source: branches/Corsika7500Compatibility/macros/pointspreadfunction.C@ 20051

Last change on this file since 20051 was 3119, checked in by jlopez, 21 years ago
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1/* ======================================================================== *\
2!
3! *
4! * This file is part of MARS, the MAGIC Analysis and Reconstruction
5! * Software. It is distributed to you in the hope that it can be a useful
6! * and timesaving tool in analysing Data of imaging Cerenkov telescopes.
7! * It is distributed WITHOUT ANY WARRANTY.
8! *
9! * Permission to use, copy, modify and distribute this software and its
10! * documentation for any purpose is hereby granted without fee,
11! * provided that the above copyright notice appear in all copies and
12! * that both that copyright notice and this permission notice appear
13! * in supporting documentation. It is provided "as is" without express
14! * or implied warranty.
15! *
16!
17! Author(s): Javier Lopez, 12/2003 <mailto:jlopez@ifae.es>
18! Author(s): Alex Armada, 1/2004 <mailto:armada@ifae.es>
19!
20! Copyright: MAGIC Software Development, 2000-2003
21!
22!
23\* ======================================================================== */
24
25
26//------------------------------------------------------------------------- //
27// //
28// This macro fits the dc signal of a star using a two dimension gaussian //
29// for each dc measurement. Then the values of parameters of the fit are //
30// stored in histograms and shown at the end of the macro. //
31// //
32// USAGE: //
33// It has two arguments, //
34// 1- The first one is the dc file with the tracked star //
35// 2- The second one is a continuos light file used to intercalibrate //
36// the gain of the photomultipliers. //
37// (It's possible not to use the calibration file and then the gain //
38// of the pmts are supouse to be the same for all of them. //
39// 3- The third argument is just the number of dc measurements you want //
40// analize. If you put 0 it just stops after each fit and show you //
41// results. //
42// //
43//--------------------------------------------------------------------------//
44
45const Int_t numPixels = 577;
46Int_t nPixelsFitted;
47Bool_t isPixelsFitted[numPixels];
48Float_t z[numPixels],x[numPixels],y[numPixels],errorz[numPixels];
49Float_t chisquare;
50
51//______________________________________________________________________________
52//
53// Function used by Minuit to do the fit
54//
55void fcn(Int_t &npar, Double_t *gin, Double_t &f, Double_t *par, Int_t iflag)
56{
57 Int_t i;
58
59//calculate chisquare
60 Double_t chisq = 0;
61 Double_t delta;
62 nPixelsFitted=0;
63 for (i=1;i<numPixels; i++) {
64 if (isPixelsFitted[i])
65 {
66 if (errorz[i] != 0.0)
67 {
68 delta = (z[i]-func(x[i],y[i],par))/errorz[i];
69 chisq += delta*delta;
70 nPixelsFitted++;
71 }
72 else
73 cout << "This should never happen errorz[" << i << "] " << errorz[i] << endl;
74 }
75 }
76 f = chisq;
77 chisquare = chisq;
78}
79
80//______________________________________________________________________________
81//
82// The 2D gaussian fucntion used to fit the spot of the star
83//
84Double_t func(float x,float y,Double_t *par)
85{
86 Double_t value=par[0]*TMath::exp(-(x-par[1])*(x-par[1])/(2*par[2]*par[2]))*TMath::exp(-(y-par[3])*(y-par[3])/(2*par[4]*par[4]));
87 return value;
88}
89
90Bool_t HandleInput()
91{
92 TTimer timer("gSystem->ProcessEvents();", 50, kFALSE);
93
94 while (1)
95 {
96 //
97 // While reading the input process gui events asynchronously
98 //
99 timer.TurnOn();
100 TString input = Getline("Type 'q' to exit, <return> to go on: ");
101 timer.TurnOff();
102
103 if (input=="q\n")
104 return kFALSE;
105
106 if (input=="\n")
107 return kTRUE;
108 };
109
110 return kFALSE;
111}
112
113
114void pointspreadfunction(TString fname, TString clname = "NULL", Int_t userNumLines = 1000)
115{
116
117
118 Float_t currmean[numPixels];
119 Float_t currsquaremean[numPixels];
120 Float_t currrms[numPixels];
121 Float_t meanofcurrmean = 0;
122
123 for (Int_t swpix=0; swpix<numPixels; swpix++)
124 {
125 currmean[swpix] = 0.;
126 currsquaremean[swpix] = 0.;
127 currrms[swpix] = 0.;
128 }
129
130 Int_t numLines=0;
131
132 //containers
133 MGeomCamMagic geomcam;
134 MCameraDC curr;
135 MCameraDC currbis;
136
137 const Float_t conv4mm2deg = geomcam.GetConvMm2Deg();
138
139
140 if (clname != "NULL")
141 {
142
143 //
144 // First run over continuos light files to have a DC calibration
145 //
146
147 MParList plist0;
148
149 MTaskList tlist0;
150 plist0.AddToList(&tlist0);
151
152 plist0.AddToList(&geomcam);
153 plist0.AddToList(&curr);
154
155 MReportFileRead read0(clname);
156 read0.SetHasNoHeader();
157 read0.AddToList("MReportCurrents");
158
159 tlist0.AddToList(&read0);
160
161 MEvtLoop evtloop0;
162 evtloop0.SetParList(&plist0);
163
164
165 if (!evtloop0.PreProcess())
166 return;
167
168 while (tlist0.Process())
169 {
170 for (Int_t swpix=0; swpix<numPixels; swpix++)
171 {
172 meanofcurrmean += curr[swpix];
173 currmean[swpix] += curr[swpix];
174 currsquaremean[swpix] += curr[swpix]*curr[swpix];
175 }
176 numLines++;
177 }
178
179 evtloop0.PostProcess();
180
181 meanofcurrmean /= (numLines*numPixels);
182 for (Int_t swpix=0; swpix<numPixels; swpix++)
183 {
184
185 currmean[swpix] /= numLines;
186 currsquaremean[swpix] /= numLines;
187 currrms[swpix] = sqrt(fabs(currsquaremean[swpix] - currmean[swpix]*currmean[swpix]));
188
189 curr[swpix] = currmean[swpix];
190 currbis[swpix] = currrms[swpix];
191
192 currmean[swpix] /= meanofcurrmean;
193 currrms[swpix] /= meanofcurrmean;
194
195 }
196
197
198/* MHCamera display0(geomcam);
199 display0.SetPrettyPalette();
200 display0.Draw();
201
202 // curr.Print();
203 display0.SetCamContent(currbis);
204 cout << "PSF>> DC mean values drawn" << endl;
205 // Remove the comments if you want to go through the file
206 // event-by-event:
207 if (!HandleInput())
208 break;
209*/
210 }
211 else
212 {
213 // If you don't use the continuous light this is the currrms[] array
214 // is the error associated to the currents TMinuit will use.
215 for (Int_t swpix=0; swpix<numPixels; swpix++)
216 {
217 currmean[swpix] = 1.;
218 currrms[swpix] = 0.2;
219 }
220
221 }
222
223//
224// Now we can run over the dc data to extract the psf.
225//
226 const Int_t maxNumLines = 10000;
227
228 Double_t ux[maxNumLines];
229 Double_t uy[maxNumLines];
230 Double_t sx[maxNumLines];
231 Double_t sy[maxNumLines];
232 Double_t chisqu[maxNumLines];
233 Double_t time[maxNumLines];
234
235 MParList plist;
236
237 MGeomCamMagic geomcam;
238 MCameraDC curr;
239 MTaskList tlist;
240
241 plist.AddToList(&geomcam);
242 plist.AddToList(&curr);
243 plist.AddToList(&tlist);
244
245 MReportFileRead read(fname);
246 read.SetHasNoHeader();
247 read.AddToList("MReportCurrents");
248
249 tlist.AddToList(&read);
250
251 MEvtLoop evtloop;
252 evtloop.SetParList(&plist);
253
254 if (!evtloop.PreProcess())
255 return;
256
257 MHCamera display(geomcam);
258 display.SetPrettyPalette();
259 display.Draw();
260 gPad->SetLogy();
261 gPad->cd(1);
262
263 Double_t amin,edm,errdef;
264 Int_t nvpar,nparx,icstat;
265
266 Double_t max,maxerror;
267 Double_t xmean,xsigma,ymean,ysigma;
268 Double_t xmeanerror,xsigmaerror,ymeanerror,ysigmaerror;
269
270 TEllipse ellipse;
271 ellipse.SetFillStyle(4000);
272 ellipse.SetLineWidth(2);
273 ellipse.SetLineColor(2);
274
275 ellipse.Draw();
276
277 Int_t nbinsxy = 80;
278 Float_t minxy = -600*conv4mm2deg;
279 Float_t maxxy = 600*conv4mm2deg;
280 Float_t fromdegtobin = (maxxy-minxy)/nbinsxy;
281
282 TH2D psfhist("psfhist","",nbinsxy,minxy,maxxy,nbinsxy,minxy,maxxy);
283 psfhist->GetXaxis()->SetTitle("[deg]");
284 psfhist->GetYaxis()->SetTitle("[deg]");
285 psfhist->GetZaxis()->SetTitle("DC [uA]");
286
287 TCanvas *psfcanvas = new TCanvas("psfcanvas","Point Spread Funtion 2D",200,20,900,700);
288
289
290 //
291 // Using the first dc measurement we search the pixels which contains the star and define
292 // an area to be fitted by Minuit which is 3 rings of neightbords around the peak of the star.
293 //
294
295 tlist.Process();
296
297 Int_t numLines=0;
298 Float_t minDCStar = 6.0;
299
300 Int_t numPixelsInStar = 0;
301 Float_t maxDC = 0;
302 Int_t swpixelmaxDC;
303
304 Bool_t isPixelsFittedTmp[numPixels];
305
306 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
307 isPixelsFittedTmp[swpixel] = kFALSE;
308
309 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
310 {
311 if(curr[swpixel] > maxDC)
312 {
313 swpixelmaxDC = swpixel;
314 maxDC = curr[swpixelmaxDC];
315 }
316
317 if(curr[swpixel]>minDCStar)
318 {
319 numPixelsInStar++;
320 isPixelsFitted[swpixel] = kTRUE;
321 }
322 else
323 isPixelsFitted[swpixel] = kFALSE;
324 }
325
326 if (numPixelsInStar == 0)
327 {
328 cout << "PSF>> Warning: none pixel over minDCStar(" << minDCStar << ')' << endl;
329 return;
330 }
331
332//1st neighboor ring
333 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
334 if (isPixelsFitted[swpixel])
335 for(Int_t next=0; next<geomcam[swpixel].GetNumNeighbors(); next++)
336 isPixelsFittedTmp[geomcam[swpixel].GetNeighbor(next)] = kTRUE;
337
338 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
339 if (isPixelsFittedTmp[swpixel])
340 isPixelsFitted[swpixel] = kTRUE;
341
342//2on neighboor ring
343 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
344 if (isPixelsFitted[swpixel])
345 for(Int_t next=0; next<geomcam[swpixel].GetNumNeighbors(); next++)
346 isPixelsFittedTmp[geomcam[swpixel].GetNeighbor(next)] = kTRUE;
347
348 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
349 if (isPixelsFittedTmp[swpixel])
350 isPixelsFitted[swpixel] = kTRUE;
351
352
353//3rt neighboor ring
354 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
355 if (isPixelsFitted[swpixel])
356 for(Int_t next=0; next<geomcam[swpixel].GetNumNeighbors(); next++)
357 isPixelsFittedTmp[geomcam[swpixel].GetNeighbor(next)] = kTRUE;
358
359 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
360 if (isPixelsFittedTmp[swpixel])
361 isPixelsFitted[swpixel] = kTRUE;
362
363
364 for(Int_t swpixel=1; swpixel<numPixels; swpixel++)
365 curr[swpixel] = (Float_t)isPixelsFitted[swpixel];
366
367/* MHCamera display0(geomcam);
368 display0.SetPrettyPalette();
369 display0.Draw();
370
371 display0.SetCamContent(curr);
372 cout << "PSF>> Fitted pixels drawn" << endl;
373 // Remove the comments if you want to go through the file
374 // event-by-event:
375 if (!HandleInput())
376 break;
377*/
378
379 // Minuit initialization
380
381 TMinuit *gMinuit = new TMinuit(7); //initialize TMinuit with a maximum of 5 params
382 gMinuit->SetFCN(fcn);
383
384 Double_t arglist[10];
385 Int_t ierflg = 0;
386
387 arglist[0] = 1;
388 gMinuit->mnexcm("SET ERR", arglist ,1,ierflg);
389// arglist[0] = -1;
390 arglist[0] = 0;
391 gMinuit->mnexcm("SET PRI", arglist ,1,ierflg);
392
393// Set starting values and step sizes for parameters
394 Double_t vstart[5];
395 Double_t step[5];
396 Double_t lowlimit[5] = {minDCStar, -2., 0.05, -2, 0.05};
397 Double_t uplimit[5] = {30., 2., 1., 2., 1.};
398
399 vstart[0] = maxDC;
400 vstart[1] = geomcam[swpixelmaxDC].GetX()*conv4mm2deg;
401 vstart[2] = 30*TMath::Sqrt(numPixelsInStar/2)*conv4mm2deg;
402 vstart[3] = geomcam[swpixelmaxDC].GetY()*conv4mm2deg;
403 vstart[4] = 30*TMath::Sqrt(numPixelsInStar/2)*conv4mm2deg;
404
405 for(Int_t i=0; i<5; i++)
406 {
407 if (vstart[i] != 0)
408 step[i] = TMath::Abs(vstart[i]/sqrt(2));
409 else
410 step[i] = uplimit[i]/2;
411 }
412
413 gMinuit->mnparm(0, "max", vstart[0], step[0], lowlimit[0], uplimit[0],ierflg);
414 gMinuit->mnparm(1, "xmean", vstart[1], step[1], lowlimit[1], uplimit[1],ierflg);
415 gMinuit->mnparm(2, "xsigma", vstart[2], step[2], lowlimit[2], uplimit[2],ierflg);
416 gMinuit->mnparm(3, "ymean", vstart[3], step[3], lowlimit[3], uplimit[3],ierflg);
417 gMinuit->mnparm(4, "ysigma", vstart[4], step[4], lowlimit[4], uplimit[4],ierflg);
418
419 while (tlist.Process() && numLines < maxNumLines)
420 {
421
422 for (Int_t swpixel=1; swpixel<577; swpixel++)
423 {
424
425 x[swpixel] = geomcam[swpixel].GetX()*conv4mm2deg;
426 y[swpixel] = geomcam[swpixel].GetY()*conv4mm2deg;
427 z[swpixel] = curr[swpixel]/currmean[swpixel];
428 errorz[swpixel] = TMath::Sqrt((curr[swpixel]*currrms[swpixel]/(currmean[swpixel]*currmean[swpixel]))*(curr[swpixel]*currrms[swpixel]/(currmean[swpixel]*currmean[swpixel]))+(0.1)/currmean[swpixel]*(0.1)/currmean[swpixel]);
429
430
431 psfhist->SetBinContent((Int_t)((x[swpixel]+600*conv4mm2deg)/fromdegtobin),(Int_t)((y[swpixel]+600*conv4mm2deg)/fromdegtobin),z[swpixel]);
432 }
433
434 psfcanvas->cd(1);
435 psfhist->Draw("lego2");
436
437// Now ready for minimization step
438 arglist[0] = 500;
439 arglist[1] = 1.;
440 gMinuit->mnexcm("MIGRAD", arglist ,2,ierflg);
441
442// Print results
443/* gMinuit->mnstat(amin,edm,errdef,nvpar,nparx,icstat);
444 gMinuit->mnprin(3,amin);
445*/
446 gMinuit->GetParameter(0,max,maxerror);
447 gMinuit->GetParameter(1,xmean,xmeanerror);
448 gMinuit->GetParameter(2,xsigma,xsigmaerror);
449 gMinuit->GetParameter(3,ymean,ymeanerror);
450 gMinuit->GetParameter(4,ysigma,ysigmaerror);
451
452/* cout << endl;
453 cout << "numLine " << numLines << endl;
454 cout << "max \t" << max << " +- " << maxerror << endl;
455 cout << "xmean \t" << xmean << " +- " << xmeanerror << endl;
456 cout << "xsigma \t" << TMath::Abs(xsigma) << " +- " << xsigmaerror << endl;
457 cout << "ymean \t" << ymean << " +- " << ymeanerror << endl;
458 cout << "ysigma \t" << TMath::Abs(ysigma) << " +- " << ysigmaerror << endl;
459 cout << "chisquare/ndof \t" << chisquare/(nPixelsFitted-5) << endl;
460*/
461
462 chisqu[numLines]=chisquare/(nPixelsFitted-5);
463
464 if(chisqu[numLines]<100.)
465 {
466 ux[numLines]=xmean;
467 uy[numLines]=ymean;
468 sx[numLines]=TMath::Abs(xsigma);
469 sy[numLines]=TMath::Abs(ysigma);
470 time[numLines]=numLines;
471
472 display.SetCamContent(curr);
473 gPad->cd(1);
474 ellipse.SetX1(xmean/conv4mm2deg);
475 ellipse.SetY1(ymean/conv4mm2deg);
476 ellipse.SetR1(TMath::Abs(xsigma)/conv4mm2deg);
477 ellipse.SetR2(TMath::Abs(ysigma)/conv4mm2deg);
478
479 gPad->Modified();
480 gPad->Update();
481
482 // Remove the comments if you want to go through the file
483 //event-by-event:
484 if (userNumLines>0)
485 {
486 if (numLines>userNumLines)
487 break;
488 }
489 else
490 {
491 if (!HandleInput())
492 break;
493 }
494 numLines++;
495 }
496 }
497
498
499 evtloop.PostProcess();
500
501 //
502 // Draw the ditributions of the sigmas the point spread function
503 //
504
505 cout<<"PSF>> Number of lines "<<numLines<<endl;
506
507 gROOT->Reset();
508 gStyle->SetCanvasColor(0);
509 gStyle->SetCanvasBorderMode(0);
510 gStyle->SetPadBorderMode(0);
511 gStyle->SetFrameBorderMode(0);
512 gStyle->SetOptStat(00000000);
513
514//
515// Find in the file name the date, run and project name to put it in the title
516//
517
518 Size_t pos = fname.Last('/');
519 TString iRun = TString(fname(pos+24,5));
520 TString iYear = TString(fname(pos+4,4));
521 TString iMonth = TString(fname(pos+9,2));
522 TString iDay = TString(fname(pos+12,2));
523
524 TString iHour = TString(fname(pos+15,2));
525 TString iMin = TString(fname(pos+18,2));
526 TString iSec = TString(fname(pos+21,2));
527
528 Size_t poslast = fname.Last('.');
529 Size_t posfirst = poslast-1;
530 while (fname[posfirst] != '_')
531 posfirst--;
532
533 TString iSource = TString(fname(posfirst+1,poslast-posfirst-1));
534
535
536 char str[100];
537
538// sprintf(str,"Date %s/%s/%s Run %s Source %s",iYear.Data(),iMonth.Data(),iDay.Data(),iRun.Data(),iSource.Data());
539 sprintf(str,"Date %s/%s/%s StartTime %s:%s:%s Run %s Source %s",iYear.Data(),iMonth.Data(),iDay.Data(),iHour.Data(),iMin.Data(),iSec.Data(),iRun.Data(),iSource.Data());
540
541 c1 = new TCanvas("c1",str,0,0,1200,850);
542// c1 = new TCanvas("c1","Time evolution & distributions",0,0,1200,850);
543 c1->Divide(3,2);
544
545 c1->cd(1);
546
547 TMath math;
548
549 Double_t minmeanx, maxmeanx;
550 minmeanx = ux[math.LocMin(numLines,ux)];
551 maxmeanx = ux[math.LocMax(numLines,ux)];
552
553 Double_t minmeany, maxmeany;
554 minmeany = uy[math.LocMin(numLines,uy)];
555 maxmeany = uy[math.LocMax(numLines,uy)];
556
557 Double_t minmean, maxmean;
558 minmean = math.Min(minmeanx,minmeany);
559 maxmean = math.Max(maxmeanx,maxmeany);
560
561 Double_t diff;
562 diff = maxmean - minmean;
563 diff = 0.1*diff;
564 minmean = minmean - diff;
565 maxmean = maxmean + diff;
566
567 Double_t mintime, maxtime;
568 mintime = time[math.LocMin(numLines,time)];
569 maxtime = time[math.LocMax(numLines,time)];
570
571 TH2D *h1 = new TH2D("h1","",1,mintime-1,maxtime+1,1,minmean,maxmean);
572 h1->GetXaxis()->SetTitle("Event number");
573 h1->GetYaxis()->SetTitle("mean position (deg)");
574 h1->Draw();
575
576 TGraph *grtimeevolmeanx = new TGraph(numLines,time,ux);
577 grtimeevolmeanx->SetMarkerColor(3);
578 grtimeevolmeanx->SetMarkerStyle(20);
579 grtimeevolmeanx->SetMarkerSize (0.4);
580 grtimeevolmeanx->Draw("P");
581
582 TGraph *grtimeevolmeany = new TGraph(numLines,time,uy);
583 grtimeevolmeany->SetMarkerColor(6);
584 grtimeevolmeany->SetMarkerStyle(24);
585 grtimeevolmeany->SetMarkerSize (0.4);
586 grtimeevolmeany->Draw("P");
587
588 legmeanxy = new TLegend(0.8,0.85,0.95,0.95);
589 legmeanxy.SetTextSize(0.03);
590 legmeanxy.AddEntry(grtimeevolmeanx,"mean x","P");
591 legmeanxy.AddEntry(grtimeevolmeany,"mean y","P");
592 legmeanxy.Draw();
593
594 c1->cd(2);
595
596 TMath math;
597
598 Double_t minsigmax, maxsigmax;
599 minsigmax = sx[math.LocMin(numLines,sx)];
600 maxsigmax = sx[math.LocMax(numLines,sx)];
601
602 Double_t minsigmay, maxsigmay;
603 minsigmay = sy[math.LocMin(numLines,sy)];
604 maxsigmay = sy[math.LocMax(numLines,sy)];
605
606 Double_t minsigma, maxsigma;
607 minsigma = math.Min(minsigmax,minsigmay);
608 maxsigma = math.Max(maxsigmax,maxsigmay);
609
610 diff = maxsigma - minsigma;
611 diff = 0.1*diff;
612 minsigma = minsigma - diff;
613 maxsigma = maxsigma + diff;
614
615 TH2D *h2 = new TH2D("h2","",1,mintime-1,maxtime+1,1,minsigma,maxsigma);
616 h2->GetXaxis()->SetTitle("Event number");
617 h2->GetYaxis()->SetTitle("PSF Rms (deg)");
618 h2->Draw();
619
620 TGraph* grtimeevolsigmax= new TGraph(numLines,time,sx);
621 grtimeevolsigmax->SetMarkerColor(3);
622 grtimeevolsigmax->SetMarkerStyle(20);
623 grtimeevolsigmax->SetMarkerSize (0.4);
624 grtimeevolsigmax->Draw("P");
625
626 TGraph* grtimeevolsigmay= new TGraph(numLines,time,sy);
627 grtimeevolsigmay->SetMarkerColor(6);
628 grtimeevolsigmay->SetMarkerStyle(24);
629 grtimeevolsigmay->SetMarkerSize (0.4);
630 grtimeevolsigmay->Draw("P");
631
632 legsigmaxy = new TLegend(0.8,0.85,0.95,0.95);
633 legsigmaxy.SetTextSize(0.03);
634 legsigmaxy.AddEntry(grtimeevolsigmax,"sigma x","P");
635 legsigmaxy.AddEntry(grtimeevolsigmay,"sigma y","P");
636 legsigmaxy.Draw();
637
638 c1->cd(3);
639
640 Double_t minchisqu, maxchisqu;
641
642 minchisqu = chisqu[math.LocMin(numLines,chisqu)];
643 maxchisqu = chisqu[math.LocMax(numLines,chisqu)];
644
645 diff = maxchisqu - minchisqu;
646 diff = 0.1*diff;
647 minchisqu = minchisqu - diff;
648 maxchisqu = maxchisqu + diff;
649
650 TH2D *h3 = new TH2D("h3","",1,mintime-1,maxtime+1,1,minchisqu,maxchisqu);
651 h3->GetXaxis()->SetTitle("Event number");
652 h3->Draw();
653
654 TGraph * grtimeevolchisqu = new TGraph(numLines,time,chisqu);
655 grtimeevolchisqu->SetMarkerColor(215);
656 grtimeevolchisqu->SetMarkerStyle(20);
657 grtimeevolchisqu->SetMarkerSize(0.4);
658 grtimeevolchisqu->Draw("P");
659
660 legchisqu = new TLegend(0.55,0.90,0.95,0.95);
661 legchisqu.SetTextSize(0.03);
662 legchisqu.AddEntry(grtimeevolchisqu,"chi square / ndof","P");
663 legchisqu.Draw();
664
665//***************************************
666
667 const Int_t nbins = 100;
668
669 TH1D *xsigmahist = new TH1D("xsigmahist","",nbins,minsigma,maxsigma);
670 TH1D *ysigmahist = new TH1D("ysigmahist","",nbins,minsigma,maxsigma);
671 TH1D *xmeanhist = new TH1D("xmeanhist","",nbins,minmean,maxmean);
672 TH1D *ymeanhist = new TH1D("ymeanhist","",nbins,minmean,maxmean);
673 TH1D *chisquhist = new TH1D("chisquhist","",nbins,minchisqu,maxchisqu);
674
675 for (Int_t i=0; i<numLines; i++)
676 {
677 xsigmahist->Fill(TMath::Abs(sx[i]));
678 ysigmahist->Fill(TMath::Abs(sy[i]));
679 xmeanhist->Fill(ux[i]);
680 ymeanhist->Fill(uy[i]);
681 chisquhist->Fill(chisqu[i]);
682
683 }
684
685 c1->cd(5);
686
687 TMath math;
688 Double_t maxsigma;
689 Int_t binmaxx, binmaxy;
690 xsigmahist->SetLineColor(3);
691 xsigmahist->SetLineWidth(2);
692 xsigmahist->SetXTitle("RMS [deg]");
693 binmaxx = xsigmahist->GetMaximumBin();
694 binmaxx = xsigmahist->GetBinContent(binmaxx);
695
696 ysigmahist->SetLineColor(6);
697 ysigmahist->SetLineWidth(2);
698 binmaxy = ysigmahist->GetMaximumBin();
699 binmaxy = ysigmahist->GetBinContent(binmaxy);
700
701 maxsigma = math.Max(binmaxx,binmaxy);
702 maxsigma += 1;
703
704 xsigmahist->SetMaximum(maxsigma);
705 ysigmahist->SetMaximum(maxsigma);
706 xsigmahist->DrawCopy();
707 ysigmahist->DrawCopy("Same");
708
709 TLegend *legendsigma = new TLegend(.3,.8,.95,.95);
710 legendsigma->SetTextSize(0.03);
711 char xsigmatitle[100];
712 char ysigmatitle[100];
713 sprintf(xsigmatitle,"PSF Rms on X axis -- %5.2f +/- %5.2f deg",xsigmahist->GetMean(),xsigmahist->GetRMS());
714 sprintf(ysigmatitle,"PSF Rms on Y axis -- %5.2f +/- %5.2f deg",ysigmahist->GetMean(),ysigmahist->GetRMS());
715 legendsigma->AddEntry(xsigmahist,xsigmatitle,"F");
716 legendsigma->AddEntry(ysigmahist,ysigmatitle,"F");
717 legendsigma->Draw();
718
719 c1->cd(4);
720
721 Double_t maxmean;
722
723 xmeanhist->SetLineColor(3);
724 xmeanhist->SetLineWidth(2);
725 xmeanhist->SetXTitle("mean [deg]");
726 binmaxx = xmeanhist->GetMaximumBin();
727 binmaxx = xmeanhist->GetBinContent(binmaxx);
728
729 ymeanhist->SetLineColor(6);
730 ymeanhist->SetLineWidth(2);
731 binmaxy = ymeanhist->GetMaximumBin();
732 binmaxy = ymeanhist->GetBinContent(binmaxy);
733
734 maxmean = math.Max(binmaxx,binmaxy);
735 maxmean += 1;
736
737 xmeanhist->SetMaximum(maxmean);
738 ymeanhist->SetMaximum(maxmean);
739 xmeanhist->DrawCopy();
740 ymeanhist->DrawCopy("Same");
741
742 TLegend *legendmean = new TLegend(.35,.8,.95,.95);
743 legendmean->SetTextSize(0.03);
744 char xmeantitle[100];
745 char ymeantitle[100];
746 sprintf(xmeantitle,"mean on X axis -- %5.2f +/- %5.2f deg",xmeanhist->GetMean(),xmeanhist->GetRMS());
747 sprintf(ymeantitle,"mean on Y axis -- %5.2f +/- %5.2f deg",ymeanhist->GetMean(),ymeanhist->GetRMS());
748 legendmean->AddEntry(xmeanhist,xmeantitle,"F");
749 legendmean->AddEntry(ymeanhist,ymeantitle,"F");
750 legendmean->Draw();
751
752 //meancanvas->Modified();
753 //meancanvas->Update();
754
755 c1->cd(6);
756
757 chisquhist->SetLineColor(215);
758 chisquhist->SetLineWidth(2);
759 chisquhist->SetXTitle("chi square / ndof");
760 TAxis * axis = chisquhist->GetXaxis();
761 axis->SetLabelSize(0.025);
762 chisquhist->DrawCopy();
763
764 TLegend *legendchisqu = new TLegend(.4,.85,.95,.95);
765 legendchisqu->SetTextSize(0.03);
766 char chisqutitle[100];
767 sprintf(chisqutitle,"chi square / ndof -- %5.2f +/- %5.2f ",chisquhist->GetMean(),chisquhist->GetRMS());
768 legendchisqu->AddEntry(chisquhist,chisqutitle,"F");
769 legendchisqu->Draw();
770
771
772 return;
773
774}
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