad, ltmFraction);
2239}
2240
832bb12c 2241
4f3934a1 2242void AliTPCCalibViewer::CreateObjectList(const Char_t *filename, TObjArray *calibObjects){
2243 //
2244 // Function to create a TObjArray out of a given file
2245 // the file must be in the following format:
2246 // (each colum separated by tabs, "dependingOnType" can have 2 or 3 colums)
2247 //
2248 //
2249 // type path dependingOnType
2250 //
2251 // type == "CE":
2252 // dependingOnType = CETmean CEQmean CETrms
2253 //
2254 // type == "Pulser":
2255 // dependingOnType = PulserTmean PulsterQmean PulserTrms
2256 //
2257 // type == "Pedestals":
2258 // dependingOnType = Pedestals Noise
2259 //
2260 // type == "CalPad":
2261 // dependingOnType = NameInFile NameToWriteToFile
2262 //
2263 //
2264 //
2265 if ( calibObjects == 0x0 ) return;
2266 ifstream in;
2267 in.open(filename);
2268 if ( !in.is_open() ){
2269 fprintf(stderr,"Error: cannot open list file '%s'", filename);
2270 return;
2271 }
2272
2273 AliTPCCalPad *calPad=0x0;
2274
2275 TString sFile;
2276 sFile.ReadFile(in);
2277 in.close();
2278
2279 TObjArray *arrFileLine = sFile.Tokenize("\n");
2280 TIter nextLine(arrFileLine);
2281
2282 TObjString *sObjLine = 0x0;
2283 while ( (sObjLine = (TObjString*)nextLine()) ){
2284 TString sLine(sObjLine->GetString());
2285
2286 TObjArray *arrCol = sLine.Tokenize("\t");
2287 Int_t nCols = arrCol->GetEntriesFast();
2288
2289 TObjString *sObjType = (TObjString*)(arrCol->At(0));
2290 TObjString *sObjFileName = (TObjString*)(arrCol->At(1));
2291 TObjString *sObjName = 0x0;
2292
2293 if ( !sObjType || !sObjFileName ) continue;
2294 TString sType(sObjType->GetString());
2295 TString sFileName(sObjFileName->GetString());
2296 printf("Type %s, opening %s \n", sType.Data(), sFileName.Data());
2297 TFile *fIn = TFile::Open(sFileName);
2298 if ( !fIn ){
2299 fprintf(stderr,"File not found: '%s'", sFileName.Data());
2300 continue;
2301 }
2302
2303 if ( sType == "CE" ){ // next three colums are the names for CETmean, CEQmean and CETrms
2304 AliTPCCalibCE *ce = (AliTPCCalibCE*)fIn->Get("AliTPCCalibCE");
2305 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadT0());
2306 if (nCols > 2) { // check, if the name is provided
2307 sObjName = (TObjString*)(arrCol->At(2));
2308 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2309 }
2310 else calPad->SetNameTitle("CETmean","CETmean");
2311 calibObjects->Add(calPad);
2312
2313 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadQ());
2314 if (nCols > 3) { // check, if the name is provided
2315 sObjName = (TObjString*)(arrCol->At(3));
2316 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2317 }
2318 else calPad->SetNameTitle("CEQmean","CEQmean");
2319 calibObjects->Add(calPad);
2320
2321 calPad = new AliTPCCalPad((TObjArray*)ce->GetCalPadRMS());
2322 if (nCols > 4) { // check, if the name is provided
2323 sObjName = (TObjString*)(arrCol->At(4));
2324 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2325 }
2326 else calPad->SetNameTitle("CETrms","CETrms");
2327 calibObjects->Add(calPad);
2328
2329 } else if ( sType == "Pulser") {
2330 AliTPCCalibPulser *sig = (AliTPCCalibPulser*)fIn->Get("AliTPCCalibPulser");
2331
2332 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadT0());
2333 if (nCols > 2) {
2334 sObjName = (TObjString*)(arrCol->At(2));
2335 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2336 }
2337 else calPad->SetNameTitle("PulserTmean","PulserTmean");
2338 calibObjects->Add(calPad);
2339
2340 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadQ());
2341 if (nCols > 3) {
2342 sObjName = (TObjString*)(arrCol->At(3));
2343 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2344 }
2345 else calPad->SetNameTitle("PulserQmean","PulserQmean");
2346 calibObjects->Add(calPad);
2347
2348 calPad = new AliTPCCalPad((TObjArray*)sig->GetCalPadRMS());
2349 if (nCols > 4) {
2350 sObjName = (TObjString*)(arrCol->At(4));
2351 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2352 }
2353 else calPad->SetNameTitle("PulserTrms","PulserTrms");
2354 calibObjects->Add(calPad);
2355
2356 } else if ( sType == "Pedestals") {
2357 AliTPCCalibPedestal *ped = (AliTPCCalibPedestal*)fIn->Get("AliTPCCalibPedestal");
2358
2359 calPad = new AliTPCCalPad((TObjArray*)ped->GetCalPadPedestal());
2360 if (nCols > 2) {
2361 sObjName = (TObjString*)(arrCol->At(2));
2362 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2363 }
2364 else calPad->SetNameTitle("Pedestals","Pedestals");
2365 calibObjects->Add(calPad);
2366
2367 calPad = new AliTPCCalPad((TObjArray*)ped->GetCalPadRMS());
2368 if (nCols > 3) {
2369 sObjName = (TObjString*)(arrCol->At(3));
2370 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2371 }
2372 else calPad->SetNameTitle("Noise","Noise");
2373 calibObjects->Add(calPad);
2374
2375 } else if ( sType == "CalPad") {
2376 if (nCols > 2) sObjName = (TObjString*)(arrCol->At(2));
2377 else continue;
2378 calPad = new AliTPCCalPad(*(AliTPCCalPad*)fIn->Get(sObjName->GetString().Data()));
2379 if (nCols > 3) {
2380 sObjName = (TObjString*)(arrCol->At(3));
2381 calPad->SetNameTitle(sObjName->GetString().Data(), sObjName->GetString().Data());
2382 }
2383 calibObjects->Add(calPad);
2384 } else {
2385 fprintf(stderr,"Undefined Type: '%s'",sType.Data());
2386 }
2387 delete fIn;
2388 }
2389}
2390
2391
2392