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|
// -*- C++ -*-
//
// LEPEventShapes.cc is a part of Herwig++ - A multi-purpose Monte Carlo event generator
// Copyright (C) 2002-2011 The Herwig Collaboration
//
// Herwig++ is licenced under version 2 of the GPL, see COPYING for details.
// Please respect the MCnet academic guidelines, see GUIDELINES for details.
//
//
// This is the implementation of the non-inlined, non-templated member
// functions of the LEPEventShapes class.
//
#include "LEPEventShapes.h"
#include "EventShapes.h"
#include "ThePEG/EventRecord/Event.h"
#include "ThePEG/Interface/Reference.h"
#include "ThePEG/Interface/ClassDocumentation.h"
#include "ThePEG/Persistency/PersistentOStream.h"
#include "ThePEG/Persistency/PersistentIStream.h"
#include "ThePEG/Repository/CurrentGenerator.h"
using namespace Herwig;
void LEPEventShapes::analyze(tEventPtr event, long ieve,
int loop, int state) {
AnalysisHandler::analyze(event, ieve, loop, state);
if ( loop > 0 || state != 0 || !event ) return;
// get the final-state particles
tPVector hadrons=event->getFinalState();
// event shapes
}
LorentzRotation LEPEventShapes::transform(tEventPtr) const {
return LorentzRotation();
// Return the Rotation to the frame in which you want to perform the analysis.
}
void LEPEventShapes::analyze(const tPVector & ) {
double eventweight = generator()->currentEvent()->weight();
_omthr ->addWeighted( 1.-_shapes->thrust() ,eventweight);
_maj ->addWeighted( _shapes->thrustMajor() ,eventweight);
_min ->addWeighted( _shapes->thrustMinor() ,eventweight);
_obl ->addWeighted( _shapes->oblateness() ,eventweight);
_c ->addWeighted( _shapes->CParameter() ,eventweight);
_d ->addWeighted( _shapes->DParameter() ,eventweight);
_sph ->addWeighted( _shapes->sphericity() ,eventweight);
_apl ->addWeighted( _shapes->aplanarity() ,eventweight);
_pla ->addWeighted( _shapes->planarity() ,eventweight);
_mhi ->addWeighted( _shapes->Mhigh2() ,eventweight);
_mlo ->addWeighted( _shapes->Mlow2() ,eventweight);
_mdiff ->addWeighted( _shapes->Mdiff2() ,eventweight);
_bmax ->addWeighted( _shapes->Bmax() ,eventweight);
_bmin ->addWeighted( _shapes->Bmin() ,eventweight);
_bsum ->addWeighted( _shapes->Bsum() ,eventweight);
_bdiff ->addWeighted( _shapes->Bdiff() ,eventweight);
}
void LEPEventShapes::persistentOutput(PersistentOStream & os) const {
os << _shapes;
}
void LEPEventShapes::persistentInput(PersistentIStream & is, int) {
is >> _shapes;
}
ClassDescription<LEPEventShapes> LEPEventShapes::initLEPEventShapes;
// Definition of the static class description member.
void LEPEventShapes::Init() {
static ClassDocumentation<LEPEventShapes> documentation
("The LEPEventShapes class compares event shapes at the Z mass"
"with experimental results",
"The LEP EventShapes analysis uses data from \\cite{Pfeifenschneider:1999rz,Abreu:1996na}.",
"%\\cite{Pfeifenschneider:1999rz}\n"
"\\bibitem{Pfeifenschneider:1999rz}\n"
" P.~Pfeifenschneider {\\it et al.} [JADE collaboration and OPAL\n"
" Collaboration],\n"
" ``QCD analyses and determinations of alpha(s) in e+ e- annihilation at\n"
" %energies between 35-GeV and 189-GeV,''\n"
" Eur.\\ Phys.\\ J.\\ C {\\bf 17}, 19 (2000)\n"
" [arXiv:hep-ex/0001055].\n"
" %%CITATION = EPHJA,C17,19;%%\n"
"%\\cite{Abreu:1996na}\n"
"\\bibitem{Abreu:1996na}\n"
" P.~Abreu {\\it et al.} [DELPHI Collaboration],\n"
" ``Tuning and test of fragmentation models based on identified particles and\n"
" %precision event shape data,''\n"
" Z.\\ Phys.\\ C {\\bf 73}, 11 (1996).\n"
" %%CITATION = ZEPYA,C73,11;%%\n"
);
static Reference<LEPEventShapes,EventShapes> interfaceEventShapes
("EventShapes",
"Pointer to the object which calculates the event shapes",
&LEPEventShapes::_shapes, false, false, true, false, false);
}
void LEPEventShapes::dofinish() {
useMe();
AnalysisHandler::dofinish();
string fname = generator()->filename() +
string("-") + name() + string(".top");
ofstream output(fname.c_str());
using namespace HistogramOptions;
_omthr->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"1-T compared to DELPHI data",
" ",
"1/SdS/d(1-T)",
" G G ",
"1-T",
" ");
_maj->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Thrust Major compared to DELPHI data",
" ",
"1/SdS/dMajor",
" G G ",
"Major",
" ");
_min->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Thrust Minor compared to DELPHI data",
" ",
"1/SdS/dMinor",
" G G ",
"Minor",
" ");
_obl->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Oblateness compared to DELPHI data",
" ",
"1/SdS/dO",
" G G ",
"O",
" ");
_sph->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Sphericity compared to DELPHI data",
" ",
"1/SdS/dS",
" G G ",
"S",
" ");
_apl->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Aplanarity compared to DELPHI data",
" ",
"1/SdS/dA",
" G G ",
"A",
" ");
_pla->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Planarity compared to DELPHI data",
" ",
"1/SdS/dP",
" G G ",
"P",
" ");
_c->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"C parameter compared to DELPHI data",
" ",
"1/SdS/dC",
" G G ",
"C",
" ");
_d->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"D parameter compared to DELPHI data",
" ",
"1/SdS/dD",
" G G ",
"D",
" ");
_mhi->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"High hemisphere mass compared to DELPHI data",
" ",
"1/SdS/dM0high1",
" G G X X",
"M0high1",
" X X");
_mlo->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Low hemisphere mass compared to DELPHI data",
" ",
"1/SdS/dM0low1",
" G G X X",
"M0low1",
" X X");
_mdiff->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Difference in hemisphere masses compared to DELPHI data",
" ",
"1/SdS/dM0diff1",
" G G X X",
"M0diff1",
" X X");
_bmax->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Wide jet broadening measure compared to DELPHI data",
" ",
"1/SdS/dB0max1",
" G G X X",
"B0max1",
" X X");
_bmin->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Narrow jet broadening measure compared to DELPHI data",
" ",
"1/SdS/dB0min1",
" G G X X",
"B0min1",
" X X");
_bsum->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Sum of jet broadening measures compared to DELPHI data",
" ",
"1/SdS/dB0sum1",
" G G X X",
"B0sum1",
" X X");
_bdiff->topdrawOutput(output,Frame|Errorbars|Ylog,
"RED",
"Difference of jet broadenings measure compared to DELPHI data",
" ",
"1/SdS/dB0diff1",
" G G X X",
"B0diff1",
" X X");
// chi squareds
double chisq=0.,minfrac=0.05;
unsigned int ndegrees;
_omthr->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI thrust distribution\n";
_maj->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI major distribution\n";
_min->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI minor distribution\n";
_obl->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI oblateness distribution\n";
_sph->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI sphericity distribution\n";
_apl->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI aplanarity distribution\n";
_pla->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI planarity distribution\n";
_c->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI C distribution\n";
_d->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI D distribution\n";
_mhi->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI m_high distribution\n";
_mlo->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI m_low distribution\n";
_mdiff->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI m_diff distribution\n";
_bmax->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI B_max distribution\n";
_bmin->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI B_min distribution\n";
_bsum->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI B_sum distribution\n";
_bdiff->chiSquared(chisq,ndegrees,minfrac);
generator()->log() << "Chi Square = " << chisq << " for " << ndegrees
<< " degrees of freedom for DELPHI B_diff distribution\n";
}
void LEPEventShapes::doinitrun() {
AnalysisHandler::doinitrun();
vector<double> bins,data,error;
// 1-T
double vals1[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.070, 0.080, 0.090,
0.100, 0.120, 0.140, 0.160, 0.180,
0.200, 0.250, 0.300, 0.350, 0.400,
0.500};
double data1[]= { 1.030,10.951,17.645,14.192,10.009,
7.572, 5.760, 4.619, 3.792, 3.176,
2.456, 1.825, 1.401, 1.074, 0.8262,
0.5525,0.3030,0.1312,0.0238,0.0007};
double error1stat[]={0.019 ,0.051 ,0.066 ,0.061 ,0.050 ,
0.044 ,0.038 ,0.034 ,0.031 ,0.028 ,
0.018 ,0.015 ,0.013 ,0.011 ,0.0100 ,
0.0051 ,0.0038 ,0.0025 ,0.0012 ,0.0002 };
double error1syst[]={0.076 , 0.527 , 0.547 , 0.292 , 0.152 ,
0.101 , 0.076 , 0.062 , 0.051 , 0.042 ,
0.032 , 0.022 , 0.016 , 0.011 , 0.0083,
0.0065 , 0.0058, 0.0044, 0.0014, 0.0001};
double error1[20];
for(unsigned int ix=0;ix<20;++ix){error1[ix]=sqrt(sqr(error1stat[ix])+
sqr(error1syst[ix]));}
bins = vector<double>(vals1 ,vals1 +21);
data = vector<double>(data1 ,data1 +20);
error = vector<double>(error1,error1+20);
_omthr= new_ptr(Histogram(bins,data,error));
// major
double vals2[] = {0.000, 0.020, 0.040, 0.050, 0.060,
0.070, 0.080, 0.100, 0.120, 0.140,
0.160, 0.200, 0.240, 0.280, 0.320,
0.360, 0.400, 0.440, 0.480, 0.520,
0.560, 0.600, 0.640};
double data2[]={0.00040 ,0.0590 ,0.642 ,2.178 ,4.303 ,
5.849 ,6.889 ,6.342 ,4.890 ,3.900 ,
2.960 ,2.124 ,1.5562 ,1.1807 ,0.8693,
0.6493 ,0.4820 ,0.3493 ,0.2497 ,0.1489,
0.0714 ,0.0203};
double error2stat[]={0.00090 ,0.0030 ,0.013 ,0.024 ,0.034 ,
0.039 ,0.030 ,0.028 ,0.024 ,0.021 ,
0.013 ,0.011 ,0.0095 ,0.0083 ,0.0071 ,
0.0061 ,0.0052 ,0.0044 ,0.0037 ,0.0028 ,
0.0019 ,0.0010};
double error2syst[]={0.00005 ,0.0058 ,0.028 ,0.086 ,0.155 ,
0.192 ,0.194 ,0.143 ,0.085 ,0.050 ,
0.030 ,0.021 ,0.0156 ,0.0118 ,0.0087 ,
0.0065 ,0.0048 ,0.0055 ,0.0065 ,0.0058 ,
0.0038 ,0.0014};
double error2[22];
for(unsigned int ix=0;ix<22;++ix){error2[ix]=sqrt(sqr(error2stat[ix])+
sqr(error2syst[ix]));}
bins = vector<double>(vals2 ,vals2 +23);
data = vector<double>(data2 ,data2 +22);
error = vector<double>(error2,error2+22);
_maj= new_ptr(Histogram(bins,data,error));
// minor
double vals3[] = {0.000, 0.020, 0.040, 0.050, 0.060,
0.070, 0.080, 0.100, 0.120, 0.140,
0.160, 0.200, 0.240, 0.280, 0.320,
0.400};
double data3[]={ 0.0156 , 1.236 , 5.706 , 9.714 ,12.015 ,
12.437 ,10.404 , 6.918 , 4.250 , 2.517 ,
1.2561 , 0.4895 , 0.2112 , 0.0879 , 0.0250 };
double error3stat[]={0.0017 ,0.013 ,0.037 ,0.048 ,0.054 ,
0.055 ,0.036 ,0.029 ,0.023 ,0.017 ,
0.0086 ,0.0054 ,0.0036 ,0.0023 ,0.0009};
double error3syst[]={0.0036,0.066 ,0.073 ,0.125 ,0.155 ,
0.161 ,0.136 ,0.092 ,0.058 ,0.035 ,
0.0187,0.0080,0.0039,0.0018,0.0006};
double error3[15];
for(unsigned int ix=0;ix<15;++ix){error3[ix]=sqrt(sqr(error3stat[ix])+
sqr(error3syst[ix]));}
bins = vector<double>(vals3 ,vals3 +16);
data = vector<double>(data3 ,data3 +15);
error = vector<double>(error3,error3+15);
_min= new_ptr(Histogram(bins,data,error));
// oblateness
double vals4[] = {0.000, 0.020, 0.040, 0.060, 0.080,
0.100, 0.120, 0.140, 0.160, 0.200,
0.240, 0.280, 0.320, 0.360, 0.400,
0.440, 0.520};
double data4[]={ 9.357 ,11.508 , 7.215 , 4.736 , 3.477 ,
2.696 , 2.106 , 1.690 , 1.2648 , 0.8403 ,
0.5674 , 0.3842 , 0.2573 , 0.1594 , 0.0836 ,
0.0221 };
double error4stat[]={0.036 ,0.038 ,0.029 ,0.023 ,0.020 ,
0.018 ,0.016 ,0.014 ,0.0085 ,0.0069 ,
0.0056 ,0.0046 ,0.0037 ,0.0029 ,0.0020 ,
0.0007};
double error4syst[]={0.178 ,0.140 ,0.072 ,0.047 ,0.035 ,
0.027 ,0.021 ,0.017 ,0.0126,0.0087,
0.0065,0.0050,0.0043,0.0037,0.0030,
0.0015};
double error4[16];
for(unsigned int ix=0;ix<16;++ix){error4[ix]=sqrt(sqr(error4stat[ix])+
sqr(error4syst[ix]));}
bins = vector<double>(vals4 ,vals4 +17);
data = vector<double>(data4 ,data4 +16);
error = vector<double>(error4,error4+16);
_obl= new_ptr(Histogram(bins,data,error));
// sphericity
double vals5[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.080, 0.100, 0.120,
0.160, 0.200, 0.250, 0.300, 0.350,
0.400, 0.500, 0.600, 0.700, 0.850};
double data5[]={16.198 ,20.008 ,12.896 , 8.237 , 5.885 ,
4.458 , 3.272 , 2.290 , 1.699 , 1.2018 ,
0.7988 , 0.5610 , 0.3926 , 0.2810 , 0.2099 ,
0.1441 , 0.0842 , 0.04160 , 0.00758 };
double error5stat[]={0.067 ,0.072 ,0.056 ,0.043 ,0.037 ,
0.032 ,0.019 ,0.016 ,0.014 ,0.0082 ,
0.0067 ,0.0050 ,0.0042 ,0.0035 ,0.0030 ,
0.0018 ,0.0013 ,0.00092 ,0.00032};
double error5syst[]={0.208 ,0.246 ,0.153 ,0.094 ,0.065 ,
0.048 ,0.034 ,0.023 ,0.017 ,0.0120 ,
0.0080 ,0.0063 ,0.0051 ,0.0043 ,0.0037 ,
0.0032 ,0.0023 ,0.00129,0.00024};
double error5[19];
for(unsigned int ix=0;ix<19;++ix){error5[ix]=sqrt(sqr(error5stat[ix])+
sqr(error5syst[ix]));}
bins = vector<double>(vals5 ,vals5 +20);
data = vector<double>(data5 ,data5 +19);
error = vector<double>(error5,error5+19);
_sph=new_ptr(Histogram(bins,data,error));
// aplanarity
double vals6[] = {0.000, 0.005, 0.010, 0.015, 0.020,
0.030, 0.040, 0.060, 0.080, 0.100,
0.120, 0.140, 0.160, 0.200, 0.250,
0.300};
double data6[]={75.10 ,55.31 ,26.03 ,13.927 , 6.768 ,
3.014 , 1.281 , 0.5181 , 0.2619 , 0.1461 ,
0.0758 , 0.0467 , 0.0234 , 0.00884 , 0.00310 };
double error6stat[]={0.19 ,0.17 ,0.11 ,0.079 ,0.038 ,
0.025 ,0.012 ,0.0075 ,0.0054 ,0.0041 ,
0.0029 ,0.0023 ,0.0011 ,0.00061 ,0.00040 };
double error6syst[]={0.75 ,0.55 ,0.28 ,0.176 ,0.098 ,
0.056 ,0.035 ,0.0188 ,0.0118 ,0.0079 ,
0.0043 ,0.0027 ,0.0014 ,0.00052,0.00018};
double error6[15];
for(unsigned int ix=0;ix<15;++ix){error6[ix]=sqrt(sqr(error6stat[ix])+
sqr(error6syst[ix]));}
bins = vector<double>(vals6 ,vals6 +16);
data = vector<double>(data6 ,data6 +15);
error = vector<double>(error6,error6+15);
_apl= new_ptr(Histogram(bins,data,error));
// planarity
double vals7[] = {0.000, 0.005, 0.010, 0.015, 0.020,
0.025, 0.030, 0.035, 0.040, 0.050,
0.060, 0.080, 0.100, 0.120, 0.160,
0.200, 0.250, 0.300, 0.350, 0.400,
0.500};
double data7[]={68.69 ,31.66 ,17.091 ,11.370 , 8.417 ,
6.578 , 5.479 , 4.493 , 3.610 , 2.749 ,
1.987 , 1.362 , 1.008 , 0.6676 , 0.4248 ,
0.2692 , 0.1742 , 0.1042 , 0.0566 , 0.0145 };
double error7stat[]={0.19 ,0.12 ,0.088 ,0.072 ,0.062 ,
0.055 ,0.050 ,0.045 ,0.029 ,0.025 ,
0.015 ,0.012 ,0.011 ,0.0061 ,0.0048 ,
0.0034 ,0.0028 ,0.0021 ,0.0015 ,0.0006};
double error7syst[]={0.74 ,0.35 ,0.188 ,0.127 ,0.095 ,
0.075 ,0.063 ,0.052 ,0.042 ,0.033 ,
0.024 ,0.017 ,0.013 ,0.0093,0.0063,
0.0042 ,0.0029,0.0019,0.0011,0.0003};
double error7[20];
for(unsigned int ix=0;ix<20;++ix){error7[ix]=sqrt(sqr(error7stat[ix])+
sqr(error7syst[ix]));}
bins = vector<double>(vals7 ,vals7 +21);
data = vector<double>(data7 ,data7 +20);
error = vector<double>(error7,error7+20);
_pla= new_ptr(Histogram(bins,data,error));
// C
double vals8[] = {0.000, 0.040, 0.080, 0.120, 0.160,
0.200, 0.240, 0.280, 0.320, 0.360,
0.400, 0.440, 0.480, 0.520, 0.560,
0.600, 0.640, 0.680, 0.720, 0.760,
0.800, 0.840, 0.880, 0.920};
double data8[]={0.0881 ,1.5383 ,3.909 ,3.833 ,2.835 ,
2.164 ,1.716 ,1.3860 ,1.1623 ,0.9720 ,
0.8349 ,0.7161 ,0.6205 ,0.5441 ,0.4844 ,
0.4209 ,0.3699 ,0.3286 ,0.2813 ,0.2178 ,
0.1287 ,0.0542 ,0.0212 };
double error8stat[]={0.0030 ,0.0100 ,0.016 ,0.016 ,0.013 ,
0.012 ,0.010 ,0.0092 ,0.0084 ,0.0077 ,
0.0072 ,0.0066 ,0.0061 ,0.0057 ,0.0054 ,
0.0050 ,0.0046 ,0.0044 ,0.0040 ,0.0033 ,
0.0026 ,0.0016 ,0.0009};
double error8syst[]={0.0067,0.0831,0.142 ,0.088 ,0.040 ,
0.022 ,0.017 ,0.0139,0.0116,0.0097,
0.0083,0.0072,0.0062,0.0054,0.0050,
0.0063,0.0079,0.0099,0.0129,0.0151,
0.0130,0.0076,0.0040};
double error8[23];
for(unsigned int ix=0;ix<23;++ix){error8[ix]=sqrt(sqr(error8stat[ix])+
sqr(error8syst[ix]));}
bins = vector<double>(vals8 ,vals8 +24);
data = vector<double>(data8 ,data8 +23);
error = vector<double>(error8,error8+23);
_c= new_ptr(Histogram(bins,data,error));
// D
double vals9[] = {0.000, 0.008, 0.016, 0.030, 0.044,
0.066, 0.088, 0.112, 0.136, 0.162,
0.188, 0.218, 0.248, 0.284, 0.320,
0.360, 0.400, 0.450, 0.500, 0.560,
0.620, 0.710, 0.800};
double data9[]={22.228 ,22.766 ,12.107 , 6.879 , 4.284 ,
2.727 , 1.909 , 1.415 , 1.051 , 0.7977 ,
0.6155 , 0.4566 , 0.3341 , 0.2452 , 0.1774 ,
0.1234 , 0.0902 , 0.0603 , 0.0368 , 0.0222 ,
0.0128 , 0.0052 };
double error9stat[]={0.082 ,0.085 ,0.047 ,0.035 ,0.022 ,
0.018 ,0.014 ,0.012 ,0.010 ,0.0089 ,
0.0073 ,0.0063 ,0.0049 ,0.0042 ,0.0033 ,
0.0028 ,0.0021 ,0.0017 ,0.0012 ,0.0009 ,
0.0006 ,0.0004};
double error9syst[]={0.868 ,0.440 ,0.150 ,0.079 ,0.053 ,
0.036 ,0.028 ,0.022 ,0.018 ,0.0145,
0.0117 ,0.0089,0.0065,0.0049,0.0037 ,
0.0028,0.0023 ,0.0018,0.0013,0.0009,
0.0006,0.0003};
double error9[22];
for(unsigned int ix=0;ix<22;++ix){error9[ix]=sqrt(sqr(error9stat[ix])+
sqr(error9syst[ix]));}
bins = vector<double>(vals9 ,vals9 +23);
data = vector<double>(data9 ,data9 +22);
error = vector<double>(error9,error9+22);
_d= new_ptr(Histogram(bins,data,error));
// M high
double vals10[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.080, 0.100, 0.120,
0.140, 0.160, 0.200, 0.250, 0.300,
0.350, 0.400};
double data10[]={ 1.994 ,18.580 ,20.678 ,13.377 , 8.965 ,
6.558 , 4.515 , 2.914 , 1.991 , 1.406 ,
1.010 , 0.6319 , 0.3085 , 0.1115 , 0.0184 ,
0.0008 };
double error10stat[]={0.027 ,0.065 ,0.076 ,0.060 ,0.049 ,
0.041 ,0.024 ,0.019 ,0.016 ,0.013 ,
0.011 ,0.0063 ,0.0039 ,0.0022 ,0.0008 ,
0.0002 };
double error10syst[]={0.166 ,0.709 ,0.729 ,0.412 ,0.239 ,
0.151 ,0.082 ,0.037 ,0.020 ,0.014 ,
0.010 ,0.0063,0.0051,0.0039,0.0012,
0.0001};
double error10[16];
for(unsigned int ix=0;ix<16;++ix){error10[ix]=sqrt(sqr(error10stat[ix])+
sqr(error10syst[ix]));}
bins = vector<double>(vals10 ,vals10 +17);
data = vector<double>(data10 ,data10 +16);
error = vector<double>(error10,error10+16);
_mhi= new_ptr(Histogram(bins,data,error));
// M low
double vals11[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.080, 0.100, 0.120};
double data11[]={23.414 ,39.12 ,18.080 , 7.704 , 3.922 ,
2.128 , 1.013 , 0.3748 , 0.1412 };
double error11stat[]={0.074 ,0.11 ,0.081 ,0.052 ,0.036 ,
0.026 ,0.013 ,0.0079 ,0.0050};
double error11syst[]={1.595 ,2.65 ,1.215 ,0.514 ,0.260 ,
0.140 ,0.066 ,0.0241,0.0089};
double error11[9];
for(unsigned int ix=0;ix<9;++ix){error11[ix]=sqrt(sqr(error11stat[ix])+
sqr(error11syst[ix]));}
bins = vector<double>(vals11 ,vals11 +10);
data = vector<double>(data11 ,data11 + 9);
error = vector<double>(error11,error11+ 9);
_mlo= new_ptr(Histogram(bins,data,error));
// M diff
double vals12[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.060, 0.080, 0.120, 0.160, 0.200,
0.250, 0.300, 0.350, 0.400};
double data12[]={35.393 ,20.745 ,11.426 , 7.170 , 4.344 ,
2.605 , 1.4238 , 0.7061 , 0.3831 , 0.1836 ,
0.0579 , 0.0075 , 0.0003};
double error12stat[]={0.092 ,0.071 ,0.052 ,0.041 ,0.023 ,
0.017 ,0.0092 ,0.0064 ,0.0046 ,0.0028 ,
0.0015 ,0.0006 ,0.0002};
double error12syst[]={0.354 ,0.207 ,0.114 ,0.072 ,0.043 ,
0.026 ,0.0142,0.0071,0.0044,0.0032,
0.0018,0.0006,0.0001};
double error12[13];
for(unsigned int ix=0;ix<13;++ix){error12[ix]=sqrt(sqr(error12stat[ix])+
sqr(error12syst[ix]));}
bins = vector<double>(vals12 ,vals12 +14);
data = vector<double>(data12 ,data12 +13);
error = vector<double>(error12,error12+13);
_mdiff= new_ptr(Histogram(bins,data,error));
// Bmax
double vals13[] = {0.010, 0.020, 0.030, 0.040, 0.050,
0.060, 0.070, 0.080, 0.100, 0.120,
0.140, 0.170, 0.200, 0.240, 0.280,
0.320};
double data13[]={0.6707 , 7.538 ,14.690 ,13.942 ,11.298 ,
9.065 , 7.387 , 5.445 , 3.796 , 2.670 ,
1.756 , 1.0580 , 0.5288 , 0.1460 , 0.0029 };
double error13stat[]={0.0096 ,0.038 ,0.058 ,0.057 ,0.053 ,
0.048 ,0.043 ,0.026 ,0.022 ,0.018 ,
0.012 ,0.0092 ,0.0056 ,0.0028 ,0.0004};
double error13syst[]={0.1077,0.809 ,0.745 ,0.592 ,0.379 ,
0.266 ,0.222 ,0.176 ,0.127 ,0.087 ,
0.051 ,0.0218,0.0053,0.0071,0.0003};
double error13[15];
for(unsigned int ix=0;ix<15;++ix){error13[ix]=sqrt(sqr(error13stat[ix])+
sqr(error13syst[ix]));}
bins = vector<double>(vals13 ,vals13 +16);
data = vector<double>(data13 ,data13 +15);
error = vector<double>(error13,error13+15);
_bmax= new_ptr(Histogram(bins,data,error));
// Bmin
double vals14[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.080, 0.100, 0.120,
0.150, 0.180};
double data14[]={0.645 ,11.169 ,28.908 ,25.972 ,14.119 ,
7.500 , 3.405 , 1.320 , 0.5448 , 0.1916 ,
0.0366};
double error14stat[]={0.010 ,0.045 ,0.082 ,0.083 ,0.061 ,
0.044 ,0.021 ,0.013 ,0.0082 ,0.0040 ,
0.0017};
double error14syst[]={0.096 ,1.006 ,1.823 ,1.478 ,0.860 ,
0.494 ,0.233 ,0.089 ,0.0328,0.0104,
0.0034};
double error14[11];
for(unsigned int ix=0;ix<11;++ix){error14[ix]=sqrt(sqr(error14stat[ix])+
sqr(error14syst[ix]));}
bins = vector<double>(vals14 ,vals14 +12);
data = vector<double>(data14 ,data14 +11);
error = vector<double>(error14,error14+11);
_bmin= new_ptr(Histogram(bins,data,error));
// Bsum
double vals15[] = {0.020, 0.030, 0.040, 0.050, 0.060,
0.070, 0.080, 0.090, 0.100, 0.110,
0.130, 0.150, 0.170, 0.190, 0.210,
0.240, 0.270, 0.300, 0.330, 0.360};
double data15[]={0.2030 ,1.628 ,4.999 ,8.190 ,9.887 ,
9.883 ,9.007 ,7.746 ,6.714 ,5.393 ,
3.998 ,2.980 ,2.294 ,1.747 ,1.242 ,
0.8125 ,0.4974 ,0.2285 ,0.0732 };
double error15stat[]={0.0055 ,0.015 ,0.031 ,0.041 ,0.047 ,
0.049 ,0.047 ,0.044 ,0.041 ,0.026 ,
0.023 ,0.019 ,0.017 ,0.015 ,0.010 ,
0.0080 ,0.0062 ,0.0041 ,0.0024};
double error15syst[]={0.0383,0.183 ,0.463 ,0.644 ,0.661 ,
0.564 ,0.443 ,0.332 ,0.255 ,0.180 ,
0.125 ,0.098 ,0.085 ,0.075 ,0.063 ,
0.0469,0.0296,0.0119,0.0007};
double error15[19];
for(unsigned int ix=0;ix<19;++ix){error15[ix]=sqrt(sqr(error15stat[ix])+
sqr(error15syst[ix]));}
bins = vector<double>(vals15 ,vals15 +20);
data = vector<double>(data15 ,data15 +19);
error = vector<double>(error15,error15+19);
_bsum= new_ptr(Histogram(bins,data,error));
// Bdiff
double vals16[] = {0.000, 0.010, 0.020, 0.030, 0.040,
0.050, 0.060, 0.070, 0.080, 0.090,
0.100, 0.120, 0.140, 0.160, 0.180,
0.200, 0.240, 0.280};
double data16[]={26.630 ,18.684 ,12.343 , 8.819 , 6.688 ,
5.111 , 4.071 , 3.271 , 2.681 , 2.233 ,
1.647 , 1.111 , 0.7618 , 0.5138 , 0.3167 ,
0.1265 , 0.0117};
double error16stat[]={0.081 ,0.066 ,0.054 ,0.046 ,0.040 ,
0.035 ,0.031 ,0.028 ,0.025 ,0.023 ,
0.014 ,0.011 ,0.0095 ,0.0078 ,0.0062 ,
0.0026 ,0.0008};
double error16syst[]={0.459 ,0.292 ,0.186 ,0.134 ,0.106 ,
0.084 ,0.068 ,0.054 ,0.043 ,0.035 ,
0.026 ,0.019 ,0.0144,0.0119,0.0098,
0.0056,0.0008};
double error16[17];
for(unsigned int ix=0;ix<17;++ix){error16[ix]=sqrt(sqr(error16stat[ix])+
sqr(error16syst[ix]));}
bins = vector<double>(vals16 ,vals16 +18);
data = vector<double>(data16 ,data16 +17);
error = vector<double>(error16,error16+17);
_bdiff= new_ptr(Histogram(bins,data,error));
}
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