- Timestamp:
- 06/27/12 17:36:10 (12 years ago)
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fact/tools/marsmacros/singlepe.C
r14241 r14242 153 153 154 154 fSignal.SetName("Signal"); 155 fSignal.SetTitle(" Title");156 fSignal.SetXTitle(" X title");157 fSignal.SetYTitle(" Y title");155 fSignal.SetTitle("pulse integral spectrum"); 156 fSignal.SetXTitle("pixel [SoftID]"); 157 fSignal.SetYTitle("time [a.u.]"); 158 158 fSignal.SetDirectory(NULL); 159 159 160 160 fTime.SetName("Time"); 161 fTime.SetTitle(" Title");162 fTime.SetXTitle(" X title");163 fTime.SetYTitle(" Y title");161 fTime.SetTitle("arival time spectrum"); 162 fTime.SetXTitle("pixel [SoftID]"); 163 fTime.SetYTitle("time [a.u.]"); 164 164 fTime.SetDirectory(NULL); 165 165 166 166 fPulse.SetName("Pulse"); 167 fPulse.SetTitle(" Title");168 fPulse.SetXTitle(" X title");169 fPulse.SetYTitle(" Y title");167 fPulse.SetTitle("average pulse shape spectrum"); 168 fPulse.SetXTitle("pixel [SoftID]"); 169 fPulse.SetYTitle("time [a.u.]"); 170 170 fPulse.SetDirectory(NULL); 171 171 } … … 417 417 Int_t maxbin, double fwhm, Double_t gain ); 418 418 419 int singlepe(const char *runfile, const char *drsfile, const char *outfile) 419 Double_t MedianOfH1 ( 420 TH1* inputHisto 421 ); 422 423 int singlepe( 424 // const char *runfile, const char *drsfile, const char *outfile 425 ) 420 426 { 427 421 428 // ====================================================== 422 429 423 //const char *drsfile = "/fact/raw/2012/05/18/20120518_012.drs.fits.gz"; 430 const char *drsfile = "/fact/raw/2012/05/18/20120518_003.drs.fits.gz"; 431 // const char *drsfile = "/fact/raw/2012/06/25/20120625_112.drs.fits.gz"; 424 432 425 433 MDirIter iter; 426 //iter.AddDirectory("/fact/raw/2012/05/18", "20120518_005.fits.gz"); 427 iter.AddDirectory(gSystem->DirName(runfile), gSystem->BaseName(runfile)); 434 iter.AddDirectory("/fact/raw/2012/05/18", "20120518_005.fits.gz"); 435 // iter.AddDirectory(gSystem->DirName(runfile), gSystem->BaseName(runfile)); 436 437 // TString filename; 438 // for (UInt_t fileNr = 116; fileNr < 147; fileNr++) 439 // { 440 // filename = "20120625_"; 441 // filename += fileNr; 442 // filename += ".fits.gz"; 443 // iter.AddDirectory("/fact/raw/2012/06/25", filename); 444 // } 445 446 // iter.AddDirectory("/fact/raw/2012/06/25", "20120625_116.fits.gz"); 447 // iter.AddDirectory("/fact/raw/2012/06/25", "20120625_117.fits.gz"); 448 // iter.AddDirectory("/fact/raw/2012/06/25", "20120625_118.fits.gz"); 449 // iter.AddDirectory("/fact/raw/2012/06/25", "20120625_119.fits.gz"); 428 450 429 451 // ====================================================== … … 570 592 d->AddTab("Time"); 571 593 TH1 *ht = htime->ProjectionY(); 594 ht->SetYTitle("Counts [a.u.]"); 572 595 ht->Scale(1./1440); 573 596 ht->Draw(); … … 575 598 d->AddTab("Pulse"); 576 599 TH1 *hp = hpulse->ProjectionY(); 600 hp->SetYTitle("Counts [a.u.]"); 577 601 hp->Scale(1./1440); 578 602 hp->Draw(); … … 582 606 // AFTER this the Code for the spektrum fit follows 583 607 // access the spektrumhistogram by the pointer *hist 584 UInt_t maxOrder = 6;608 UInt_t maxOrder = 8; 585 609 586 610 587 611 MGeomCamFACT fact; 588 612 MHCamera hcam(fact); 613 MHCamera hcam2(fact); 589 614 590 615 //built an array of Amplitude spectra 591 616 TH1F hAmplitude ("Rate", "Average number of dark counts per event", 592 617 200, 0, 20); 618 hAmplitude.SetXTitle("Amplitude [a.u.]"); 619 hAmplitude.SetYTitle("Rate"); 620 593 621 TH1F hGain ("Gain", "Gain distribution", 594 622 50, 100, 300); 623 hGain.SetXTitle("gain [a.u.]"); 624 hGain.SetYTitle("Rate"); 625 595 626 TH1F hGainRMS ("RelSigma", "Distribution of rel. Sigma", 596 627 100, 0, 30); 628 hGainRMS.SetXTitle("gainRMS [a.u.]"); 629 hGainRMS.SetYTitle("Rate"); 630 hGainRMS.SetStats(false); 631 597 632 TH1F hCrosstlk ("Crosstalk", "Distribution of crosstalk probability", 598 633 100, 0, 25); 634 hCrosstlk.SetXTitle("crosstalk [a.u.]"); 635 hCrosstlk.SetYTitle("Rate"); 636 599 637 TH1F hOffset ("Offset", "Baseline offset distribution", 600 638 50, -7.5, 2.5); 639 hOffset.SetXTitle("baseline offset [a.u.]"); 640 hOffset.SetYTitle("Rate"); 641 601 642 TH1F hFitProb ("FitProb", "FitProb distribution", 602 643 50, 0, 100); 603 TH1F hSum ("Sum1", "Sum of all pixel amplitude Spectra", 644 hFitProb.SetXTitle("FitProb p-value [a.u.]"); 645 hFitProb.SetYTitle("Rate"); 646 hFitProb.SetStats(false); 647 648 649 TH1F hSum ("Sum1", "Sum of all pixel's' integral spectra", 604 650 100, 0, 2000); 651 hSum.SetXTitle("pulse integral [a.u.]"); 652 hSum.SetYTitle("Rate"); 653 hSum.SetStats(false); 605 654 hSum.Sumw2(); 606 655 656 607 657 TH1F hSumScale ("Sum2", 608 "Sum of all pixel amplitude Spectra (scaled with gain)",658 "Sum of all pixel's' integral spectra (scaled with gain)", 609 659 100, 0.05, 10.05); 660 hSumScale.SetXTitle("pulse integral [pe]"); 661 hSumScale.SetYTitle("Rate"); 662 hSumScale.SetStats(false); 610 663 hSumScale.Sumw2(); 611 664 … … 616 669 617 670 // define fit function for Amplitudespectrum 618 TF1 func 2("sum_spektrum", fcn_cross, 0, 2000, 6);619 func 2.SetParNames("Maximum", "Gain", "Sigma", "XtalkProb", "Offset", "PowOfXtalk");620 func 2.SetLineColor(kBlue);671 TF1 funcSum("sum_spektrum", fcn, 0, 2000, 5); 672 funcSum.SetParNames("Maximum", "Gain", "Sigma", "XtalkProb", "Offset", "PowOfXtalk"); 673 funcSum.SetLineColor(kBlue); 621 674 622 675 // define fit function for Amplitudespectrum 623 TF1 func 3("gain_sum_spektrum", fcn, 0, 10, 5);624 func 3.SetParNames("Maximum", "Gain", "Sigma", "XtalkProb", "Offset");625 func 3.SetLineColor(kBlue);676 TF1 funcScaled("gain_sum_spektrum", fcn, 0, 10, 5); 677 funcScaled.SetParNames("Maximum", "Gain", "Sigma", "XtalkProb", "Offset"); 678 funcScaled.SetLineColor(kBlue); 626 679 627 680 … … 673 726 } 674 727 } 675 for(UInt_t bin = 1; bin < hSum.GetNbinsX()+1; bin++)728 for(UInt_t bin = 1; bin < (UInt_t)hSum.GetNbinsX()+1; bin++) 676 729 { 677 730 hSum.SetBinError(bin, hSum.GetBinContent(bin)*0.1); … … 680 733 gROOT->SetSelectedPad(0); 681 734 TCanvas &c11 = d->AddTab("SumHist"); 735 c11.cd(); 682 736 gPad->SetLogy(); 683 737 gPad->SetGridx(); … … 689 743 const Double_t ampl = hSum.GetBinContent(maxbin); 690 744 691 double fwhm 2= 0;745 double fwhmSum = 0; 692 746 693 747 //Calculate full width half Maximum … … 695 749 if (hSum.GetBinContent(maxbin-i)+hSum.GetBinContent(maxbin+i)<ampl*2) 696 750 { 697 fwhm 2= (2*i+1)*binwidth;751 fwhmSum = (2*i+1)*binwidth; 698 752 break; 699 753 } 700 if (fwhm 2==0)754 if (fwhmSum==0) 701 755 { 702 756 cout << "Could not determine start value for sigma." << endl; … … 706 760 Double_t sum_par[6] = 707 761 { 708 ampl, hSum.GetBinCenter(maxbin), fwhm 2*1.4, 0.1, -10, 1762 ampl, hSum.GetBinCenter(maxbin), fwhmSum*1.4, 0.1, -10, 1 709 763 }; 710 func 2.SetParameters(sum_par);764 funcSum.SetParameters(sum_par); 711 765 712 766 //calculate fit range 713 const double min = sum_par[1]-fwhm2*2; 714 const double max = sum_par[1]*(maxOrder+1); 715 func2.SetRange(min, max); 767 const double min = sum_par[1]-fwhmSum*2; 768 const double max = sum_par[1]*(maxOrder); 769 funcSum.SetRange(min, max); 770 funcSum.FixParameter(5,0.1); 716 771 717 772 //Fit and draw spectrum 718 hSum.Fit(&func 2, "NOS", "", min, max);719 func 2.DrawCopy("SAME");720 func 2.GetParameters(sum_par);773 hSum.Fit(&funcSum, "NOQS", "", min, max); 774 funcSum.DrawCopy("SAME"); 775 funcSum.GetParameters(sum_par); 721 776 722 777 //Set Parameters for following fits 723 const float Amplitude = sum_par[0];778 // const float Amplitude = sum_par[0]; 724 779 const float gain = sum_par[1]; 725 const float GainRMS = sum_par[2];780 // const float GainRMS = sum_par[2]; 726 781 const float Crosstlk = sum_par[3]; 727 782 const float Offset = sum_par[4]; 728 const float PowCrosstlk = sum_par[5];783 // const float PowCrosstlk = sum_par[5]; 729 784 730 785 … … 733 788 // create histo for height of Maximum amplitudes vs. pe 734 789 double min_bin = hSum.GetBinCenter(maxbin); 735 double max_bin = hSum.GetBinCenter( maxOrder*(maxbin));790 double max_bin = hSum.GetBinCenter((maxOrder-2)*(maxbin)); 736 791 double bin_width= (max_bin - min_bin)/10; 737 792 … … 741 796 FitGaussiansToSpectrum 742 797 ( 743 maxOrder ,798 maxOrder-2, 744 799 hSum, 745 800 hMaxHeightsSum, 746 801 maxbin, 747 fwhm 2,802 fwhmSum, 748 803 gain 749 804 ); … … 757 812 TF1 fExpo1( "fExpo1","expo", min, max); 758 813 fExpo1.SetLineColor(kRed); 759 hMaxHeightsSum.Fit(&fExpo1, " WLN0S" );760 hMaxHeightsSum.DrawCopy("SAME");761 fExpo1.DrawCopy("SAME");814 hMaxHeightsSum.Fit(&fExpo1, "N0QS" ); 815 // hMaxHeightsSum.DrawCopy("SAME"); 816 // fExpo1.DrawCopy("SAME"); 762 817 763 818 // EOF: Fill and calculate sum spectrum … … 781 836 hist->SetDirectory(0); 782 837 783 for(UInt_t bin = 1; bin < hSum.GetNbinsX()+1; bin++)838 for(UInt_t bin = 1; bin < (UInt_t)hSum.GetNbinsX()+1; bin++) 784 839 { 785 840 hist->SetBinError(bin, hSum.GetBinContent(bin)*0.1); … … 841 896 842 897 //Fit Pixels spectrum 843 const TFitResultPtr rc = hist->Fit(&func, " WLN0QS", "", fit_min, fit_max);898 const TFitResultPtr rc = hist->Fit(&func, "N0QS", "", fit_min, fit_max); 844 899 845 900 const bool ok = int(rc)==0; … … 853 908 // const float fCrossOrd = func.GetParameter(5); 854 909 855 if (suspicous[pixel] == true)856 {857 cout << "Amplitude, 1.Max, Sigma, fwhm:\t"858 << fAmplitude << "\t"859 << fGain << "\t"860 << f2GainRMS << "\t"861 << fwhm << "\t" << endl;862 }863 864 910 hAmplitude.Fill(fAmplitude); 865 911 hGain.Fill(fGain); … … 871 917 872 918 hcam.SetBinContent(pixel+1, fGain); 919 hcam2.SetBinContent(pixel+1, 100*f2GainRMS/fGain); 873 920 874 921 usePixel[pixel] = ok; … … 884 931 { 885 932 // hSum.Fill(hist->GetBinCenter(b), hist->GetBinContent(b)); 886 hSumScale.Fill((hist->GetBinCenter(b)-fOffset)/fGain, hist->GetBinContent(b));933 hSumScale.Fill((hist->GetBinCenter(b)-fOffset)/fGain, (hist->GetBinContent(b))); 887 934 } 888 935 … … 895 942 TCanvas &c = d->AddTab(Form("Pix%d", pixel)); 896 943 c.cd(); 944 gPad->SetLogy(); 945 gPad->SetGridx(); 946 gPad->SetGridy(); 947 948 hist->SetStats(false); 949 hist->SetYTitle("Counts [a.u.]"); 897 950 hist->SetName(Form("Pix%d", pixel)); 898 951 hist->DrawCopy("hist")->SetDirectory(0); … … 911 964 912 965 hcam.SetUsed(usePixel); 966 hcam2.SetUsed(usePixel); 913 967 914 968 TCanvas &canv = d->AddTab("Gain"); 915 969 canv.cd(); 970 canv.Divide(2,2); 971 972 canv.cd(1); 916 973 hcam.SetNameTitle( "gain","Gain distribution over whole camera"); 917 974 hcam.DrawCopy(); 975 976 canv.cd(2); 977 hcam2.SetNameTitle( "gainRMS","GainRMS distribution over whole camera"); 978 hcam2.DrawCopy(); 979 980 TCanvas &cam_canv = d->AddTab("Camera_Gain"); 918 981 919 982 //------------------ Draw gain corrected sum specetrum ------------------- 920 983 gROOT->SetSelectedPad(0); 921 984 TCanvas &c12 = d->AddTab("GainHist"); 985 c12.cd(); 922 986 gPad->SetLogy(); 923 987 gPad->SetGridx(); 924 988 gPad->SetGridy(); 925 for(UInt_t bin = 1; bin < hSum.GetNbinsX()+1; bin++) 989 990 for(UInt_t bin = 1; bin < (UInt_t)hSum.GetNbinsX()+1; bin++) 926 991 { 927 992 hSumScale.SetBinError(bin, hSum.GetBinContent(bin)*0.1); … … 936 1001 937 1002 //Calculate full width half Maximum 938 fwhm2= 0;1003 double fwhmScaled = 0; 939 1004 for (int i=1; i<maxbin; i++) 940 1005 if (hSumScale.GetBinContent(maxbin2-i)+hSumScale.GetBinContent(maxbin2+i)<ampl2*2) 941 1006 { 942 fwhm 2= (2*i+1)*binwidth2;1007 fwhmScaled = (2*i+1)*binwidth2; 943 1008 break; 944 1009 } 945 if (fwhm 2==0)1010 if (fwhmScaled==0) 946 1011 { 947 1012 cout << "Could not determine start value for sigma." << endl; … … 949 1014 950 1015 //Set fit parameters 951 Double_t par2[ 5] =952 { 953 ampl2, 1, fwhm2*1.4, Crosstlk, 01016 Double_t par2[6] = 1017 { 1018 ampl2, 0.9, fwhmScaled*1.4, Crosstlk, 0, 1.1 954 1019 }; 955 1020 956 func3.SetParameters(par2); 957 func3.FixParameter(1,1); 958 func3.FixParameter(4,0); 959 960 const double min2 = par2[1]-fwhm2*1.4; 961 const double max2 = par2[1]*maxOrder; 962 // func.SetRange(min2-fwhm2, max); 963 hSumScale.Fit(&func3, "WLN0QS", "", min2, max2); 964 func3.DrawCopy("SAME"); 965 1021 funcScaled.SetParameters(par2); 1022 // funcScaled.FixParameter(1,0.9); 1023 funcScaled.FixParameter(4,0); 1024 funcScaled.FixParameter(5,Crosstlk); 1025 1026 const double minScaled = par2[1]-fwhmScaled; 1027 const double maxScaled = par2[1]*maxOrder; 1028 cout << "par2[1]" << par2[1] << endl; 1029 cout << "maxScaled\t" << maxScaled 1030 << " \t\t minScaled\t" << minScaled << endl; 1031 1032 funcScaled.SetRange(minScaled, maxScaled); 1033 hSumScale.Fit(&funcScaled, "N0QS", "", minScaled, maxScaled); 1034 funcScaled.DrawCopy("SAME"); 966 1035 //--------fit gausses to peaks of gain corrected sum specetrum ----------- 967 1036 … … 972 1041 FitGaussiansToSpectrum 973 1042 ( 974 maxOrder ,1043 maxOrder-2, 975 1044 hSumScale, 976 1045 hMaxHeights, 977 1046 maxbin2, 978 fwhm 2,1047 fwhmScaled, 979 1048 1 980 1049 ); … … 986 1055 hMaxHeights.SetLineColor(kRed); 987 1056 // hMaxHeights.DrawCopy("SAME"); 988 TF1 fExpo( "fExpo","expo", 0, maxOrder- 1);1057 TF1 fExpo( "fExpo","expo", 0, maxOrder-2); 989 1058 fExpo.SetLineColor(kRed); 990 1059 hMaxHeights.Fit(&fExpo, "N0QS" ); 991 fExpo.DrawCopy("SAME");1060 // fExpo.DrawCopy("SAME"); 992 1061 // c12.cd(); 993 1062 // fExpo.DrawCopy("SAME"); … … 1001 1070 c2.cd(2); 1002 1071 gPad->SetLogy(); 1003 TF1 GainGaus( "GainGaus", "gaus"); 1072 // hGain.DrawCopy(); 1073 1074 1075 TF1 GainGaus( "GainGaus", "gaus", 0, hGain.GetXaxis()->GetXmax()); 1076 hGain.Rebin(2); 1004 1077 hGain.Fit(&GainGaus, "N0QS"); 1078 1079 // float gain_mean = GainGaus.GetParameter(1); 1080 float gain_median = MedianOfH1(&hGain); 1081 TH1F hNormGain ("NormGain", "median normalized Gain distribution", 1082 hGain.GetNbinsX(), 1083 (hGain.GetXaxis()->GetXmin())/gain_median, 1084 (hGain.GetXaxis()->GetXmax())/gain_median 1085 ); 1086 hNormGain.SetXTitle("gain [fraction of median gain value]"); 1087 hNormGain.SetYTitle("Counts"); 1088 1089 1090 hNormGain.Add(&hGain); 1091 // hNormGain.SetStats(false); 1092 hNormGain.GetXaxis()->SetRangeUser( 1093 1-(hNormGain.GetXaxis()->GetXmax()-1), 1094 hNormGain.GetXaxis()->GetXmax() 1095 ); 1096 hNormGain.DrawCopy(); 1097 hNormGain.Fit(&GainGaus, "N0QS"); 1098 GainGaus.DrawCopy("SAME"); 1099 1100 //plot normailzed camera view 1101 cam_canv.cd(); 1102 MHCamera hNormCam(fact); 1103 hNormCam.SetStats(false); 1104 for (UInt_t pixel =1; pixel <= 1440; pixel++) 1105 { 1106 hNormCam.SetBinContent(pixel, hcam.GetBinContent(pixel)/gain_median); 1107 } 1108 1109 hNormCam.SetNameTitle( "gain","normalized [Median] Gain distribution over whole camera"); 1110 hNormCam.SetZTitle("Horst"); 1111 hNormCam.SetUsed(usePixel); 1112 hNormCam.DrawCopy(); 1005 1113 // hGain.Scale(1/GainGaus.GetParameter(1)); 1006 hGain.DrawCopy(); 1007 GainGaus.DrawCopy("SAME"); 1114 // GainGaus.DrawCopy("SAME"); 1008 1115 1009 1116 c2.cd(3); … … 1022 1129 gPad->SetLogy(); 1023 1130 hFitProb.DrawCopy(); 1131 1132 1133 TCanvas &c25 = d->AddTab("Spectra"); 1134 c25.Divide(2,1); 1135 c25.cd(1); 1136 gPad->SetLogy(); 1137 gPad->SetGrid(); 1138 hSum.DrawCopy("hist"); 1139 funcSum.DrawCopy("SAME"); 1140 1141 c25.cd(2); 1142 gPad->SetLogy(); 1143 gPad->SetGrid(); 1144 hSumScale.DrawCopy("hist"); 1145 funcScaled.DrawCopy("SAME"); 1146 1024 1147 1025 1148 /* … … 1029 1152 */ 1030 1153 1031 d->SaveAs(outfile);1154 // d->SaveAs(outfile); 1032 1155 return 0; 1033 1156 } … … 1073 1196 Double_t cross = par[3]; 1074 1197 Double_t shift = par[4]; 1075 Double_t powOfX = par[5];1198 // Double_t powOfX = par[5]; 1076 1199 1077 1200 Double_t xTalk = 1; … … 1086 1209 y += xTalk*gauss; 1087 1210 1211 // xTalk = pow(cross, order*powOfX); 1088 1212 // for (int j = 1; j < powOfX; j++) 1089 1213 // { … … 1135 1259 } 1136 1260 1261 Double_t MedianOfH1 ( 1262 TH1* inputHisto 1263 ) 1264 { 1265 //compute the median for 1-d histogram h1 1266 Int_t nbins = inputHisto->GetXaxis()->GetNbins(); 1267 Double_t *x = new Double_t[nbins]; 1268 Double_t *y = new Double_t[nbins]; 1269 for (Int_t i=0;i<nbins;i++) { 1270 x[i] = inputHisto->GetXaxis()->GetBinCenter(i+1); 1271 y[i] = inputHisto->GetBinContent(i+1); 1272 } 1273 Double_t median = TMath::Median(nbins,x,y); 1274 delete [] x; 1275 delete [] y; 1276 return median; 1277 } 1278 // end of PlotMedianEachSliceOfPulse 1279 //----------------------------------------------------------------------------
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