diff --git a/buildmaster/filters/ATLASWRAP11.cc b/buildmaster/filters/ATLASWRAP11.cc new file mode 100644 index 0000000000..856a6ff66e --- /dev/null +++ b/buildmaster/filters/ATLASWRAP11.cc @@ -0,0 +1,82 @@ +/* + This file implements the W production subset of the ATLASWZRAP11CC data set. + This is required to separate CC DY from NC DY. + Implemented by ERN June 2023. +*/ + +#include "ATLASWRAP11CC.h" + +// Central selection +void ATLASWRAP11CCFilter::ReadData() +{ + + // Opening files + fstream f1; + + stringstream datafile(""); + datafile << dataPath() << "rawdata/ATLASWZRAP11CC/wzrap11.dat"; + + f1.open(datafile.str().c_str(), ios::in); + + if (f1.fail()) { + cerr << "Error opening data file " << datafile.str() << endl; + exit(-1); + } + + // Dummy string + std::string dummy; + + // Read the names of systematics + std::string *sysNames = new std::string[fNSys]; + sysNames[0] = "UNCORR"; + for (int i=0; i<5; i++) f1 >> dummy; + for (int i=0; i> sysNames[i]; + + const int nBins = 2; + const int ndataWZ[nBins] = {11,22}; // Data thresholds for W+ and W- + const double MWZ2[nBins]= {pow(MW,2.0), pow(MW,2.0)}; //Mass squared of W (+ and -) + + int low_bin = 0; + for (int b = 0; b < nBins; b++) + { + for (int i = low_bin; i < ndataWZ[b]; i++) + { + double etamin, etamax; + + // Kinematics + f1 >> dummy; f1 >> etamin; f1 >> etamax; + fKin1[i] = etamin + (etamax - etamin)/2.0; + fKin2[i] = MWZ2[b]; + fKin3[i] = 7000; + + // Observable + f1 >> fData[i]; + fData[i] *= 1000; // pb -> fb + + // Statistical errors - percentage with respect the observable + f1 >> fStat[i]; + fStat[i] *= fData[i]*1e-2; + + // Correlated systematic errors + for (int l = 0; l < fNSys; l++) + { + f1 >> fSys[i][l].mult; + fSys[i][l].type = MULT; + fSys[i][l].name = sysNames[l]; + } + + // Additive errors + for (int l = 0; l < fNSys; l++) + fSys[i][l].add = fSys[i][l].mult*fData[i]*1e-2; + } + // Update lowest point in bin + low_bin = ndataWZ[b]; + } + + delete[] sysNames; + + f1.close(); +} + + diff --git a/buildmaster/filters/ATLASWRAP36PB.cc b/buildmaster/filters/ATLASWRAP36PB.cc new file mode 100644 index 0000000000..98c337d7c1 --- /dev/null +++ b/buildmaster/filters/ATLASWRAP36PB.cc @@ -0,0 +1,130 @@ +/* + This file implements the W production subset of the ATLASWZRAP36PB data set. + This is required to separate CC DY from NC DY. + Implemented by ERN June 2023. +*/ + +#include "ATLASWRAP36PB.h" + +void ATLASWRAP36PBFilter::ReadData() +{ + // Opening files + fstream fWZ[2]; + + stringstream datafile(""); + datafile << dataPath() << "rawdata/ATLASWZRAP36PB/ATLAS-36pb-Wplrap.data"; + fWZ[0].open(datafile.str().c_str(), ios::in); + + if (fWZ[0].fail()) { + cerr << "Error opening data file " << datafile.str() << endl; + exit(-1); + } + + stringstream datafile2(""); + datafile2 << dataPath() << "rawdata/ATLASWZRAP36PB/ATLAS-36pb-Wmlrap.data"; + fWZ[1].open(datafile2.str().c_str(), ios::in); + + if (fWZ[1].fail()) { + cerr << "Error opening data file " << datafile2.str() << endl; + exit(-1); + } + + // Starting filter + const double lcorr = 1.0187; // correction factor due to luminosity upgrade + const int ndataWZ[2] = {11,11}; //Number of data for W+, W- + const double convfac = lcorr*1000.; // Must multiply from pb to fb + const double MWZ2[2] = {pow(MW,2.0), pow(MW,2.0)}; //Mass squared of W (+ and -) and Z + + string line; + int idat = 0; + double etamin,etamax,tmp; + + for (int iWZ = 0; iWZ < 2; iWZ++) + { + // rapidity + getline(fWZ[iWZ],line); + istringstream lstream(line); + for (int i = 0; i < ndataWZ[iWZ]; i++) + { + lstream >> etamin >> etamax; + fKin1[idat+i] = etamin + (etamax-etamin)*0.5; + } + + // M_W + for (int i = 0; i < ndataWZ[iWZ]; i++) + fKin2[idat+i] = MWZ2[iWZ]; + + // sqrt(s) + for (int i = 0; i < ndataWZ[iWZ]; i++) + fKin3[idat+i] = 7000; + + // obs + getline(fWZ[iWZ],line); + istringstream lstream2(line); + for (int i = 0; i < ndataWZ[iWZ]; i++) + { + lstream2 >> fData[idat+i]; + fData[idat+i] *= convfac; + } + + // stat (%, converted later) + getline(fWZ[iWZ],line); + istringstream lstream3(line); + for (int i = 0; i < ndataWZ[iWZ]; i++) + lstream3 >> fStat[idat+i]; + + // uncorrelated sys + getline(fWZ[iWZ],line); + istringstream lstream4(line); + for (int i = 0; i < ndataWZ[iWZ]; i++) + { + lstream4 >> fSys[idat+i][0].mult; + fSys[idat+i][0].name = "UNCORR"; + } + + // total correlated sys (unused) + getline(fWZ[iWZ],line); + + // total uncertainty (unused) + getline(fWZ[iWZ],line); + + // correlated systematics + for (int isys = 2; isys < fNSys; isys++) //2 to skip uncorr and lumi + { + getline(fWZ[iWZ],line); + istringstream lstream(line); + lstream >> tmp; + for (int i = 0; i < ndataWZ[iWZ]; i++) + { + lstream >> fSys[idat+i][isys].mult; + ostringstream sysname; + sysname << "ATLASWZRAP36PB_" << isys-2; + fSys[idat+1][isys].name = sysname.str(); + } + } + + // luminosity: 3.4% + for (int i = 0; i < ndataWZ[iWZ]; i++) + { + fSys[idat+i][1].mult = 3.5; + fSys[idat+i][1].name = "ATLASLUMI10"; + } + + idat+=ndataWZ[iWZ]; + } + + // Convert additive uncertainties to absolute form + for (int i = 0; i < fNData; i++) + { + fStat[i] *= fData[i]*1e-2; + for(int l = 0; l < fNSys; l++) + { + fSys[i][l].type = MULT; // All systematics multiplicative + fSys[i][l].add = fSys[i][l].mult*fData[i]*1e-2; + } + } + + + fWZ[0].close(); + fWZ[1].close(); +} diff --git a/buildmaster/filters/ATLASZRAP11.cc b/buildmaster/filters/ATLASZRAP11.cc new file mode 100644 index 0000000000..4cc4a6e8c5 --- /dev/null +++ b/buildmaster/filters/ATLASZRAP11.cc @@ -0,0 +1,84 @@ +/* + This file implements the Z production subset of the ATLASWZRAP11CC data set. + This is required to separate NC DY from CC DY. + Implemented by ERN June 2023. +*/ + +#include "ATLASZRAP11CC.h" + +// Central selection +void ATLASZRAP11CCFilter::ReadData() +{ + + // Opening files + fstream f1; + + stringstream datafile(""); + datafile << dataPath() << "rawdata/ATLASWZRAP11CC/wzrap11.dat"; + + f1.open(datafile.str().c_str(), ios::in); + + if (f1.fail()) { + cerr << "Error opening data file " << datafile.str() << endl; + exit(-1); + } + + // Dummy string + std::string dummy; + + // Read the names of systematics + std::string *sysNames = new std::string[fNSys]; + sysNames[0] = "UNCORR"; + for (int i=0; i<5; i++) f1 >> dummy; + for (int i=0; i> sysNames[i]; + + const int nBins = 3; + const int ndataWZ[nBins] = {6,18,24}; // Data thresholds for (Z_low, Z_peak, Z_high) respectively + const double MWZ2[nBins]= {pow(56.0,2.0), pow(91.0,2.0), pow(133.0,2.0)}; //Mass squared of (Z_low, Z_peak, Z_high) + + string line; + for(int iline=0; iline<23; iline++) + getline(f1,line); + + int low_bin = 0; + for (int b = 0; b < nBins; b++) + { + for (int i = low_bin; i < ndataWZ[b]; i++) + { + double etamin, etamax; + + // Kinematics + f1 >> dummy; f1 >> etamin; f1 >> etamax; + fKin1[i] = etamin + (etamax - etamin)/2.0; + fKin2[i] = MWZ2[b]; + fKin3[i] = 7000; + + // Observable + f1 >> fData[i]; + fData[i] *= 1000; // pb -> fb + + // Statistical errors - percentage with respect the observable + f1 >> fStat[i]; + fStat[i] *= fData[i]*1e-2; + + // Correlated systematic errors + for (int l = 0; l < fNSys; l++) + { + f1 >> fSys[i][l].mult; + fSys[i][l].type = MULT; + fSys[i][l].name = sysNames[l]; + } + + // Additive errors + for (int l = 0; l < fNSys; l++) + fSys[i][l].add = fSys[i][l].mult*fData[i]*1e-2; + } + // Update lowest point in bin + low_bin = ndataWZ[b]; + } + + delete[] sysNames; + + f1.close(); +} diff --git a/buildmaster/filters/ATLASZRAP36PB.cc b/buildmaster/filters/ATLASZRAP36PB.cc new file mode 100644 index 0000000000..e8a75edc82 --- /dev/null +++ b/buildmaster/filters/ATLASZRAP36PB.cc @@ -0,0 +1,113 @@ +/* + This file implements the Z production subset of the ATLASWZRAP36PB data set. + This is required to separate NC DY from CC DY. + Implemented by ERN June 2023. +*/ + +#include "ATLASZRAP36PB.h" + +void ATLASZRAP36PBFilter::ReadData() +{ + // Opening files + fstream fWZ; + + stringstream datafile(""); + datafile << dataPath() << "rawdata/ATLASWZRAP36PB/ATLAS-36pb-Zrap.data"; + fWZ.open(datafile.str().c_str(), ios::in); + + if (fWZ.fail()) { + cerr << "Error opening data file " << datafile.str() << endl; + exit(-1); + } + + // Starting filter + const double lcorr = 1.0187; // correction factor due to luminosity upgrade + const int ndataWZ = 8; //Number of data for W+, W- and Z respectively + const double convfac = lcorr*1000.; // Must multiply from pb to fb + const double MWZ2 = pow(MZ,2.0); //Mass squared of W (+ and -) and Z + + string line; + double etamin,etamax,tmp; + + // rapidity + getline(fWZ,line); + istringstream lstream(line); + for (int i = 0; i < ndataWZ; i++) + { + lstream >> etamin >> etamax; + fKin1[i] = etamin + (etamax-etamin)*0.5; + } + + //Z + for (int i = 0; i < ndataWZ; i++) + fKin2[i] = MWZ2; + + // sqrt(s) + for (int i = 0; i < ndataWZ; i++) + fKin3[i] = 7000; + + // obs + getline(fWZ,line); + istringstream lstream2(line); + for (int i = 0; i < ndataWZ; i++) + { + lstream2 >> fData[i]; + fData[i] *= convfac; + } + + // stat (%, converted later) + getline(fWZ,line); + istringstream lstream3(line); + for (int i = 0; i < ndataWZ; i++) + lstream3 >> fStat[i]; + + // uncorrelated sys + getline(fWZ,line); + istringstream lstream4(line); + for (int i = 0; i < ndataWZ; i++) + { + lstream4 >> fSys[i][0].mult; + fSys[i][0].name = "UNCORR"; + } + + // total correlated sys (unused) + getline(fWZ,line); + + // total uncertainty (unused) + getline(fWZ,line); + + // correlated systematics + for (int isys = 2; isys < fNSys; isys++) //2 to skip uncorr and lumi + { + getline(fWZ,line); + istringstream lstream(line); + lstream >> tmp; + for (int i = 0; i < ndataWZ; i++) + { + lstream >> fSys[i][isys].mult; + ostringstream sysname; + sysname << "ATLASWZRAP36PB_" << isys-2; + fSys[i][isys].name = sysname.str(); + } + } + + // luminosity: 3.4% + for (int i = 0; i < ndataWZ; i++) + { + fSys[i][1].mult = 3.5; + fSys[i][1].name = "ATLASLUMI10"; + } + + // Convert additive uncertainties to absolute form + for (int i = 0; i < fNData; i++) + { + fStat[i] *= fData[i]*1e-2; + for(int l = 0; l < fNSys; l++) + { + fSys[i][l].type = MULT; // All systematics multiplicative + fSys[i][l].add = fSys[i][l].mult*fData[i]*1e-2; + } + } + + fWZ; +} diff --git a/buildmaster/filters/ATLAS_WZ_TOT_13TEV.cc b/buildmaster/filters/ATLAS_WZ_TOT_13TEV.cc index 4dba14955c..72708e7514 100644 --- a/buildmaster/filters/ATLAS_WZ_TOT_13TEV.cc +++ b/buildmaster/filters/ATLAS_WZ_TOT_13TEV.cc @@ -61,7 +61,7 @@ void ATLAS_WZ_TOT_13TEVFilter::ReadData() sys[i] *= 1e6; lumi[i] *= 1e6; } - + //Correlation coefficients for(int i=0; i<25; i++) { @@ -114,7 +114,7 @@ void ATLAS_WZ_TOT_13TEVFilter::ReadData() { throw runtime_error("Couldn't generate artificial systematics for " + fSetName); } - + for(int i=0; i sys(data_tot); + vector lumi(fNData); + + for(int i=0; i> sdum + >> fData[i] + >> fStat[i] + >> sys[i] + >> lumi[i] + >> fKin1[i] + >> fKin2[i] + >> fKin3[i]; + //conversion to femtobarns + fData[i] *= 1e6; + fStat[i] *= 1e6; + sys[i] *= 1e6; + lumi[i] *= 1e6; + } + + for(int i=0; i<1; i++) + { + string sdum; + double ddum; + + getline(f1,line); + istringstream lstream(line); + lstream >> sdum + >> ddum + >> ddum + >> sys[i+2] + >> ddum + >> ddum + >> ddum + >> ddum; + sys[i+2] *= 1e6; + } + + //Correlation coefficients + for(int i=0; i<25; i++) + { + getline(f2,line); + } + + double** covmat = new double*[data_tot]; + for(int i=0; i corrcoeff(3); + + for(int k=0; k<3; k++) + { + getline(f2,line); + istringstream lstream(line); + lstream >> ddum >> comma >> ddum >> comma >> corrcoeff[k]; + } + + covmat[0][1] = corrcoeff[0]; + covmat[1][0] = covmat[0][1]; + covmat[0][2] = corrcoeff[1]; + covmat[2][0] = covmat[0][2]; + covmat[1][2] = corrcoeff[2]; + covmat[2][1] = covmat[1][2]; + + for(int i=0; i sys(data_tot); + vector lumi(fNData); + + for(int i=0; i<2; i++) + { + string sdum; + double ddum; + + getline(f1,line); + istringstream lstream(line); + lstream >> sdum + >> ddum + >> ddum + >> sys[i] + >> ddum + >> ddum + >> ddum + >> ddum; + sys[i] *= 1e6; + } + + for(int i=0; i> sdum + >> fData[i] + >> fStat[i] + >> sys[i+2] + >> lumi[i] + >> fKin1[i] + >> fKin2[i] + >> fKin3[i]; + //conversion to femtobarns + fData[i] *= 1e6; + fStat[i] *= 1e6; + sys[i+2] *= 1e6; + lumi[i] *= 1e6; + } + + //Correlation coefficients + for(int i=0; i<25; i++) + { + getline(f2,line); + } + + double** covmat = new double*[data_tot]; + for(int i=0; i corrcoeff(data_tot); + + for(int k=0; k> ddum >> comma >> ddum >> comma >> corrcoeff[k]; + } + + covmat[0][1] = corrcoeff[0]; + covmat[1][0] = covmat[0][1]; + covmat[0][2] = corrcoeff[1]; + covmat[2][0] = covmat[0][2]; + covmat[1][2] = corrcoeff[2]; + covmat[2][1] = covmat[1][2]; + + for(int i=0; i> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_z[i]; + //Chck if central value is needed or not + totsys_z[i] *= pb2fb; + } + + // W+ + getline(fWp,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWp,line); + istringstream lstream(line); + + lstream >> etaavg >> etamin >> etamax; + fKin1[idat+i] = etaavg; // eta + fKin2[idat+i] = MW2; // W mass squared + fKin3[idat+i] = s; // sqrt(s) + + lstream >> fData[idat+i]; + fData[idat+i] *= pb2fb; + lstream >> fStat[idat+i]; + fStat[idat+i] *= pb2fb; + lstream >> totsys_w[idat+i]; + totsys_w[idat+i] *= pb2fb; + + lstream >> fSys[idat+i][ndata_tot].add; // Beam uncertainty + fSys[idat+i][ndata_tot].add *= pb2fb; + fSys[idat+i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot].type = MULT; + fSys[idat+i][ndata_tot].name = "LHCBBEAM7TEV"; + + lstream >> fSys[idat+i][ndata_tot+1].add; // Lumi uncertainty + fSys[idat+i][ndata_tot+1].add *= pb2fb; + fSys[idat+i][ndata_tot+1].mult = fSys[idat+i][ndata_tot+1].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot+1].type = MULT; + fSys[idat+i][ndata_tot+1].name = "LHCBLUMI7TEV"; + } + idat+=ndata_wp; + + // W- + getline(fWm,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWm,line); + istringstream lstream(line); + + lstream >> etaavg >> etamin >> etamax; + fKin1[idat+i] = etaavg; // eta + fKin2[idat+i] = MW2; // W mass squared + fKin3[idat+i] = s; // sqrt(s) + + lstream >> fData[idat+i]; + fData[idat+i] *= pb2fb; + lstream >> fStat[idat+i]; + fStat[idat+i] *= pb2fb; + lstream >> totsys_w[idat+i]; + totsys_w[idat+i] *= pb2fb; + + lstream >> fSys[idat+i][ndata_tot].add; // Beam uncertainty + fSys[idat+i][ndata_tot].add *= pb2fb; + fSys[idat+i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot].type = MULT; + fSys[idat+i][ndata_tot].name = "LHCBBEAM7TEV"; + + lstream >> fSys[idat+i][ndata_tot+1].add; // Lumi uncertainty + fSys[idat+i][ndata_tot+1].add *= pb2fb; + fSys[idat+i][ndata_tot+1].mult = fSys[idat+i][ndata_tot+1].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot+1].type = MULT; + fSys[idat+i][ndata_tot+1].name = "LHCBLUMI7TEV"; + } + idat+=ndata_wm; + + for(int i=0; i> inmat[j][i]; + } + } + for (int i = 0; i < ndata_tot; i++) { + for (int j = i+1; j < ndata_tot; j++) { + inmat[j][i] = inmat[i][j]; // symmetrize + } + } + + // Multiply by total systematic uncertainty + double** covmat = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + { + covmat[i] = new double[ndata_tot]; + for(int j = 0; j < ndata_tot; j++) + { + covmat[i][j]=inmat[i][j]*totsys[i]*totsys[j]; + } + } + + // Generate artificial systematics + double** syscor = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + syscor[i] = new double[ndata_tot]; + + if(!genArtSys(ndata_tot,covmat,syscor)) + { + cerr << " in " << fSetName << endl; + exit(-1); + } + + for (int i = 0; i < fNData; i++) + for (int l = 0; l < fNSys-2; l++) + { + fSys[i][l].add = syscor[i+ndata_z][l]; + fSys[i][l].mult = fSys[i][l].add/fData[i]*1e2; + fSys[i][l].type = MULT; + ostringstream sysname; + sysname << "LHCBWZMU7TEV_" << l; + fSys[i][l].name = sysname.str(); + } + + for(int i = 0; i < ndata_tot; i++) + { + delete[] syscor[i]; + delete[] covmat[i]; + } + delete[] syscor; + delete[] covmat; + + fZ.close(); + fWp.close(); + fWm.close(); + fCorr.close(); +} diff --git a/buildmaster/filters/LHCBWMU8TEV.cc b/buildmaster/filters/LHCBWMU8TEV.cc new file mode 100644 index 0000000000..f58603c72d --- /dev/null +++ b/buildmaster/filters/LHCBWMU8TEV.cc @@ -0,0 +1,209 @@ +/* + This file implements the W production subset of the LHCBWZMU8TEV data set. + This is required to separate CC DY from NC DY. + Implemented by ERN June 2023. +*/ + +#include "LHCBWMU8TEV.h" + +void LHCBWMU8TEVFilter::ReadData() +{ + // Opening files + fstream fZ, fWp, fWm, fCorr; + + stringstream DataFileZ(""); + DataFileZ << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_zrap.data"; + fZ.open(DataFileZ.str().c_str(), ios::in); + + if (fZ.fail()) { + cerr << "Error opening data file " << DataFileZ.str() << endl; + exit(-1); + } + + stringstream DataFileWp(""); + DataFileWp << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_wplrap.data"; + fWp.open(DataFileWp.str().c_str(), ios::in); + + if (fWp.fail()) { + cerr << "Error opening data file " << DataFileWp.str() << endl; + exit(-1); + } + + stringstream DataFileWm(""); + DataFileWm << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_wmlrap.data"; + fWm.open(DataFileWm.str().c_str(), ios::in); + + if (fWm.fail()) { + cerr << "Error opening data file " << DataFileWm.str() << endl; + } + + stringstream DataFileCorr(""); + DataFileCorr << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_corrmat.data"; + fCorr.open(DataFileCorr.str().c_str(), ios::in); + + if (fCorr.fail()) { + cerr << "Error opening data file " << DataFileCorr.str() << endl; + exit(-1); + } + + // Starting filter + const int ndata_z = 18; + const int ndata_wp = 8; + const int ndata_wm = 8; + int ndata_tot = ndata_z + ndata_wp + ndata_wm; + const double pb2fb = 1000.; // Must multiply from pb to fb + double MW2 = pow(MW,2.0); + double MZ2 = pow(MZ,2.0); + double s = 8000; + string line; + + double totsys_w[ndata_wp+ndata_wp]; + double totsys_z[ndata_z]; + double totsys[ndata_tot]; + double inmat[ndata_tot][ndata_tot]; + double etaavg, etamin, etamax; + int idat = 0; + + double ddum; + + // Z + getline(fZ,line); + for (int i = 0; i < ndata_z; i++) + { + getline(fZ,line); + istringstream lstream(line); + + lstream >> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_z[i]; + //Chck if central value is needed or not + totsys_z[i] *= pb2fb; + } + + // W+ + getline(fWp,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWp,line); + istringstream lstream(line); + + lstream >> etaavg >> etamin >> etamax; + fKin1[idat+i] = etaavg; // eta + fKin2[idat+i] = MW2; // W mass squared + fKin3[idat+i] = s; // sqrt(s) + + lstream >> fData[idat+i]; + fData[idat+i] *= pb2fb; + lstream >> fStat[idat+i]; + fStat[idat+i] *= pb2fb; + lstream >> totsys_w[idat+i]; + totsys_w[idat+i] *= pb2fb; + + lstream >> fSys[idat+i][ndata_tot].add; // Beam uncertainty + fSys[idat+i][ndata_tot].add *= pb2fb; + fSys[idat+i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot].type = MULT; + fSys[idat+i][ndata_tot].name = "LHCBBEAM8TEV"; + + lstream >> fSys[idat+i][ndata_tot+1].add; // Lumi uncertainty + fSys[idat+i][ndata_tot+1].add *= pb2fb; + fSys[idat+i][ndata_tot+1].mult = fSys[idat+i][ndata_tot+1].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot+1].type = MULT; + fSys[idat+i][ndata_tot+1].name = "LHCBLUMI8TEV"; + } + idat+=ndata_wp; + + // W- + getline(fWm,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWm,line); + istringstream lstream(line); + + lstream >> etaavg >> etamin >> etamax; + fKin1[idat+i] = etaavg; // eta + fKin2[idat+i] = MW2; // W mass squared + fKin3[idat+i] = s; // sqrt(s) + + lstream >> fData[idat+i]; + fData[idat+i] *= pb2fb; + lstream >> fStat[idat+i]; + fStat[idat+i] *= pb2fb; + lstream >> totsys_w[idat+i]; + totsys_w[idat+i] *= pb2fb; + + lstream >> fSys[idat+i][ndata_tot].add; // Beam uncertainty + fSys[idat+i][ndata_tot].add *= pb2fb; + fSys[idat+i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot].type = MULT; + fSys[idat+i][ndata_tot].name = "LHCBBEAM8TEV"; + + lstream >> fSys[idat+i][ndata_tot+1].add; // Lumi uncertainty + fSys[idat+i][ndata_tot+1].add *= pb2fb; + fSys[idat+i][ndata_tot+1].mult = fSys[idat+i][ndata_tot+1].add/fData[idat+i]*1e2; + fSys[idat+i][ndata_tot+1].type = MULT; + fSys[idat+i][ndata_tot+1].name = "LHCBLUMI8TEV"; + } + idat+=ndata_wm; + + for(int i=0; i> inmat[j][i]; + } + } + for (int i = 0; i < ndata_tot; i++) { + for (int j = i+1; j < ndata_tot; j++) { + inmat[j][i] = inmat[i][j]; // symmetrize + } + } + + // Multiply by total systematic uncertainty + double** covmat = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + { + covmat[i] = new double[ndata_tot]; + for(int j = 0; j < ndata_tot; j++) + { + covmat[i][j]=inmat[i][j]*totsys[i]*totsys[j]; + } + } + + // Generate artificial systematics + double** syscor = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + syscor[i] = new double[ndata_tot]; + + if(!genArtSys(ndata_tot,covmat,syscor)) + { + cerr << " in " << fSetName << endl; + exit(-1); + } + + for (int i = 0; i < fNData; i++) + for (int l = 0; l < fNSys-2; l++) + { + fSys[i][l].add = syscor[i+ndata_z][l]; + fSys[i][l].mult = fSys[i][l].add/fData[i]*1e2; + fSys[i][l].type = MULT; + ostringstream sysname; + sysname << "LHCBWZMU8TEV_" << l; + fSys[i][l].name = sysname.str(); + } + + for(int i = 0; i < ndata_tot; i++) + { + delete[] syscor[i]; + delete[] covmat[i]; + } + delete[] syscor; + delete[] covmat; + + fZ.close(); + fWp.close(); + fWm.close(); + fCorr.close(); +} diff --git a/buildmaster/filters/LHCBWZMU7TEV.cc b/buildmaster/filters/LHCBWZMU7TEV.cc index ddc18e2f8f..27694f1836 100644 --- a/buildmaster/filters/LHCBWZMU7TEV.cc +++ b/buildmaster/filters/LHCBWZMU7TEV.cc @@ -181,6 +181,11 @@ void LHCBWZMU7TEVFilter::ReadData() } idat+=ndata_wm; + for(int i=0; i> etaavg >> etamin >> etamax; + fKin1[i] = etaavg; // eta + fKin2[i] = MZ2; // Z mass squared + fKin3[i] = s; // sqrt(s) + + lstream >> fData[i]; + fData[i] *= pb2fb; + lstream >> fStat[i]; + fStat[i] *= pb2fb; + lstream >> totsys_z[i]; + totsys_z[i] *= pb2fb; + + lstream >> fSys[i][ndata_tot].add; // Beam uncertainty + fSys[i][ndata_tot].add *= pb2fb; + fSys[i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[i]*1e2; + fSys[i][ndata_tot].type = MULT; + fSys[i][ndata_tot].name = "LHCBBEAM7TEV"; + + lstream >> fSys[i][ndata_tot+1].add; // Lumi uncertainty + fSys[i][ndata_tot+1].add *= pb2fb; + fSys[i][ndata_tot+1].mult = fSys[i][ndata_tot+1].add/fData[i]*1e2; + fSys[i][ndata_tot+1].type = MULT; + fSys[i][ndata_tot+1].name = "LHCBLUMI7TEV"; + } + + // W+ + getline(fWp,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWp,line); + istringstream lstream(line); + + lstream >> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_w[i+idat]; + //Chck if central value is needed or not + totsys_w[i+idat] *= pb2fb; + } + idat+=ndata_wp; + + // W- + getline(fWm,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWm,line); + istringstream lstream(line); + + lstream >> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_w[i+idat]; + //Chck if central value is needed or not + totsys_w[i+idat] *= pb2fb; + } + idat+=ndata_wm; + + for(int i=0; i> inmat[j][i]; + } + } + for (int i = 0; i < ndata_tot; i++) { + for (int j = i+1; j < ndata_tot; j++) { + inmat[j][i] = inmat[i][j]; // symmetrize + } + } + + // Multiply by total systematic uncertainty + double** covmat = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + { + covmat[i] = new double[ndata_tot]; + for(int j = 0; j < ndata_tot; j++) + { + covmat[i][j]=inmat[i][j]*totsys[i]*totsys[j]; + } + } + + // Generate artificial systematics + double** syscor = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + syscor[i] = new double[ndata_tot]; + + if(!genArtSys(ndata_tot,covmat,syscor)) + { + cerr << " in " << fSetName << endl; + exit(-1); + } + + for (int i = 0; i < fNData; i++) + for (int l = 0; l < fNSys-2; l++) + { + fSys[i][l].add = syscor[i][l]; + fSys[i][l].mult = fSys[i][l].add/fData[i]*1e2; + fSys[i][l].type = MULT; + ostringstream sysname; + sysname << "LHCBWZMU7TEV_" << l; + fSys[i][l].name = sysname.str(); + } + + for(int i = 0; i < ndata_tot; i++) + { + delete[] syscor[i]; + delete[] covmat[i]; + } + delete[] syscor; + delete[] covmat; + + fZ.close(); + fWp.close(); + fWm.close(); + fCorr.close(); +} diff --git a/buildmaster/filters/LHCBZMU8TEV.cc b/buildmaster/filters/LHCBZMU8TEV.cc new file mode 100644 index 0000000000..e7be03c7a8 --- /dev/null +++ b/buildmaster/filters/LHCBZMU8TEV.cc @@ -0,0 +1,189 @@ +/* + This file implements the W production subset of the LHCBWZMU8TEV data set. + This is required to separate NC DY from CC DY. + Implemented by ERN June 2023. +*/ + +#include "LHCBZMU8TEV.h" + +void LHCBZMU8TEVFilter::ReadData() +{ + // Opening files + fstream fZ, fWp, fWm, fCorr; + + stringstream DataFileZ(""); + DataFileZ << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_zrap.data"; + fZ.open(DataFileZ.str().c_str(), ios::in); + + if (fZ.fail()) { + cerr << "Error opening data file " << DataFileZ.str() << endl; + exit(-1); + } + + stringstream DataFileWp(""); + DataFileWp << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_wplrap.data"; + fWp.open(DataFileWp.str().c_str(), ios::in); + + if (fWp.fail()) { + cerr << "Error opening data file " << DataFileWp.str() << endl; + exit(-1); + } + + stringstream DataFileWm(""); + DataFileWm << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_wmlrap.data"; + fWm.open(DataFileWm.str().c_str(), ios::in); + + if (fWm.fail()) { + cerr << "Error opening data file " << DataFileWm.str() << endl; + } + + stringstream DataFileCorr(""); + DataFileCorr << dataPath() << "rawdata/LHCBWZMU8TEV/LHCBWZMU8TEV_corrmat.data"; + fCorr.open(DataFileCorr.str().c_str(), ios::in); + + if (fCorr.fail()) { + cerr << "Error opening data file " << DataFileCorr.str() << endl; + exit(-1); + } + + // Starting filter + const int ndata_z = 18; + const int ndata_wp = 8; + const int ndata_wm = 8; + int ndata_tot = ndata_z + ndata_wp + ndata_wm; + const double pb2fb = 1000.; // Must multiply from pb to fb + double MW2 = pow(MW,2.0); + double MZ2 = pow(MZ,2.0); + double s = 8000; + string line; + + double totsys_w[ndata_wp+ndata_wp]; + double totsys_z[ndata_z]; + double totsys[ndata_tot]; + double inmat[ndata_tot][ndata_tot]; + double etaavg, etamin, etamax; + int idat = 0; + + double ddum; + + // Z + getline(fZ,line); + for (int i = 0; i < ndata_z; i++) + { + getline(fZ,line); + istringstream lstream(line); + + lstream >> etaavg >> etamin >> etamax; + fKin1[i] = etaavg; // eta + fKin2[i] = MZ2; // Z mass squared + fKin3[i] = s; // sqrt(s) + + lstream >> fData[i]; + fData[i] *= pb2fb; + lstream >> fStat[i]; + fStat[i] *= pb2fb; + lstream >> totsys_z[i]; + totsys_z[i] *= pb2fb; + + lstream >> fSys[i][ndata_tot].add; // Beam uncertainty + fSys[i][ndata_tot].add *= pb2fb; + fSys[i][ndata_tot].mult = fSys[idat+i][ndata_tot].add/fData[i]*1e2; + fSys[i][ndata_tot].type = MULT; + fSys[i][ndata_tot].name = "LHCBBEAM8TEV"; + + lstream >> fSys[i][ndata_tot+1].add; // Lumi uncertainty + fSys[i][ndata_tot+1].add *= pb2fb; + fSys[i][ndata_tot+1].mult = fSys[i][ndata_tot+1].add/fData[i]*1e2; + fSys[i][ndata_tot+1].type = MULT; + fSys[i][ndata_tot+1].name = "LHCBLUMI8TEV"; + } + + // W+ + getline(fWp,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWp,line); + istringstream lstream(line); + + lstream >> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_w[i+idat]; + //Chck if central value is needed or not + totsys_w[i+idat] *= pb2fb; + } + idat+=ndata_wp; + + // W- + getline(fWm,line); + for (int i = 0; i < ndata_wp; i++) + { + getline(fWm,line); + istringstream lstream(line); + + lstream >> ddum >> ddum >> ddum >> ddum >> ddum >> totsys_w[i+idat]; + //Chck if central value is needed or not + totsys_w[i+idat] *= pb2fb; + } + idat+=ndata_wm; + + for(int i=0; i> inmat[j][i]; + } + } + for (int i = 0; i < ndata_tot; i++) { + for (int j = i+1; j < ndata_tot; j++) { + inmat[j][i] = inmat[i][j]; // symmetrize + } + } + + // Multiply by total systematic uncertainty + double** covmat = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + { + covmat[i] = new double[ndata_tot]; + for(int j = 0; j < ndata_tot; j++) + { + covmat[i][j]=inmat[i][j]*totsys[i]*totsys[j]; + } + } + + // Generate artificial systematics + double** syscor = new double*[ndata_tot]; + for(int i = 0; i < ndata_tot; i++) + syscor[i] = new double[ndata_tot]; + + if(!genArtSys(ndata_tot,covmat,syscor)) + { + cerr << " in " << fSetName << endl; + exit(-1); + } + + for (int i = 0; i < fNData; i++) + for (int l = 0; l < fNSys-2; l++) + { + fSys[i][l].add = syscor[i][l]; + fSys[i][l].mult = fSys[i][l].add/fData[i]*1e2; + fSys[i][l].type = MULT; + ostringstream sysname; + sysname << "LHCBWZMU8TEV_" << l; + fSys[i][l].name = sysname.str(); + } + + for(int i = 0; i < ndata_tot; i++) + { + delete[] syscor[i]; + delete[] covmat[i]; + } + delete[] syscor; + delete[] covmat; + + fZ.close(); + fWp.close(); + fWm.close(); + fCorr.close(); +} diff --git a/buildmaster/inc/ATLASWRAP11CC.h b/buildmaster/inc/ATLASWRAP11CC.h new file mode 100644 index 0000000000..2c0594a5c8 --- /dev/null +++ b/buildmaster/inc/ATLASWRAP11CC.h @@ -0,0 +1,24 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +// ********* Filters ************** + +class ATLASWRAP11CCFilter: public CommonData +{ +public: ATLASWRAP11CCFilter(): + CommonData("ATLASWRAP11CC") { ReadData(); } + +private: + void ReadData(); +}; + + diff --git a/buildmaster/inc/ATLASWRAP36PB.h b/buildmaster/inc/ATLASWRAP36PB.h new file mode 100644 index 0000000000..fb0fb994f9 --- /dev/null +++ b/buildmaster/inc/ATLASWRAP36PB.h @@ -0,0 +1,22 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +// ********* Filters ************** + +class ATLASWRAP36PBFilter: public CommonData +{ +public: ATLASWRAP36PBFilter(): + CommonData("ATLASWRAP36PB") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/ATLASZRAP11CC.h b/buildmaster/inc/ATLASZRAP11CC.h new file mode 100644 index 0000000000..f13e3f7055 --- /dev/null +++ b/buildmaster/inc/ATLASZRAP11CC.h @@ -0,0 +1,24 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +// ********* Filters ************** + +class ATLASZRAP11CCFilter: public CommonData +{ +public: ATLASZRAP11CCFilter(): + CommonData("ATLASZRAP11CC") { ReadData(); } + +private: + void ReadData(); +}; + + diff --git a/buildmaster/inc/ATLASZRAP36PB.h b/buildmaster/inc/ATLASZRAP36PB.h new file mode 100644 index 0000000000..22c935c452 --- /dev/null +++ b/buildmaster/inc/ATLASZRAP36PB.h @@ -0,0 +1,22 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +// ********* Filters ************** + +class ATLASZRAP36PBFilter: public CommonData +{ +public: ATLASZRAP36PBFilter(): + CommonData("ATLASZRAP36PB") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/ATLAS_W_TOT_13TEV.h b/buildmaster/inc/ATLAS_W_TOT_13TEV.h new file mode 100644 index 0000000000..f7c66a2a39 --- /dev/null +++ b/buildmaster/inc/ATLAS_W_TOT_13TEV.h @@ -0,0 +1,15 @@ +#pragma once +/* + * See the rawdata folder for details. +*/ + +#include "buildmaster_utils.h" + +class ATLAS_W_TOT_13TEVFilter: public CommonData +{ +public: ATLAS_W_TOT_13TEVFilter(): + CommonData("ATLAS_W_TOT_13TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/ATLAS_Z_TOT_13TEV.h b/buildmaster/inc/ATLAS_Z_TOT_13TEV.h new file mode 100644 index 0000000000..eb83bcb43f --- /dev/null +++ b/buildmaster/inc/ATLAS_Z_TOT_13TEV.h @@ -0,0 +1,15 @@ +#pragma once +/* + * See the rawdata folder for details. +*/ + +#include "buildmaster_utils.h" + +class ATLAS_Z_TOT_13TEVFilter: public CommonData +{ +public: ATLAS_Z_TOT_13TEVFilter(): + CommonData("ATLAS_Z_TOT_13TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/LHCBWMU7TEV.h b/buildmaster/inc/LHCBWMU7TEV.h new file mode 100644 index 0000000000..e9d0a2ae1a --- /dev/null +++ b/buildmaster/inc/LHCBWMU7TEV.h @@ -0,0 +1,20 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +class LHCBWMU7TEVFilter: public CommonData +{ +public: LHCBWMU7TEVFilter(): + CommonData("LHCBWMU7TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/LHCBWMU8TEV.h b/buildmaster/inc/LHCBWMU8TEV.h new file mode 100644 index 0000000000..01c4efbcce --- /dev/null +++ b/buildmaster/inc/LHCBWMU8TEV.h @@ -0,0 +1,20 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +class LHCBWMU8TEVFilter: public CommonData +{ +public: LHCBWMU8TEVFilter(): + CommonData("LHCBWMU8TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/LHCBZMU7TEV.h b/buildmaster/inc/LHCBZMU7TEV.h new file mode 100644 index 0000000000..de5c06956b --- /dev/null +++ b/buildmaster/inc/LHCBZMU7TEV.h @@ -0,0 +1,20 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +class LHCBZMU7TEVFilter: public CommonData +{ +public: LHCBZMU7TEVFilter(): + CommonData("LHCBZMU7TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/inc/LHCBZMU8TEV.h b/buildmaster/inc/LHCBZMU8TEV.h new file mode 100644 index 0000000000..46412123f0 --- /dev/null +++ b/buildmaster/inc/LHCBZMU8TEV.h @@ -0,0 +1,20 @@ +// $Id +// +// NNPDF++ 2013 +// +// Authors: Nathan Hartland, n.p.hartland@ed.ac.uk +// Stefano Carrazza, stefano.carrazza@mi.infn.it +// Luigi Del Debbio, luigi.del.debbio@ed.ac.uk + +#pragma once + +#include "buildmaster_utils.h" + +class LHCBZMU8TEVFilter: public CommonData +{ +public: LHCBZMU8TEVFilter(): + CommonData("LHCBZMU8TEV") { ReadData(); } + +private: + void ReadData(); +}; diff --git a/buildmaster/meta/ATLASWRAP11CC.yaml b/buildmaster/meta/ATLASWRAP11CC.yaml new file mode 100644 index 0000000000..e052a004ee --- /dev/null +++ b/buildmaster/meta/ATLASWRAP11CC.yaml @@ -0,0 +1,4 @@ +ndata: 22 +nsys: 133 +setname: "ATLASWRAP11CC" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/ATLASWRAP36PB.yaml b/buildmaster/meta/ATLASWRAP36PB.yaml new file mode 100644 index 0000000000..7506fed2e8 --- /dev/null +++ b/buildmaster/meta/ATLASWRAP36PB.yaml @@ -0,0 +1,4 @@ +ndata: 22 +nsys: 32 +setname: "ATLASWRAP36PB" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/ATLASZRAP11CC.yaml b/buildmaster/meta/ATLASZRAP11CC.yaml new file mode 100644 index 0000000000..3c0e8cbaa5 --- /dev/null +++ b/buildmaster/meta/ATLASZRAP11CC.yaml @@ -0,0 +1,4 @@ +ndata: 24 +nsys: 133 +setname: "ATLASZRAP11CC" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/ATLASZRAP36PB.yaml b/buildmaster/meta/ATLASZRAP36PB.yaml new file mode 100644 index 0000000000..e9008e9306 --- /dev/null +++ b/buildmaster/meta/ATLASZRAP36PB.yaml @@ -0,0 +1,4 @@ +ndata: 8 +nsys: 32 +setname: "ATLASZRAP36PB" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/ATLAS_W_TOT_13TEV.yaml b/buildmaster/meta/ATLAS_W_TOT_13TEV.yaml new file mode 100644 index 0000000000..d4c109ea38 --- /dev/null +++ b/buildmaster/meta/ATLAS_W_TOT_13TEV.yaml @@ -0,0 +1,4 @@ +ndata: 2 +nsys: 4 +setname: "ATLAS_W_TOT_13TEV" +proctype: "INC" diff --git a/buildmaster/meta/ATLAS_Z_TOT_13TEV.yaml b/buildmaster/meta/ATLAS_Z_TOT_13TEV.yaml new file mode 100644 index 0000000000..c27cb5b6d0 --- /dev/null +++ b/buildmaster/meta/ATLAS_Z_TOT_13TEV.yaml @@ -0,0 +1,4 @@ +ndata: 1 +nsys: 4 +setname: "ATLAS_Z_TOT_13TEV" +proctype: "INC" diff --git a/buildmaster/meta/LHCBWMU7TEV.yaml b/buildmaster/meta/LHCBWMU7TEV.yaml new file mode 100644 index 0000000000..021b1bdb3d --- /dev/null +++ b/buildmaster/meta/LHCBWMU7TEV.yaml @@ -0,0 +1,4 @@ +ndata: 16 +nsys: 35 +setname: "LHCBWMU7TEV" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/LHCBWMU8TEV.yaml b/buildmaster/meta/LHCBWMU8TEV.yaml new file mode 100644 index 0000000000..b82825f9af --- /dev/null +++ b/buildmaster/meta/LHCBWMU8TEV.yaml @@ -0,0 +1,4 @@ +ndata: 16 +nsys: 36 +setname: "LHCBWMU8TEV" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/LHCBZMU7TEV.yaml b/buildmaster/meta/LHCBZMU7TEV.yaml new file mode 100644 index 0000000000..20f7fb7412 --- /dev/null +++ b/buildmaster/meta/LHCBZMU7TEV.yaml @@ -0,0 +1,4 @@ +ndata: 17 +nsys: 35 +setname: "LHCBZMU7TEV" +proctype: "EWK_RAP" diff --git a/buildmaster/meta/LHCBZMU8TEV.yaml b/buildmaster/meta/LHCBZMU8TEV.yaml new file mode 100644 index 0000000000..88b261be00 --- /dev/null +++ b/buildmaster/meta/LHCBZMU8TEV.yaml @@ -0,0 +1,4 @@ +ndata: 18 +nsys: 36 +setname: "LHCBZMU8TEV" +proctype: "EWK_RAP" diff --git a/buildmaster/src/buildmaster.cc b/buildmaster/src/buildmaster.cc index 51cb38395d..c5f588a4aa 100644 --- a/buildmaster/src/buildmaster.cc +++ b/buildmaster/src/buildmaster.cc @@ -57,6 +57,12 @@ #include "H1F2B.h" #include "ATLASWZTOT13TEV81PB.h" #include "ATLAS_WZ_TOT_13TEV.h" +#include "ATLAS_W_TOT_13TEV.h" +#include "ATLAS_Z_TOT_13TEV.h" +#include "ATLASWRAP36PB.h" +#include "ATLASZRAP36PB.h" +#include "ATLASWRAP11CC.h" +#include "ATLASZRAP11CC.h" #include "ATLASZPT7TEV.h" #include "ATLASZPT8TEV.h" #include "ATLASTTBARTOT.h" @@ -115,6 +121,11 @@ #include "CMS_HMDY_13TEV.h" #include "ATLAS_DY_2D_8TEV_LOWMASS.h" #include "ATLAS_WMU_8TEV.h" +#include "LHCBWMU7TEV.h" +#include "LHCBZMU7TEV.h" +#include "LHCBWMU8TEV.h" +#include "LHCBZMU8TEV.h" + /** * \param argv the filename containing the configuration */ @@ -154,7 +165,11 @@ vector> InitCommonData() // ************************* ATLAS ****************************** target.emplace_back(new ATLASWZRAP36PBFilter()); + target.emplace_back(new ATLASWRAP36PBFilter()); + target.emplace_back(new ATLASZRAP36PBFilter()); target.emplace_back(new ATLASWZRAP11CCFilter()); + target.emplace_back(new ATLASWRAP11CCFilter()); + target.emplace_back(new ATLASZRAP11CCFilter()); target.emplace_back(new ATLASWZRAP11CFFilter()); target.emplace_back(new ATLASR04JETS36PBFilter()); target.emplace_back(new ATLASR06JETS36PBFilter()); @@ -166,6 +181,8 @@ vector> InitCommonData() target.emplace_back(new ATLASLOMASSDY11EXTFilter()); target.emplace_back(new ATLASWZTOT13TEV81PBFilter()); target.emplace_back(new ATLAS_WZ_TOT_13TEVFilter()); + target.emplace_back(new ATLAS_W_TOT_13TEVFilter()); + target.emplace_back(new ATLAS_Z_TOT_13TEVFilter()); // target.emplace_back(new ATLASZPT7TEVFilter()); target.emplace_back(new ATLAS_WCHARM_WP_DIFF_7TEVFilter()); @@ -329,7 +346,11 @@ vector> InitCommonData() target.emplace_back(new LHCBZEE2FBFilter()); target.emplace_back(new LHCBZEE2FB_40Filter()); target.emplace_back(new LHCBWZMU7TEVFilter()); + target.emplace_back(new LHCBWMU7TEVFilter()); + target.emplace_back(new LHCBZMU7TEVFilter()); target.emplace_back(new LHCBWZMU8TEVFilter()); + target.emplace_back(new LHCBWMU8TEVFilter()); + target.emplace_back(new LHCBZMU8TEVFilter()); target.emplace_back(new LHCB_WENU_8TEV_RFilter()); target.emplace_back(new LHCB_WENU_8TEV_AFilter()); target.emplace_back(new LHCB_Z_13TEV_DIMUONFilter()); diff --git a/conda-recipe/meta.yaml b/conda-recipe/meta.yaml index fb9edea8bf..d2c41ea803 100644 --- a/conda-recipe/meta.yaml +++ b/conda-recipe/meta.yaml @@ -51,7 +51,7 @@ requirements: - sphinxcontrib-bibtex - curio >=1.0 - pineappl >=0.5.8 - - eko >=0.13.4,<0.14 + - eko >=0.13.5,<0.14 - banana-hep >=0.6.8 - fiatlux diff --git a/doc/sphinx/source/n3fit/figures/plot_pdf.png b/doc/sphinx/source/n3fit/figures/plot_pdf.png new file mode 100644 index 0000000000..59d086a139 Binary files /dev/null and b/doc/sphinx/source/n3fit/figures/plot_pdf.png differ diff --git a/doc/sphinx/source/n3fit/methodology.rst b/doc/sphinx/source/n3fit/methodology.rst index 0eb3ed2362..8380d5526d 100644 --- a/doc/sphinx/source/n3fit/methodology.rst +++ b/doc/sphinx/source/n3fit/methodology.rst @@ -126,6 +126,56 @@ provide a faster convergence to the solution. .. important:: Parameters like the number of layers, nodes, activation functions are hyper-parameters that require tuning. + +To see the structure of the model, one can use Keras's ``plot_model`` function as illustrated in the script below. +See the `Keras documentation `_ for more details. + +.. code-block:: python + + from tensorflow.keras.utils import plot_model + from n3fit.model_gen import pdfNN_layer_generator + from validphys.api import API + + fit_info = API.fit(fit="NNPDF40_nnlo_as_01180_1000").as_input() + basis_info = fit_info["fitting"]["basis"] + + pdf_models = pdfNN_layer_generator( + nodes=[25, 20, 8], + activations=["tanh", "tanh", "linear"], + initializer_name="glorot_normal", + layer_type="dense", + flav_info=basis_info, + fitbasis="EVOL", + out=14, + seed=42, + dropout=0.0, + regularizer=None, + regularizer_args=None, + impose_sumrule="All", + scaler=None, + parallel_models=1, + ) + + pdf_model = pdf_models[0] + nn_model = pdf_model.get_layer("NN_0") + msr_model = pdf_model.get_layer("impose_msr") + models_to_plot = { + 'plot_pdf': pdf_model, + 'plot_nn': nn_model, + 'plot_msr': msr_model + } + + for name, model in models_to_plot.items(): + plot_model(model, to_file=f"./{name}.png", show_shapes=True) + + +This will produce for instance the plot of the PDF model below, and can also be used to plot the +neural network model, and the momentum sum rule model. + +.. image:: + figures/plot_pdf.png + + .. _preprocessing: Preprocessing diff --git a/doc/sphinx/source/tutorials/run-fit.md b/doc/sphinx/source/tutorials/run-fit.md index f0a1d10201..0a5c5bb2b8 100644 --- a/doc/sphinx/source/tutorials/run-fit.md +++ b/doc/sphinx/source/tutorials/run-fit.md @@ -122,15 +122,6 @@ following the points presented above you can proceed with a fit. downloaded automatically. Alternatively they can be obtained with the ``vp-get`` tool. - ```eval_rst - .. note:: - This step is not strictly necessary when producing a standard fit with - ``n3fit`` but it is required by :ref:`validphys ` - and it should therefore always be done. Note that :ref:`vp-upload ` - will fail unless this step has been followed. If necessary, this step can - be done after the fit has been run. - ``` - 2. The ``n3fit`` program takes a ``runcard.yml`` as input and a replica number, e.g. ```n3fit runcard.yml replica``` where ``replica`` goes from 1-n where n is the maximum number of desired replicas. Note that if you desire, for example, a 100 diff --git a/n3fit/runcards/examples/Basic_runcard_qed.yml b/n3fit/runcards/examples/Basic_runcard_qed.yml index 309f5901d5..9fd98ce1b1 100644 --- a/n3fit/runcards/examples/Basic_runcard_qed.yml +++ b/n3fit/runcards/examples/Basic_runcard_qed.yml @@ -95,7 +95,7 @@ datacuts: ############################################################ theory: - theoryid: 522 # database id + theoryid: 523 # database id ############################################################ trvlseed: 1551864071 @@ -169,3 +169,4 @@ fiatlux: luxset: NNPDF40_nnlo_as_01180 additional_errors: true # should be set to true only for the last iteration luxseed: 1234567890 + eps_base: 1e-2 diff --git a/n3fit/runcards/examples/developing_weights.h5 b/n3fit/runcards/examples/developing_weights.h5 index a337c5b6a4..542fca06f9 100644 Binary files a/n3fit/runcards/examples/developing_weights.h5 and b/n3fit/runcards/examples/developing_weights.h5 differ diff --git a/n3fit/src/evolven3fit_new/eko_utils.py b/n3fit/src/evolven3fit_new/eko_utils.py index 1a6f5c8a5d..d636b82354 100644 --- a/n3fit/src/evolven3fit_new/eko_utils.py +++ b/n3fit/src/evolven3fit_new/eko_utils.py @@ -30,7 +30,6 @@ } NFREF_DEFAULT = 5 -NF0_DEFAULT = 4 def construct_eko_cards( @@ -58,51 +57,77 @@ def construct_eko_cards( theory = Loader().check_theoryID(theoryID).get_description() theory.pop("FNS") theory.update(theory_card_dict) - if "nfref" not in theory: - theory["nfref"] = NFREF_DEFAULT - if "nf0" not in theory: - theory["nf0"] = NF0_DEFAULT - + # Prepare the thresholds according to MaxNfPdf thresholds = {"c": theory["kcThr"], "b": theory["kbThr"], "t": theory["ktThr"]} if theory["MaxNfPdf"] < 5: thresholds["b"] = np.inf if theory["MaxNfPdf"] < 6: thresholds["t"] = np.inf - + + if "nfref" not in theory: + theory["nfref"] = NFREF_DEFAULT + + # Set nf_0 according to the fitting scale unless set explicitly + mu0 = theory["Q0"] + if "nf0" not in theory: + if mu0 < theory["mc"] * thresholds["c"]: + theory["nf0"] = 3 + elif mu0 < theory["mb"] * thresholds["b"]: + theory["nf0"] = 4 + elif mu0 < theory["mt"] * thresholds["t"]: + theory["nf0"] = 5 + else: + theory["nf0"] = 6 + # Setting the thresholds in the theory card to inf if necessary - theory.update({"kbThr":thresholds["b"], "ktThr":thresholds["t"] }) - + theory.update({"kbThr": thresholds["b"], "ktThr": thresholds["t"]}) + # The Legacy function is able to construct a theory card for eko starting from an NNPDF theory legacy_class = runcards.Legacy(theory, {}) theory_card = legacy_class.new_theory - # if Qedref = Qref alphaem is running, otherwise it's fixed - if theory["QED"] > 0: - if np.isclose(theory["Qref"], theory["Qedref"]): - theory_card.couplings.em_running = True - - # construct operator card + # Generate the q2grid, if q_fin and q_points are None, use `nf0` to select a default q2_grid = utils.generate_q2grid( - theory["Q0"], + mu0, q_fin, q_points, - {theory["mb"]: thresholds["b"], theory["mt"]: thresholds["t"]}, + { + theory["mc"]: thresholds["c"], + theory["mb"]: thresholds["b"], + theory["mt"]: thresholds["t"], + }, + theory["nf0"], ) + + # construct operator card op_card = default_op_card masses = np.array([theory["mc"], theory["mb"], theory["mt"]]) ** 2 thresholds_ratios = np.array([thresholds["c"], thresholds["b"], thresholds["t"]]) ** 2 atlas = Atlas( matching_scales=MatchingScales(masses * thresholds_ratios), - origin=(theory["Q0"] ** 2, theory["nf0"]), - ) - op_card.update( - { - "mu0": theory["Q0"], - "mugrid": [(float(np.sqrt(q2)), int(nf_default(q2, atlas))) for q2 in q2_grid], - } + origin=(mu0**2, theory["nf0"]), ) + + # Create the eko operator q2grid + # This is a grid which contains information on (q, nf) + # in VFNS values at the matching scales need to be doubled so that they are considered in both sides + + ep = 1e-4 + mugrid = [] + for q2 in q2_grid: + q = float(np.sqrt(q2)) + if nf_default(q2 + ep, atlas) != nf_default(q2 - ep, atlas): + nf_l = int(nf_default(q2 - ep, atlas)) + nf_u = int(nf_default(q2 + ep, atlas)) + mugrid.append((q, nf_l)) + mugrid.append((q, nf_u)) + else: + mugrid.append((q, int(nf_default(q2, atlas)))) + + op_card.update({"mu0": theory["Q0"], "mugrid": mugrid}) + op_card["xgrid"] = x_grid # Specific defaults for evolven3fit evolution if theory["ModEv"] == "TRN": @@ -121,22 +146,3 @@ def construct_eko_cards( op_card = runcards.OperatorCard.from_dict(op_card) return theory_card, op_card - - -def split_evolgrid(evolgrid): - """Split the evolgrid in blocks according to the number of flavors and repeating the last entry of one block in the first entry of the next.""" - evolgrid_index_list = [] - evolgrid.sort() - starting_nf = evolgrid[0][1] - for evo_point in evolgrid: - current_nf = evo_point[1] - if current_nf != starting_nf: - evolgrid_index_list.append(evolgrid.index(evo_point)) - starting_nf = current_nf - start_index = 0 - evolgrid_list = [] - for index in evolgrid_index_list: - evolgrid_list.append(evolgrid[start_index : index + 1]) - start_index = index - evolgrid_list.append(evolgrid[start_index:]) - return evolgrid_list diff --git a/n3fit/src/evolven3fit_new/evolve.py b/n3fit/src/evolven3fit_new/evolve.py index cddb1eb308..8caab4e3e2 100644 --- a/n3fit/src/evolven3fit_new/evolve.py +++ b/n3fit/src/evolven3fit_new/evolve.py @@ -1,3 +1,4 @@ +from collections import defaultdict import logging import pathlib import sys @@ -145,7 +146,7 @@ def load_fit(usr_path): """ nnfitpath = usr_path / "nnfit" pdf_dict = {} - for yaml_file in nnfitpath.glob("replica_*/*.exportgrid"): + for yaml_file in nnfitpath.glob(f"replica_*/{usr_path.name}.exportgrid"): data = yaml.safe_load(yaml_file.read_text(encoding="UTF-8")) pdf_dict[yaml_file.parent.stem] = data return pdf_dict @@ -178,19 +179,27 @@ def evolve_exportgrid(exportgrid, eko, x_grid, qed): # generate block to dump targetgrid = eko.bases.targetgrid.tolist() - def ev_pdf(pid, x, Q2): - return x * evolved_pdf[Q2]["pdfs"][pid][targetgrid.index(x)] + # Finally separate by nf block (and order per nf/q) + by_nf = defaultdict(list) + for q, nf in sorted(eko.evolgrid, key=lambda ep: ep[1]): + by_nf[nf].append(q) + q2block_per_nf = {nf: sorted(qs) for nf, qs in by_nf.items()} - evolgrid_list = eko_utils.split_evolgrid(eko.evolgrid) blocks = [] - for evgrid in evolgrid_list: + for nf, q2grid in q2block_per_nf.items(): + + def pdf_xq2(pid, x, Q2): + x_idx = targetgrid.index(x) + return x * evolved_pdf[(Q2, nf)]["pdfs"][pid][x_idx] + block = genpdf.generate_block( - ev_pdf, + pdf_xq2, xgrid=targetgrid, - evolgrid=evgrid, + sorted_q2grid=q2grid, pids=basis_rotation.flavor_basis_pids, ) blocks.append(block) + return blocks diff --git a/n3fit/src/evolven3fit_new/utils.py b/n3fit/src/evolven3fit_new/utils.py index f1303fcbd7..4df9274459 100644 --- a/n3fit/src/evolven3fit_new/utils.py +++ b/n3fit/src/evolven3fit_new/utils.py @@ -7,7 +7,7 @@ from reportengine.compat import yaml from validphys.pdfbases import PIDS_DICT -DEFAULT_Q2GRID = ( +Q2GRID_Nf04 = ( np.array( [ 1.6500000e00, @@ -22,7 +22,6 @@ 3.8800751e00, 4.3584516e00, 4.9200000e00, - 4.9200000e00, 5.5493622e00, 6.2897452e00, 7.1650687e00, @@ -65,6 +64,62 @@ ** 2 ) +Q2GRID_Nf03 = ( + np.array( + [ + 1.0000000e00, + 1.0768843e00, + 1.1642787e00, + 1.2640247e00, + 1.3783565e00, + 1.5100000e00, + 1.6573843e00, + 1.8279487e00, + 2.0263188e00, + 2.2582323e00, + 2.5308507e00, + 2.8531703e00, + 3.2365690e00, + 3.6955380e00, + 4.2486693e00, + 4.9200000e00, + 5.6571821e00, + 6.5475141e00, + 7.6300446e00, + 8.9555329e00, + 1.0590474e01, + 1.2622686e01, + 1.5169120e01, + 1.8386905e01, + 2.2489085e01, + 2.7767274e01, + 3.4624624e01, + 4.3624282e01, + 5.5561424e01, + 7.1571582e01, + 9.3295496e01, + 1.2313315e02, + 1.6464038e02, + 2.2315640e02, + 3.0681103e02, + 4.2816505e02, + 6.0692308e02, + 8.7449251e02, + 1.2817733e03, + 1.9127020e03, + 2.9082314e03, + 4.5095982e03, + 7.1379509e03, + 1.1543948e04, + 1.9094934e04, + 3.2338760e04, + 5.6137084e04, + 1.0000000e05, + ] + ) + ** 2 +) + class LhapdfLike: """ @@ -123,7 +178,7 @@ def get_theoryID_from_runcard(usr_path): return my_runcard["theory"]["theoryid"] -def generate_q2grid(Q0, Qfin, Q_points, match_dict): +def generate_q2grid(Q0, Qfin, Q_points, match_dict, nf0=None): """Generate the q2grid used in the final evolved pdfs or use the default grid if Qfin or Q_points is not provided. @@ -131,7 +186,14 @@ def generate_q2grid(Q0, Qfin, Q_points, match_dict): in order to obtain the relative matching scale. """ if Qfin is None and Q_points is None: - return DEFAULT_Q2GRID + if nf0 == 4: + return Q2GRID_Nf04 + elif nf0 == 3: + return Q2GRID_Nf03 + elif nf0 is None: + raise ValueError("In order to use a default grid, a value of nf0 must be provided") + else: + raise NotImplementedError(f"No default grid in Q available for {nf0=}") elif Qfin is None or Q_points is None: raise ValueError("q_fin and q_points must be specified either both or none of them") else: @@ -148,7 +210,9 @@ def generate_q2grid(Q0, Qfin, Q_points, match_dict): frac_of_point = np.log(match_scale / Q_ini) / np.log(Qfin / Q0) num_points = int(Q_points * frac_of_point) num_points_list.append(num_points) - grids.append(np.geomspace(Q_ini**2, match_scale**2, num=num_points)) + grids.append( + np.geomspace(Q_ini**2, match_scale**2, num=num_points, endpoint=False) + ) Q_ini = match_scale num_points = Q_points - sum(num_points_list) grids.append(np.geomspace(Q_ini**2, Qfin**2, num=num_points)) diff --git a/n3fit/src/n3fit/backends/keras_backend/operations.py b/n3fit/src/n3fit/backends/keras_backend/operations.py index 8cf1065849..efff803b92 100644 --- a/n3fit/src/n3fit/backends/keras_backend/operations.py +++ b/n3fit/src/n3fit/backends/keras_backend/operations.py @@ -23,20 +23,22 @@ equally operations are automatically converted to layers when used as such. """ +from typing import Optional + import numpy as np +import numpy.typing as npt import tensorflow as tf +from tensorflow.keras import backend as K +from tensorflow.keras.layers import Input from tensorflow.keras.layers import Lambda as keras_Lambda from tensorflow.keras.layers import multiply as keras_multiply from tensorflow.keras.layers import subtract as keras_subtract -from tensorflow.keras.layers import Input -from tensorflow.keras import backend as K - from validphys.convolution import OP def evaluate(tensor): - """ Evaluate input tensor using the backend """ + """Evaluate input tensor using the backend""" return K.eval(tensor) @@ -107,36 +109,29 @@ def numpy_to_tensor(ival, **kwargs): # f(x: tensor) -> y: tensor def batchit(x, batch_dimension=0, **kwarg): - """ Add a batch dimension to tensor x """ + """Add a batch dimension to tensor x""" return tf.expand_dims(x, batch_dimension, **kwarg) # layer generation -def numpy_to_input(numpy_array, no_reshape=False, name=None): +def numpy_to_input(numpy_array: npt.NDArray, name: Optional[str] = None): """ - Takes a numpy array and generates a Input layer. - By default it adds a batch dimension (of size 1) so that the shape of the layer - is that of the array + Takes a numpy array and generates an Input layer with the same shape, + but with a batch dimension (of size 1) added. Parameters ---------- numpy_array: np.ndarray - no_reshape: bool - if true, don't add batch dimension, take the first dimension of the array as the batch - name: bool + name: str name to give to the layer """ - if no_reshape: - batched_array = numpy_array - batch_size = numpy_array.shape[0] - shape = numpy_array.shape[1:] - else: - batched_array = np.expand_dims(numpy_array, 0) - batch_size = 1 - shape = numpy_array.shape - input_layer = Input(batch_size=batch_size, shape=shape, name=name) + batched_array = np.expand_dims(numpy_array, 0) + shape = list(numpy_array.shape) + # set the number of gridpoints to None, otherwise shapes don't show in model.summary + shape[0] = None + + input_layer = Input(batch_size=1, shape=shape, name=name) input_layer.tensor_content = batched_array - input_layer.original_shape = no_reshape return input_layer @@ -174,7 +169,7 @@ def op_gather_keep_dims(tensor, indices, axis=0, **kwargs): both eager and non-eager tensors """ if indices == -1: - indices = tensor.shape[axis]-1 + indices = tensor.shape[axis] - 1 def tmp(x): y = tf.gather(x, indices, axis=axis, **kwargs) @@ -189,6 +184,7 @@ def tmp(x): # f(x: tensor[s]) -> y: tensor # + # Generation operations # generate tensors of given shape/content @tf.function @@ -216,7 +212,7 @@ def many_replication(grid, replications, axis=0, **kwargs): # modify properties of the tensor like the shape or elements it has @tf.function def flatten(x): - """ Flatten tensor x """ + """Flatten tensor x""" return tf.reshape(x, (-1,)) @@ -240,7 +236,7 @@ def transpose(tensor, **kwargs): def stack(tensor_list, axis=0, **kwargs): - """ Stack a list of tensors + """Stack a list of tensors see full `docs `_ """ return tf.stack(tensor_list, axis=axis, **kwargs) @@ -280,8 +276,8 @@ def pdf_masked_convolution(raw_pdf, basis_mask): pdf_x_pdf: tf.tensor rank3 (len(mask_true), xgrid, xgrid, replicas) """ - if raw_pdf.shape[-1] == 1: # only one replica! - pdf = tf.squeeze(raw_pdf, axis=(0,-1)) + if raw_pdf.shape[-1] == 1: # only one replica! + pdf = tf.squeeze(raw_pdf, axis=(0, -1)) luminosity = tensor_product(pdf, pdf, axes=0) lumi_tmp = K.permute_dimensions(luminosity, (3, 1, 2, 0)) pdf_x_pdf = batchit(boolean_mask(lumi_tmp, basis_mask), -1) @@ -309,6 +305,14 @@ def tensor_product(*args, **kwargs): return tf.tensordot(*args, **kwargs) +@tf.function +def pow(tensor, power): + """ + Computes the power of the tensor + """ + return tf.pow(tensor, power) + + @tf.function(experimental_relax_shapes=True) def op_log(o_tensor, **kwargs): """ diff --git a/n3fit/src/n3fit/layers/msr_normalization.py b/n3fit/src/n3fit/layers/msr_normalization.py index 51219ad73f..552f618b59 100644 --- a/n3fit/src/n3fit/layers/msr_normalization.py +++ b/n3fit/src/n3fit/layers/msr_normalization.py @@ -16,8 +16,7 @@ class MSR_Normalization(MetaLayer): _msr_enabled = False _vsr_enabled = False - def __init__(self, output_dim=14, mode="ALL", photons_contribution=None, **kwargs): - self._photons = photons_contribution + def __init__(self, output_dim=14, mode="ALL", **kwargs): if mode == True or mode.upper() == "ALL": self._msr_enabled = True self._vsr_enabled = True @@ -38,9 +37,9 @@ def __init__(self, output_dim=14, mode="ALL", photons_contribution=None, **kwarg op.scatter_to_one, op_kwargs={"indices": idx, "output_dim": output_dim} ) - super().__init__(**kwargs, name="normalizer") + super().__init__(**kwargs) - def call(self, pdf_integrated, ph_replica): + def call(self, pdf_integrated, photon_integral): """Imposes the valence and momentum sum rules: A_g = (1-sigma-photon)/g A_v = A_v24 = A_v35 = 3/V @@ -49,17 +48,24 @@ def call(self, pdf_integrated, ph_replica): A_v15 = 3/V_15 Note that both the input and the output are in the 14-flavours fk-basis + + Parameters + ---------- + pdf_integrated: (Tensor(1,None,14)) + the integrated PDF + photon_integral: (Tensor(1)): + the integrated photon, not included in PDF + + Returns + ------- + normalization_factor: Tensor(14) + The normalization factors per flavour. """ y = op.flatten(pdf_integrated) norm_constants = [] - if self._photons: - photon_integral = self._photons[ph_replica] - else: - photon_integral = 0.0 - if self._msr_enabled: - n_ag = [(1.0 - y[GLUON_IDX[0][0] - 1] - photon_integral) / y[GLUON_IDX[0][0]]] * len( + n_ag = [(1.0 - y[GLUON_IDX[0][0] - 1] - photon_integral[0]) / y[GLUON_IDX[0][0]]] * len( GLUON_IDX ) norm_constants += n_ag diff --git a/n3fit/src/n3fit/layers/preprocessing.py b/n3fit/src/n3fit/layers/preprocessing.py index 56278224bf..e5d45c7038 100644 --- a/n3fit/src/n3fit/layers/preprocessing.py +++ b/n3fit/src/n3fit/layers/preprocessing.py @@ -1,11 +1,10 @@ -from n3fit.backends import MetaLayer -from n3fit.backends import constraints +from n3fit.backends import MetaLayer, constraints from n3fit.backends import operations as op class Preprocessing(MetaLayer): """ - Applies preprocessing to the PDF. + Computes preprocessing factor for the PDF. This layer generates a factor (1-x)^beta*x^(1-alpha) where both beta and alpha are model paramters that can be trained. If feature scaling is used, the preprocessing @@ -21,7 +20,7 @@ class Preprocessing(MetaLayer): Parameters ---------- flav_info: list - list of dicts containing the information about the fitting of the preprocessing + list of dicts containing the information about the fitting of the preprocessing factor This corresponds to the `fitting::basis` parameter in the nnpdf runcard. The dicts can contain the following fields: `smallx`: range of alpha @@ -29,21 +28,18 @@ class Preprocessing(MetaLayer): `trainable`: whether these alpha-beta should be trained during the fit (defaults to true) large_x: bool - Whether large x preprocessing should be active + Whether large x preprocessing factor should be active seed: int seed for the initializer of the random alpha and beta values """ def __init__( - self, - flav_info=None, - seed=0, - initializer="random_uniform", - large_x=True, - **kwargs, + self, flav_info=None, seed=0, initializer="random_uniform", large_x=True, **kwargs, ): if flav_info is None: - raise ValueError("Trying to instantiate a preprocessing with no basis information") + raise ValueError( + "Trying to instantiate a preprocessing factor with no basis information" + ) self.flav_info = flav_info self.seed = seed self.output_dim = len(flav_info) diff --git a/n3fit/src/n3fit/layers/rotations.py b/n3fit/src/n3fit/layers/rotations.py index 686d3c5bbb..ed58cdbe15 100644 --- a/n3fit/src/n3fit/layers/rotations.py +++ b/n3fit/src/n3fit/layers/rotations.py @@ -56,44 +56,39 @@ def __init__( super().__init__(rotation_matrix, axes=1, **kwargs) -class FkRotation(MetaLayer): +class FkRotation(Rotation): """ - Applies a transformation from the dimension-8 evolution basis + Applies a transformation from the dimension-9 evolution basis to the dimension-14 evolution basis used by the fktables. The input to this layer is a `pdf_raw` variable which is expected to have - a shape (1, None, 8), and it is then rotated to an output (1, None, 14) + a shape (1, None, 9), and it is then rotated to an output (1, None, 14) """ - - # TODO: Generate a rotation matrix in the input and just do tf.tensordot in call - # the matrix should be: (8, 14) so that we can just do tf.tensordot(pdf, rotmat, axes=1) - # i.e., create the matrix and inherit from the Rotation layer above def __init__(self, output_dim=14, name="evolution", **kwargs): self.output_dim = output_dim - super().__init__(name=name, **kwargs) - - def call(self, pdf_raw): - # Transpose the PDF so that the flavour index is the first one - x = op.transpose(pdf_raw) - pdf_raw_list = [ - 0 * x[0], # photon - x[0], # sigma - x[1], # g - x[2], # v - x[3], # v3 - x[4], # v8 - x[8], # v15 - x[2], # v24 - x[2], # v35 - x[5], # t3 - x[6], # t8 - x[0] - 4 * x[7], # t15 (c-) - x[0], # t24 - x[0], # t35 - ] - ret = op.concatenate(pdf_raw_list) - # Concatenating destroys the batch index so we have to regenerate it - return op.batchit(ret) + rotation_matrix = self._create_rotation_matrix() + super().__init__(rotation_matrix, axes=1, name=name, **kwargs) + + def _create_rotation_matrix(self): + """Create the rotation matrix""" + array = np.array([ + [0, 0, 0, 0, 0, 0, 0, 0, 0], # photon + [1, 0, 0, 0, 0, 0, 0, 0, 0], # sigma + [0, 1, 0, 0, 0, 0, 0, 0, 0], # g + [0, 0, 1, 0, 0, 0, 0, 0, 0], # v + [0, 0, 0, 1, 0, 0, 0, 0, 0], # v3 + [0, 0, 0, 0, 1, 0, 0, 0, 0], # v8 + [0, 0, 0, 0, 0, 0, 0, 0, 1], # v15 + [0, 0, 1, 0, 0, 0, 0, 0, 0], # v24 + [0, 0, 1, 0, 0, 0, 0, 0, 0], # v35 + [0, 0, 0, 0, 0, 1, 0, 0, 0], # t3 + [0, 0, 0, 0, 0, 0, 1, 0, 0], # t8 + [1, 0, 0, 0, 0, 0, 0,-4, 0], # t15 (c-) + [1, 0, 0, 0, 0, 0, 0, 0, 0], # t24 + [1, 0, 0, 0, 0, 0, 0, 0, 0], # t35 + ]) + tensor = op.numpy_to_tensor(array.T) + return tensor class AddPhoton(MetaLayer): diff --git a/n3fit/src/n3fit/layers/x_operations.py b/n3fit/src/n3fit/layers/x_operations.py index f3cc9c32e9..a71a42d93d 100644 --- a/n3fit/src/n3fit/layers/x_operations.py +++ b/n3fit/src/n3fit/layers/x_operations.py @@ -1,7 +1,7 @@ """ This module contains layers acting on the x-grid input of the NN - The three operations included are: + The two operations included are: - ``xDivide`` - ``xIntegrator`` @@ -9,18 +9,21 @@ for all flavours. The choice of flavours on which to act in a different way is given as an input argument. """ +from typing import List, Optional from n3fit.backends import MetaLayer from n3fit.backends import operations as op -BASIS_SIZE=14 +BASIS_SIZE = 14 + class xDivide(MetaLayer): """ - Divide some PDFs by x + Create tensor of either 1/x or ones depending on the flavour, + to be used to divide some PDFs by x by multiplying with the result. - By default it utilizes the 14-flavour FK basis and divides [v, v3, v8] - which corresponds to indices (3,4,5) from + By default it utilizes the 14-flavour FK basis and divides [v, v3, v8, v15] + which corresponds to indices (3, 4, 5, 6) from (photon, sigma, g, v, v3, v8, v15, v24, v35, t3, t8, t15, t24, t35) Parameters: @@ -28,27 +31,27 @@ class xDivide(MetaLayer): output_dim: int dimension of the pdf div_list: list - list of indices to be divided by X (by default [3,4,5]; [v, v3, v8] + list of indices to be divided by X (by default [3, 4, 5, 6]; [v, v3, v8, v15] """ - def __init__(self, output_dim=BASIS_SIZE, div_list=None, **kwargs): + def __init__( + self, output_dim: int = BASIS_SIZE, div_list: Optional[List[int]] = None, **kwargs + ): if div_list is None: div_list = [3, 4, 5, 6] self.output_dim = output_dim self.div_list = div_list super().__init__(**kwargs) + self.powers = [-1 if i in div_list else 0 for i in range(output_dim)] + def call(self, x): - out_array = [] - one = op.tensor_ones_like(x) - for i in range(self.output_dim): - if i in self.div_list: - res = one / x - else: - res = one - out_array.append(res) - out_tensor = op.concatenate(out_array) - return out_tensor + return op.pow(x, self.powers) + + def get_config(self): + config = super().get_config() + config.update({"output_dim": self.output_dim, "div_list": self.div_list}) + return config class xIntegrator(MetaLayer): diff --git a/n3fit/src/n3fit/model_gen.py b/n3fit/src/n3fit/model_gen.py index ca7844d12a..2bd898021b 100644 --- a/n3fit/src/n3fit/model_gen.py +++ b/n3fit/src/n3fit/model_gen.py @@ -10,6 +10,7 @@ """ from dataclasses import dataclass +from typing import Callable, List import numpy as np @@ -27,7 +28,8 @@ losses, ) from n3fit.layers.observable import is_unique -from n3fit.msr import msr_impose +from n3fit.msr import generate_msr_model_and_grid +from validphys.photon.compute import Photon # only used for type hint here @dataclass @@ -299,13 +301,13 @@ def observable_generator( # Network generation functions def generate_dense_network( - nodes_in, - nodes, - activations, - initializer_name="glorot_normal", - seed=0, - dropout_rate=0.0, - regularizer=None, + nodes_in: int, + nodes: int, + activations: List[str], + initializer_name: str = "glorot_normal", + seed: int = 0, + dropout_rate: float = 0.0, + regularizer: str = None, ): """ Generates a dense network @@ -355,7 +357,6 @@ def generate_dense_per_flavour_network( number_of_layers = len(nodes) current_seed = seed for i, (nodes_out, activation) in enumerate(zip(nodes, activations)): - initializers = [] for _ in range(basis_size): # select the initializer and move the seed @@ -396,29 +397,28 @@ def output_layer(ilayer): def pdfNN_layer_generator( - inp=2, - nodes=None, - activations=None, - initializer_name="glorot_normal", - layer_type="dense", - flav_info=None, - fitbasis="NN31IC", - out=14, - seed=None, - dropout=0.0, - regularizer=None, - regularizer_args=None, - impose_sumrule=None, - scaler=None, - parallel_models=1, - photons=None, + nodes: List[int] = None, + activations: List[str] = None, + initializer_name: str = "glorot_normal", + layer_type: str = "dense", + flav_info: dict = None, + fitbasis: str = "NN31IC", + out: int = 14, + seed: int = None, + dropout: float = 0.0, + regularizer: str = None, + regularizer_args: dict = None, + impose_sumrule: str = None, + scaler: Callable = None, + parallel_models: int = 1, + photons: Photon = None, ): # pylint: disable=too-many-locals """ Generates the PDF model which takes as input a point in x (from 0 to 1) and outputs a basis of 14 PDFs. It generates the preprocessing of the x into a set (x, log(x)), the arbitrary NN to fit the form of the PDF - and the preprocessing factors. + and the preprocessing factor. The funtional form of the output of this function is of: @@ -453,7 +453,7 @@ def pdfNN_layer_generator( A function is constructed that joins all those layers. The function takes a tensor as the input and applies all layers for NN in order. - 4. Create a preprocessing layer (that takes as input the same tensor x as the NN) + 4. Create a preprocessing factor layer (that takes as input the same tensor x as the NN) and multiply it to the NN. We have now: N(x)_{j} * x^{1-alpha_{j}} * (1-x)^{beta_{j}} @@ -476,8 +476,6 @@ def pdfNN_layer_generator( Parameters ---------- - inp: int - dimension of the xgrid. If inp=2, turns the x point into a (x, log(x)) pair nodes: list(int) list of the number of nodes per layer of the PDF NN. Default: [15,8] activation: list @@ -499,9 +497,10 @@ def pdfNN_layer_generator( rate of dropout layer by layer impose_sumrule: str whether to impose sumrules on the output pdf and which one to impose (All, MSR, VSR) - scaler: scaler + scaler: callable Function to apply to the input. If given the input to the model will be a (1, None, 2) tensor where dim [:,:,0] is scaled + When None, instead turn the x point into a (x, log(x)) pair parallel_models: int How many models should be trained in parallel photon: :py:class:`validphys.photon.compute.Photon` @@ -527,9 +526,6 @@ def pdfNN_layer_generator( if impose_sumrule is None: impose_sumrule = "All" - if scaler: - inp = 1 - if activations is None: activations = ["tanh", "linear"] elif callable(activations): @@ -544,135 +540,206 @@ def pdfNN_layer_generator( # The number of nodes in the last layer is equal to the number of fitted flavours last_layer_nodes = nodes[-1] # (== len(flav_info)) - # Generate the generic layers that will not depend on extra considerations - - # First prepare the input for the PDF model and any scaling if needed - placeholder_input = Input(shape=(None, 1), batch_size=1) + # Process input options. There are 2 options: + # 1. Scale the input + # 2. Concatenate log(x) to the input + use_feature_scaling = scaler is not None - subtract_one = False - process_input = Lambda(lambda x: x) - input_x_eq_1 = [1.0] # When scaler is active we also want to do the subtraction of large x # TODO: make it its own option (i.e., one could want to use this without using scaler) - if scaler: - # change the input domain [0,1] -> [-1,1] - process_input = Lambda(lambda x: 2 * x - 1) - subtract_one = True - input_x_eq_1 = scaler([1.0])[0] - placeholder_input = Input(shape=(None, 2), batch_size=1) - elif inp == 2: - # If the input is of type (x, logx) - # create a x --> (x, logx) layer to preppend to everything - process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1)) - - model_input = {"pdf_input": placeholder_input} + subtract_one = use_feature_scaling + + # Feature scaling happens before the pdf model and changes x->(scaler(x), x), + # so it adds an input dimension + pdf_input_dimensions = 2 if use_feature_scaling else 1 + # Adding of logs happens inside, but before the NN and adds a dimension there + nn_input_dimensions = 1 if use_feature_scaling else 2 + + # Define the main input + do_nothing = lambda x: x + if use_feature_scaling: + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='scaledx_x') + process_input = do_nothing + extract_nn_input = Lambda(lambda x: op.op_gather_keep_dims(x, 0, axis=-1), name='x_scaled') + extract_original = Lambda(lambda x: op.op_gather_keep_dims(x, 1, axis=-1), name='x') + else: # add log(x) + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='x') + process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1), name='x_logx') + extract_original = do_nothing + extract_nn_input = do_nothing + + model_input = {"pdf_input": pdf_input} + if subtract_one: - layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1)) + input_x_eq_1 = [1.0] + if use_feature_scaling: + input_x_eq_1 = scaler(input_x_eq_1)[0] + # the layer that subtracts 1 from the NN output + subtract_one_layer = Lambda(op.op_subtract, name='subtract_one') + layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1), name='x_eq_1') model_input["layer_x_eq_1"] = layer_x_eq_1 - # Evolution layer - layer_evln = FkRotation(input_shape=(last_layer_nodes,), output_dim=out) + # the layer that multiplies the NN output by the preprocessing factor + apply_preprocessing_factor = Lambda(op.op_multiply, name='prefactor_times_NN') # Photon layer - layer_photon = AddPhoton(photons=photons) + layer_photon = AddPhoton(photons=photons, name="add_photon") # Basis rotation - basis_rotation = FlavourToEvolution(flav_info=flav_info, fitbasis=fitbasis) + basis_rotation = FlavourToEvolution( + flav_info=flav_info, fitbasis=fitbasis, name="pdf_evolution_basis" + ) + + # Evolution layer + layer_evln = FkRotation(input_shape=(last_layer_nodes,), output_dim=out, name="pdf_FK_basis") # Normalization and sum rules if impose_sumrule: - sumrule_layer, integrator_input = msr_impose( + sumrule_layer, integrator_input = generate_msr_model_and_grid( mode=impose_sumrule, scaler=scaler, photons=photons ) model_input["integrator_input"] = integrator_input else: sumrule_layer = lambda x: x - # Now we need a trainable network per model to be trained in parallel + # Now we need a trainable network per replica to be trained in parallel pdf_models = [] - for i, layer_seed in enumerate(seed): - if layer_type == "dense": - reg = regularizer_selector(regularizer, **regularizer_args) - list_of_pdf_layers = generate_dense_network( - inp, - nodes, - activations, - initializer_name, - seed=layer_seed, - dropout_rate=dropout, - regularizer=reg, + + # Only these layers change from replica to replica: + nn_replicas = [] + preprocessing_factor_replicas = [] + for i_replica, replica_seed in enumerate(seed): + preprocessing_factor_replicas.append( + Preprocessing( + flav_info=flav_info, + input_shape=(1,), + name=f"preprocessing_factor_{i_replica}", + seed=replica_seed + number_of_layers, + large_x=not subtract_one, ) - elif layer_type == "dense_per_flavour": - # Define the basis size attending to the last layer in the network - # TODO: this information should come from the basis information - # once the basis information is passed to this class - list_of_pdf_layers = generate_dense_per_flavour_network( - inp, - nodes, - activations, - initializer_name, - seed=layer_seed, - basis_size=last_layer_nodes, + ) + nn_replicas.append( + generate_nn( + layer_type=layer_type, + input_dimensions=nn_input_dimensions, + nodes=nodes, + activations=activations, + initializer_name=initializer_name, + replica_seed=replica_seed, + dropout=dropout, + regularizer=regularizer, + regularizer_args=regularizer_args, + last_layer_nodes=last_layer_nodes, + name=f"NN_{i_replica}", ) - - def dense_me(x): - """Takes an input tensor `x` and applies all layers - from the `list_of_pdf_layers` in order""" - processed_x = process_input(x) - curr_fun = list_of_pdf_layers[0](processed_x) - - for dense_layer in list_of_pdf_layers[1:]: - curr_fun = dense_layer(curr_fun) - return curr_fun - - preproseed = layer_seed + number_of_layers - layer_preproc = Preprocessing( - flav_info=flav_info, - input_shape=(1,), - name=f"pdf_prepro_{i}", - seed=preproseed, - large_x=not subtract_one, ) - # Apply preprocessing and basis - def layer_fitbasis(x): - """The tensor x has a expected shape of (1, None, {1,2}) - where x[...,0] corresponds to the feature_scaled input and x[...,-1] the original input - """ - x_scaled = op.op_gather_keep_dims(x, 0, axis=-1) - x_original = op.op_gather_keep_dims(x, -1, axis=-1) - - nn_output = dense_me(x_scaled) - if subtract_one: - nn_at_one = dense_me(layer_x_eq_1) - nn_output = op.op_subtract([nn_output, nn_at_one]) - - ret = op.op_multiply([nn_output, layer_preproc(x_original)]) - if basis_rotation.is_identity(): - # if we don't need to rotate basis we don't want spurious layers - return ret - return basis_rotation(ret) - - # Rotation layer, changes from the 8-basis to the 14-basis - def layer_pdf(x): - return layer_evln(layer_fitbasis(x)) - - # Final PDF (apply normalization) - normalized_pdf = sumrule_layer(layer_pdf, i) - - # Photon layer, changes the photon from zero to non-zero - def apply_photon(x): - # if photon is None then the photon layer is not applied - if photons: - return layer_photon(normalized_pdf(x), i) - else: - return normalized_pdf(x) - - final_pdf = apply_photon + # All layers have been made, now we need to connect them, + # do this in a function so we can call it for both grids and each replica + # Since all layers are already made, they will be reused + def compute_unnormalized_pdf(x, neural_network, compute_preprocessing_factor): + # Preprocess the input grid + x_nn_input = extract_nn_input(x) + x_original = extract_original(x) + x_processed = process_input(x_nn_input) + + # Compute the neural network output + nn_output = neural_network(x_processed) + if subtract_one: + x_eq_1_processed = process_input(layer_x_eq_1) + nn_at_one = neural_network(x_eq_1_processed) + nn_output = subtract_one_layer([nn_output, nn_at_one]) + + # Compute the preprocessing factor and multiply + preprocessing_factor = compute_preprocessing_factor(x_original) + pref_nn = apply_preprocessing_factor([nn_output, preprocessing_factor]) + + # Apply basis rotation if needed + if not basis_rotation.is_identity(): + pref_nn = basis_rotation(pref_nn) + + # Transform to FK basis + pdf_unnormalized = layer_evln(pref_nn) + + return pdf_unnormalized + + # Finally compute the normalized PDFs for each replica + pdf_models = [] + for i_replica, (preprocessing_factor, nn) in enumerate( + zip(preprocessing_factor_replicas, nn_replicas) + ): + pdf_unnormalized = compute_unnormalized_pdf(pdf_input, nn, preprocessing_factor) + + if impose_sumrule: + pdf_integration_grid = compute_unnormalized_pdf( + integrator_input, nn, preprocessing_factor + ) + pdf_normalized = sumrule_layer( + { + "pdf_x": pdf_unnormalized, + "pdf_xgrid_integration": pdf_integration_grid, + "xgrid_integration": integrator_input, + # The photon is treated separately, need to get its integrals to normalize the pdf + "photon_integral": op.numpy_to_tensor( + 0.0 if not photons else photons.integral[i_replica] + ), + } + ) + pdf = pdf_normalized + else: + pdf = pdf_unnormalized + + if photons: + # Add in the photon component + pdf = layer_photon(pdf, i_replica) # Create the model - pdf_model = MetaModel( - model_input, final_pdf(placeholder_input), name=f"PDF_{i}", scaler=scaler - ) + pdf_model = MetaModel(model_input, pdf, name=f"PDF_{i_replica}", scaler=scaler) pdf_models.append(pdf_model) + return pdf_models + + +def generate_nn( + layer_type: str, + input_dimensions: int, + nodes: List[int], + activations: List[str], + initializer_name: str, + replica_seed: int, + dropout: float, + regularizer: str, + regularizer_args: dict, + last_layer_nodes: int, + name: str, +) -> MetaModel: + """ + Create the part of the model that contains all of the actual neural network + layers. + """ + common_args = { + 'nodes_in': input_dimensions, + 'nodes': nodes, + 'activations': activations, + 'initializer_name': initializer_name, + 'seed': replica_seed, + } + if layer_type == "dense": + reg = regularizer_selector(regularizer, **regularizer_args) + list_of_pdf_layers = generate_dense_network( + **common_args, dropout_rate=dropout, regularizer=reg + ) + elif layer_type == "dense_per_flavour": + list_of_pdf_layers = generate_dense_per_flavour_network( + **common_args, basis_size=last_layer_nodes + ) + + # Note: using a Sequential model would be more appropriate, but it would require + # creating a MetaSequential model. + x = Input(shape=(None, input_dimensions), batch_size=1, name='xgrids_processed') + pdf = x + for layer in list_of_pdf_layers: + pdf = layer(pdf) + + model = MetaModel({'NN_input': x}, pdf, name=name) + return model diff --git a/n3fit/src/n3fit/model_trainer.py b/n3fit/src/n3fit/model_trainer.py index 1f1a5a4011..2f77590a6e 100644 --- a/n3fit/src/n3fit/model_trainer.py +++ b/n3fit/src/n3fit/model_trainer.py @@ -13,13 +13,13 @@ import logging import numpy as np -from scipy.interpolate import PchipInterpolator from n3fit import model_gen from n3fit.backends import MetaModel, callbacks, clear_backend_state from n3fit.backends import operations as op import n3fit.hyper_optimization.penalties import n3fit.hyper_optimization.rewards +from n3fit.scaler import generate_scaler from n3fit.stopping import Stopping from n3fit.vpinterface import N3PDF from validphys.photon.compute import Photon @@ -472,6 +472,12 @@ def _model_generation(self, xinput, pdf_models, partition, partition_idx): if self.print_summary: training.summary() + pdf_model = training.get_layer("PDF_0") + pdf_model.summary() + nn_model = pdf_model.get_layer("NN_0") + nn_model.summary() + msr_model = pdf_model.get_layer("impose_msr") + msr_model.summary() models = { "training": training, @@ -600,53 +606,7 @@ def _generate_observables( # Store a reference to the interpolator as self._scaler if interpolation_points: - input_arr = np.concatenate(self.input_list, axis=1) - input_arr = np.sort(input_arr) - input_arr_size = input_arr.size - - # Define an evenly spaced grid in the domain [0,1] - # force_set_smallest is used to make sure the smallest point included in the scaling is - # 1e-9, to prevent trouble when saving it to the LHAPDF grid - force_set_smallest = input_arr.min() > 1e-9 - if force_set_smallest: - new_xgrid = np.linspace( - start=1 / input_arr_size, stop=1.0, endpoint=False, num=input_arr_size - ) - else: - new_xgrid = np.linspace(start=0, stop=1.0, endpoint=False, num=input_arr_size) - - # When mapping the FK xgrids onto our new grid, we need to consider degeneracies among - # the x-values in the FK grids - unique, counts = np.unique(input_arr, return_counts=True) - map_to_complete = [] - for cumsum_ in np.cumsum(counts): - # Make sure to include the smallest new_xgrid value, such that we have a point at - # x<=1e-9 - map_to_complete.append(new_xgrid[cumsum_ - counts[0]]) - map_to_complete = np.array(map_to_complete) - map_from_complete = unique - - # If needed, set feature_scaling(x=1e-9)=0 - if force_set_smallest: - map_from_complete = np.insert(map_from_complete, 0, 1e-9) - map_to_complete = np.insert(map_to_complete, 0, 0.0) - - # Select the indices of the points that will be used by the interpolator - onein = map_from_complete.size / (int(interpolation_points) - 1) - selected_points = [round(i * onein - 1) for i in range(1, int(interpolation_points))] - if selected_points[0] != 0: - selected_points = [0] + selected_points - map_from = map_from_complete[selected_points] - map_from = np.log(map_from) - map_to = map_to_complete[selected_points] - - try: - scaler = PchipInterpolator(map_from, map_to) - except ValueError: - raise ValueError( - "interpolation_points is larger than the number of unique " "input x-values" - ) - self._scaler = lambda x: np.concatenate([scaler(np.log(x)), x], axis=-1) + self._scaler = generate_scaler(self.input_list, interpolation_points) def _generate_pdf( self, @@ -886,9 +846,7 @@ def hyperparametrizable(self, params): # Initialize all photon classes for the different replicas: if self.lux_params: photons = Photon( - theoryid=self.theoryid, - lux_params=self.lux_params, - replicas=self.replicas, + theoryid=self.theoryid, lux_params=self.lux_params, replicas=self.replicas, ) else: photons = None @@ -960,11 +918,7 @@ def hyperparametrizable(self, params): for model in models.values(): model.compile(**params["optimizer"]) - passed = self._train_and_fit( - models["training"], - stopping_object, - epochs=epochs, - ) + passed = self._train_and_fit(models["training"], stopping_object, epochs=epochs,) if self.mode_hyperopt: # If doing a hyperparameter scan we need to keep track of the loss function diff --git a/n3fit/src/n3fit/msr.py b/n3fit/src/n3fit/msr.py index 9db718f285..17392d3022 100644 --- a/n3fit/src/n3fit/msr.py +++ b/n3fit/src/n3fit/msr.py @@ -2,15 +2,114 @@ The constraint module include functions to impose the momentum sum rules on the PDFs """ import logging +from typing import Callable, Optional import numpy as np +from n3fit.backends import Input, Lambda, MetaModel from n3fit.backends import operations as op from n3fit.layers import MSR_Normalization, xDivide, xIntegrator log = logging.getLogger(__name__) +def generate_msr_model_and_grid( + output_dim: int = 14, + mode: str = "ALL", + nx: int = int(2e3), + scaler: Optional[Callable] = None, + **kwargs +) -> MetaModel: + """ + Generates a model that applies the sum rules to the PDF. + + Parameters + ---------- + output_dim: int + Number of flavours of the output PDF + mode: str + Mode of sum rules to apply. It can be: + - "ALL": applies both the momentum and valence sum rules + - "MSR": applies only the momentum sum rule + - "VSR": applies only the valence sum rule + nx: int + Number of points of the integration grid + scaler: Scaler + Scaler to be applied to the PDF before applying the sum rules + + Returns + ------- + model: MetaModel + Model that applies the sum rules to the PDF + It takes as inputs: + - pdf_x: the PDF output of the model + - pdf_xgrid_integration: the PDF output of the model evaluated at the integration grid + - xgrid_integration: the integration grid + - photon_integral: the integrated photon contribution + It returns the PDF with the sum rules applied + xgrid_integration: dict + Dictionary with the integration grid, with: + - values: the integration grid + - input: the input layer of the integration grid + """ + # 0. Prepare input layers to MSR model + pdf_x = Input(shape=(None, output_dim), batch_size=1, name="pdf_x") + pdf_xgrid_integration = Input( + shape=(nx, output_dim), batch_size=1, name="pdf_xgrid_integration" + ) + + # 1. Generate the grid and weights that will be used to integrate + xgrid_integration, weights_array = gen_integration_input(nx) + # 1b If a scaler is provided, scale the input xgrid + if scaler: + xgrid_integration = scaler(xgrid_integration) + + # Turn into input layer. + xgrid_integration = op.numpy_to_input(xgrid_integration, name="integration_grid") + + # 1c Get the original grid + if scaler: + get_original = Lambda( + lambda x: op.op_gather_keep_dims(x, -1, axis=-1), name="x_original_integ" + ) + else: + get_original = lambda x: x + x_original = get_original(xgrid_integration) + + # 2. Divide the grid by x depending on the flavour + x_divided = xDivide()(x_original) + + # 3. Prepare the pdf for integration by dividing by x + pdf_integrand = Lambda(op.op_multiply, name="pdf_integrand")([x_divided, pdf_xgrid_integration]) + + # 4. Integrate the pdf + pdf_integrated = xIntegrator(weights_array, input_shape=(nx,))(pdf_integrand) + + # 5. THe input for the photon integral, will be set to 0 if no photons + photon_integral = Input(shape=(), batch_size=1, name='photon_integral') + + # 6. Compute the normalization factor + # For now set the photon component to None + normalization_factor = MSR_Normalization(output_dim, mode, name="msr_weights")( + pdf_integrated, photon_integral + ) + + # 7. Apply the normalization factor to the pdf + pdf_normalized = Lambda(lambda pdf_norm: pdf_norm[0] * pdf_norm[1], name="pdf_normalized")( + [pdf_x, normalization_factor] + ) + + inputs = { + "pdf_x": pdf_x, + "pdf_xgrid_integration": pdf_xgrid_integration, + "xgrid_integration": xgrid_integration, + "photon_integral": photon_integral, + } + model = MetaModel(inputs, pdf_normalized, name="impose_msr") + + return model, xgrid_integration + + def gen_integration_input(nx): """ Generates a np.array (shaped (nx,1)) of nx elements where the @@ -34,67 +133,3 @@ def gen_integration_input(nx): weights_array = np.array(weights).reshape(nx, 1) return xgrid, weights_array - - -def msr_impose(nx=int(2e3), mode='All', scaler=None, photons=None): - """ - This function receives: - Generates a function that applies a normalization layer to the fit. - - fit_layer: the 8-basis layer of PDF which we fit - The normalization is computed from the direct output of the NN (so the 7,8-flavours basis) - - final_layer: the 14-basis which is fed to the fktable - and it is applied to the input of the fktable (i.e., to the 14-flavours fk-basis). - It uses pdf_fit to compute the sum rule and returns a modified version of - the final_pdf layer with a normalisation by which the sum rule is imposed - - Parameters - ---------- - nx: int - number of points for the integration grid, default: 2000 - mode: str - what sum rules to compute (MSR, VSR or All), default: All - scaler: scaler - Function to apply to the input. If given the input to the model - will be a (1, None, 2) tensor where dim [:,:,0] is scaled - photon: :py:class:`validphys.photon.compute.Photon` - If given, gives the AddPhoton layer a function to compute the MSR component for the photon - """ - - # 1. Generate the fake input which will be used to integrate - xgrid, weights_array = gen_integration_input(nx) - # 1b If a scaler is provided, scale the input xgrid - if scaler: - xgrid = scaler(xgrid) - - # 2. Prepare the pdf for integration - # for that we need to multiply several flavours with 1/x - division_by_x = xDivide() - # 3. Now create the integration layer (the layer that will simply integrate, given some weight - integrator = xIntegrator(weights_array, input_shape=(nx,)) - - # 3.1 If a photon is given, compute the photon component of the MSR - photons_c = None - if photons: - photons_c = photons.integral - - # 4. Now create the normalization by selecting the right integrations - normalizer = MSR_Normalization(mode=mode, photons_contribution=photons_c) - - # 5. Make the xgrid array into a backend input layer so it can be given to the normalization - xgrid_input = op.numpy_to_input(xgrid, name="integration_grid") - # Finally prepare a function which will take as input the output of the PDF model - # and will return it appropiately normalized. - def apply_normalization(layer_pdf, ph_replica): - """ - layer_pdf: output of the PDF, unnormalized, ready for the fktable - """ - x_original = op.op_gather_keep_dims(xgrid_input, -1, axis=-1) - pdf_integrand = op.op_multiply([division_by_x(x_original), layer_pdf(xgrid_input)]) - normalization = normalizer(integrator(pdf_integrand), ph_replica) - - def ultimate_pdf(x): - return layer_pdf(x) * normalization - - return ultimate_pdf - - return apply_normalization, xgrid_input diff --git a/n3fit/src/n3fit/scaler.py b/n3fit/src/n3fit/scaler.py new file mode 100644 index 0000000000..2129f24d7f --- /dev/null +++ b/n3fit/src/n3fit/scaler.py @@ -0,0 +1,77 @@ +from typing import Callable, List, Optional + +import numpy as np +import numpy.typing as npt +from scipy.interpolate import PchipInterpolator + + +def generate_scaler( + input_list: List[npt.NDArray], interpolation_points: Optional[int] = None +) -> Callable: + """ + Generate the scaler function that applies feature scaling to the input data. + + Parameters + ---------- + input_list : list of numpy.ndarray + The list of input data arrays. + interpolation_points : int, optional + + Returns + ------- + _scaler : Callable + The scaler function that applies feature scaling to the input data. + """ + input_arr = np.concatenate(input_list, axis=1) + input_arr = np.sort(input_arr) + input_arr_size = input_arr.size + + # Define an evenly spaced grid in the domain [0,1] + # force_set_smallest is used to make sure the smallest point included in the scaling is + # 1e-9, to prevent trouble when saving it to the LHAPDF grid + force_set_smallest = input_arr.min() > 1e-9 + if force_set_smallest: + new_xgrid = np.linspace( + start=1 / input_arr_size, stop=1.0, endpoint=False, num=input_arr_size + ) + else: + new_xgrid = np.linspace(start=0, stop=1.0, endpoint=False, num=input_arr_size) + + # When mapping the FK xgrids onto our new grid, we need to consider degeneracies among + # the x-values in the FK grids + unique, counts = np.unique(input_arr, return_counts=True) + map_to_complete = [] + for cumsum_ in np.cumsum(counts): + # Make sure to include the smallest new_xgrid value, such that we have a point at + # x<=1e-9 + map_to_complete.append(new_xgrid[cumsum_ - counts[0]]) + map_to_complete = np.array(map_to_complete) + map_from_complete = unique + + # If needed, set feature_scaling(x=1e-9)=0 + if force_set_smallest: + map_from_complete = np.insert(map_from_complete, 0, 1e-9) + map_to_complete = np.insert(map_to_complete, 0, 0.0) + + # Select the indices of the points that will be used by the interpolator + onein = map_from_complete.size / (int(interpolation_points) - 1) + selected_points = [round(i * onein - 1) for i in range(1, int(interpolation_points))] + if selected_points[0] != 0: + selected_points = [0] + selected_points + map_from = map_from_complete[selected_points] + map_from = np.log(map_from) + map_to = map_to_complete[selected_points] + + try: + scaler = PchipInterpolator(map_from, map_to) + except ValueError as e: + raise ValueError( + "interpolation_points is larger than the number of unique input x-values" + ) from e + + def _scaler(x): + x_scaled = scaler(np.log(x)) + x_scaled = 2 * x_scaled - 1 + return np.concatenate([x_scaled, x], axis=-1) + + return _scaler diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml new file mode 100644 index 0000000000..84a880c44e --- /dev/null +++ b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml @@ -0,0 +1,93 @@ +# +# Configuration file for n3fit regression tests +# This runcard includes two DIS datasets, one Hadronic dataset +# and two positivity datasets +# + +############################################################ +description: n3fit regression test + +############################################################ +# frac: training fraction +# ewk: apply ewk k-factors +# sys: systematics treatment (see systypes) +dataset_inputs: +- { dataset: NMC, frac: 0.5 } +- { dataset: SLACP_dwsh, frac: 0.5} +- { dataset: CMSZDIFF12, frac: 0.5, cfac: ['QCD'], sys: 10 } +- { dataset: ATLASTTBARTOT8TEV, frac: 1.0, cfac: ['QCD'] } + +############################################################ +datacuts: + t0pdfset: NNPDF40_nnlo_as_01180 # PDF set to generate t0 covmat + q2min : 3.49 # Q2 minimum + w2min : 12.5 # W2 minimum + combocuts : NNPDF31 # NNPDF3.0 final kin. cuts + jetptcut_tev : 0 # jet pt cut for tevatron + jetptcut_lhc : 0 # jet pt cut for lhc + wptcut_lhc : 30.0 # Minimum pT for W pT diff distributions + jetycut_tev : 1e30 # jet rap. cut for tevatron + jetycut_lhc : 1e30 # jet rap. cut for lhc + dymasscut_min: 0 # dy inv.mass. min cut + dymasscut_max: 1e30 # dy inv.mass. max cut + jetcfactcut : 1e30 # jet cfact. cut + +############################################################ +theory: + theoryid: 398 # database id + +############################################################ +genrep: True # on = generate MC replicas, False = use real data +trvlseed: 3 +nnseed: 2 +mcseed: 1 + +load: "weights.h5" + +parameters: # This defines the parameter dictionary that is passed to the Model Trainer + nodes_per_layer: [15, 10, 8] + activation_per_layer: ['sigmoid', 'sigmoid', 'linear'] + initializer: 'glorot_normal' + optimizer: + optimizer_name: 'RMSprop' + learning_rate: 0.00001 + clipnorm: 1.0 + epochs: 1100 + positivity: + multiplier: 1.05 + initial: 1.5 + stopping_patience: 0.10 # percentage of the number of epochs + layer_type: 'dense' + dropout: 0.0 + threshold_chi2: 10.0 + +fitting: + fitbasis: NN31IC # EVOL (7), EVOLQED (8), etc. + basis: + - { fl: sng, smallx: [1.05,1.19], largex: [1.47,2.70] } + - { fl: g, smallx: [0.94,1.25], largex: [0.11,5.87] } + - { fl: v, smallx: [0.54,0.75], largex: [1.15,2.76] } + - { fl: v3, smallx: [0.21,0.57], largex: [1.35,3.08] } + - { fl: v8, smallx: [0.52,0.76], largex: [0.77,3.56] } + - { fl: t3, smallx: [-0.37,1.52], largex: [1.74,3.39] } + - { fl: t8, smallx: [0.56,1.29], largex: [1.45,3.03] } + - { fl: cp, smallx: [0.12,1.19], largex: [1.83,6.70] } + +############################################################ +positivity: + posdatasets: + - { dataset: POSF2U, maxlambda: 1e6 } # Positivity Lagrange Multiplier + - { dataset: POSDYS, maxlambda: 1e5 } + +integrability: + integdatasets: + - {dataset: INTEGXT8, maxlambda: 1e2} + +############################################################ +debug: true + +fiatlux: + luxset: NNPDF40_nnlo_as_01180 + additional_errors: true # should be set to true only for the last iteration + luxseed: 1234567890 + eps_base: 1e-2 diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_qed_1.json b/n3fit/src/n3fit/tests/regressions/quickcard_qed_1.json new file mode 100644 index 0000000000..a960f7da9f --- /dev/null +++ b/n3fit/src/n3fit/tests/regressions/quickcard_qed_1.json @@ -0,0 +1,95 @@ +{ + "preprocessing": [ + { + "fl": "sng", + "smallx": 1.1307647228240967, + "largex": 2.6348154544830322, + "trainable": true + }, + { + "fl": "g", + "smallx": 1.1853630542755127, + "largex": 1.5627975463867188, + "trainable": true + }, + { + "fl": "v", + "smallx": 0.5399999022483826, + "largex": 2.004500150680542, + "trainable": true + }, + { + "fl": "v3", + "smallx": 0.3061824142932892, + "largex": 2.624323606491089, + "trainable": true + }, + { + "fl": "v8", + "smallx": 0.5774596929550171, + "largex": 2.120253801345825, + "trainable": true + }, + { + "fl": "t3", + "smallx": 1.3441987037658691, + "largex": 1.7566683292388916, + "trainable": true + }, + { + "fl": "t8", + "smallx": 1.04995858669281, + "largex": 1.945939064025879, + "trainable": true + }, + { + "fl": "cp", + "smallx": 0.7400740385055542, + "largex": 3.461853504180908, + "trainable": true + } + ], + "stop_epoch": 1100, + "best_epoch": 1099, + "erf_tr": 31.486101150512695, + "erf_vl": 28.4218692779541, + "chi2": 19.611825942993164, + "pos_state": "POS_VETO", + "arc_lengths": [ + 1.035533162554303, + 1.1953713068471692, + 1.0881025884095246, + 1.3414978876721764, + 1.0839843290638607 + ], + "integrability": [ + 0.002653829054906187, + 0.002653829054905521, + 0.0002567724250169823, + 3.2896786332130423, + 0.003927801561079747 + ], + "timing": { + "walltime": { + "Total": 58.37841296195984, + "start": 0.0, + "replica_set": 0.3208029270172119, + "replica_fitted": 58.37802076339722, + "replica_set_to_replica_fitted": 58.057217836380005 + }, + "cputime": { + "Total": 61.517351913999995, + "start": 0.0, + "replica_set": 2.813359167999998, + "replica_fitted": 61.516948647, + "replica_set_to_replica_fitted": 58.703589479 + } + }, + "version": { + "keras": "2.11.0", + "tensorflow": "2.11.0, mkl=False", + "numpy": "1.22.4", + "nnpdf": "4.0.6.846+g0a926fdf1", + "validphys": "4.0.6.846+g0a926fdf1" + } +} diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_qed_2.json b/n3fit/src/n3fit/tests/regressions/quickcard_qed_2.json new file mode 100644 index 0000000000..18e6a605ae --- /dev/null +++ b/n3fit/src/n3fit/tests/regressions/quickcard_qed_2.json @@ -0,0 +1,95 @@ +{ + "preprocessing": [ + { + "fl": "sng", + "smallx": 1.1090763807296753, + "largex": 2.683891534805298, + "trainable": true + }, + { + "fl": "g", + "smallx": 0.9399998784065247, + "largex": 1.6250606775283813, + "trainable": true + }, + { + "fl": "v", + "smallx": 0.7499998211860657, + "largex": 1.7267229557037354, + "trainable": true + }, + { + "fl": "v3", + "smallx": 0.21201331913471222, + "largex": 1.3532426357269287, + "trainable": true + }, + { + "fl": "v8", + "smallx": 0.7599998712539673, + "largex": 2.390087127685547, + "trainable": true + }, + { + "fl": "t3", + "smallx": 1.4388009309768677, + "largex": 2.2958621978759766, + "trainable": true + }, + { + "fl": "t8", + "smallx": 1.0386217832565308, + "largex": 1.7531665563583374, + "trainable": true + }, + { + "fl": "cp", + "smallx": 0.24638080596923828, + "largex": 2.7976953983306885, + "trainable": true + } + ], + "stop_epoch": 1100, + "best_epoch": 1099, + "erf_tr": 3.5809452533721924, + "erf_vl": 3.6826603412628174, + "chi2": 2.141340732574463, + "pos_state": "POS_VETO", + "arc_lengths": [ + 1.3194883264768875, + 1.1995146017416334, + 1.054266019685804, + 5.074692492247958, + 1.0689068380364566 + ], + "integrability": [ + 0.02917606895789332, + 0.029176068957894374, + 0.0003924771135637162, + 12.764093160629272, + 0.02982003148645135 + ], + "timing": { + "walltime": { + "Total": 57.77593541145325, + "start": 0.0, + "replica_set": 0.31868839263916016, + "replica_fitted": 57.77560114860535, + "replica_set_to_replica_fitted": 57.45691275596619 + }, + "cputime": { + "Total": 60.771742980000006, + "start": 0.0, + "replica_set": 2.6913169609999983, + "replica_fitted": 60.771408723, + "replica_set_to_replica_fitted": 58.080091762 + } + }, + "version": { + "keras": "2.11.0", + "tensorflow": "2.11.0, mkl=False", + "numpy": "1.22.4", + "nnpdf": "4.0.6.846+g0a926fdf1", + "validphys": "4.0.6.846+g0a926fdf1" + } +} diff --git a/n3fit/src/n3fit/tests/regressions/weights_1.h5 b/n3fit/src/n3fit/tests/regressions/weights_1.h5 index bcc79666b0..2c5b02e71e 100644 Binary files a/n3fit/src/n3fit/tests/regressions/weights_1.h5 and b/n3fit/src/n3fit/tests/regressions/weights_1.h5 differ diff --git a/n3fit/src/n3fit/tests/regressions/weights_2.h5 b/n3fit/src/n3fit/tests/regressions/weights_2.h5 index cd7b3d2d3c..e5a8adea86 100644 Binary files a/n3fit/src/n3fit/tests/regressions/weights_2.h5 and b/n3fit/src/n3fit/tests/regressions/weights_2.h5 differ diff --git a/n3fit/src/n3fit/tests/test_evolven3fit.py b/n3fit/src/n3fit/tests/test_evolven3fit.py index 1796095df1..9dd372c60e 100644 --- a/n3fit/src/n3fit/tests/test_evolven3fit.py +++ b/n3fit/src/n3fit/tests/test_evolven3fit.py @@ -23,11 +23,6 @@ def assert_sorted(arr, title): raise ValueError(f"The values of {title} are not sorted!") -def check_consecutive_members(grid, value): - """Check if the first occurrence of value in grid is followed by value again""" - return np.allclose(grid[list(grid).index(value) + 1], value) - - def check_lhapdf_info(info_path): """Check the LHAPDF info file is correct""" info = yaml.load(info_path.open("r", encoding="utf-8")) @@ -77,24 +72,40 @@ def check_lhapdf_dat(dat_path, info): # Use allclose here to avoid failing because of a different in the 7th place np.testing.assert_allclose(q[-1], info["QMax"]) + +def test_generate_q2grid(): + """Tests the creation of the default grids for different values of nf + and whether the matched grid is generating points in the desired locations + """ + # nf 3, q0 = 1.0 + grid = utils.generate_q2grid(None, None, None, {}, 3) + assert grid[0] == 1.0**2 + # nf 4, q0 = 1.65 + grid = utils.generate_q2grid(None, None, None, {}, 4) + assert grid[0] == 1.65**2 + + for nf in [1, 2, 5, 6]: + with pytest.raises(NotImplementedError): + grid = utils.generate_q2grid(None, None, None, {}, nf) + + with pytest.raises(ValueError): + grid = utils.generate_q2grid(None, None, None, {}) -def test_utils(): - # Testing the default grid - grid = utils.generate_q2grid(1.65, None, None, {}) - assert_allclose(1.65**2, grid[0]) - assert len(grid) == 50 - # We expect the bottom mass to be repeated twice because it is intended once in 4 flavors and once in 5 flavors. - assert check_consecutive_members(grid, 4.92**2) - # Testing if the points of the matching are correctly repeated twice matched_grid = utils.generate_q2grid(1.65, 1.0e5, 100, {4.92: 2.0, 100: 1.0}) - assert len(matched_grid) == 100 + t1 = 4.92 * 2.0 + t2 = 100.0 * 1.0 + + assert_allclose((1.65) ** 2, matched_grid[0]) assert_allclose((1.0e5) ** 2, matched_grid[-1]) - assert check_consecutive_members(matched_grid, (4.92 * 2.0) ** 2) - assert check_consecutive_members(matched_grid, (100.0 * 1.0) ** 2) + assert t1**2 in matched_grid + assert t2**2 in matched_grid + + +def test_utils(): # Testing the fake LHAPDF class q20 = 1.65**2 x_grid = np.geomspace(1.0e-7, 1.0, 30) - fake_grids = [[x * (1.0 - x) for x in x_grid] for pid in PIDS_DICT.keys()] + fake_grids = [[x * (1.0 - x) for x in x_grid] for _ in PIDS_DICT.keys()] pdf_grid = dict([(pid, v) for pid, v in zip(range(len(PIDS_DICT)), fake_grids)]) my_PDF = utils.LhapdfLike(pdf_grid, q20, x_grid) assert my_PDF.hasFlavor(6) @@ -133,10 +144,15 @@ def test_eko_utils(tmp_path): t_card_dict["order"][0] == pto + 1 ) # This is due to a different convention in eko orders due to QED assert_allclose(op_card_dict["xgrid"], x_grid) - assert_allclose(op_card_dict["mugrid"][0], (1.65, 4)) + # In theory 162 the charm threshold is at 1.51 + # and we should find two entries, one for nf=3 and another one for nf=4 + assert_allclose(op_card_dict["mugrid"][0], (1.51, 3)) + assert_allclose(op_card_dict["mugrid"][1], (1.51, 4)) + # Then (with the number of points we chosen it will happen in position 2,3 + # we will find the bottom threshold at two different nf + assert_allclose(op_card_dict["mugrid"][2], (4.92, 4)) + assert_allclose(op_card_dict["mugrid"][3], (4.92, 5)) assert_allclose(op_card_dict["mugrid"][-1], (q_fin, 5)) - # In this case there are not enough points to have twice the bottom matching scale - assert_allclose(op_card_dict["mugrid"][1], (4.92, 5)) # Testing computation of eko save_path = tmp_path / "ekotest.tar" runner.solve(t_card, op_card, save_path) @@ -145,12 +161,13 @@ def test_eko_utils(tmp_path): assert_allclose(list(eko_op.operator_card.raw["mugrid"]), op_card_dict["mugrid"]) -@pytest.mark.parametrize("fitname", ["Basic_runcard_3replicas_lowprec_399"]) +@pytest.mark.parametrize("fitname", ["Basic_runcard_3replicas_lowprec_399", "Basic_runcard_qed_3replicas_lowprec_398"]) def test_perform_evolution(tmp_path, fitname): """Test that evolven3fit_new is able to utilize the current eko in the respective theory. In addition checks that the generated .info files are correct """ fit = API.fit(fit=fitname) + _ = API.theoryid(theoryid=fit.as_input()['theory']['theoryid']) # Move the fit to a temporary folder tmp_fit = tmp_path / fitname shutil.copytree(fit.path, tmp_fit) @@ -169,3 +186,4 @@ def test_perform_evolution(tmp_path, fitname): info = check_lhapdf_info(tmp_info) for datpath in tmp_nnfit.glob("replica_*/*.dat"): check_lhapdf_dat(datpath, info) + diff --git a/n3fit/src/n3fit/tests/test_fit.py b/n3fit/src/n3fit/tests/test_fit.py index 80a329faa0..97d7d55175 100644 --- a/n3fit/src/n3fit/tests/test_fit.py +++ b/n3fit/src/n3fit/tests/test_fit.py @@ -33,6 +33,7 @@ log = logging.getLogger(__name__) REGRESSION_FOLDER = pathlib.Path(__file__).with_name("regressions") QUICKNAME = "quickcard" +QUICKNAME_QED = "quickcard_qed" EXE = "n3fit" REPLICA = "1" EXPECTED_MAX_FITTIME = 130 # seen mac ~ 180 and linux ~ 90 @@ -64,22 +65,22 @@ def test_initialize_seeds(): assert len({replica_mcseed(rep, 1, True) for rep in same_replicas}) == 1 -def auxiliary_performfit(tmp_path, replica=1, timing=True, rel_error=2e-3): +def auxiliary_performfit(tmp_path, runcard=QUICKNAME, replica=1, timing=True, rel_error=2e-3): """Fits quickcard and checks the json file to ensure the results have not changed. """ - quickcard = f"{QUICKNAME}.yml" + quickcard = f"{runcard}.yml" # Prepare the runcard quickpath = REGRESSION_FOLDER / quickcard weightpath = REGRESSION_FOLDER / f"weights_{replica}.h5" # read up the previous json file for the given replica - old_json = load_data(REGRESSION_FOLDER / f"{QUICKNAME}_{replica}.json") + old_json = load_data(REGRESSION_FOLDER / f"{runcard}_{replica}.json") # cp runcard and weights to tmp folder shutil.copy(quickpath, tmp_path) shutil.copy(weightpath, tmp_path / "weights.h5") # run the fit sp.run(f"{EXE} {quickcard} {replica}".split(), cwd=tmp_path, check=True) # read up json files - full_json = tmp_path / f"{QUICKNAME}/nnfit/replica_{replica}/{QUICKNAME}.json" + full_json = tmp_path / f"{runcard}/nnfit/replica_{replica}/{runcard}.json" new_json = load_data(full_json) # Now compare to regression results, taking into account precision won't be 100% equal_checks = ["stop_epoch", "pos_state"] @@ -101,14 +102,16 @@ def auxiliary_performfit(tmp_path, replica=1, timing=True, rel_error=2e-3): @pytest.mark.darwin -def test_performfit(tmp_path): - auxiliary_performfit(tmp_path, replica=2, timing=False, rel_error=1e-1) +@pytest.mark.parametrize("runcard", [QUICKNAME, QUICKNAME_QED]) +def test_performfit(tmp_path, runcard): + auxiliary_performfit(tmp_path, runcard=runcard, replica=2, timing=False, rel_error=1e-1) @pytest.mark.linux @pytest.mark.parametrize("replica", [1, 2]) -def test_performfit_and_timing(tmp_path, replica): - auxiliary_performfit(tmp_path, replica=replica, timing=True) +@pytest.mark.parametrize("runcard", [QUICKNAME, QUICKNAME_QED]) +def test_performfit_and_timing(tmp_path, runcard, replica): + auxiliary_performfit(tmp_path, runcard=runcard, replica=replica, timing=True) @pytest.mark.skip(reason="Still not implemented in parallel mode") diff --git a/n3fit/src/n3fit/tests/test_xops.py b/n3fit/src/n3fit/tests/test_xops.py new file mode 100644 index 0000000000..99ed67f64e --- /dev/null +++ b/n3fit/src/n3fit/tests/test_xops.py @@ -0,0 +1,34 @@ +""" + Test the x operations +""" +import numpy as np + +from n3fit.layers import xDivide + + +def test_xdivide_default(): + """Check that the default xDivide works as expected""" + x_div = xDivide() + test_input = np.array([1, 2, 3], dtype=np.float32).reshape((1, 3, 1)) + test_output = x_div(test_input) + + expected_output = np.ones(shape=(1, 3, 14)) + default_indices = [3, 4, 5, 6] + for i in default_indices: + expected_output[:, :, i] = 1 / test_input[:, :, 0] + + np.testing.assert_allclose(test_output, expected_output, rtol=1e-05) + + +def test_xdivide_indices(): + """Check that the default xDivide works as expected""" + custom_indices = [0, 1, 7] + x_div = xDivide(div_list=custom_indices) + test_input = np.array([1, 2, 3], dtype=np.float32).reshape((1, 3, 1)) + test_output = x_div(test_input) + + expected_output = np.ones(shape=(1, 3, 14)) + for i in custom_indices: + expected_output[:, :, i] = 1 / test_input[:, :, 0] + + np.testing.assert_allclose(test_output, expected_output, rtol=1e-05) diff --git a/n3fit/src/n3fit/vpinterface.py b/n3fit/src/n3fit/vpinterface.py index 52cf001980..7e2e754e0f 100644 --- a/n3fit/src/n3fit/vpinterface.py +++ b/n3fit/src/n3fit/vpinterface.py @@ -224,10 +224,12 @@ def get_preprocessing_factors(self, replica=None): if replica is None: replica = 1 # Replicas start counting in 1 so: - preprocessing_layers = self._models[replica - 1].get_layer_re(r"pdf_prepro_\d") - if len(preprocessing_layers) != 1: + preprocessing_layers = self._models[replica - 1].get_layer_re(r"preprocessing_factor_\d") + if len(preprocessing_layers) > 1: # We really don't want to fail at this point, but print a warning at least... log.warning("More than one preprocessing layer found within the model!") + elif len(preprocessing_layers) < 1: + log.warning("No preprocessing layer found within the model!") preprocessing_layer = preprocessing_layers[0] alphas_and_betas = None diff --git a/nnpdfcpp/data/commondata/DATA_ATLASWRAP11CC.dat b/nnpdfcpp/data/commondata/DATA_ATLASWRAP11CC.dat new file mode 100644 index 0000000000..6bf2ca0f41 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_ATLASWRAP11CC.dat @@ -0,0 +1,23 @@ +ATLASWRAP11CC 133 22 + 1 EWK_RAP 1.050000000000e-01 6.463838404000e+03 7.000000000000e+03 5.771500000000e+05 6.263808950000e+02 7.609145600000e+02 1.318400000000e-01 -1.269730000000e+02 -2.200000000000e-02 5.771500000000e+00 1.000000000000e-03 5.771500000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -5.771500000000e+00 -1.000000000000e-03 2.885750000000e+01 5.000000000000e-03 -6.925800000000e+01 -1.200000000000e-02 8.195530000000e+02 1.420000000000e-01 1.644877500000e+03 2.850000000000e-01 2.770320000000e+02 4.800000000000e-02 2.885750000000e+01 5.000000000000e-03 2.020025000000e+02 3.500000000000e-02 0.000000000000e+00 0.000000000000e+00 6.579510000000e+02 1.140000000000e-01 5.194350000000e+01 9.000000000000e-03 1.731450000000e+01 3.000000000000e-03 4.040050000000e+01 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-7.502950000000e+01 -1.300000000000e-02 1.154300000000e+01 2.000000000000e-03 1.038870000000e+02 1.800000000000e-02 2.308600000000e+01 4.000000000000e-03 5.194350000000e+01 9.000000000000e-03 -4.617200000000e+01 -8.000000000000e-03 1.096585000000e+02 1.900000000000e-02 1.154300000000e+01 2.000000000000e-03 1.731450000000e+02 3.000000000000e-02 -1.154300000000e+02 -2.000000000000e-02 -1.154300000000e+01 -2.000000000000e-03 9.234400000000e+01 1.600000000000e-02 1.096585000000e+02 1.900000000000e-02 7.502950000000e+01 1.300000000000e-02 2.250885000000e+02 3.900000000000e-02 4.617200000000e+01 8.000000000000e-03 -1.154300000000e+01 -2.000000000000e-03 2.885750000000e+01 5.000000000000e-03 1.846880000000e+02 3.200000000000e-02 1.789165000000e+02 3.100000000000e-02 1.038870000000e+02 1.800000000000e-02 1.269730000000e+02 2.200000000000e-02 -1.038870000000e+02 -1.800000000000e-02 4.040050000000e+01 7.000000000000e-03 -4.040050000000e+01 -7.000000000000e-03 -2.885750000000e+01 -5.000000000000e-03 -1.096585000000e+02 -1.900000000000e-02 -0.000000000000e+00 -0.000000000000e+00 1.327445000000e+02 2.300000000000e-02 8.080100000000e+01 1.400000000000e-02 5.771500000000e+01 1.000000000000e-02 1.038870000000e+02 1.800000000000e-02 -4.617200000000e+02 -8.000000000000e-02 -2.424030000000e+02 -4.200000000000e-02 -1.327445000000e+02 -2.300000000000e-02 1.500590000000e+02 2.600000000000e-02 3.462900000000e+01 6.000000000000e-03 -2.770320000000e+02 -4.800000000000e-02 -2.539460000000e+02 -4.400000000000e-02 -2.885750000000e+01 -5.000000000000e-03 1.096585000000e+02 1.900000000000e-02 1.327445000000e+02 2.300000000000e-02 -8.657250000000e+01 -1.500000000000e-02 6.925800000000e+01 1.200000000000e-02 4.617200000000e+01 8.000000000000e-03 5.194350000000e+01 9.000000000000e-03 1.731450000000e+01 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.500590000000e+02 2.600000000000e-02 1.442875000000e+02 2.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 5.771500000000e+01 1.000000000000e-02 -2.885750000000e+01 -5.000000000000e-03 -6.925800000000e+01 -1.200000000000e-02 -9.234400000000e+01 -1.600000000000e-02 2.654890000000e+02 4.600000000000e-02 2.885750000000e+01 5.000000000000e-03 5.194350000000e+01 9.000000000000e-03 -2.020025000000e+02 -3.500000000000e-02 8.080100000000e+01 1.400000000000e-02 1.154300000000e+01 2.000000000000e-03 -1.148528500000e+03 -1.990000000000e-01 -1.962310000000e+02 -3.400000000000e-02 -5.021205000000e+02 -8.700000000000e-02 3.462900000000e+01 6.000000000000e-03 -1.616020000000e+02 -2.800000000000e-02 5.482925000000e+02 9.500000000000e-02 5.194350000000e+01 9.000000000000e-03 6.637225000000e+02 1.150000000000e-01 6.406365000000e+02 1.110000000000e-01 7.214375000000e+02 1.250000000000e-01 -1.500590000000e+02 -2.600000000000e-02 -5.540640000000e+02 -9.600000000000e-02 1.038870000000e+02 1.800000000000e-02 2.308600000000e+01 4.000000000000e-03 -1.154300000000e+01 -2.000000000000e-03 -8.657250000000e+01 -1.500000000000e-02 2.308600000000e+01 4.000000000000e-03 2.308600000000e+01 4.000000000000e-03 4.097765000000e+02 7.100000000000e-02 1.038870000000e+04 1.800000000000e+00 7.156660000000e+02 1.240000000000e-01 + 2 EWK_RAP 3.150000000000e-01 6.463838404000e+03 7.000000000000e+03 5.768700000000e+05 6.209428680000e+02 8.455760460000e+02 1.465800000000e-01 -9.229920000000e+01 -1.600000000000e-02 1.153740000000e+01 2.000000000000e-03 1.153740000000e+01 2.000000000000e-03 5.768700000000e+00 1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.884350000000e+01 5.000000000000e-03 -6.922440000000e+01 -1.200000000000e-02 6.691692000000e+02 1.160000000000e-01 1.488324600000e+03 2.580000000000e-01 -5.768700000000e+00 -1.000000000000e-03 -4.614960000000e+01 -8.000000000000e-03 1.961358000000e+02 3.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.634005000000e+02 1.150000000000e-01 5.191830000000e+01 9.000000000000e-03 1.730610000000e+01 3.000000000000e-03 4.038090000000e+01 7.000000000000e-03 1.153740000000e+02 2.000000000000e-02 6.345570000000e+01 1.100000000000e-02 -8.076180000000e+01 -1.400000000000e-02 -1.153740000000e+01 -2.000000000000e-03 -1.153740000000e+01 -2.000000000000e-03 -2.307480000000e+01 -4.000000000000e-03 -5.768700000000e+00 -1.000000000000e-03 4.038090000000e+01 7.000000000000e-03 -2.884350000000e+01 -5.000000000000e-03 3.461220000000e+01 6.000000000000e-03 -4.038090000000e+01 -7.000000000000e-03 2.307480000000e+01 4.000000000000e-03 4.038090000000e+01 7.000000000000e-03 -1.730610000000e+01 -3.000000000000e-03 2.884350000000e+01 5.000000000000e-03 1.730610000000e+01 3.000000000000e-03 5.768700000000e+00 1.000000000000e-03 -2.307480000000e+01 -4.000000000000e-03 9.806790000000e+01 1.700000000000e-02 8.653050000000e+01 1.500000000000e-02 1.153740000000e+01 2.000000000000e-03 5.191830000000e+01 9.000000000000e-03 2.538228000000e+02 4.400000000000e-02 1.499862000000e+02 2.600000000000e-02 1.730610000000e+01 3.000000000000e-03 -6.345570000000e+01 -1.100000000000e-02 2.307480000000e+01 4.000000000000e-03 7.499310000000e+01 1.300000000000e-02 1.153740000000e+01 2.000000000000e-03 2.307480000000e+01 4.000000000000e-03 -2.884350000000e+01 -5.000000000000e-03 8.653050000000e+01 1.500000000000e-02 2.884350000000e+01 5.000000000000e-03 1.672923000000e+02 2.900000000000e-02 -1.096053000000e+02 -1.900000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.557549000000e+02 -2.700000000000e-02 -1.384488000000e+02 -2.400000000000e-02 2.884350000000e+01 5.000000000000e-03 1.730610000000e+02 3.000000000000e-02 -1.153740000000e+02 -2.000000000000e-02 1.153740000000e+01 2.000000000000e-03 -1.096053000000e+02 -1.900000000000e-02 5.191830000000e+01 9.000000000000e-03 2.884350000000e+01 5.000000000000e-03 -5.768700000000e+00 -1.000000000000e-03 2.307480000000e+01 4.000000000000e-03 2.307480000000e+01 4.000000000000e-03 1.672923000000e+02 2.900000000000e-02 -9.806790000000e+01 -1.700000000000e-02 -2.480541000000e+02 -4.300000000000e-02 -7.499310000000e+01 -1.300000000000e-02 -0.000000000000e+00 -0.000000000000e+00 1.499862000000e+02 2.600000000000e-02 1.096053000000e+02 1.900000000000e-02 -2.884350000000e+01 -5.000000000000e-03 5.768700000000e+00 1.000000000000e-03 -7.499310000000e+01 -1.300000000000e-02 -5.768700000000e+01 -1.000000000000e-02 -7.499310000000e+01 -1.300000000000e-02 -2.307480000000e+02 -4.000000000000e-02 3.461220000000e+02 6.000000000000e-02 -5.191830000000e+01 -9.000000000000e-03 -3.461220000000e+02 -6.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.153740000000e+01 -2.000000000000e-03 1.384488000000e+02 2.400000000000e-02 2.884350000000e+01 5.000000000000e-03 8.076180000000e+01 1.400000000000e-02 4.038090000000e+01 7.000000000000e-03 3.461220000000e+01 6.000000000000e-03 1.153740000000e+01 2.000000000000e-03 -5.768700000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 2.249793000000e+02 3.900000000000e-02 -1.730610000000e+01 -3.000000000000e-03 3.461220000000e+01 6.000000000000e-03 -3.461220000000e+01 -6.000000000000e-03 -4.614960000000e+01 -8.000000000000e-03 -9.229920000000e+01 -1.600000000000e-02 8.653050000000e+01 1.500000000000e-02 6.345570000000e+01 1.100000000000e-02 2.884350000000e+01 5.000000000000e-03 -1.730610000000e+01 -3.000000000000e-03 -5.768700000000e+00 -1.000000000000e-03 5.768700000000e+00 1.000000000000e-03 -4.038090000000e+01 -7.000000000000e-03 -1.130665200000e+03 -1.960000000000e-01 -2.365167000000e+02 -4.100000000000e-02 -4.961082000000e+02 -8.600000000000e-02 9.229920000000e+01 1.600000000000e-02 2.307480000000e+01 4.000000000000e-03 9.979851000000e+02 1.730000000000e-01 9.229920000000e+01 1.600000000000e-02 6.403257000000e+02 1.110000000000e-01 5.941761000000e+02 1.030000000000e-01 6.749379000000e+02 1.170000000000e-01 -1.326801000000e+02 -2.300000000000e-02 -3.172785000000e+02 -5.500000000000e-02 2.307480000000e+01 4.000000000000e-03 4.614960000000e+01 8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.557549000000e+02 -2.700000000000e-02 4.038090000000e+01 7.000000000000e-03 -6.345570000000e+01 -1.100000000000e-02 1.845984000000e+02 3.200000000000e-02 1.038366000000e+04 1.800000000000e+00 6.634005000000e+02 1.150000000000e-01 + 3 EWK_RAP 5.250000000000e-01 6.463838404000e+03 7.000000000000e+03 5.817500000000e+05 5.346224325000e+02 7.192757000000e+02 1.236400000000e-01 -2.152475000000e+02 -3.700000000000e-02 2.327000000000e+01 4.000000000000e-03 1.745250000000e+01 3.000000000000e-03 -5.817500000000e+00 -1.000000000000e-03 1.163500000000e+01 2.000000000000e-03 7.562750000000e+01 1.300000000000e-02 -1.279850000000e+02 -2.200000000000e-02 7.853625000000e+02 1.350000000000e-01 1.320572500000e+03 2.270000000000e-01 -2.617875000000e+02 -4.500000000000e-02 -1.047150000000e+02 -1.800000000000e-02 1.919775000000e+02 3.300000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.631950000000e+02 1.140000000000e-01 5.235750000000e+01 9.000000000000e-03 1.745250000000e+01 3.000000000000e-03 3.490500000000e+01 6.000000000000e-03 1.047150000000e+02 1.800000000000e-02 6.399250000000e+01 1.100000000000e-02 -2.327000000000e+01 -4.000000000000e-03 -1.745250000000e+01 -3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.327000000000e+01 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.490500000000e+01 6.000000000000e-03 -4.072250000000e+01 -7.000000000000e-03 2.908750000000e+01 5.000000000000e-03 -1.745250000000e+01 -3.000000000000e-03 1.745250000000e+01 3.000000000000e-03 -4.072250000000e+01 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 8.726250000000e+01 1.500000000000e-02 5.817500000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -2.908750000000e+01 -5.000000000000e-03 1.047150000000e+02 1.800000000000e-02 2.327000000000e+01 4.000000000000e-03 -2.385175000000e+02 -4.100000000000e-02 2.094300000000e+02 3.600000000000e-02 1.861600000000e+02 3.200000000000e-02 6.399250000000e+01 1.100000000000e-02 -5.817500000000e+00 -1.000000000000e-03 -8.726250000000e+01 -1.500000000000e-02 -2.908750000000e+01 -5.000000000000e-03 5.817500000000e+01 1.000000000000e-02 -1.163500000000e+01 -2.000000000000e-03 -2.327000000000e+01 -4.000000000000e-03 -1.745250000000e+01 -3.000000000000e-03 4.072250000000e+01 7.000000000000e-03 5.817500000000e+00 1.000000000000e-03 1.745250000000e+02 3.000000000000e-02 -1.221675000000e+02 -2.100000000000e-02 5.817500000000e+00 1.000000000000e-03 -1.512550000000e+02 -2.600000000000e-02 -1.512550000000e+02 -2.600000000000e-02 5.235750000000e+01 9.000000000000e-03 9.889750000000e+01 1.700000000000e-02 5.817500000000e+00 1.000000000000e-03 2.908750000000e+01 5.000000000000e-03 -5.817500000000e+00 -1.000000000000e-03 1.687075000000e+02 2.900000000000e-02 9.308000000000e+01 1.600000000000e-02 -4.654000000000e+01 -8.000000000000e-03 -6.981000000000e+01 -1.200000000000e-02 -9.889750000000e+01 -1.700000000000e-02 3.490500000000e+01 6.000000000000e-03 -9.308000000000e+01 -1.600000000000e-02 -3.839550000000e+02 -6.600000000000e-02 -4.654000000000e+01 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.268825000000e+02 3.900000000000e-02 1.977950000000e+02 3.400000000000e-02 4.072250000000e+01 7.000000000000e-03 -1.745250000000e+01 -3.000000000000e-03 -5.817500000000e+00 -1.000000000000e-03 -5.817500000000e+00 -1.000000000000e-03 -5.235750000000e+01 -9.000000000000e-03 -3.432325000000e+02 -5.900000000000e-02 3.665025000000e+02 6.300000000000e-02 1.163500000000e+01 2.000000000000e-03 -8.726250000000e+01 -1.500000000000e-02 -9.889750000000e+01 -1.700000000000e-02 4.072250000000e+01 7.000000000000e-03 -1.163500000000e+01 -2.000000000000e-03 7.562750000000e+01 1.300000000000e-02 9.889750000000e+01 1.700000000000e-02 3.490500000000e+01 6.000000000000e-03 2.327000000000e+01 4.000000000000e-03 5.817500000000e+00 1.000000000000e-03 -1.163500000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 8.144500000000e+01 1.400000000000e-02 -5.817500000000e+00 -1.000000000000e-03 5.817500000000e+00 1.000000000000e-03 -2.908750000000e+01 -5.000000000000e-03 -8.726250000000e+01 -1.500000000000e-02 -9.308000000000e+01 -1.600000000000e-02 5.235750000000e+01 9.000000000000e-03 -1.163500000000e+01 -2.000000000000e-03 5.817500000000e+01 1.000000000000e-02 2.327000000000e+01 4.000000000000e-03 -5.817500000000e+00 -1.000000000000e-03 -1.163500000000e+01 -2.000000000000e-03 -5.817500000000e+01 -1.000000000000e-02 -1.169317500000e+03 -2.010000000000e-01 -2.036125000000e+02 -3.500000000000e-02 -4.886700000000e+02 -8.400000000000e-02 2.908750000000e+01 5.000000000000e-03 1.745250000000e+01 3.000000000000e-03 7.562750000000e+02 1.300000000000e-01 1.338025000000e+02 2.300000000000e-02 6.748300000000e+02 1.160000000000e-01 6.224725000000e+02 1.070000000000e-01 6.224725000000e+02 1.070000000000e-01 -5.235750000000e+01 -9.000000000000e-03 -4.421300000000e+02 -7.600000000000e-02 1.221675000000e+02 2.100000000000e-02 1.803425000000e+02 3.100000000000e-02 5.817500000000e+00 1.000000000000e-03 1.687075000000e+02 2.900000000000e-02 -5.817500000000e+00 -1.000000000000e-03 3.199625000000e+02 5.500000000000e-02 4.595825000000e+02 7.900000000000e-02 1.047150000000e+04 1.800000000000e+00 6.050200000000e+02 1.040000000000e-01 + 4 EWK_RAP 7.350000000000e-01 6.463838404000e+03 7.000000000000e+03 5.860700000000e+05 5.851322880000e+02 6.731013950000e+02 1.148500000000e-01 -4.102490000000e+01 -7.000000000000e-03 5.274630000000e+01 9.000000000000e-03 2.344280000000e+01 4.000000000000e-03 5.860700000000e+00 1.000000000000e-03 5.860700000000e+00 1.000000000000e-03 5.860700000000e+01 1.000000000000e-02 -8.791050000000e+01 -1.500000000000e-02 7.618910000000e+02 1.300000000000e-01 1.213164900000e+03 2.070000000000e-01 -4.922988000000e+02 -8.400000000000e-02 -1.523782000000e+02 -2.600000000000e-02 1.816817000000e+02 3.100000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.622591000000e+02 1.130000000000e-01 5.274630000000e+01 9.000000000000e-03 1.758210000000e+01 3.000000000000e-03 4.102490000000e+01 7.000000000000e-03 9.963190000000e+01 1.700000000000e-02 6.446770000000e+01 1.100000000000e-02 -2.344280000000e+01 -4.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 -2.344280000000e+01 -4.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 2.344280000000e+01 4.000000000000e-03 -1.758210000000e+01 -3.000000000000e-03 5.860700000000e+00 1.000000000000e-03 -1.172140000000e+01 -2.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 -1.758210000000e+01 -3.000000000000e-03 -7.032840000000e+01 -1.200000000000e-02 1.172140000000e+01 2.000000000000e-03 1.758210000000e+01 3.000000000000e-03 1.172140000000e+01 2.000000000000e-03 1.406568000000e+02 2.400000000000e-02 3.164778000000e+02 5.400000000000e-02 8.791050000000e+01 1.500000000000e-02 -7.032840000000e+01 -1.200000000000e-02 1.172140000000e+01 2.000000000000e-03 9.377120000000e+01 1.600000000000e-02 8.791050000000e+01 1.500000000000e-02 -5.860700000000e+00 -1.000000000000e-03 -5.860700000000e+01 -1.000000000000e-02 5.860700000000e+00 1.000000000000e-03 2.344280000000e+01 4.000000000000e-03 1.758210000000e+01 3.000000000000e-03 -2.344280000000e+01 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.344280000000e+01 4.000000000000e-03 1.758210000000e+01 3.000000000000e-03 1.758210000000e+02 3.000000000000e-02 -1.230747000000e+02 -2.100000000000e-02 1.172140000000e+01 2.000000000000e-03 -1.875424000000e+02 -3.200000000000e-02 -1.465175000000e+02 -2.500000000000e-02 9.377120000000e+01 1.600000000000e-02 -2.109852000000e+02 -3.600000000000e-02 4.688560000000e+01 8.000000000000e-03 4.102490000000e+01 7.000000000000e-03 1.054926000000e+02 1.800000000000e-02 1.523782000000e+02 2.600000000000e-02 2.051245000000e+02 3.500000000000e-02 -8.791050000000e+01 -1.500000000000e-02 -1.582389000000e+02 -2.700000000000e-02 4.688560000000e+01 8.000000000000e-03 2.285673000000e+02 3.900000000000e-02 -8.204980000000e+01 -1.400000000000e-02 -9.963190000000e+01 -1.700000000000e-02 -1.113533000000e+02 -1.900000000000e-02 0.000000000000e+00 0.000000000000e+00 2.871743000000e+02 4.900000000000e-02 2.754529000000e+02 4.700000000000e-02 1.113533000000e+02 1.900000000000e-02 -7.618910000000e+01 -1.300000000000e-02 2.402887000000e+02 4.100000000000e-02 1.113533000000e+02 1.900000000000e-02 -3.340599000000e+02 -5.700000000000e-02 1.875424000000e+02 3.200000000000e-02 3.809455000000e+02 6.500000000000e-02 2.461494000000e+02 4.200000000000e-02 -2.344280000000e+01 -4.000000000000e-03 3.516420000000e+01 6.000000000000e-03 -1.054926000000e+02 -1.800000000000e-02 -7.032840000000e+01 -1.200000000000e-02 2.109852000000e+02 3.600000000000e-02 1.289354000000e+02 2.200000000000e-02 3.516420000000e+01 6.000000000000e-03 1.172140000000e+01 2.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 -5.860700000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 2.930350000000e+01 5.000000000000e-03 7.032840000000e+01 1.200000000000e-02 4.688560000000e+01 8.000000000000e-03 4.102490000000e+01 7.000000000000e-03 -1.758210000000e+01 -3.000000000000e-03 4.688560000000e+01 8.000000000000e-03 -1.523782000000e+02 -2.600000000000e-02 -7.618910000000e+01 -1.300000000000e-02 7.618910000000e+01 1.300000000000e-02 -5.860700000000e+01 -1.000000000000e-02 1.758210000000e+01 3.000000000000e-03 -1.758210000000e+01 -3.000000000000e-03 3.516420000000e+01 6.000000000000e-03 -1.201443500000e+03 -2.050000000000e-01 -3.575027000000e+02 -6.100000000000e-02 -5.098809000000e+02 -8.700000000000e-02 -7.032840000000e+01 -1.200000000000e-02 -1.172140000000e+02 -2.000000000000e-02 8.146373000000e+02 1.390000000000e-01 9.963190000000e+01 1.700000000000e-02 6.681198000000e+02 1.140000000000e-01 7.384482000000e+02 1.260000000000e-01 6.739805000000e+02 1.150000000000e-01 -1.523782000000e+02 -2.600000000000e-02 -4.981595000000e+02 -8.500000000000e-02 2.227066000000e+02 3.800000000000e-02 1.406568000000e+02 2.400000000000e-02 1.172140000000e+01 2.000000000000e-03 3.575027000000e+02 6.100000000000e-02 3.516420000000e+01 6.000000000000e-03 4.688560000000e+01 8.000000000000e-03 2.988957000000e+02 5.100000000000e-02 1.054926000000e+04 1.800000000000e+00 7.501696000000e+02 1.280000000000e-01 + 5 EWK_RAP 9.450000000000e-01 6.463838404000e+03 7.000000000000e+03 5.863300000000e+05 6.058547890000e+02 8.474813820000e+02 1.445400000000e-01 2.345320000000e+01 4.000000000000e-03 7.622290000000e+01 1.300000000000e-02 2.931650000000e+01 5.000000000000e-03 5.863300000000e+00 1.000000000000e-03 5.863300000000e+00 1.000000000000e-03 7.035960000000e+01 1.200000000000e-02 -9.381280000000e+01 -1.600000000000e-02 8.970849000000e+02 1.530000000000e-01 1.108163700000e+03 1.890000000000e-01 -6.860061000000e+02 -1.170000000000e-01 -1.817623000000e+02 -3.100000000000e-02 1.641724000000e+02 2.800000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.625529000000e+02 1.130000000000e-01 4.690640000000e+01 8.000000000000e-03 1.758990000000e+01 3.000000000000e-03 3.517980000000e+01 6.000000000000e-03 9.381280000000e+01 1.600000000000e-02 6.449630000000e+01 1.100000000000e-02 -5.863300000000e+00 -1.000000000000e-03 -5.863300000000e+00 -1.000000000000e-03 5.863300000000e+00 1.000000000000e-03 -1.172660000000e+02 -2.000000000000e-02 -1.758990000000e+01 -3.000000000000e-03 1.758990000000e+01 3.000000000000e-03 1.172660000000e+01 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -5.863300000000e+00 -1.000000000000e-03 -5.863300000000e+00 -1.000000000000e-03 -5.863300000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.172660000000e+01 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.172660000000e+01 2.000000000000e-03 -2.521219000000e+02 -4.300000000000e-02 2.579852000000e+02 4.400000000000e-02 5.276970000000e+01 9.000000000000e-03 -6.449630000000e+01 -1.100000000000e-02 -0.000000000000e+00 -0.000000000000e+00 7.035960000000e+01 1.200000000000e-02 4.690640000000e+01 8.000000000000e-03 -2.931650000000e+01 -5.000000000000e-03 -4.690640000000e+01 -8.000000000000e-03 -5.863300000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.172660000000e+01 2.000000000000e-03 -4.690640000000e+01 -8.000000000000e-03 1.172660000000e+01 2.000000000000e-03 5.863300000000e+00 1.000000000000e-03 3.517980000000e+01 6.000000000000e-03 1.817623000000e+02 3.100000000000e-02 -1.289926000000e+02 -2.200000000000e-02 1.758990000000e+01 3.000000000000e-03 -8.208620000000e+01 -1.400000000000e-02 -9.381280000000e+01 -1.600000000000e-02 9.967610000000e+01 1.700000000000e-02 -1.524458000000e+02 -2.600000000000e-02 -1.758990000000e+01 -3.000000000000e-03 5.863300000000e+01 1.000000000000e-02 1.289926000000e+02 2.200000000000e-02 7.622290000000e+01 1.300000000000e-02 2.462586000000e+02 4.200000000000e-02 -1.465825000000e+02 -2.500000000000e-02 -3.517980000000e+01 -6.000000000000e-03 2.345320000000e+01 4.000000000000e-03 3.517980000000e+01 6.000000000000e-03 1.172660000000e+01 2.000000000000e-03 -1.700357000000e+02 -2.900000000000e-02 -2.931650000000e+01 -5.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.934889000000e+02 3.300000000000e-02 1.758990000000e+02 3.000000000000e-02 8.208620000000e+01 1.400000000000e-02 -1.172660000000e+01 -2.000000000000e-03 4.104310000000e+01 7.000000000000e-03 1.172660000000e+01 2.000000000000e-03 1.524458000000e+02 2.600000000000e-02 2.052155000000e+02 3.500000000000e-02 3.459347000000e+02 5.900000000000e-02 -3.517980000000e+02 -6.000000000000e-02 3.283448000000e+02 5.600000000000e-02 9.381280000000e+01 1.600000000000e-02 -2.931650000000e+01 -5.000000000000e-03 -7.622290000000e+01 -1.300000000000e-02 -1.231293000000e+02 -2.100000000000e-02 1.348559000000e+02 2.300000000000e-02 2.931650000000e+01 5.000000000000e-03 1.172660000000e+01 2.000000000000e-03 5.863300000000e+00 1.000000000000e-03 -1.172660000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.055394000000e+02 -1.800000000000e-02 -3.517980000000e+01 -6.000000000000e-03 9.381280000000e+01 1.600000000000e-02 -4.690640000000e+01 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 8.794950000000e+01 1.500000000000e-02 -1.172660000000e+01 -2.000000000000e-03 -1.934889000000e+02 -3.300000000000e-02 7.035960000000e+01 1.200000000000e-02 -7.622290000000e+01 -1.300000000000e-02 4.690640000000e+01 8.000000000000e-03 -1.758990000000e+01 -3.000000000000e-03 8.794950000000e+01 1.500000000000e-02 -1.190249900000e+03 -2.030000000000e-01 -9.381280000000e+01 -1.600000000000e-02 -5.218337000000e+02 -8.900000000000e-02 1.641724000000e+02 2.800000000000e-02 2.931650000000e+01 5.000000000000e-03 7.094593000000e+02 1.210000000000e-01 8.794950000000e+01 1.500000000000e-02 7.094593000000e+02 1.210000000000e-01 8.091354000000e+02 1.380000000000e-01 6.508263000000e+02 1.110000000000e-01 -8.794950000000e+01 -1.500000000000e-02 -1.993522000000e+02 -3.400000000000e-02 1.993522000000e+02 3.400000000000e-02 4.690640000000e+02 8.000000000000e-02 1.172660000000e+01 2.000000000000e-03 -5.511502000000e+02 -9.400000000000e-02 2.052155000000e+02 3.500000000000e-02 -1.348559000000e+02 -2.300000000000e-02 -2.228054000000e+02 -3.800000000000e-02 1.055394000000e+04 1.800000000000e+00 7.387758000000e+02 1.260000000000e-01 + 6 EWK_RAP 1.210000000000e+00 6.463838404000e+03 7.000000000000e+03 5.990700000000e+05 4.668013347000e+02 7.669294140000e+02 1.280200000000e-01 1.138233000000e+02 1.900000000000e-02 1.377861000000e+02 2.300000000000e-02 5.391630000000e+01 9.000000000000e-03 5.990700000000e+00 1.000000000000e-03 -5.990700000000e+00 -1.000000000000e-03 1.377861000000e+02 2.300000000000e-02 -1.258047000000e+02 -2.100000000000e-02 7.308654000000e+02 1.220000000000e-01 1.006437600000e+03 1.680000000000e-01 -8.746422000000e+02 -1.460000000000e-01 -2.336373000000e+02 -3.900000000000e-02 1.437768000000e+02 2.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.649677000000e+02 1.110000000000e-01 4.792560000000e+01 8.000000000000e-03 1.797210000000e+01 3.000000000000e-03 3.594420000000e+01 6.000000000000e-03 7.787910000000e+01 1.300000000000e-02 5.990700000000e+01 1.000000000000e-02 1.198140000000e+01 2.000000000000e-03 5.990700000000e+00 1.000000000000e-03 1.557582000000e+02 2.600000000000e-02 1.198140000000e+01 2.000000000000e-03 -1.198140000000e+01 -2.000000000000e-03 1.797210000000e+01 3.000000000000e-03 1.797210000000e+01 3.000000000000e-03 -1.198140000000e+01 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -5.990700000000e+00 -1.000000000000e-03 -5.990700000000e+00 -1.000000000000e-03 1.198140000000e+01 2.000000000000e-03 -5.990700000000e+00 -1.000000000000e-03 1.797210000000e+01 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 8.986050000000e+01 1.500000000000e-02 -5.990700000000e+00 -1.000000000000e-03 -6.589770000000e+01 -1.100000000000e-02 1.198140000000e+01 2.000000000000e-03 1.198140000000e+01 2.000000000000e-03 5.391630000000e+01 9.000000000000e-03 -2.995350000000e+01 -5.000000000000e-03 -2.995350000000e+01 -5.000000000000e-03 4.792560000000e+01 8.000000000000e-03 -1.198140000000e+01 -2.000000000000e-03 4.792560000000e+01 8.000000000000e-03 -2.396280000000e+02 -4.000000000000e-02 -5.990700000000e+00 -1.000000000000e-03 7.787910000000e+01 1.300000000000e-02 3.594420000000e+01 6.000000000000e-03 1.677396000000e+02 2.800000000000e-02 -1.198140000000e+02 -2.000000000000e-02 2.396280000000e+01 4.000000000000e-03 -9.585120000000e+01 -1.600000000000e-02 1.497675000000e+02 2.500000000000e-02 1.377861000000e+02 2.300000000000e-02 -2.156652000000e+02 -3.600000000000e-02 1.198140000000e+01 2.000000000000e-03 8.386980000000e+01 1.400000000000e-02 1.258047000000e+02 2.100000000000e-02 -3.594420000000e+01 -6.000000000000e-03 -2.995350000000e+02 -5.000000000000e-02 1.677396000000e+02 2.800000000000e-02 -8.386980000000e+01 -1.400000000000e-02 0.000000000000e+00 0.000000000000e+00 4.792560000000e+01 8.000000000000e-03 -2.216559000000e+02 -3.700000000000e-02 -2.576001000000e+02 -4.300000000000e-02 -6.589770000000e+01 -1.100000000000e-02 0.000000000000e+00 0.000000000000e+00 2.096745000000e+02 3.500000000000e-02 1.617489000000e+02 2.700000000000e-02 9.585120000000e+01 1.600000000000e-02 5.990700000000e+00 1.000000000000e-03 2.396280000000e+01 4.000000000000e-03 2.995350000000e+01 5.000000000000e-03 3.714234000000e+02 6.200000000000e-02 6.589770000000e+01 1.100000000000e-02 1.976931000000e+02 3.300000000000e-02 -8.386980000000e+01 -1.400000000000e-02 1.138233000000e+02 1.900000000000e-02 1.677396000000e+02 2.800000000000e-02 -2.396280000000e+01 -4.000000000000e-03 -6.589770000000e+01 -1.100000000000e-02 -1.497675000000e+02 -2.500000000000e-02 1.317954000000e+02 2.200000000000e-02 5.391630000000e+01 9.000000000000e-03 5.990700000000e+00 1.000000000000e-03 -5.990700000000e+00 -1.000000000000e-03 -1.198140000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -3.055257000000e+02 -5.100000000000e-02 1.797210000000e+01 3.000000000000e-03 2.995350000000e+01 5.000000000000e-03 -2.396280000000e+01 -4.000000000000e-03 2.995350000000e+01 5.000000000000e-03 5.990700000000e+01 1.000000000000e-02 7.787910000000e+01 1.300000000000e-02 -1.018419000000e+02 -1.700000000000e-02 9.585120000000e+01 1.600000000000e-02 -1.797210000000e+01 -3.000000000000e-03 -2.995350000000e+01 -5.000000000000e-03 -1.198140000000e+01 -2.000000000000e-03 -5.990700000000e+00 -1.000000000000e-03 -1.264037700000e+03 -2.110000000000e-01 -1.557582000000e+02 -2.600000000000e-02 -5.451537000000e+02 -9.100000000000e-02 7.787910000000e+01 1.300000000000e-02 3.594420000000e+01 6.000000000000e-03 7.188840000000e+02 1.200000000000e-01 1.857117000000e+02 3.100000000000e-02 7.308654000000e+02 1.220000000000e-01 8.926143000000e+02 1.490000000000e-01 7.428468000000e+02 1.240000000000e-01 1.797210000000e+01 3.000000000000e-03 -4.253397000000e+02 -7.100000000000e-02 4.193490000000e+02 7.000000000000e-02 1.617489000000e+02 2.700000000000e-02 2.995350000000e+01 5.000000000000e-03 6.410049000000e+02 1.070000000000e-01 -4.193490000000e+01 -7.000000000000e-03 2.815629000000e+02 4.700000000000e-02 -2.995350000000e+02 -5.000000000000e-02 1.078326000000e+04 1.800000000000e+00 6.230328000000e+02 1.040000000000e-01 + 7 EWK_RAP 1.445000000000e+00 6.463838404000e+03 7.000000000000e+03 5.967500000000e+05 7.952290500000e+02 1.951014450000e+03 3.269400000000e-01 -1.432200000000e+02 -2.400000000000e-02 3.103100000000e+02 5.200000000000e-02 1.133825000000e+02 1.900000000000e-02 -5.370750000000e+01 -9.000000000000e-03 -2.983750000000e+01 -5.000000000000e-03 4.057900000000e+02 6.800000000000e-02 -3.461150000000e+02 -5.800000000000e-02 7.578725000000e+02 1.270000000000e-01 1.098020000000e+03 1.840000000000e-01 -5.132050000000e+02 -8.600000000000e-02 -1.909600000000e+02 -3.200000000000e-02 1.133825000000e+02 1.900000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.743275000000e+02 1.130000000000e-01 4.774000000000e+01 8.000000000000e-03 1.790250000000e+01 3.000000000000e-03 3.580500000000e+01 6.000000000000e-03 5.967500000000e+01 1.000000000000e-02 6.564250000000e+01 1.100000000000e-02 4.774000000000e+01 8.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 -8.354500000000e+01 -1.400000000000e-02 2.387000000000e+01 4.000000000000e-03 -5.967500000000e+00 -1.000000000000e-03 -1.193500000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 7.757750000000e+01 1.300000000000e-02 2.983750000000e+01 5.000000000000e-03 2.685375000000e+02 4.500000000000e-02 -1.133825000000e+02 -1.900000000000e-02 4.774000000000e+01 8.000000000000e-03 -1.253175000000e+02 -2.100000000000e-02 3.580500000000e+01 6.000000000000e-03 2.387000000000e+01 4.000000000000e-03 -3.580500000000e+01 -6.000000000000e-03 -8.354500000000e+01 -1.400000000000e-02 5.370750000000e+01 9.000000000000e-03 2.983750000000e+01 5.000000000000e-03 3.580500000000e+01 6.000000000000e-03 -1.491875000000e+02 -2.500000000000e-02 5.967500000000e+00 1.000000000000e-03 -5.370750000000e+02 -9.000000000000e-02 -4.415950000000e+02 -7.400000000000e-02 6.265875000000e+02 1.050000000000e-01 3.282125000000e+02 5.500000000000e-02 -4.177250000000e+01 -7.000000000000e-03 1.790250000000e+02 3.000000000000e-02 -3.580500000000e+01 -6.000000000000e-03 -1.133825000000e+02 -1.900000000000e-02 -4.774000000000e+01 -8.000000000000e-03 1.551550000000e+02 2.600000000000e-02 -1.014475000000e+02 -1.700000000000e-02 1.790250000000e+01 3.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 6.564250000000e+01 1.100000000000e-02 4.774000000000e+01 8.000000000000e-03 -1.790250000000e+01 -3.000000000000e-03 -2.983750000000e+01 -5.000000000000e-03 7.161000000000e+01 1.200000000000e-02 1.193500000000e+01 2.000000000000e-03 8.354500000000e+01 1.400000000000e-02 1.790250000000e+01 3.000000000000e-03 -1.193500000000e+01 -2.000000000000e-03 2.387000000000e+01 4.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 2.983750000000e+01 5.000000000000e-03 -5.967500000000e+01 -1.000000000000e-02 -1.014475000000e+02 -1.700000000000e-02 -3.580500000000e+01 -6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.566025000000e+02 4.300000000000e-02 7.757750000000e+01 1.300000000000e-02 5.967500000000e+00 1.000000000000e-03 5.967500000000e+00 1.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 -5.967500000000e+00 -1.000000000000e-03 2.983750000000e+01 5.000000000000e-03 -1.790250000000e+01 -3.000000000000e-03 2.566025000000e+02 4.300000000000e-02 -4.774000000000e+01 -8.000000000000e-03 1.193500000000e+01 2.000000000000e-03 1.193500000000e+01 2.000000000000e-03 1.790250000000e+01 3.000000000000e-03 1.790250000000e+01 3.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 1.074150000000e+02 1.800000000000e-02 6.564250000000e+01 1.100000000000e-02 2.387000000000e+01 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -5.967500000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 3.580500000000e+01 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -5.967500000000e+00 -1.000000000000e-03 -5.967500000000e+00 -1.000000000000e-03 1.790250000000e+01 3.000000000000e-03 -5.967500000000e+00 -1.000000000000e-03 3.580500000000e+01 6.000000000000e-03 5.967500000000e+00 1.000000000000e-03 -1.193500000000e+01 -2.000000000000e-03 -5.967500000000e+00 -1.000000000000e-03 -2.387000000000e+01 -4.000000000000e-03 -1.271077500000e+03 -2.130000000000e-01 -1.193500000000e+02 -2.000000000000e-02 -4.356275000000e+02 -7.300000000000e-02 5.370750000000e+01 9.000000000000e-03 -7.757750000000e+01 -1.300000000000e-02 8.175475000000e+02 1.370000000000e-01 1.133825000000e+02 1.900000000000e-02 8.533525000000e+02 1.430000000000e-01 1.062215000000e+03 1.780000000000e-01 8.354500000000e+02 1.400000000000e-01 1.372525000000e+02 2.300000000000e-02 -3.580500000000e+02 -6.000000000000e-02 1.730575000000e+02 2.900000000000e-02 1.849925000000e+02 3.100000000000e-02 3.580500000000e+01 6.000000000000e-03 3.162775000000e+02 5.300000000000e-02 8.354500000000e+01 1.400000000000e-02 9.548000000000e+01 1.600000000000e-02 -4.177250000000e+01 -7.000000000000e-03 1.074150000000e+04 1.800000000000e+00 8.533525000000e+02 1.430000000000e-01 + 8 EWK_RAP 1.630000000000e+00 6.463838404000e+03 7.000000000000e+03 6.041700000000e+05 6.369160140000e+02 7.841522430000e+02 1.297900000000e-01 -3.625020000000e+01 -6.000000000000e-03 8.458380000000e+01 1.400000000000e-02 2.416680000000e+01 4.000000000000e-03 -6.041700000000e+00 -1.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 1.087506000000e+02 1.800000000000e-02 -9.666720000000e+01 -1.600000000000e-02 7.793793000000e+02 1.290000000000e-01 9.606303000000e+02 1.590000000000e-01 -1.027089000000e+03 -1.700000000000e-01 -2.718765000000e+02 -4.500000000000e-02 1.027089000000e+02 1.700000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.766704000000e+02 1.120000000000e-01 4.833360000000e+01 8.000000000000e-03 1.812510000000e+01 3.000000000000e-03 3.020850000000e+01 5.000000000000e-03 5.437530000000e+01 9.000000000000e-03 6.041700000000e+01 1.000000000000e-02 4.229190000000e+01 7.000000000000e-03 -2.416680000000e+01 -4.000000000000e-03 1.208340000000e+01 2.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -1.208340000000e+01 -2.000000000000e-03 6.041700000000e+00 1.000000000000e-03 -1.812510000000e+01 -3.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 -1.812510000000e+01 -3.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 -7.250040000000e+01 -1.200000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.812510000000e+01 -3.000000000000e-03 9.062550000000e+01 1.500000000000e-02 -1.812510000000e+01 -3.000000000000e-03 -4.833360000000e+01 -8.000000000000e-03 -1.812510000000e+01 -3.000000000000e-03 6.041700000000e+00 1.000000000000e-03 7.250040000000e+01 1.200000000000e-02 -1.812510000000e+01 -3.000000000000e-03 1.208340000000e+01 2.000000000000e-03 1.208340000000e+01 2.000000000000e-03 -3.020850000000e+01 -5.000000000000e-03 1.208340000000e+01 2.000000000000e-03 -1.510425000000e+02 -2.500000000000e-02 1.389591000000e+02 2.300000000000e-02 -1.570842000000e+02 -2.600000000000e-02 5.437530000000e+01 9.000000000000e-03 1.752093000000e+02 2.900000000000e-02 -1.329174000000e+02 -2.200000000000e-02 2.416680000000e+01 4.000000000000e-03 4.168773000000e+02 6.900000000000e-02 9.666720000000e+02 1.600000000000e-01 -2.416680000000e+01 -4.000000000000e-03 -7.250040000000e+01 -1.200000000000e-02 -1.329174000000e+02 -2.200000000000e-02 1.268757000000e+02 2.100000000000e-02 3.020850000000e+01 5.000000000000e-03 6.041700000000e+01 1.000000000000e-02 -1.208340000000e+02 -2.000000000000e-02 -5.014611000000e+02 -8.300000000000e-02 -3.625020000000e+01 -6.000000000000e-03 -1.027089000000e+02 -1.700000000000e-02 1.812510000000e+01 3.000000000000e-03 -1.752093000000e+02 -2.900000000000e-02 -3.625020000000e+02 -6.000000000000e-02 1.208340000000e+01 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 3.141684000000e+02 5.200000000000e-02 7.854210000000e+01 1.300000000000e-02 -1.812510000000e+02 -3.000000000000e-02 -6.041700000000e+01 -1.000000000000e-02 -3.625020000000e+01 -6.000000000000e-03 -6.645870000000e+01 -1.100000000000e-02 -7.250040000000e+01 -1.200000000000e-02 -2.416680000000e+01 -4.000000000000e-03 2.779182000000e+02 4.600000000000e-02 -6.041700000000e+01 -1.000000000000e-02 3.625020000000e+01 6.000000000000e-03 -3.020850000000e+01 -5.000000000000e-03 3.020850000000e+01 5.000000000000e-03 1.450008000000e+02 2.400000000000e-02 6.041700000000e+01 1.000000000000e-02 1.329174000000e+02 2.200000000000e-02 4.833360000000e+01 8.000000000000e-03 3.020850000000e+01 5.000000000000e-03 -6.041700000000e+00 -1.000000000000e-03 -1.208340000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 2.779182000000e+02 4.600000000000e-02 4.833360000000e+01 8.000000000000e-03 6.041700000000e+00 1.000000000000e-03 -1.812510000000e+01 -3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -6.041700000000e+00 -1.000000000000e-03 6.041700000000e+00 1.000000000000e-03 1.933344000000e+02 3.200000000000e-02 6.041700000000e+01 1.000000000000e-02 -1.208340000000e+01 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.208340000000e+01 -2.000000000000e-03 -3.020850000000e+01 -5.000000000000e-03 -1.305007200000e+03 -2.160000000000e-01 -1.993761000000e+02 -3.300000000000e-02 -5.618781000000e+02 -9.300000000000e-02 1.087506000000e+02 1.800000000000e-02 -2.356263000000e+02 -3.900000000000e-02 7.250040000000e+02 1.200000000000e-01 2.537514000000e+02 4.200000000000e-02 7.975044000000e+02 1.320000000000e-01 1.178131500000e+03 1.950000000000e-01 7.250040000000e+02 1.200000000000e-01 -4.833360000000e+01 -8.000000000000e-03 -5.135445000000e+02 -8.500000000000e-02 2.537514000000e+02 4.200000000000e-02 1.268757000000e+02 2.100000000000e-02 3.625020000000e+01 6.000000000000e-03 1.812510000000e+02 3.000000000000e-02 1.329174000000e+02 2.200000000000e-02 3.625020000000e+01 6.000000000000e-03 -4.833360000000e+01 -8.000000000000e-03 1.087506000000e+04 1.800000000000e+00 8.156295000000e+02 1.350000000000e-01 + 9 EWK_RAP 1.845000000000e+00 6.463838404000e+03 7.000000000000e+03 6.069300000000e+05 6.999116760000e+02 1.071656301000e+03 1.765700000000e-01 -6.069300000000e+00 -1.000000000000e-03 6.676230000000e+01 1.100000000000e-02 1.820790000000e+01 3.000000000000e-03 6.069300000000e+00 1.000000000000e-03 1.213860000000e+01 2.000000000000e-03 6.069300000000e+01 1.000000000000e-02 -5.462370000000e+01 -9.000000000000e-03 7.586625000000e+02 1.250000000000e-01 8.982564000000e+02 1.480000000000e-01 -1.122820500000e+03 -1.850000000000e-01 -2.913264000000e+02 -4.800000000000e-02 7.890090000000e+01 1.300000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.372765000000e+02 1.050000000000e-01 4.248510000000e+01 7.000000000000e-03 1.213860000000e+01 2.000000000000e-03 3.034650000000e+01 5.000000000000e-03 4.248510000000e+01 7.000000000000e-03 5.462370000000e+01 9.000000000000e-03 4.855440000000e+01 8.000000000000e-03 -2.427720000000e+01 -4.000000000000e-03 1.820790000000e+01 3.000000000000e-03 -1.213860000000e+01 -2.000000000000e-03 -6.069300000000e+00 -1.000000000000e-03 6.069300000000e+00 1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.820790000000e+01 -3.000000000000e-03 6.676230000000e+01 1.100000000000e-02 -1.213860000000e+01 -2.000000000000e-03 6.069300000000e+00 1.000000000000e-03 -1.213860000000e+01 -2.000000000000e-03 1.213860000000e+01 2.000000000000e-03 -1.820790000000e+01 -3.000000000000e-03 1.213860000000e+01 2.000000000000e-03 -6.069300000000e+00 -1.000000000000e-03 1.092474000000e+02 1.800000000000e-02 -1.820790000000e+01 -3.000000000000e-03 -2.427720000000e+01 -4.000000000000e-03 -2.427720000000e+01 -4.000000000000e-03 -1.213860000000e+01 -2.000000000000e-03 2.427720000000e+01 4.000000000000e-03 -6.676230000000e+01 -1.100000000000e-02 -9.710880000000e+01 -1.600000000000e-02 -3.641580000000e+01 -6.000000000000e-03 -1.213860000000e+02 -2.000000000000e-02 -1.031781000000e+02 -1.700000000000e-02 -1.274553000000e+02 -2.100000000000e-02 4.855440000000e+01 8.000000000000e-03 -2.427720000000e+01 -4.000000000000e-03 3.034650000000e+01 5.000000000000e-03 1.760097000000e+02 2.900000000000e-02 -1.335246000000e+02 -2.200000000000e-02 3.034650000000e+01 5.000000000000e-03 3.641580000000e+01 6.000000000000e-03 -3.034650000000e+01 -5.000000000000e-03 2.245641000000e+02 3.700000000000e-02 7.890090000000e+01 1.300000000000e-02 -1.395939000000e+02 -2.300000000000e-02 1.092474000000e+02 1.800000000000e-02 -3.034650000000e+01 -5.000000000000e-03 2.002869000000e+02 3.300000000000e-02 1.820790000000e+01 3.000000000000e-03 -1.274553000000e+02 -2.100000000000e-02 -8.497020000000e+01 -1.400000000000e-02 -1.335246000000e+02 -2.200000000000e-02 -1.153167000000e+02 -1.900000000000e-02 3.641580000000e+01 6.000000000000e-03 1.037850300000e+03 1.710000000000e-01 -8.497020000000e+01 -1.400000000000e-02 0.000000000000e+00 0.000000000000e+00 2.245641000000e+02 3.700000000000e-02 2.367027000000e+02 3.900000000000e-02 -1.517325000000e+02 -2.500000000000e-02 1.456632000000e+02 2.400000000000e-02 -1.578018000000e+02 -2.600000000000e-02 3.034650000000e+02 5.000000000000e-02 6.069300000000e+00 1.000000000000e-03 -5.462370000000e+01 -9.000000000000e-03 3.156036000000e+02 5.200000000000e-02 -9.710880000000e+01 -1.600000000000e-02 7.283160000000e+01 1.200000000000e-02 -2.913264000000e+02 -4.800000000000e-02 1.820790000000e+01 3.000000000000e-03 -9.710880000000e+01 -1.600000000000e-02 -6.069300000000e+00 -1.000000000000e-03 1.395939000000e+02 2.300000000000e-02 3.034650000000e+01 5.000000000000e-03 4.855440000000e+01 8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -6.069300000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.820790000000e+01 3.000000000000e-03 1.820790000000e+01 3.000000000000e-03 8.497020000000e+01 1.400000000000e-02 1.395939000000e+02 2.300000000000e-02 4.248510000000e+01 7.000000000000e-03 -3.641580000000e+01 -6.000000000000e-03 5.462370000000e+01 9.000000000000e-03 -1.820790000000e+01 -3.000000000000e-03 5.462370000000e+01 9.000000000000e-03 1.578018000000e+02 2.600000000000e-02 -4.248510000000e+01 -7.000000000000e-03 -1.153167000000e+02 -1.900000000000e-02 6.069300000000e+00 1.000000000000e-03 -1.056058200000e+03 -1.740000000000e-01 -1.456632000000e+02 -2.400000000000e-02 -5.098212000000e+02 -8.400000000000e-02 3.641580000000e+01 6.000000000000e-03 -1.760097000000e+02 -2.900000000000e-02 7.161774000000e+02 1.180000000000e-01 2.609799000000e+02 4.300000000000e-02 6.919002000000e+02 1.140000000000e-01 1.347384600000e+03 2.220000000000e-01 6.797616000000e+02 1.120000000000e-01 1.213860000000e+01 2.000000000000e-03 -7.404546000000e+02 -1.220000000000e-01 2.549106000000e+02 4.200000000000e-02 2.367027000000e+02 3.900000000000e-02 4.248510000000e+01 7.000000000000e-03 3.823659000000e+02 6.300000000000e-02 1.213860000000e+02 2.000000000000e-02 1.820790000000e+02 3.000000000000e-02 7.890090000000e+01 1.300000000000e-02 1.092474000000e+04 1.800000000000e+00 1.019642400000e+03 1.680000000000e-01 + 10 EWK_RAP 2.065000000000e+00 6.463838404000e+03 7.000000000000e+03 5.934000000000e+05 6.707793600000e+02 8.547927000000e+02 1.440500000000e-01 -2.373600000000e+01 -4.000000000000e-03 3.560400000000e+01 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -5.934000000000e+00 -1.000000000000e-03 -1.780200000000e+01 -3.000000000000e-03 2.967000000000e+01 5.000000000000e-03 -2.967000000000e+01 -5.000000000000e-03 7.773540000000e+02 1.310000000000e-01 8.485620000000e+02 1.430000000000e-01 -1.145262000000e+03 -1.930000000000e-01 -2.848320000000e+02 -4.800000000000e-02 5.934000000000e+01 1.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.230700000000e+02 1.050000000000e-01 4.153800000000e+01 7.000000000000e-03 1.186800000000e+01 2.000000000000e-03 2.373600000000e+01 4.000000000000e-03 2.967000000000e+01 5.000000000000e-03 5.340600000000e+01 9.000000000000e-03 4.747200000000e+01 8.000000000000e-03 -2.373600000000e+01 -4.000000000000e-03 2.967000000000e+01 5.000000000000e-03 -1.780200000000e+01 -3.000000000000e-03 3.560400000000e+01 6.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 1.186800000000e+01 2.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 1.186800000000e+01 2.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 5.934000000000e+00 1.000000000000e-03 -2.373600000000e+01 -4.000000000000e-03 1.780200000000e+01 3.000000000000e-03 -1.780200000000e+01 -3.000000000000e-03 1.246140000000e+02 2.100000000000e-02 -3.560400000000e+01 -6.000000000000e-03 -4.747200000000e+01 -8.000000000000e-03 -5.934000000000e+00 -1.000000000000e-03 1.186800000000e+01 2.000000000000e-03 2.967000000000e+01 5.000000000000e-03 -7.120800000000e+01 -1.200000000000e-02 -5.340600000000e+01 -9.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.246140000000e+02 -2.100000000000e-02 5.934000000000e+01 1.000000000000e-02 -1.127460000000e+02 -1.900000000000e-02 2.967000000000e+01 5.000000000000e-03 -5.340600000000e+01 -9.000000000000e-03 2.373600000000e+01 4.000000000000e-03 1.720860000000e+02 2.900000000000e-02 -1.305480000000e+02 -2.200000000000e-02 2.967000000000e+01 5.000000000000e-03 5.340600000000e+01 9.000000000000e-03 -1.780200000000e+02 -3.000000000000e-02 2.136240000000e+02 3.600000000000e-02 1.068120000000e+02 1.800000000000e-02 -2.492280000000e+02 -4.200000000000e-02 1.068120000000e+02 1.800000000000e-02 -2.967000000000e+01 -5.000000000000e-03 1.661520000000e+02 2.800000000000e-02 3.323040000000e+02 5.600000000000e-02 5.934000000000e+00 1.000000000000e-03 2.076900000000e+02 3.500000000000e-02 -2.967000000000e+01 -5.000000000000e-03 3.560400000000e+01 6.000000000000e-03 1.186800000000e+02 2.000000000000e-02 3.560400000000e+02 6.000000000000e-02 5.934000000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 4.509840000000e+02 7.600000000000e-02 -2.076900000000e+02 -3.500000000000e-02 1.483500000000e+02 2.500000000000e-02 3.916440000000e+02 6.600000000000e-02 2.195580000000e+02 3.700000000000e-02 -4.035120000000e+02 -6.800000000000e-02 -3.560400000000e+01 -6.000000000000e-03 -4.747200000000e+01 -8.000000000000e-03 3.382380000000e+02 5.700000000000e-02 2.788980000000e+02 4.700000000000e-02 -1.127460000000e+02 -1.900000000000e-02 1.424160000000e+02 2.400000000000e-02 -2.017560000000e+02 -3.400000000000e-02 1.898880000000e+02 3.200000000000e-02 -2.432940000000e+02 -4.100000000000e-02 8.307600000000e+01 1.400000000000e-02 5.340600000000e+01 9.000000000000e-03 2.373600000000e+01 4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 6.527400000000e+01 1.100000000000e-02 -2.967000000000e+01 -5.000000000000e-03 -1.839540000000e+02 -3.100000000000e-02 0.000000000000e+00 0.000000000000e+00 -1.898880000000e+02 -3.200000000000e-02 4.153800000000e+01 7.000000000000e-03 -1.186800000000e+01 -2.000000000000e-03 -5.934000000000e+01 -1.000000000000e-02 3.560400000000e+01 6.000000000000e-03 7.714200000000e+01 1.300000000000e-02 5.340600000000e+01 9.000000000000e-03 2.254920000000e+02 3.800000000000e-02 -3.560400000000e+01 -6.000000000000e-03 -1.062186000000e+03 -1.790000000000e-01 -1.780200000000e+02 -3.000000000000e-02 -3.560400000000e+02 -6.000000000000e-02 1.068120000000e+02 1.800000000000e-02 -5.934000000000e+00 -1.000000000000e-03 7.892220000000e+02 1.330000000000e-01 2.551620000000e+02 4.300000000000e-02 6.112020000000e+02 1.030000000000e-01 1.269876000000e+03 2.140000000000e-01 5.518620000000e+02 9.300000000000e-02 -9.494400000000e+01 -1.600000000000e-02 -6.052680000000e+02 -1.020000000000e-01 -2.314260000000e+02 -3.900000000000e-02 4.213140000000e+02 7.100000000000e-02 5.340600000000e+01 9.000000000000e-03 4.450500000000e+02 7.500000000000e-02 1.246140000000e+02 2.100000000000e-02 -2.967000000000e+01 -5.000000000000e-03 1.839540000000e+02 3.100000000000e-02 1.068120000000e+04 1.800000000000e+00 8.841660000000e+02 1.490000000000e-01 + 11 EWK_RAP 2.340000000000e+00 6.463838404000e+03 7.000000000000e+03 5.584600000000e+05 6.570840360000e+02 8.081474660000e+02 1.447100000000e-01 -0.000000000000e+00 -0.000000000000e+00 3.909220000000e+01 7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.116920000000e+01 -2.000000000000e-03 2.233840000000e+01 4.000000000000e-03 -2.792300000000e+01 -5.000000000000e-03 9.773050000000e+02 1.750000000000e-01 7.930132000000e+02 1.420000000000e-01 -1.044320200000e+03 -1.870000000000e-01 -2.401378000000e+02 -4.300000000000e-02 3.909220000000e+01 7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.863830000000e+02 1.050000000000e-01 3.350760000000e+01 6.000000000000e-03 1.116920000000e+01 2.000000000000e-03 2.233840000000e+01 4.000000000000e-03 1.675380000000e+01 3.000000000000e-03 5.026140000000e+01 9.000000000000e-03 3.350760000000e+01 6.000000000000e-03 -1.675380000000e+01 -3.000000000000e-03 2.233840000000e+01 4.000000000000e-03 -2.233840000000e+01 -4.000000000000e-03 -1.116920000000e+01 -2.000000000000e-03 -3.350760000000e+01 -6.000000000000e-03 -5.584600000000e+00 -1.000000000000e-03 -1.675380000000e+01 -3.000000000000e-03 5.584600000000e+00 1.000000000000e-03 -1.116920000000e+01 -2.000000000000e-03 -5.584600000000e+00 -1.000000000000e-03 -1.116920000000e+01 -2.000000000000e-03 1.116920000000e+01 2.000000000000e-03 -1.675380000000e+01 -3.000000000000e-03 1.116920000000e+01 2.000000000000e-03 -2.233840000000e+01 -4.000000000000e-03 1.172766000000e+02 2.100000000000e-02 -1.675380000000e+01 -3.000000000000e-03 -2.233840000000e+01 -4.000000000000e-03 -5.584600000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.233840000000e+01 4.000000000000e-03 -1.005228000000e+02 -1.800000000000e-02 -5.026140000000e+01 -9.000000000000e-03 -7.259980000000e+01 -1.300000000000e-02 -2.233840000000e+01 -4.000000000000e-03 3.350760000000e+01 6.000000000000e-03 -1.172766000000e+02 -2.100000000000e-02 3.350760000000e+01 6.000000000000e-03 -4.467680000000e+01 -8.000000000000e-03 3.909220000000e+01 7.000000000000e-03 -4.467680000000e+01 -8.000000000000e-03 -7.259980000000e+01 -1.300000000000e-02 2.792300000000e+01 5.000000000000e-03 3.239068000000e+02 5.800000000000e-02 -2.010456000000e+02 -3.600000000000e-02 2.680608000000e+02 4.800000000000e-02 1.563688000000e+02 2.800000000000e-02 2.177994000000e+02 3.900000000000e-02 8.935360000000e+01 1.600000000000e-02 7.818440000000e+01 1.400000000000e-02 4.355988000000e+02 7.800000000000e-02 2.122148000000e+02 3.800000000000e-02 4.020912000000e+02 7.200000000000e-02 3.350760000000e+02 6.000000000000e-02 1.675380000000e+02 3.000000000000e-02 2.568916000000e+02 4.600000000000e-02 1.675380000000e+01 3.000000000000e-03 -1.787072000000e+02 -3.200000000000e-02 4.802756000000e+02 8.600000000000e-02 0.000000000000e+00 0.000000000000e+00 6.087214000000e+02 1.090000000000e-01 -5.975522000000e+02 -1.070000000000e-01 1.954610000000e+02 3.500000000000e-02 -3.183222000000e+02 -5.700000000000e-02 -1.396150000000e+02 -2.500000000000e-02 1.061074000000e+02 1.900000000000e-02 -5.584600000000e+01 -1.000000000000e-02 5.584600000000e+00 1.000000000000e-03 1.787072000000e+02 3.200000000000e-02 1.507842000000e+02 2.700000000000e-02 6.701520000000e+01 1.200000000000e-02 9.493820000000e+01 1.700000000000e-02 4.020912000000e+02 7.200000000000e-02 -6.143060000000e+01 -1.100000000000e-02 1.675380000000e+01 3.000000000000e-03 5.584600000000e+00 1.000000000000e-03 8.376900000000e+01 1.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 1.116920000000e+01 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.451996000000e+02 -2.600000000000e-02 -1.116920000000e+01 -2.000000000000e-03 -9.493820000000e+01 -1.700000000000e-02 -6.701520000000e+01 -1.200000000000e-02 1.340304000000e+02 2.400000000000e-02 -1.061074000000e+02 -1.900000000000e-02 -6.143060000000e+01 -1.100000000000e-02 5.584600000000e+00 1.000000000000e-03 -3.685836000000e+02 -6.600000000000e-02 -1.005228000000e+02 -1.800000000000e-02 -3.909220000000e+01 -7.000000000000e-03 -4.467680000000e+01 -8.000000000000e-03 -2.233840000000e+01 -4.000000000000e-03 -1.016397200000e+03 -1.820000000000e-01 -9.493820000000e+01 -1.700000000000e-02 -1.507842000000e+02 -2.700000000000e-02 2.568916000000e+02 4.600000000000e-02 1.563688000000e+02 2.800000000000e-02 7.148288000000e+02 1.280000000000e-01 2.289686000000e+02 4.100000000000e-02 6.087214000000e+02 1.090000000000e-01 1.206273600000e+03 2.160000000000e-01 5.919676000000e+02 1.060000000000e-01 5.584600000000e+00 1.000000000000e-03 -6.757366000000e+02 -1.210000000000e-01 1.563688000000e+02 2.800000000000e-02 7.204134000000e+02 1.290000000000e-01 5.584600000000e+01 1.000000000000e-02 7.930132000000e+02 1.420000000000e-01 1.675380000000e+02 3.000000000000e-02 -6.924904000000e+02 -1.240000000000e-01 -3.685836000000e+02 -6.600000000000e-02 1.005228000000e+04 1.800000000000e+00 7.315826000000e+02 1.310000000000e-01 + 12 EWK_RAP 1.050000000000e-01 6.463838404000e+03 7.000000000000e+03 4.364500000000e+05 5.379246250000e+02 6.236870500000e+02 1.429000000000e-01 -1.178415000000e+02 -2.700000000000e-02 4.364500000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -4.364500000000e+00 -1.000000000000e-03 2.618700000000e+01 6.000000000000e-03 8.292550000000e+01 1.900000000000e-02 3.709825000000e+02 8.500000000000e-02 9.689190000000e+02 2.220000000000e-01 -2.444120000000e+02 -5.600000000000e-02 -1.003835000000e+02 -2.300000000000e-02 2.051315000000e+02 4.700000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.975530000000e+02 1.140000000000e-01 4.800950000000e+01 1.100000000000e-02 1.309350000000e+01 3.000000000000e-03 3.928050000000e+01 9.000000000000e-03 8.292550000000e+01 1.900000000000e-02 4.364500000000e+01 1.000000000000e-02 -3.055150000000e+01 -7.000000000000e-03 1.003835000000e+02 2.300000000000e-02 8.729000000000e+00 2.000000000000e-03 -1.309350000000e+01 -3.000000000000e-03 -4.364500000000e+00 -1.000000000000e-03 1.745800000000e+01 4.000000000000e-03 -8.729000000000e+00 -2.000000000000e-03 8.729000000000e+00 2.000000000000e-03 -8.729000000000e+00 -2.000000000000e-03 -4.364500000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -4.364500000000e+00 -1.000000000000e-03 8.729000000000e+00 2.000000000000e-03 4.364500000000e+00 1.000000000000e-03 1.309350000000e+01 3.000000000000e-03 -2.618700000000e+01 -6.000000000000e-03 8.729000000000e+01 2.000000000000e-02 4.364500000000e+01 1.000000000000e-02 -4.800950000000e+01 -1.100000000000e-02 -1.745800000000e+01 -4.000000000000e-03 7.419650000000e+01 1.700000000000e-02 5.673850000000e+01 1.300000000000e-02 8.292550000000e+01 1.900000000000e-02 -1.309350000000e+02 -3.000000000000e-02 4.364500000000e+00 1.000000000000e-03 5.237400000000e+01 1.200000000000e-02 2.618700000000e+01 6.000000000000e-03 -4.800950000000e+01 -1.100000000000e-02 -1.745800000000e+01 -4.000000000000e-03 2.182250000000e+01 5.000000000000e-03 4.364500000000e+00 1.000000000000e-03 1.178415000000e+02 2.700000000000e-02 -8.292550000000e+01 -1.900000000000e-02 4.364500000000e+00 1.000000000000e-03 -1.483930000000e+02 -3.400000000000e-02 3.491600000000e+01 8.000000000000e-03 1.047480000000e+02 2.400000000000e-02 1.091125000000e+02 2.500000000000e-02 1.309350000000e+01 3.000000000000e-03 3.055150000000e+01 7.000000000000e-03 -5.673850000000e+01 -1.300000000000e-02 1.265705000000e+02 2.900000000000e-02 9.165450000000e+01 2.100000000000e-02 8.729000000000e+00 2.000000000000e-03 -2.182250000000e+01 -5.000000000000e-03 -1.222060000000e+02 -2.800000000000e-02 -3.928050000000e+01 -9.000000000000e-03 -1.745800000000e+02 -4.000000000000e-02 -6.546750000000e+01 -1.500000000000e-02 3.055150000000e+01 7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.134770000000e+02 2.600000000000e-02 1.265705000000e+02 2.900000000000e-02 1.003835000000e+02 2.300000000000e-02 7.419650000000e+01 1.700000000000e-02 -3.797115000000e+02 -8.700000000000e-02 -1.702155000000e+02 -3.900000000000e-02 -1.003835000000e+02 -2.300000000000e-02 9.601900000000e+01 2.200000000000e-02 1.178415000000e+02 2.700000000000e-02 -2.225895000000e+02 -5.100000000000e-02 -2.182250000000e+02 -5.000000000000e-02 0.000000000000e+00 0.000000000000e+00 7.856100000000e+01 1.800000000000e-02 7.856100000000e+01 1.800000000000e-02 -6.110300000000e+01 -1.400000000000e-02 6.546750000000e+01 1.500000000000e-02 3.928050000000e+01 9.000000000000e-03 2.618700000000e+01 6.000000000000e-03 8.729000000000e+00 2.000000000000e-03 -4.364500000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 6.110300000000e+01 1.400000000000e-02 1.091125000000e+02 2.500000000000e-02 2.182250000000e+01 5.000000000000e-03 3.928050000000e+01 9.000000000000e-03 -3.055150000000e+01 -7.000000000000e-03 -6.983200000000e+01 -1.600000000000e-02 -7.419650000000e+01 -1.700000000000e-02 1.745800000000e+02 4.000000000000e-02 3.055150000000e+01 7.000000000000e-03 2.618700000000e+01 6.000000000000e-03 -1.789445000000e+02 -4.100000000000e-02 5.673850000000e+01 1.300000000000e-02 1.309350000000e+01 3.000000000000e-03 -8.510775000000e+02 -1.950000000000e-01 -7.768810000000e+02 -1.780000000000e-01 -6.764975000000e+02 -1.550000000000e-01 6.983200000000e+01 1.600000000000e-02 -1.658510000000e+02 -3.800000000000e-02 6.372170000000e+02 1.460000000000e-01 1.091125000000e+02 2.500000000000e-02 4.102630000000e+02 9.400000000000e-02 4.757305000000e+02 1.090000000000e-01 4.626370000000e+02 1.060000000000e-01 -3.055150000000e+01 -7.000000000000e-03 -2.531410000000e+02 -5.800000000000e-02 2.618700000000e+01 6.000000000000e-03 2.094960000000e+02 4.800000000000e-02 5.237400000000e+01 1.200000000000e-02 1.003835000000e+02 2.300000000000e-02 1.833090000000e+02 4.200000000000e-02 3.055150000000e+01 7.000000000000e-03 5.673850000000e+01 1.300000000000e-02 7.856100000000e+03 1.800000000000e+00 3.753470000000e+02 8.600000000000e-02 + 13 EWK_RAP 3.150000000000e-01 6.463838404000e+03 7.000000000000e+03 4.327800000000e+05 5.359980300000e+02 7.127453820000e+02 1.646900000000e-01 -3.029460000000e+01 -7.000000000000e-03 2.163900000000e+01 5.000000000000e-03 8.655600000000e+00 2.000000000000e-03 -4.327800000000e+00 -1.000000000000e-03 4.327800000000e+00 1.000000000000e-03 3.029460000000e+01 7.000000000000e-03 6.491700000000e+01 1.500000000000e-02 3.808464000000e+02 8.800000000000e-02 9.001824000000e+02 2.080000000000e-01 -3.029460000000e+02 -7.000000000000e-02 -1.081950000000e+02 -2.500000000000e-02 1.990788000000e+02 4.600000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.847136000000e+02 1.120000000000e-01 4.760580000000e+01 1.100000000000e-02 1.298340000000e+01 3.000000000000e-03 3.895020000000e+01 9.000000000000e-03 7.790040000000e+01 1.800000000000e-02 4.327800000000e+01 1.000000000000e-02 -2.596680000000e+01 -6.000000000000e-03 -1.731120000000e+01 -4.000000000000e-03 8.655600000000e+00 2.000000000000e-03 -1.298340000000e+01 -3.000000000000e-03 -4.327800000000e+00 -1.000000000000e-03 1.731120000000e+01 4.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 8.655600000000e+00 2.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -4.327800000000e+00 -1.000000000000e-03 1.731120000000e+01 4.000000000000e-03 4.327800000000e+00 1.000000000000e-03 4.327800000000e+00 1.000000000000e-03 -1.298340000000e+01 -3.000000000000e-03 8.655600000000e+01 2.000000000000e-02 5.193360000000e+01 1.200000000000e-02 -5.626140000000e+01 -1.300000000000e-02 2.163900000000e+01 5.000000000000e-03 8.655600000000e+01 2.000000000000e-02 4.760580000000e+01 1.100000000000e-02 -1.731120000000e+01 -4.000000000000e-03 -5.193360000000e+01 -1.200000000000e-02 4.327800000000e+00 1.000000000000e-03 1.731120000000e+01 4.000000000000e-03 3.462240000000e+01 8.000000000000e-03 -1.298340000000e+01 -3.000000000000e-03 9.521160000000e+01 2.200000000000e-02 8.222820000000e+01 1.900000000000e-02 -4.327800000000e+00 -1.000000000000e-03 1.168506000000e+02 2.700000000000e-02 -7.790040000000e+01 -1.800000000000e-02 4.327800000000e+00 1.000000000000e-03 -1.168506000000e+02 -2.700000000000e-02 -1.514730000000e+02 -3.500000000000e-02 3.029460000000e+01 7.000000000000e-03 8.655600000000e+01 2.000000000000e-02 0.000000000000e+00 0.000000000000e+00 3.029460000000e+01 7.000000000000e-03 4.327800000000e+00 1.000000000000e-03 1.168506000000e+02 2.700000000000e-02 -1.731120000000e+01 -4.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 2.207178000000e+02 5.100000000000e-02 1.384896000000e+02 3.200000000000e-02 3.462240000000e+01 8.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 -1.514730000000e+02 -3.500000000000e-02 -6.491700000000e+01 -1.500000000000e-02 0.000000000000e+00 0.000000000000e+00 1.168506000000e+02 2.700000000000e-02 1.341618000000e+02 3.100000000000e-02 3.029460000000e+01 7.000000000000e-03 -1.298340000000e+01 -3.000000000000e-03 -6.058920000000e+01 -1.400000000000e-02 -4.760580000000e+01 -1.100000000000e-02 -6.058920000000e+01 -1.400000000000e-02 -1.514730000000e+02 -3.500000000000e-02 3.029460000000e+02 7.000000000000e-02 -6.058920000000e+01 -1.400000000000e-02 -2.596680000000e+02 -6.000000000000e-02 2.596680000000e+01 6.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 8.222820000000e+01 1.900000000000e-02 2.596680000000e+01 6.000000000000e-03 6.924480000000e+01 1.600000000000e-02 3.029460000000e+01 7.000000000000e-03 1.731120000000e+01 4.000000000000e-03 4.327800000000e+00 1.000000000000e-03 -8.655600000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.255062000000e+02 2.900000000000e-02 -4.327800000000e+00 -1.000000000000e-03 4.327800000000e+01 1.000000000000e-02 -3.462240000000e+01 -8.000000000000e-03 -4.760580000000e+01 -1.100000000000e-02 -7.357260000000e+01 -1.700000000000e-02 5.193360000000e+01 1.200000000000e-02 2.163900000000e+01 5.000000000000e-03 3.462240000000e+01 8.000000000000e-03 -3.462240000000e+01 -8.000000000000e-03 -2.163900000000e+01 -5.000000000000e-03 8.655600000000e+00 2.000000000000e-03 -1.731120000000e+01 -4.000000000000e-03 -8.006430000000e+02 -1.850000000000e-01 -7.140870000000e+02 -1.650000000000e-01 -7.097592000000e+02 -1.640000000000e-01 9.088380000000e+01 2.100000000000e-02 -6.491700000000e+01 -1.500000000000e-02 3.462240000000e+02 8.000000000000e-02 5.626140000000e+01 1.300000000000e-02 3.851742000000e+02 8.900000000000e-02 4.630746000000e+02 1.070000000000e-01 4.068132000000e+02 9.400000000000e-02 -5.193360000000e+01 -1.200000000000e-02 -2.813070000000e+02 -6.500000000000e-02 9.521160000000e+01 2.200000000000e-02 1.125228000000e+02 2.600000000000e-02 6.058920000000e+01 1.400000000000e-02 1.125228000000e+02 2.600000000000e-02 1.774398000000e+02 4.100000000000e-02 -1.038672000000e+02 -2.400000000000e-02 -1.255062000000e+02 -2.900000000000e-02 7.790040000000e+03 1.800000000000e+00 3.938298000000e+02 9.100000000000e-02 + 14 EWK_RAP 5.250000000000e-01 6.463838404000e+03 7.000000000000e+03 4.292900000000e+05 4.604135250000e+02 5.713849900000e+02 1.331000000000e-01 -1.244941000000e+02 -2.900000000000e-02 3.005030000000e+01 7.000000000000e-03 1.287870000000e+01 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 8.585800000000e+00 2.000000000000e-03 4.722190000000e+01 1.100000000000e-02 1.073225000000e+02 2.500000000000e-02 3.434320000000e+02 8.000000000000e-02 8.328226000000e+02 1.940000000000e-01 -3.391391000000e+02 -7.900000000000e-02 -1.287870000000e+02 -3.000000000000e-02 1.931805000000e+02 4.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.850977000000e+02 1.130000000000e-01 4.722190000000e+01 1.100000000000e-02 1.287870000000e+01 3.000000000000e-03 3.863610000000e+01 9.000000000000e-03 7.297930000000e+01 1.700000000000e-02 4.292900000000e+01 1.000000000000e-02 -8.585800000000e+00 -2.000000000000e-03 -3.434320000000e+01 -8.000000000000e-03 1.287870000000e+01 3.000000000000e-03 -8.585800000000e+00 -2.000000000000e-03 -8.585800000000e+00 -2.000000000000e-03 1.287870000000e+01 3.000000000000e-03 -8.585800000000e+00 -2.000000000000e-03 8.585800000000e+00 2.000000000000e-03 -4.292900000000e+00 -1.000000000000e-03 -4.292900000000e+00 -1.000000000000e-03 -4.292900000000e+00 -1.000000000000e-03 -4.292900000000e+00 -1.000000000000e-03 8.585800000000e+00 2.000000000000e-03 8.585800000000e+00 2.000000000000e-03 4.292900000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 9.015090000000e+01 2.100000000000e-02 4.722190000000e+01 1.100000000000e-02 -6.439350000000e+01 -1.500000000000e-02 8.585800000000e+00 2.000000000000e-03 5.580770000000e+01 1.300000000000e-02 3.434320000000e+01 8.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.146450000000e+01 -5.000000000000e-03 5.580770000000e+01 1.300000000000e-02 -4.292900000000e+00 -1.000000000000e-03 4.292900000000e+00 1.000000000000e-03 -1.717160000000e+01 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 6.439350000000e+01 1.500000000000e-02 2.146450000000e+02 5.000000000000e-02 1.116154000000e+02 2.600000000000e-02 -7.727220000000e+01 -1.800000000000e-02 4.292900000000e+00 1.000000000000e-03 -1.159083000000e+02 -2.700000000000e-02 -1.073225000000e+02 -2.500000000000e-02 -4.292900000000e+00 -1.000000000000e-03 -1.287870000000e+01 -3.000000000000e-03 -7.297930000000e+01 -1.700000000000e-02 3.863610000000e+01 9.000000000000e-03 8.585800000000e+00 2.000000000000e-03 -1.330799000000e+02 -3.100000000000e-02 4.292900000000e+00 1.000000000000e-03 -8.585800000000e+01 -2.000000000000e-02 1.073225000000e+02 2.500000000000e-02 -9.015090000000e+01 -2.100000000000e-02 5.151480000000e+01 1.200000000000e-02 -1.116154000000e+02 -2.600000000000e-02 -2.318166000000e+02 -5.400000000000e-02 -4.292900000000e+01 -1.000000000000e-02 0.000000000000e+00 0.000000000000e+00 1.588373000000e+02 3.700000000000e-02 1.674231000000e+02 3.900000000000e-02 6.439350000000e+01 1.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -2.575740000000e+01 -6.000000000000e-03 -4.292900000000e+00 -1.000000000000e-03 -3.434320000000e+01 -8.000000000000e-03 -2.232308000000e+02 -5.200000000000e-02 2.747456000000e+02 6.400000000000e-02 -3.005030000000e+01 -7.000000000000e-03 -8.585800000000e+01 -2.000000000000e-02 -6.010060000000e+01 -1.400000000000e-02 3.863610000000e+01 9.000000000000e-03 -3.005030000000e+01 -7.000000000000e-03 3.434320000000e+01 8.000000000000e-03 6.868640000000e+01 1.600000000000e-02 3.434320000000e+01 8.000000000000e-03 1.287870000000e+01 3.000000000000e-03 4.292900000000e+00 1.000000000000e-03 -8.585800000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.717160000000e+01 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 8.585800000000e+00 2.000000000000e-03 -1.287870000000e+01 -3.000000000000e-03 -6.439350000000e+01 -1.500000000000e-02 -7.727220000000e+01 -1.800000000000e-02 2.575740000000e+01 6.000000000000e-03 -3.434320000000e+01 -8.000000000000e-03 3.863610000000e+01 9.000000000000e-03 1.287870000000e+01 3.000000000000e-03 -1.717160000000e+01 -4.000000000000e-03 -8.585800000000e+00 -2.000000000000e-03 -3.434320000000e+01 -8.000000000000e-03 -8.070652000000e+02 -1.880000000000e-01 -6.782782000000e+02 -1.580000000000e-01 -5.752486000000e+02 -1.340000000000e-01 -5.151480000000e+01 -1.200000000000e-02 -1.202012000000e+02 -2.800000000000e-02 6.353492000000e+02 1.480000000000e-01 6.010060000000e+01 1.400000000000e-02 4.121184000000e+02 9.600000000000e-02 4.421687000000e+02 1.030000000000e-01 4.722190000000e+02 1.100000000000e-01 -6.868640000000e+01 -1.600000000000e-02 -3.133817000000e+02 -7.300000000000e-02 3.005030000000e+01 7.000000000000e-03 1.416657000000e+02 3.300000000000e-02 6.439350000000e+01 1.500000000000e-02 2.704527000000e+02 6.300000000000e-02 1.717160000000e+02 4.000000000000e-02 2.962101000000e+02 6.900000000000e-02 5.151480000000e+01 1.200000000000e-02 7.727220000000e+03 1.800000000000e+00 3.863610000000e+02 9.000000000000e-02 + 15 EWK_RAP 7.350000000000e-01 6.463838404000e+03 7.000000000000e+03 4.233800000000e+05 4.952699240000e+02 5.340938700000e+02 1.261500000000e-01 -2.540280000000e+01 -6.000000000000e-03 4.233800000000e+01 1.000000000000e-02 1.693520000000e+01 4.000000000000e-03 4.233800000000e+00 1.000000000000e-03 -4.233800000000e+00 -1.000000000000e-03 4.657180000000e+01 1.100000000000e-02 7.620840000000e+01 1.800000000000e-02 3.344702000000e+02 7.900000000000e-02 8.044220000000e+02 1.900000000000e-01 -4.022110000000e+02 -9.500000000000e-02 -1.354816000000e+02 -3.200000000000e-02 1.820534000000e+02 4.300000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.741856000000e+02 1.120000000000e-01 4.657180000000e+01 1.100000000000e-02 1.270140000000e+01 3.000000000000e-03 3.810420000000e+01 9.000000000000e-03 6.774080000000e+01 1.600000000000e-02 4.233800000000e+01 1.000000000000e-02 -8.467600000000e+00 -2.000000000000e-03 -2.116900000000e+01 -5.000000000000e-03 1.270140000000e+01 3.000000000000e-03 -8.467600000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.270140000000e+01 3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -4.233800000000e+00 -1.000000000000e-03 -4.233800000000e+00 -1.000000000000e-03 -4.233800000000e+00 -1.000000000000e-03 -8.467600000000e+00 -2.000000000000e-03 8.467600000000e+00 2.000000000000e-03 8.467600000000e+00 2.000000000000e-03 -2.540280000000e+01 -6.000000000000e-03 -2.963660000000e+01 -7.000000000000e-03 8.890980000000e+01 2.100000000000e-02 2.116900000000e+01 5.000000000000e-03 -6.350700000000e+01 -1.500000000000e-02 4.657180000000e+01 1.100000000000e-02 0.000000000000e+00 0.000000000000e+00 2.370928000000e+02 5.600000000000e-02 -2.116900000000e+01 -5.000000000000e-03 -3.810420000000e+01 -9.000000000000e-03 -1.693520000000e+01 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 8.467600000000e+00 2.000000000000e-03 -2.540280000000e+01 -6.000000000000e-03 -4.233800000000e+00 -1.000000000000e-03 2.540280000000e+01 6.000000000000e-03 8.467600000000e+00 2.000000000000e-03 1.100788000000e+02 2.600000000000e-02 -7.620840000000e+01 -1.800000000000e-02 8.467600000000e+00 2.000000000000e-03 -1.354816000000e+02 -3.200000000000e-02 -8.467600000000e+01 -2.000000000000e-02 6.774080000000e+01 1.600000000000e-02 -8.890980000000e+01 -2.100000000000e-02 -4.657180000000e+01 -1.100000000000e-02 3.810420000000e+01 9.000000000000e-03 -1.439492000000e+02 -3.400000000000e-02 -1.439492000000e+02 -3.400000000000e-02 1.566506000000e+02 3.700000000000e-02 -1.100788000000e+02 -2.600000000000e-02 -1.016112000000e+02 -2.400000000000e-02 -8.890980000000e+01 -2.100000000000e-02 -2.116900000000e+01 -5.000000000000e-03 -1.354816000000e+02 -3.200000000000e-02 -2.667294000000e+02 -6.300000000000e-02 4.233800000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.032224000000e+02 4.800000000000e-02 1.947548000000e+02 4.600000000000e-02 8.044220000000e+01 1.900000000000e-02 -8.467600000000e+00 -2.000000000000e-03 1.312478000000e+02 3.100000000000e-02 9.314360000000e+01 2.200000000000e-02 -2.074562000000e+02 -4.900000000000e-02 1.312478000000e+02 3.100000000000e-02 2.667294000000e+02 6.300000000000e-02 1.397154000000e+02 3.300000000000e-02 -2.540280000000e+01 -6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -7.197460000000e+01 -1.700000000000e-02 -5.927320000000e+01 -1.400000000000e-02 1.100788000000e+02 2.600000000000e-02 7.620840000000e+01 1.800000000000e-02 3.387040000000e+01 8.000000000000e-03 4.233800000000e+00 1.000000000000e-03 -4.233800000000e+00 -1.000000000000e-03 -8.467600000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -1.693520000000e+01 -4.000000000000e-03 4.657180000000e+01 1.100000000000e-02 3.387040000000e+01 8.000000000000e-03 5.080560000000e+01 1.200000000000e-02 -8.467600000000e+00 -2.000000000000e-03 3.387040000000e+01 8.000000000000e-03 -1.016112000000e+02 -2.400000000000e-02 -7.197460000000e+01 -1.700000000000e-02 4.657180000000e+01 1.100000000000e-02 -2.116900000000e+01 -5.000000000000e-03 4.233800000000e+00 1.000000000000e-03 -1.270140000000e+01 -3.000000000000e-03 2.540280000000e+01 6.000000000000e-03 -8.298248000000e+02 -1.960000000000e-01 -5.546278000000e+02 -1.310000000000e-01 -6.223686000000e+02 -1.470000000000e-01 -5.927320000000e+01 -1.400000000000e-02 -1.735858000000e+02 -4.100000000000e-02 5.376926000000e+02 1.270000000000e-01 1.481830000000e+02 3.500000000000e-02 4.149124000000e+02 9.800000000000e-02 4.487828000000e+02 1.060000000000e-01 4.741856000000e+02 1.120000000000e-01 -8.467600000000e+01 -2.000000000000e-02 -1.820534000000e+02 -4.300000000000e-02 1.862872000000e+02 4.400000000000e-02 1.778196000000e+02 4.200000000000e-02 7.197460000000e+01 1.700000000000e-02 3.937434000000e+02 9.300000000000e-02 2.074562000000e+02 4.900000000000e-02 4.233800000000e+01 1.000000000000e-02 -1.354816000000e+02 -3.200000000000e-02 7.620840000000e+03 1.800000000000e+00 3.852758000000e+02 9.100000000000e-02 + 16 EWK_RAP 9.450000000000e-01 6.463838404000e+03 7.000000000000e+03 4.136400000000e+05 4.747346280000e+02 6.152067720000e+02 1.487300000000e-01 9.100080000000e+01 2.200000000000e-02 1.034100000000e+02 2.500000000000e-02 3.722760000000e+01 9.000000000000e-03 4.136400000000e+00 1.000000000000e-03 8.272800000000e+00 2.000000000000e-03 6.618240000000e+01 1.600000000000e-02 9.513720000000e+01 2.300000000000e-02 2.399112000000e+02 5.800000000000e-02 7.155972000000e+02 1.730000000000e-01 -4.715496000000e+02 -1.140000000000e-01 -1.571832000000e+02 -3.800000000000e-02 1.613196000000e+02 3.900000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.715496000000e+02 1.140000000000e-01 4.136400000000e+01 1.000000000000e-02 1.240920000000e+01 3.000000000000e-03 3.722760000000e+01 9.000000000000e-03 6.204600000000e+01 1.500000000000e-02 4.136400000000e+01 1.000000000000e-02 -8.272800000000e+00 -2.000000000000e-03 -4.136400000000e+00 -1.000000000000e-03 4.136400000000e+00 1.000000000000e-03 -8.272800000000e+00 -2.000000000000e-03 -4.136400000000e+00 -1.000000000000e-03 8.272800000000e+00 2.000000000000e-03 -1.654560000000e+01 -4.000000000000e-03 1.034100000000e+02 2.500000000000e-02 -4.136400000000e+00 -1.000000000000e-03 -2.895480000000e+01 -7.000000000000e-03 -8.272800000000e+00 -2.000000000000e-03 -8.272800000000e+00 -2.000000000000e-03 1.240920000000e+01 3.000000000000e-03 -4.136400000000e+00 -1.000000000000e-03 8.272800000000e+00 2.000000000000e-03 1.654560000000e+01 4.000000000000e-03 5.377320000000e+01 1.300000000000e-02 4.136400000000e+00 1.000000000000e-03 -1.778652000000e+02 -4.300000000000e-02 -1.282284000000e+02 -3.100000000000e-02 2.233656000000e+02 5.400000000000e-02 8.272800000000e+01 2.000000000000e-02 -3.309120000000e+01 -8.000000000000e-03 -5.790960000000e+01 -1.400000000000e-02 4.136400000000e+00 1.000000000000e-03 2.068200000000e+01 5.000000000000e-03 -1.654560000000e+01 -4.000000000000e-03 -3.309120000000e+01 -8.000000000000e-03 -8.272800000000e+00 -2.000000000000e-03 -4.136400000000e+00 -1.000000000000e-03 2.481840000000e+01 6.000000000000e-03 1.034100000000e+02 2.500000000000e-02 -7.031880000000e+01 -1.700000000000e-02 8.272800000000e+00 2.000000000000e-03 -6.204600000000e+01 -1.500000000000e-02 -7.031880000000e+01 -1.700000000000e-02 8.686440000000e+01 2.100000000000e-02 -7.445520000000e+01 -1.800000000000e-02 -9.513720000000e+01 -2.300000000000e-02 4.963680000000e+01 1.200000000000e-02 4.963680000000e+01 1.200000000000e-02 -9.100080000000e+01 -2.200000000000e-02 -4.963680000000e+01 -1.200000000000e-02 5.790960000000e+01 1.400000000000e-02 -9.513720000000e+01 -2.300000000000e-02 -1.571832000000e+02 -3.800000000000e-02 -1.075464000000e+02 -2.600000000000e-02 -1.199556000000e+02 -2.900000000000e-02 -2.357748000000e+02 -5.700000000000e-02 1.240920000000e+01 3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.406376000000e+02 3.400000000000e-02 1.158192000000e+02 2.800000000000e-02 2.895480000000e+01 7.000000000000e-03 1.240920000000e+01 3.000000000000e-03 1.654560000000e+01 4.000000000000e-03 1.654560000000e+01 4.000000000000e-03 9.100080000000e+01 2.200000000000e-02 1.447740000000e+02 3.500000000000e-02 2.399112000000e+02 5.800000000000e-02 -2.316384000000e+02 -5.600000000000e-02 1.985472000000e+02 4.800000000000e-02 3.309120000000e+01 8.000000000000e-03 -1.654560000000e+01 -4.000000000000e-03 -4.963680000000e+01 -1.200000000000e-02 -8.272800000000e+01 -2.000000000000e-02 7.031880000000e+01 1.700000000000e-02 3.722760000000e+01 9.000000000000e-03 8.272800000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -8.272800000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -6.618240000000e+01 -1.600000000000e-02 -2.068200000000e+01 -5.000000000000e-03 5.790960000000e+01 1.400000000000e-02 -2.068200000000e+01 -5.000000000000e-03 1.240920000000e+01 3.000000000000e-03 6.204600000000e+01 1.500000000000e-02 -8.272800000000e+00 -2.000000000000e-03 -1.282284000000e+02 -3.100000000000e-02 4.136400000000e+01 1.000000000000e-02 -3.309120000000e+01 -8.000000000000e-03 2.895480000000e+01 7.000000000000e-03 -1.240920000000e+01 -3.000000000000e-03 4.550040000000e+01 1.100000000000e-02 -8.272800000000e+02 -2.000000000000e-01 -4.177764000000e+02 -1.010000000000e-01 -3.474576000000e+02 -8.400000000000e-02 -4.963680000000e+01 -1.200000000000e-02 -1.654560000000e+02 -4.000000000000e-02 7.321428000000e+02 1.770000000000e-01 1.365012000000e+02 3.300000000000e-02 4.219128000000e+02 1.020000000000e-01 5.046408000000e+02 1.220000000000e-01 4.425948000000e+02 1.070000000000e-01 1.654560000000e+01 4.000000000000e-03 -1.654560000000e+02 -4.000000000000e-02 1.737288000000e+02 4.200000000000e-02 2.440476000000e+02 5.900000000000e-02 6.618240000000e+01 1.600000000000e-02 3.309120000000e+01 8.000000000000e-03 2.730024000000e+02 6.600000000000e-02 -1.985472000000e+02 -4.800000000000e-02 -4.798224000000e+02 -1.160000000000e-01 7.445520000000e+03 1.800000000000e+00 3.805488000000e+02 9.200000000000e-02 + 17 EWK_RAP 1.210000000000e+00 6.463838404000e+03 7.000000000000e+03 4.052600000000e+05 3.899046986000e+02 5.653782260000e+02 1.395100000000e-01 5.673640000000e+01 1.400000000000e-02 8.510460000000e+01 2.100000000000e-02 2.836820000000e+01 7.000000000000e-03 2.026300000000e+01 5.000000000000e-03 -1.215780000000e+01 -3.000000000000e-03 8.105200000000e+01 2.000000000000e-02 6.889420000000e+01 1.700000000000e-02 3.687866000000e+02 9.100000000000e-02 7.456784000000e+02 1.840000000000e-01 -5.187328000000e+02 -1.280000000000e-01 -1.580514000000e+02 -3.900000000000e-02 1.377884000000e+02 3.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.538912000000e+02 1.120000000000e-01 4.457860000000e+01 1.100000000000e-02 1.215780000000e+01 3.000000000000e-03 3.647340000000e+01 9.000000000000e-03 4.863120000000e+01 1.200000000000e-02 4.052600000000e+01 1.000000000000e-02 -4.052600000000e+00 -1.000000000000e-03 -8.105200000000e+00 -2.000000000000e-03 4.052600000000e+00 1.000000000000e-03 -2.836820000000e+01 -7.000000000000e-03 2.431560000000e+01 6.000000000000e-03 3.647340000000e+01 9.000000000000e-03 -8.915720000000e+01 -2.200000000000e-02 -2.836820000000e+01 -7.000000000000e-03 -1.621040000000e+01 -4.000000000000e-03 8.105200000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -4.052600000000e+00 -1.000000000000e-03 8.105200000000e+00 2.000000000000e-03 -8.105200000000e+00 -2.000000000000e-03 1.621040000000e+01 4.000000000000e-03 -1.215780000000e+01 -3.000000000000e-03 7.699940000000e+01 1.900000000000e-02 2.026300000000e+01 5.000000000000e-03 -2.431560000000e+01 -6.000000000000e-03 3.647340000000e+01 9.000000000000e-03 3.242080000000e+01 8.000000000000e-03 2.836820000000e+01 7.000000000000e-03 -2.026300000000e+01 -5.000000000000e-03 -3.242080000000e+01 -8.000000000000e-03 4.052600000000e+00 1.000000000000e-03 2.026300000000e+01 5.000000000000e-03 1.621040000000e+01 4.000000000000e-03 -2.026300000000e+01 -5.000000000000e-03 8.105200000000e+00 2.000000000000e-03 -1.621040000000e+01 -4.000000000000e-03 1.215780000000e+01 3.000000000000e-03 1.134728000000e+02 2.800000000000e-02 -7.699940000000e+01 -1.900000000000e-02 1.215780000000e+01 3.000000000000e-03 2.026300000000e+01 5.000000000000e-03 1.013150000000e+02 2.500000000000e-02 3.647340000000e+01 9.000000000000e-03 -1.094202000000e+02 -2.700000000000e-02 1.215780000000e+01 3.000000000000e-03 5.673640000000e+01 1.400000000000e-02 1.094202000000e+02 2.700000000000e-02 1.702092000000e+02 4.200000000000e-02 2.107352000000e+02 5.200000000000e-02 1.377884000000e+02 3.400000000000e-02 1.013150000000e+02 2.500000000000e-02 3.647340000000e+01 9.000000000000e-03 6.484160000000e+01 1.600000000000e-02 8.105200000000e+01 2.000000000000e-02 -1.742618000000e+02 -4.300000000000e-02 -5.268380000000e+01 -1.300000000000e-02 0.000000000000e+00 0.000000000000e+00 1.296832000000e+02 3.200000000000e-02 1.013150000000e+02 2.500000000000e-02 3.647340000000e+01 9.000000000000e-03 4.052600000000e+00 1.000000000000e-03 1.621040000000e+01 4.000000000000e-03 1.621040000000e+01 4.000000000000e-03 2.147878000000e+02 5.300000000000e-02 4.052600000000e+01 1.000000000000e-02 1.256306000000e+02 3.100000000000e-02 -6.078900000000e+01 -1.500000000000e-02 7.699940000000e+01 1.900000000000e-02 9.726240000000e+01 2.400000000000e-02 -2.026300000000e+01 -5.000000000000e-03 -2.836820000000e+01 -7.000000000000e-03 -8.105200000000e+01 -2.000000000000e-02 7.699940000000e+01 1.900000000000e-02 4.863120000000e+01 1.200000000000e-02 8.105200000000e+00 2.000000000000e-03 -4.052600000000e+00 -1.000000000000e-03 -8.105200000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -1.783144000000e+02 -4.400000000000e-02 2.431560000000e+01 6.000000000000e-03 1.215780000000e+01 3.000000000000e-03 -1.215780000000e+01 -3.000000000000e-03 2.431560000000e+01 6.000000000000e-03 4.457860000000e+01 1.100000000000e-02 5.268380000000e+01 1.300000000000e-02 -6.078900000000e+01 -1.500000000000e-02 6.078900000000e+01 1.500000000000e-02 -8.105200000000e+00 -2.000000000000e-03 -8.105200000000e+00 -2.000000000000e-03 -1.215780000000e+01 -3.000000000000e-03 -1.621040000000e+01 -4.000000000000e-03 -8.956246000000e+02 -2.210000000000e-01 -3.444710000000e+02 -8.500000000000e-02 -3.687866000000e+02 -9.100000000000e-02 3.647340000000e+01 9.000000000000e-03 -2.431560000000e+02 -6.000000000000e-02 8.469934000000e+02 2.090000000000e-01 1.377884000000e+02 3.400000000000e-02 4.984698000000e+02 1.230000000000e-01 6.159952000000e+02 1.520000000000e-01 5.106276000000e+02 1.260000000000e-01 -7.699940000000e+01 -1.900000000000e-02 -9.320980000000e+01 -2.300000000000e-02 1.904722000000e+02 4.700000000000e-02 1.013150000000e+02 2.500000000000e-02 7.294680000000e+01 1.800000000000e-02 6.241004000000e+02 1.540000000000e-01 8.105200000000e+01 2.000000000000e-02 2.593664000000e+02 6.400000000000e-02 -4.863120000000e+02 -1.200000000000e-01 7.294680000000e+03 1.800000000000e+00 2.796294000000e+02 6.900000000000e-02 + 18 EWK_RAP 1.445000000000e+00 6.463838404000e+03 7.000000000000e+03 3.880200000000e+05 6.490022520000e+02 1.325825538000e+03 3.416900000000e-01 -2.716140000000e+01 -7.000000000000e-03 2.289318000000e+02 5.900000000000e-02 5.820300000000e+01 1.500000000000e-02 8.148420000000e+01 2.100000000000e-02 -4.268220000000e+01 -1.100000000000e-02 2.677338000000e+02 6.900000000000e-02 2.832546000000e+02 7.300000000000e-02 3.336972000000e+02 8.600000000000e-02 6.363528000000e+02 1.640000000000e-01 -4.733844000000e+02 -1.220000000000e-01 -1.707288000000e+02 -4.400000000000e-02 1.086456000000e+02 2.800000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.384626000000e+02 1.130000000000e-01 4.268220000000e+01 1.100000000000e-02 1.164060000000e+01 3.000000000000e-03 3.104160000000e+01 8.000000000000e-03 3.880200000000e+01 1.000000000000e-02 3.880200000000e+01 1.000000000000e-02 7.760400000000e+00 2.000000000000e-03 -4.656240000000e+01 -1.200000000000e-02 0.000000000000e+00 0.000000000000e+00 1.164060000000e+01 3.000000000000e-03 -1.940100000000e+01 -5.000000000000e-03 -7.760400000000e+00 -2.000000000000e-03 5.432280000000e+01 1.400000000000e-02 -2.716140000000e+01 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.164060000000e+01 -3.000000000000e-03 -2.328120000000e+01 -6.000000000000e-03 -7.760400000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -7.760400000000e+00 -2.000000000000e-03 4.268220000000e+01 1.100000000000e-02 1.940100000000e+01 5.000000000000e-03 4.656240000000e+01 1.200000000000e-02 7.760400000000e+00 2.000000000000e-03 -7.760400000000e+00 -2.000000000000e-03 9.312480000000e+01 2.400000000000e-02 1.940100000000e+01 5.000000000000e-03 -1.552080000000e+01 -4.000000000000e-03 7.760400000000e+00 2.000000000000e-03 -3.880200000000e+00 -1.000000000000e-03 -3.880200000000e+00 -1.000000000000e-03 3.492180000000e+01 9.000000000000e-03 3.880200000000e+00 1.000000000000e-03 2.328120000000e+01 6.000000000000e-03 -1.552080000000e+01 -4.000000000000e-03 -4.656240000000e+01 -1.200000000000e-02 -6.208320000000e+01 -1.600000000000e-02 9.700500000000e+01 2.500000000000e-02 -6.596340000000e+01 -1.700000000000e-02 1.164060000000e+01 3.000000000000e-03 -5.432280000000e+01 -1.400000000000e-02 -7.760400000000e+00 -2.000000000000e-03 1.552080000000e+01 4.000000000000e-03 -1.164060000000e+01 -3.000000000000e-03 -1.552080000000e+01 -4.000000000000e-03 5.432280000000e+01 1.400000000000e-02 -3.880200000000e+00 -1.000000000000e-03 1.164060000000e+01 3.000000000000e-03 7.760400000000e+00 2.000000000000e-03 7.760400000000e+00 2.000000000000e-03 2.328120000000e+01 6.000000000000e-03 -2.716140000000e+01 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.328120000000e+01 -6.000000000000e-03 -8.148420000000e+01 -2.100000000000e-02 3.880200000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.746090000000e+02 4.500000000000e-02 5.820300000000e+01 1.500000000000e-02 1.164060000000e+01 3.000000000000e-03 1.164060000000e+01 3.000000000000e-03 -1.940100000000e+01 -5.000000000000e-03 -7.760400000000e+00 -2.000000000000e-03 7.760400000000e+00 2.000000000000e-03 3.880200000000e+00 1.000000000000e-03 1.823694000000e+02 4.700000000000e-02 -4.268220000000e+01 -1.100000000000e-02 0.000000000000e+00 0.000000000000e+00 7.760400000000e+00 2.000000000000e-03 7.760400000000e+00 2.000000000000e-03 7.760400000000e+00 2.000000000000e-03 -1.940100000000e+01 -5.000000000000e-03 6.984360000000e+01 1.800000000000e-02 4.656240000000e+01 1.200000000000e-02 1.164060000000e+01 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -7.760400000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -3.880200000000e+00 -1.000000000000e-03 2.716140000000e+01 7.000000000000e-03 3.880200000000e+00 1.000000000000e-03 3.880200000000e+00 1.000000000000e-03 -3.880200000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.880200000000e+00 1.000000000000e-03 -1.164060000000e+01 -3.000000000000e-03 2.328120000000e+01 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.164060000000e+01 -3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.164060000000e+01 -3.000000000000e-03 -8.924460000000e+02 -2.300000000000e-01 -2.483328000000e+02 -6.400000000000e-02 -4.345824000000e+02 -1.120000000000e-01 3.104160000000e+01 8.000000000000e-03 -1.008852000000e+02 -2.600000000000e-02 7.527588000000e+02 1.940000000000e-01 -1.940100000000e+01 -5.000000000000e-03 4.307022000000e+02 1.110000000000e-01 8.032014000000e+02 2.070000000000e-01 2.871348000000e+02 7.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -6.208320000000e+01 -1.600000000000e-02 6.596340000000e+01 1.700000000000e-02 1.474476000000e+02 3.800000000000e-02 5.432280000000e+01 1.400000000000e-02 2.405724000000e+02 6.200000000000e-02 1.396872000000e+02 3.600000000000e-02 2.328120000000e+01 6.000000000000e-03 -1.629684000000e+02 -4.200000000000e-02 6.984360000000e+03 1.800000000000e+00 4.539834000000e+02 1.170000000000e-01 + 19 EWK_RAP 1.630000000000e+00 6.463838404000e+03 7.000000000000e+03 3.775100000000e+05 5.202087800000e+02 6.224762390000e+02 1.648900000000e-01 -1.510040000000e+01 -4.000000000000e-03 4.907630000000e+01 1.300000000000e-02 7.550200000000e+00 2.000000000000e-03 -7.550200000000e+00 -2.000000000000e-03 -3.775100000000e+00 -1.000000000000e-03 5.285140000000e+01 1.400000000000e-02 5.662650000000e+01 1.500000000000e-02 2.529317000000e+02 6.700000000000e-02 7.814457000000e+02 2.070000000000e-01 -5.624899000000e+02 -1.490000000000e-01 -1.774297000000e+02 -4.700000000000e-02 9.437750000000e+01 2.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.416867000000e+02 1.170000000000e-01 4.152610000000e+01 1.100000000000e-02 1.132530000000e+01 3.000000000000e-03 3.020080000000e+01 8.000000000000e-03 3.020080000000e+01 8.000000000000e-03 4.152610000000e+01 1.100000000000e-02 7.550200000000e+00 2.000000000000e-03 -2.265060000000e+01 -6.000000000000e-03 1.132530000000e+01 3.000000000000e-03 -7.550200000000e+00 -2.000000000000e-03 -3.775100000000e+00 -1.000000000000e-03 7.550200000000e+00 2.000000000000e-03 3.775100000000e+00 1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -3.775100000000e+00 -1.000000000000e-03 -3.775100000000e+00 -1.000000000000e-03 -7.550200000000e+00 -2.000000000000e-03 1.132530000000e+01 3.000000000000e-03 -3.775100000000e+00 -1.000000000000e-03 1.132530000000e+01 3.000000000000e-03 3.775100000000e+00 1.000000000000e-03 8.305220000000e+01 2.200000000000e-02 1.132530000000e+01 3.000000000000e-03 -4.152610000000e+01 -1.100000000000e-02 1.132530000000e+01 3.000000000000e-03 4.152610000000e+01 1.100000000000e-02 2.642570000000e+01 7.000000000000e-03 -1.510040000000e+01 -4.000000000000e-03 -1.887550000000e+01 -5.000000000000e-03 -1.132530000000e+01 -3.000000000000e-03 -1.510040000000e+01 -4.000000000000e-03 1.132530000000e+01 3.000000000000e-03 -5.285140000000e+01 -1.400000000000e-02 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 2.642570000000e+01 7.000000000000e-03 1.132530000000e+02 3.000000000000e-02 -7.550200000000e+01 -2.000000000000e-02 1.132530000000e+01 3.000000000000e-03 9.060240000000e+01 2.400000000000e-02 5.775903000000e+02 1.530000000000e-01 -3.775100000000e+01 -1.000000000000e-02 1.132530000000e+01 3.000000000000e-03 4.530120000000e+01 1.200000000000e-02 7.172690000000e+01 1.900000000000e-02 6.795180000000e+01 1.800000000000e-02 -2.642570000000e+01 -7.000000000000e-03 -8.682730000000e+01 -2.300000000000e-02 -1.321285000000e+02 -3.500000000000e-02 6.417670000000e+01 1.700000000000e-02 2.642570000000e+01 7.000000000000e-03 2.642570000000e+01 7.000000000000e-03 7.550200000000e+00 2.000000000000e-03 -1.812048000000e+02 -4.800000000000e-02 -3.775100000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.774297000000e+02 4.700000000000e-02 5.285140000000e+01 1.400000000000e-02 -1.472289000000e+02 -3.900000000000e-02 -6.040160000000e+01 -1.600000000000e-02 -1.887550000000e+01 -5.000000000000e-03 -5.662650000000e+01 -1.500000000000e-02 -6.417670000000e+01 -1.700000000000e-02 -7.550200000000e+00 -2.000000000000e-03 1.585542000000e+02 4.200000000000e-02 -5.285140000000e+01 -1.400000000000e-02 2.642570000000e+01 7.000000000000e-03 -1.887550000000e+01 -5.000000000000e-03 2.265060000000e+01 6.000000000000e-03 1.094779000000e+02 2.900000000000e-02 4.907630000000e+01 1.300000000000e-02 6.795180000000e+01 1.800000000000e-02 4.907630000000e+01 1.300000000000e-02 2.265060000000e+01 6.000000000000e-03 -3.775100000000e+00 -1.000000000000e-03 -7.550200000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 2.038554000000e+02 5.400000000000e-02 4.152610000000e+01 1.100000000000e-02 -3.775100000000e+00 -1.000000000000e-03 -1.132530000000e+01 -3.000000000000e-03 7.550200000000e+00 2.000000000000e-03 7.550200000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.434538000000e+02 3.800000000000e-02 3.775100000000e+01 1.000000000000e-02 -1.510040000000e+01 -4.000000000000e-03 1.132530000000e+01 3.000000000000e-03 -7.550200000000e+00 -2.000000000000e-03 -3.020080000000e+01 -8.000000000000e-03 -9.173493000000e+02 -2.430000000000e-01 -9.815260000000e+01 -2.600000000000e-02 -5.322891000000e+02 -1.410000000000e-01 -4.530120000000e+01 -1.200000000000e-02 6.795180000000e+01 1.800000000000e-02 5.549397000000e+02 1.470000000000e-01 2.151807000000e+02 5.700000000000e-02 5.171887000000e+02 1.370000000000e-01 8.003212000000e+02 2.120000000000e-01 5.473895000000e+02 1.450000000000e-01 -4.907630000000e+01 -1.300000000000e-02 1.849799000000e+02 4.900000000000e-02 9.437750000000e+01 2.500000000000e-02 1.698795000000e+02 4.500000000000e-02 8.682730000000e+01 2.300000000000e-02 1.812048000000e+02 4.800000000000e-02 2.076305000000e+02 5.500000000000e-02 8.305220000000e+01 2.200000000000e-02 -2.906827000000e+02 -7.700000000000e-02 6.795180000000e+03 1.800000000000e+00 4.492369000000e+02 1.190000000000e-01 + 20 EWK_RAP 1.845000000000e+00 6.463838404000e+03 7.000000000000e+03 3.658200000000e+05 4.324358220000e+02 7.412976480000e+02 2.026400000000e-01 -5.487300000000e+01 -1.500000000000e-02 9.511320000000e+01 2.600000000000e-02 7.316400000000e+00 2.000000000000e-03 1.097460000000e+01 3.000000000000e-03 -3.658200000000e+00 -1.000000000000e-03 9.877140000000e+01 2.700000000000e-02 9.877140000000e+01 2.700000000000e-02 3.292380000000e+02 9.000000000000e-02 7.535892000000e+02 2.060000000000e-01 -5.450718000000e+02 -1.490000000000e-01 -1.755936000000e+02 -4.800000000000e-02 7.316400000000e+01 2.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.024020000000e+02 1.100000000000e-01 4.024020000000e+01 1.100000000000e-02 7.316400000000e+00 2.000000000000e-03 2.926560000000e+01 8.000000000000e-03 2.194920000000e+01 6.000000000000e-03 4.024020000000e+01 1.100000000000e-02 1.463280000000e+01 4.000000000000e-03 -4.024020000000e+01 -1.100000000000e-02 7.316400000000e+00 2.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 3.658200000000e+00 1.000000000000e-03 7.316400000000e+00 2.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 7.316400000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.097460000000e+01 -3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 7.316400000000e+00 2.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 7.316400000000e+00 2.000000000000e-03 8.048040000000e+01 2.200000000000e-02 1.097460000000e+01 3.000000000000e-03 -1.829100000000e+01 -5.000000000000e-03 1.097460000000e+01 3.000000000000e-03 2.194920000000e+01 6.000000000000e-03 1.829100000000e+01 5.000000000000e-03 -1.829100000000e+01 -5.000000000000e-03 -1.097460000000e+01 -3.000000000000e-03 1.097460000000e+01 3.000000000000e-03 -2.560740000000e+01 -7.000000000000e-03 -3.658200000000e+00 -1.000000000000e-03 -4.389840000000e+01 -1.200000000000e-02 7.316400000000e+00 2.000000000000e-03 -1.463280000000e+01 -4.000000000000e-03 7.316400000000e+00 2.000000000000e-03 1.170624000000e+02 3.200000000000e-02 -8.048040000000e+01 -2.200000000000e-02 1.097460000000e+01 3.000000000000e-03 -1.463280000000e+01 -4.000000000000e-03 -1.353534000000e+02 -3.700000000000e-02 5.853120000000e+01 1.600000000000e-02 1.536444000000e+02 4.200000000000e-02 7.316400000000e+01 2.000000000000e-02 6.218940000000e+01 1.700000000000e-02 1.097460000000e+01 3.000000000000e-03 4.024020000000e+01 1.100000000000e-02 -8.048040000000e+01 -2.200000000000e-02 -1.463280000000e+01 -4.000000000000e-03 1.207206000000e+02 3.300000000000e-02 0.000000000000e+00 0.000000000000e+00 -1.463280000000e+01 -4.000000000000e-03 1.463280000000e+01 4.000000000000e-03 2.560740000000e+02 7.000000000000e-02 -2.926560000000e+01 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.390116000000e+02 3.800000000000e-02 1.134042000000e+02 3.100000000000e-02 -9.511320000000e+01 -2.600000000000e-02 5.853120000000e+01 1.600000000000e-02 -6.584760000000e+01 -1.800000000000e-02 9.511320000000e+01 2.600000000000e-02 -1.829100000000e+01 -5.000000000000e-03 -1.097460000000e+01 -3.000000000000e-03 1.719354000000e+02 4.700000000000e-02 -6.218940000000e+01 -1.700000000000e-02 3.292380000000e+01 9.000000000000e-03 -1.134042000000e+02 -3.100000000000e-02 3.658200000000e+00 1.000000000000e-03 -7.316400000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 7.316400000000e+01 2.000000000000e-02 4.389840000000e+01 1.200000000000e-02 2.194920000000e+01 6.000000000000e-03 3.658200000000e+00 1.000000000000e-03 -3.658200000000e+00 -1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 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2.580000000000e-01 5.560464000000e+02 1.520000000000e-01 5.487300000000e+01 1.500000000000e-02 1.390116000000e+02 3.800000000000e-02 6.218940000000e+01 1.700000000000e-02 9.877140000000e+01 2.700000000000e-02 6.950580000000e+01 1.900000000000e-02 3.328962000000e+02 9.100000000000e-02 1.792518000000e+02 4.900000000000e-02 1.938846000000e+02 5.300000000000e-02 -3.292380000000e+01 -9.000000000000e-03 6.584760000000e+03 1.800000000000e+00 5.121480000000e+02 1.400000000000e-01 + 21 EWK_RAP 2.065000000000e+00 6.463838404000e+03 7.000000000000e+03 3.447000000000e+05 4.351492800000e+02 5.844043800000e+02 1.695400000000e-01 -4.825800000000e+01 -1.400000000000e-02 5.515200000000e+01 1.600000000000e-02 -3.447000000000e+00 -1.000000000000e-03 -1.378800000000e+01 -4.000000000000e-03 -1.723500000000e+01 -5.000000000000e-03 5.515200000000e+01 1.600000000000e-02 6.894000000000e+01 2.000000000000e-02 1.930320000000e+02 5.600000000000e-02 8.100450000000e+02 2.350000000000e-01 -5.963310000000e+02 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6.204600000000e+01 1.800000000000e-02 1.378800000000e+01 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 3.447000000000e+01 1.000000000000e-02 1.723500000000e+01 5.000000000000e-03 -8.962200000000e+01 -2.600000000000e-02 6.894000000000e+00 2.000000000000e-03 -7.928100000000e+01 -2.300000000000e-02 2.068200000000e+01 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.447000000000e+01 -1.000000000000e-02 2.412900000000e+01 7.000000000000e-03 3.447000000000e+01 1.000000000000e-02 2.412900000000e+01 7.000000000000e-03 9.306900000000e+01 2.700000000000e-02 -3.102300000000e+01 -9.000000000000e-03 -8.272800000000e+02 -2.400000000000e-01 -1.895850000000e+02 -5.500000000000e-02 -3.102300000000e+02 -9.000000000000e-02 -5.515200000000e+01 -1.600000000000e-02 -6.894000000000e+01 -2.000000000000e-02 5.170500000000e+02 1.500000000000e-01 2.309490000000e+02 6.700000000000e-02 4.205340000000e+02 1.220000000000e-01 9.755010000000e+02 2.830000000000e-01 3.826170000000e+02 1.110000000000e-01 -1.137510000000e+02 -3.300000000000e-02 9.651600000000e+01 2.800000000000e-02 -6.204600000000e+01 -1.800000000000e-02 1.620090000000e+02 4.700000000000e-02 6.549300000000e+01 1.900000000000e-02 1.413270000000e+02 4.100000000000e-02 1.689030000000e+02 4.900000000000e-02 6.894000000000e+01 2.000000000000e-02 -5.515200000000e+01 -1.600000000000e-02 6.204600000000e+03 1.800000000000e+00 4.412160000000e+02 1.280000000000e-01 + 22 EWK_RAP 2.340000000000e+00 6.463838404000e+03 7.000000000000e+03 3.190400000000e+05 4.441036800000e+02 6.182038080000e+02 1.937700000000e-01 1.276160000000e+01 4.000000000000e-03 5.742720000000e+01 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-1.400000000000e-02 -1.914240000000e+01 -6.000000000000e-03 6.380800000000e+00 2.000000000000e-03 -1.627104000000e+02 -5.100000000000e-02 -5.423680000000e+01 -1.700000000000e-02 -2.871360000000e+01 -9.000000000000e-03 -2.552320000000e+01 -8.000000000000e-03 -3.509440000000e+01 -1.100000000000e-02 -8.518368000000e+02 -2.670000000000e-01 -2.360896000000e+02 -7.400000000000e-02 -3.860384000000e+02 -1.210000000000e-01 -5.742720000000e+01 -1.800000000000e-02 -1.754720000000e+02 -5.500000000000e-02 5.136544000000e+02 1.610000000000e-01 2.392800000000e+02 7.500000000000e-02 4.051808000000e+02 1.270000000000e-01 9.922144000000e+02 3.110000000000e-01 4.913216000000e+02 1.540000000000e-01 -3.828480000000e+01 -1.200000000000e-02 2.456608000000e+02 7.700000000000e-02 -1.084736000000e+02 -3.400000000000e-02 2.743744000000e+02 8.600000000000e-02 6.061760000000e+01 1.900000000000e-02 6.763648000000e+02 2.120000000000e-01 1.531392000000e+02 4.800000000000e-02 -5.136544000000e+02 -1.610000000000e-01 -5.487488000000e+02 -1.720000000000e-01 5.742720000000e+03 1.800000000000e+00 3.796576000000e+02 1.190000000000e-01 diff --git a/nnpdfcpp/data/commondata/DATA_ATLASWRAP36PB.dat b/nnpdfcpp/data/commondata/DATA_ATLASWRAP36PB.dat new file mode 100644 index 0000000000..b451172842 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_ATLASWRAP36PB.dat @@ -0,0 +1,23 @@ +ATLASWRAP36PB 32 22 + 1 EWK_RAP 1.050000000000e-01 6.463838404000e+03 7.000000000000e+03 6.132574000000e+05 6.132574000000e+03 7.113785840000e+03 1.160000000000e+00 2.146400900000e+04 3.500000000000e+00 1.410492020000e+03 2.300000000000e-01 -1.103863320000e+03 -1.800000000000e-01 5.519316600000e+02 9.000000000000e-02 1.226514800000e+03 2.000000000000e-01 1.839772200000e+02 3.000000000000e-02 -6.132574000000e+01 -1.000000000000e-02 1.839772200000e+02 3.000000000000e-02 1.839772200000e+02 3.000000000000e-02 4.906059200000e+02 8.000000000000e-02 6.132574000000e+02 1.000000000000e-01 7.972346200000e+02 1.300000000000e-01 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2.100000000000e-01 3.683639574000e+02 6.000000000000e-02 -6.139399290000e+02 -1.000000000000e-01 + 3 EWK_RAP 5.250000000000e-01 6.463838404000e+03 7.000000000000e+03 6.317468050000e+05 5.622546564500e+03 6.127944008500e+03 9.700000000000e-01 2.211113817500e+04 3.500000000000e+00 1.453017651500e+03 2.300000000000e-01 -1.137144249000e+03 -1.800000000000e-01 5.685721245000e+02 9.000000000000e-02 1.263493610000e+03 2.000000000000e-01 1.895240415000e+02 3.000000000000e-02 -6.317468050000e+01 -1.000000000000e-02 1.263493610000e+02 2.000000000000e-02 2.526987220000e+02 4.000000000000e-02 3.790480830000e+02 6.000000000000e-02 8.844455270000e+02 1.400000000000e-01 8.212708465000e+02 1.300000000000e-01 4.422227635000e+02 7.000000000000e-02 -2.526987220000e+03 -4.000000000000e-01 2.526987220000e+02 4.000000000000e-02 -1.010794888000e+03 -1.600000000000e-01 -1.073969568500e+03 -1.700000000000e-01 -3.474607427500e+03 -5.500000000000e-01 2.969209983500e+03 4.700000000000e-01 2.779685942000e+03 4.400000000000e-01 1.073969568500e+03 1.700000000000e-01 -1.768891054000e+03 -2.800000000000e-01 -7.580961660000e+02 -1.200000000000e-01 3.790480830000e+02 6.000000000000e-02 -3.158734025000e+02 -5.000000000000e-02 3.790480830000e+02 6.000000000000e-02 3.158734025000e+02 5.000000000000e-02 1.453017651500e+03 2.300000000000e-01 1.579367012500e+03 2.500000000000e-01 1.895240415000e+02 3.000000000000e-02 -4.422227635000e+02 -7.000000000000e-02 + 4 EWK_RAP 7.350000000000e-01 6.463838404000e+03 7.000000000000e+03 6.261847030000e+05 5.948754678500e+03 7.013268673600e+03 1.120000000000e+00 2.191646460500e+04 3.500000000000e+00 1.440224816900e+03 2.300000000000e-01 -1.127132465400e+03 -1.800000000000e-01 5.635662327000e+02 9.000000000000e-02 1.252369406000e+03 2.000000000000e-01 2.504738812000e+02 4.000000000000e-02 -6.261847030000e+01 -1.000000000000e-02 2.504738812000e+02 4.000000000000e-02 1.252369406000e+02 2.000000000000e-02 5.635662327000e+02 9.000000000000e-02 7.514216436000e+02 1.200000000000e-01 7.514216436000e+02 1.200000000000e-01 4.383292921000e+02 7.000000000000e-02 -2.943068104100e+03 -4.700000000000e-01 6.261847030000e+01 1.000000000000e-02 -1.001895524800e+03 -1.600000000000e-01 -1.440224816900e+03 -2.300000000000e-01 -3.944963628900e+03 -6.300000000000e-01 2.943068104100e+03 4.700000000000e-01 2.191646460500e+03 3.500000000000e-01 1.440224816900e+03 2.300000000000e-01 -6.261847030000e+02 -1.000000000000e-01 -6.261847030000e+01 -1.000000000000e-02 3.130923515000e+02 5.000000000000e-02 -8.140401139000e+02 -1.300000000000e-01 -5.635662327000e+02 -9.000000000000e-02 1.127132465400e+03 1.800000000000e-01 8.766585842000e+02 1.400000000000e-01 1.628080227800e+03 2.600000000000e-01 1.878554109000e+02 3.000000000000e-02 -5.635662327000e+02 -9.000000000000e-02 + 5 EWK_RAP 9.450000000000e-01 6.463838404000e+03 7.000000000000e+03 6.526301550000e+05 6.134723457000e+03 6.983142658500e+03 1.070000000000e+00 2.284205542500e+04 3.500000000000e+00 1.501049356500e+03 2.300000000000e-01 -1.174734279000e+03 -1.800000000000e-01 5.873671395000e+02 9.000000000000e-02 1.305260310000e+03 2.000000000000e-01 2.610520620000e+02 4.000000000000e-02 0.000000000000e+00 0.000000000000e+00 2.610520620000e+02 4.000000000000e-02 2.610520620000e+02 4.000000000000e-02 4.568411085000e+02 7.000000000000e-02 7.178931705000e+02 1.100000000000e-01 1.239997294500e+03 1.900000000000e-01 6.526301550000e+02 1.000000000000e-01 -3.132624744000e+03 -4.800000000000e-01 3.263150775000e+02 5.000000000000e-02 -1.435786341000e+03 -2.200000000000e-01 -1.501049356500e+03 -2.300000000000e-01 -3.002098713000e+03 -4.600000000000e-01 4.176832992000e+03 6.400000000000e-01 1.827364434000e+03 2.800000000000e-01 1.827364434000e+03 2.800000000000e-01 -2.023153480500e+03 -3.100000000000e-01 -5.221041240000e+02 -8.000000000000e-02 6.526301550000e+01 1.000000000000e-02 1.696838403000e+03 2.600000000000e-01 -1.957890465000e+02 -3.000000000000e-02 2.610520620000e+02 4.000000000000e-02 8.484192015000e+02 1.300000000000e-01 1.174734279000e+03 1.800000000000e-01 3.263150775000e+02 5.000000000000e-02 -1.239997294500e+03 -1.900000000000e-01 + 6 EWK_RAP 1.210000000000e+00 6.463838404000e+03 7.000000000000e+03 6.593128270000e+05 4.747052354400e+03 5.472296464100e+03 8.300000000000e-01 2.307594894500e+04 3.500000000000e+00 1.516419502100e+03 2.300000000000e-01 -1.186763088600e+03 -1.800000000000e-01 5.933815443000e+02 9.000000000000e-02 1.318625654000e+03 2.000000000000e-01 2.637251308000e+02 4.000000000000e-02 -6.593128270000e+01 -1.000000000000e-02 1.318625654000e+02 2.000000000000e-02 0.000000000000e+00 0.000000000000e+00 7.252441097000e+02 1.100000000000e-01 9.889692405000e+02 1.500000000000e-01 7.252441097000e+02 1.100000000000e-01 6.593128270000e+02 1.000000000000e-01 -3.032839004200e+03 -4.600000000000e-01 5.274502616000e+02 8.000000000000e-02 -1.516419502100e+03 -2.300000000000e-01 -1.450488219400e+03 -2.200000000000e-01 -4.351464658200e+03 -6.600000000000e-01 2.373526177200e+03 3.600000000000e-01 1.912007198300e+03 2.900000000000e-01 1.912007198300e+03 2.900000000000e-01 -1.120831805900e+03 -1.700000000000e-01 0.000000000000e+00 0.000000000000e+00 -3.296564135000e+02 -5.000000000000e-02 -2.637251308000e+02 -4.000000000000e-02 1.318625654000e+02 2.000000000000e-02 1.450488219400e+03 2.200000000000e-01 1.186763088600e+03 1.800000000000e-01 1.384556936700e+03 2.100000000000e-01 3.296564135000e+02 5.000000000000e-02 -5.933815443000e+02 -9.000000000000e-02 + 7 EWK_RAP 1.445000000000e+00 6.463838404000e+03 7.000000000000e+03 6.425348380000e+05 8.802727280600e+03 8.352952894000e+03 1.300000000000e+00 2.248871933000e+04 3.500000000000e+00 1.477830127400e+03 2.300000000000e-01 -1.156562708400e+03 -1.800000000000e-01 5.782813542000e+02 9.000000000000e-02 1.285069676000e+03 2.000000000000e-01 3.855209028000e+02 6.000000000000e-02 -1.285069676000e+02 -2.000000000000e-02 1.285069676000e+02 2.000000000000e-02 -1.927604514000e+02 -3.000000000000e-02 1.092309224600e+03 1.700000000000e-01 1.156562708400e+03 1.800000000000e-01 7.710418056000e+02 1.200000000000e-01 4.497743866000e+02 7.000000000000e-02 -3.919462511800e+03 -6.100000000000e-01 5.140278704000e+02 8.000000000000e-02 -1.156562708400e+03 -1.800000000000e-01 -1.670590578800e+03 -2.600000000000e-01 -6.425348380000e+03 -1.000000000000e+00 2.570139352000e+03 4.000000000000e-01 6.425348380000e+02 1.000000000000e-01 3.084167222400e+03 4.800000000000e-01 -1.927604514000e+03 -3.000000000000e-01 1.927604514000e+02 3.000000000000e-02 -1.220816192200e+03 -1.900000000000e-01 -4.497743866000e+02 -7.000000000000e-02 1.285069676000e+02 2.000000000000e-02 3.148420706200e+03 4.900000000000e-01 2.634392835800e+03 4.100000000000e-01 2.955660254800e+03 4.600000000000e-01 9.638022570000e+02 1.500000000000e-01 2.313125416800e+03 3.600000000000e-01 + 8 EWK_RAP 1.630000000000e+00 6.463838404000e+03 7.000000000000e+03 6.409354790000e+05 5.383858023600e+03 4.999296736200e+03 7.800000000000e-01 2.243274176500e+04 3.500000000000e+00 1.474151601700e+03 2.300000000000e-01 -1.153683862200e+03 -1.800000000000e-01 5.768419311000e+02 9.000000000000e-02 1.281870958000e+03 2.000000000000e-01 2.563741916000e+02 4.000000000000e-02 -6.409354790000e+01 -1.000000000000e-02 1.281870958000e+02 2.000000000000e-02 0.000000000000e+00 0.000000000000e+00 7.050290269000e+02 1.100000000000e-01 7.050290269000e+02 1.100000000000e-01 7.691225748000e+02 1.200000000000e-01 7.050290269000e+02 1.100000000000e-01 -3.140583847100e+03 -4.900000000000e-01 3.845612874000e+02 6.000000000000e-02 -1.666432245400e+03 -2.600000000000e-01 -1.345964505900e+03 -2.100000000000e-01 -4.101987065600e+03 -6.400000000000e-01 2.371461272300e+03 3.700000000000e-01 1.089590314300e+03 1.700000000000e-01 1.730525793300e+03 2.700000000000e-01 -7.050290269000e+02 -1.100000000000e-01 6.409354790000e+01 1.000000000000e-02 -7.050290269000e+02 -1.100000000000e-01 8.973096706000e+02 1.400000000000e-01 1.922806437000e+02 3.000000000000e-02 8.332161227000e+02 1.300000000000e-01 1.153683862200e+03 1.800000000000e-01 1.153683862200e+03 1.800000000000e-01 3.204677395000e+02 5.000000000000e-02 -1.922806437000e+02 -3.000000000000e-02 + 9 EWK_RAP 1.845000000000e+00 6.463838404000e+03 7.000000000000e+03 6.609834950000e+05 5.816654756000e+03 5.816654756000e+03 8.800000000000e-01 2.313442232500e+04 3.500000000000e+00 1.520262038500e+03 2.300000000000e-01 -1.189770291000e+03 -1.800000000000e-01 5.948851455000e+02 9.000000000000e-02 1.321966990000e+03 2.000000000000e-01 3.304917475000e+02 5.000000000000e-02 -6.609834950000e+01 -1.000000000000e-02 1.321966990000e+02 2.000000000000e-02 0.000000000000e+00 0.000000000000e+00 7.931801940000e+02 1.200000000000e-01 7.931801940000e+02 1.200000000000e-01 8.592785435000e+02 1.300000000000e-01 7.270818445000e+02 1.100000000000e-01 -3.371015824500e+03 -5.100000000000e-01 5.948851455000e+02 9.000000000000e-02 -1.718557087000e+03 -2.600000000000e-01 -1.586360388000e+03 -2.400000000000e-01 -4.098097669000e+03 -6.200000000000e-01 3.040524077000e+03 4.600000000000e-01 1.850753786000e+03 2.800000000000e-01 2.445638931500e+03 3.700000000000e-01 -1.057573592000e+03 -1.600000000000e-01 7.270818445000e+02 1.100000000000e-01 -6.609834950000e+02 -1.000000000000e-01 -7.931801940000e+02 -1.200000000000e-01 -1.321966990000e+02 -2.000000000000e-02 1.784655436500e+03 2.700000000000e-01 1.454163689000e+03 2.200000000000e-01 1.916852135500e+03 2.900000000000e-01 5.287867960000e+02 8.000000000000e-02 -1.321966990000e+02 -2.000000000000e-02 + 10 EWK_RAP 2.065000000000e+00 6.463838404000e+03 7.000000000000e+03 6.398760310000e+05 5.438946263500e+03 5.566921469700e+03 8.700000000000e-01 2.239566108500e+04 3.500000000000e+00 1.471714871300e+03 2.300000000000e-01 -1.151776855800e+03 -1.800000000000e-01 5.758884279000e+02 9.000000000000e-02 1.279752062000e+03 2.000000000000e-01 1.919628093000e+02 3.000000000000e-02 0.000000000000e+00 0.000000000000e+00 1.919628093000e+02 3.000000000000e-02 1.919628093000e+02 3.000000000000e-02 7.038636341000e+02 1.100000000000e-01 7.678512372000e+02 1.200000000000e-01 8.318388403000e+02 1.300000000000e-01 7.038636341000e+02 1.100000000000e-01 -2.815454536400e+03 -4.400000000000e-01 4.479132217000e+02 7.000000000000e-02 -1.663677680600e+03 -2.600000000000e-01 -1.087789252700e+03 -1.700000000000e-01 -3.839256186000e+03 -6.000000000000e-01 2.303553711600e+03 3.600000000000e-01 1.343739665100e+03 2.100000000000e-01 1.599690077500e+03 2.500000000000e-01 -1.599690077500e+03 -2.500000000000e-01 -6.398760310000e+01 -1.000000000000e-02 -6.398760310000e+02 -1.000000000000e-01 -1.919628093000e+02 -3.000000000000e-02 -4.479132217000e+02 -7.000000000000e-02 2.815454536400e+03 4.400000000000e-01 1.151776855800e+03 1.800000000000e-01 1.535702474400e+03 2.400000000000e-01 5.758884279000e+02 9.000000000000e-02 -3.839256186000e+02 -6.000000000000e-02 + 11 EWK_RAP 2.340000000000e+00 6.463838404000e+03 7.000000000000e+03 5.892058930000e+05 5.243932447700e+03 5.774217751400e+03 9.800000000000e-01 2.062220625500e+04 3.500000000000e+00 1.355173553900e+03 2.300000000000e-01 -1.060570607400e+03 -1.800000000000e-01 5.302853037000e+02 9.000000000000e-02 1.178411786000e+03 2.000000000000e-01 1.178411786000e+02 2.000000000000e-02 -5.892058930000e+01 -1.000000000000e-02 4.713647144000e+02 8.000000000000e-02 -1.767617679000e+02 -3.000000000000e-02 2.946029465000e+02 5.000000000000e-02 6.481264823000e+02 1.100000000000e-01 1.414094143200e+03 2.400000000000e-01 5.892058930000e+01 1.000000000000e-02 -2.828188286400e+03 -4.800000000000e-01 2.946029465000e+02 5.000000000000e-02 -1.708697089700e+03 -2.900000000000e-01 -1.414094143200e+03 -2.400000000000e-01 -4.831488322600e+03 -8.200000000000e-01 2.710347107800e+03 4.600000000000e-01 1.355173553900e+03 2.300000000000e-01 1.119491196700e+03 1.900000000000e-01 -1.944379446900e+03 -3.300000000000e-01 4.713647144000e+02 8.000000000000e-02 -1.119491196700e+03 -1.900000000000e-01 -2.356823572000e+02 -4.000000000000e-02 -5.892058930000e+01 -1.000000000000e-02 1.590855911100e+03 2.700000000000e-01 1.119491196700e+03 1.900000000000e-01 1.826538268300e+03 3.100000000000e-01 3.535235358000e+02 6.000000000000e-02 -1.178411786000e+02 -2.000000000000e-02 + 12 EWK_RAP 1.050000000000e-01 6.463838404000e+03 7.000000000000e+03 4.546661840000e+05 5.274127734400e+03 5.865193773600e+03 1.290000000000e+00 1.591331644000e+04 3.500000000000e+00 4.546661840000e+02 1.000000000000e-01 8.183991312000e+02 1.800000000000e-01 1.045732223200e+03 2.300000000000e-01 8.638657496000e+02 1.900000000000e-01 1.363998552000e+02 3.000000000000e-02 -4.546661840000e+01 -1.000000000000e-02 1.818664736000e+02 4.000000000000e-02 2.273330920000e+02 5.000000000000e-02 3.182663288000e+02 7.000000000000e-02 5.001328024000e+02 1.100000000000e-01 7.729325128000e+02 1.700000000000e-01 2.727997104000e+02 6.000000000000e-02 -1.909597972800e+03 -4.200000000000e-01 3.637329472000e+02 8.000000000000e-02 -8.183991312000e+02 -1.800000000000e-01 -1.318531933600e+03 -2.900000000000e-01 -2.591597248800e+03 -5.700000000000e-01 1.773198117600e+03 3.900000000000e-01 1.363998552000e+03 3.000000000000e-01 1.545865025600e+03 3.400000000000e-01 -1.864131354400e+03 -4.100000000000e-01 -5.001328024000e+02 -1.100000000000e-01 5.455994208000e+02 1.200000000000e-01 -5.001328024000e+02 -1.100000000000e-01 -9.093323680000e+01 -2.000000000000e-02 2.318797538400e+03 5.100000000000e-01 -3.637329472000e+02 -8.000000000000e-02 5.001328024000e+02 1.100000000000e-01 3.182663288000e+02 7.000000000000e-02 -7.274658944000e+02 -1.600000000000e-01 + 13 EWK_RAP 3.150000000000e-01 6.463838404000e+03 7.000000000000e+03 4.484928620000e+05 4.843722909600e+03 5.067969340600e+03 1.130000000000e+00 1.569725017000e+04 3.500000000000e+00 4.484928620000e+02 1.000000000000e-01 8.072871516000e+02 1.800000000000e-01 1.031533582600e+03 2.300000000000e-01 8.521364378000e+02 1.900000000000e-01 1.345478586000e+02 3.000000000000e-02 0.000000000000e+00 0.000000000000e+00 2.242464310000e+02 5.000000000000e-02 2.690957172000e+02 6.000000000000e-02 3.139450034000e+02 7.000000000000e-02 4.933421482000e+02 1.100000000000e-01 8.072871516000e+02 1.800000000000e-01 4.036435758000e+02 9.000000000000e-02 -1.883670020400e+03 -4.200000000000e-01 2.242464310000e+02 5.000000000000e-02 -8.969857240000e+02 -2.000000000000e-01 -1.300629299800e+03 -2.900000000000e-01 -2.152765737600e+03 -4.800000000000e-01 1.973368592800e+03 4.400000000000e-01 1.659423589400e+03 3.700000000000e-01 1.524875730800e+03 3.400000000000e-01 -1.704272875600e+03 -3.800000000000e-01 -3.587942896000e+02 -8.000000000000e-02 7.624378654000e+02 1.700000000000e-01 -8.072871516000e+02 -1.800000000000e-01 -7.175885792000e+02 -1.600000000000e-01 1.838820734200e+03 4.100000000000e-01 -6.727392930000e+02 -1.500000000000e-01 9.418350102000e+02 2.100000000000e-01 3.139450034000e+02 7.000000000000e-02 -4.484928620000e+02 -1.000000000000e-01 + 14 EWK_RAP 5.250000000000e-01 6.463838404000e+03 7.000000000000e+03 4.635696220000e+05 4.821124068800e+03 5.099265842000e+03 1.100000000000e+00 1.622493677000e+04 3.500000000000e+00 4.635696220000e+02 1.000000000000e-01 8.344253196000e+02 1.800000000000e-01 1.066210130600e+03 2.300000000000e-01 8.807822818000e+02 1.900000000000e-01 1.854278488000e+02 4.000000000000e-02 -4.635696220000e+01 -1.000000000000e-02 2.781417732000e+02 6.000000000000e-02 1.390708866000e+02 3.000000000000e-02 3.244987354000e+02 7.000000000000e-02 4.172126598000e+02 9.000000000000e-02 7.417113952000e+02 1.600000000000e-01 2.781417732000e+02 6.000000000000e-02 -2.086063299000e+03 -4.500000000000e-01 2.317848110000e+02 5.000000000000e-02 -9.271392440000e+02 -2.000000000000e-01 -1.437065828200e+03 -3.100000000000e-01 -2.410562034400e+03 -5.200000000000e-01 2.317848110000e+03 5.000000000000e-01 1.483422790400e+03 3.200000000000e-01 1.483422790400e+03 3.200000000000e-01 -1.297994941600e+03 -2.800000000000e-01 -3.708556976000e+02 -8.000000000000e-02 8.807822818000e+02 1.900000000000e-01 -6.489974708000e+02 -1.400000000000e-01 -6.489974708000e+02 -1.400000000000e-01 2.317848110000e+03 5.000000000000e-01 -8.344253196000e+02 -1.800000000000e-01 5.562835464000e+02 1.200000000000e-01 2.317848110000e+02 5.000000000000e-02 -4.635696220000e+02 -1.000000000000e-01 + 15 EWK_RAP 7.350000000000e-01 6.463838404000e+03 7.000000000000e+03 4.480344470000e+05 5.017985806400e+03 5.824447811000e+03 1.300000000000e+00 1.568120564500e+04 3.500000000000e+00 4.480344470000e+02 1.000000000000e-01 8.064620046000e+02 1.800000000000e-01 1.030479228100e+03 2.300000000000e-01 8.512654493000e+02 1.900000000000e-01 1.792137788000e+02 4.000000000000e-02 -4.480344470000e+01 -1.000000000000e-02 2.240172235000e+02 5.000000000000e-02 2.688206682000e+02 6.000000000000e-02 3.584275576000e+02 8.000000000000e-02 4.480344470000e+02 1.000000000000e-01 8.064620046000e+02 1.800000000000e-01 4.032310023000e+02 9.000000000000e-02 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2.616449454000e+02 6.000000000000e-02 -6.105048726000e+02 -1.400000000000e-01 + 17 EWK_RAP 1.210000000000e+00 6.463838404000e+03 7.000000000000e+03 4.267232430000e+05 3.840509187000e+03 4.053870808500e+03 9.500000000000e-01 1.493531350500e+04 3.500000000000e+00 4.267232430000e+02 1.000000000000e-01 7.681018374000e+02 1.800000000000e-01 9.814634589000e+02 2.300000000000e-01 8.107741617000e+02 1.900000000000e-01 1.706892972000e+02 4.000000000000e-02 0.000000000000e+00 0.000000000000e+00 2.133616215000e+02 5.000000000000e-02 1.280169729000e+02 3.000000000000e-02 4.693955673000e+02 1.100000000000e-01 5.547402159000e+02 1.300000000000e-01 7.681018374000e+02 1.800000000000e-01 5.547402159000e+02 1.300000000000e-01 -2.090943890700e+03 -4.900000000000e-01 4.693955673000e+02 1.100000000000e-01 -1.365514377600e+03 -3.200000000000e-01 -1.450859026200e+03 -3.400000000000e-01 -2.560339458000e+03 -6.000000000000e-01 1.578875999100e+03 3.700000000000e-01 1.408186701900e+03 3.300000000000e-01 1.920254593500e+03 4.500000000000e-01 -2.005599242100e+03 -4.700000000000e-01 -8.534464860000e+01 -2.000000000000e-02 1.280169729000e+02 3.000000000000e-02 -6.400848645000e+02 -1.500000000000e-01 -4.693955673000e+02 -1.100000000000e-01 1.066808107500e+03 2.500000000000e-01 -8.534464860000e+01 -2.000000000000e-02 1.152152756100e+03 2.700000000000e-01 3.840509187000e+02 9.000000000000e-02 -4.267232430000e+02 -1.000000000000e-01 + 18 EWK_RAP 1.445000000000e+00 6.463838404000e+03 7.000000000000e+03 3.945119490000e+05 7.061763887100e+03 5.325911311500e+03 1.350000000000e+00 1.380791821500e+04 3.500000000000e+00 3.945119490000e+02 1.000000000000e-01 7.101215082000e+02 1.800000000000e-01 9.073774827000e+02 2.300000000000e-01 7.495727031000e+02 1.900000000000e-01 1.972559745000e+02 5.000000000000e-02 -7.890238980000e+01 -2.000000000000e-02 1.578047796000e+02 4.000000000000e-02 2.367071694000e+02 6.000000000000e-02 4.734143388000e+02 1.200000000000e-01 7.495727031000e+02 1.900000000000e-01 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-9.000000000000e-02 1.251876355200e+03 3.200000000000e-01 3.129690888000e+02 8.000000000000e-02 1.173634083000e+02 3.000000000000e-02 + 20 EWK_RAP 1.845000000000e+00 6.463838404000e+03 7.000000000000e+03 3.823079230000e+05 4.473002699100e+03 3.937771606900e+03 1.030000000000e+00 1.338077730500e+04 3.500000000000e+00 3.823079230000e+02 1.000000000000e-01 6.881542614000e+02 1.800000000000e-01 8.793082229000e+02 2.300000000000e-01 7.263850537000e+02 1.900000000000e-01 1.911539615000e+02 5.000000000000e-02 0.000000000000e+00 0.000000000000e+00 1.529231692000e+02 4.000000000000e-02 1.146923769000e+02 3.000000000000e-02 3.823079230000e+02 1.000000000000e-01 4.205387153000e+02 1.100000000000e-01 7.263850537000e+02 1.900000000000e-01 4.970002999000e+02 1.300000000000e-01 -2.064462784200e+03 -5.400000000000e-01 4.970002999000e+02 1.300000000000e-01 -1.338077730500e+03 -3.500000000000e-01 -1.414539315100e+03 -3.700000000000e-01 -2.332078330300e+03 -6.100000000000e-01 1.796847238100e+03 4.700000000000e-01 1.261616145900e+03 3.300000000000e-01 1.835078030400e+03 4.800000000000e-01 -1.682154861200e+03 -4.400000000000e-01 -3.823079230000e+01 -1.000000000000e-02 4.205387153000e+02 1.100000000000e-01 -8.793082229000e+02 -2.300000000000e-01 -3.823079230000e+02 -1.000000000000e-01 1.376308522800e+03 3.600000000000e-01 -3.058463384000e+02 -8.000000000000e-02 9.557698075000e+02 2.500000000000e-01 3.058463384000e+02 8.000000000000e-02 -3.823079230000e+01 -1.000000000000e-02 + 21 EWK_RAP 2.065000000000e+00 6.463838404000e+03 7.000000000000e+03 3.640731930000e+05 4.114027080900e+03 3.567917291400e+03 9.800000000000e-01 1.274256175500e+04 3.500000000000e+00 3.640731930000e+02 1.000000000000e-01 6.553317474000e+02 1.800000000000e-01 8.373683439000e+02 2.300000000000e-01 6.917390667000e+02 1.900000000000e-01 1.456292772000e+02 4.000000000000e-02 -3.640731930000e+01 -1.000000000000e-02 1.456292772000e+02 4.000000000000e-02 1.820365965000e+02 5.000000000000e-02 3.640731930000e+02 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8.092308312000e+02 2.400000000000e-01 3.034615617000e+02 9.000000000000e-02 9.778205877000e+02 2.900000000000e-01 3.034615617000e+02 9.000000000000e-02 0.000000000000e+00 0.000000000000e+00 diff --git a/nnpdfcpp/data/commondata/DATA_ATLASZRAP11CC.dat b/nnpdfcpp/data/commondata/DATA_ATLASZRAP11CC.dat new file mode 100644 index 0000000000..1dd11d57d4 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_ATLASZRAP11CC.dat @@ -0,0 +1,25 @@ +ATLASZRAP11CC 133 24 + 1 EWK_RAP 2.000000000000e-01 3.136000000000e+03 7.000000000000e+03 3.524400000000e+03 3.421839960000e+01 1.824828588000e+01 5.177700000000e-01 -1.621224000000e+00 -4.600000000000e-02 1.515492000000e+00 4.300000000000e-02 5.533308000000e+00 1.570000000000e-01 1.057320000000e+00 3.000000000000e-02 9.868320000000e-01 2.800000000000e-02 -1.409760000000e+00 -4.000000000000e-02 1.198296000000e+00 3.400000000000e-02 -1.832688000000e+00 -5.200000000000e-02 1.621224000000e+00 4.600000000000e-02 -6.943068000000e+00 -1.970000000000e-01 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5.991480000000e-01 1.700000000000e-02 -5.639040000000e-01 -1.600000000000e-02 -2.467080000000e-01 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 5.639040000000e-01 1.600000000000e-02 -3.524400000000e-01 -1.000000000000e-02 7.048800000000e-02 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.467080000000e-01 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.762200000000e-01 5.000000000000e-03 -2.467080000000e-01 -7.000000000000e-03 1.057320000000e-01 3.000000000000e-03 -4.581720000000e-01 -1.300000000000e-02 2.467080000000e-01 7.000000000000e-03 -2.819520000000e-01 -8.000000000000e-03 -2.713788000000e+00 -7.700000000000e-02 -2.008908000000e+00 -5.700000000000e-02 -8.811000000000e-01 -2.500000000000e-02 -1.057320000000e-01 -3.000000000000e-03 -1.409760000000e-01 -4.000000000000e-03 -3.524400000000e-02 -1.000000000000e-03 -5.991480000000e-01 -1.700000000000e-02 1.867932000000e+00 5.300000000000e-02 5.991480000000e-01 1.700000000000e-02 1.163052000000e+00 3.300000000000e-02 2.467080000000e-01 7.000000000000e-03 1.339272000000e+00 3.800000000000e-02 -1.233540000000e+00 -3.500000000000e-02 -1.092564000000e+00 -3.100000000000e-02 -2.114640000000e-01 -6.000000000000e-03 -8.811000000000e-01 -2.500000000000e-02 -7.048800000000e-01 -2.000000000000e-02 -4.581720000000e-01 -1.300000000000e-02 6.696360000000e-01 1.900000000000e-02 6.343920000000e+01 1.800000000000e+00 4.881294000000e+00 1.385000000000e-01 + 2 EWK_RAP 6.000000000000e-01 3.136000000000e+03 7.000000000000e+03 3.549000000000e+03 3.363600240000e+01 1.683965010000e+01 4.744900000000e-01 -1.206660000000e+00 -3.400000000000e-02 1.774500000000e+00 5.000000000000e-02 5.500950000000e+00 1.550000000000e-01 7.452900000000e-01 2.100000000000e-02 2.058420000000e+00 5.800000000000e-02 -1.597050000000e+00 -4.500000000000e-02 9.582300000000e-01 2.700000000000e-02 9.227400000000e-01 2.600000000000e-02 1.206660000000e+00 3.400000000000e-02 -7.239960000000e+00 -2.040000000000e-01 8.801520000000e+00 2.480000000000e-01 5.288010000000e+00 1.490000000000e-01 7.098000000000e-02 2.000000000000e-03 2.129400000000e-01 6.000000000000e-03 1.110837000000e+01 3.130000000000e-01 2.839200000000e-01 8.000000000000e-03 9.582300000000e-01 2.700000000000e-02 2.484300000000e-01 7.000000000000e-03 1.064700000000e-01 3.000000000000e-03 4.968600000000e-01 1.400000000000e-02 -2.484300000000e-01 -7.000000000000e-03 1.064700000000e-01 3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.549000000000e-02 -1.000000000000e-03 -1.419600000000e-01 -4.000000000000e-03 2.129400000000e-01 6.000000000000e-03 -1.774500000000e-01 -5.000000000000e-03 1.064700000000e-01 3.000000000000e-03 -1.064700000000e-01 -3.000000000000e-03 -7.098000000000e-02 -2.000000000000e-03 -3.549000000000e-02 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.064700000000e-01 -3.000000000000e-03 7.098000000000e-02 2.000000000000e-03 -7.098000000000e-02 -2.000000000000e-03 4.613700000000e-01 1.300000000000e-02 -2.839200000000e-01 -8.000000000000e-03 3.549000000000e-02 1.000000000000e-03 3.549000000000e-02 1.000000000000e-03 -2.484300000000e-01 -7.000000000000e-03 -1.774500000000e-01 -5.000000000000e-03 -3.549000000000e-01 -1.000000000000e-02 1.064700000000e-01 3.000000000000e-03 -1.419600000000e-01 -4.000000000000e-03 -4.613700000000e-01 -1.300000000000e-02 3.549000000000e-02 1.000000000000e-03 -6.388200000000e-01 -1.800000000000e-02 1.064700000000e-01 3.000000000000e-03 -3.903900000000e-01 -1.100000000000e-02 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 5.678400000000e-01 1.600000000000e-02 2.725632000000e+01 7.680000000000e-01 -2.200380000000e+00 -6.200000000000e-02 -1.880970000000e+00 -5.300000000000e-02 2.981160000000e+00 8.400000000000e-02 -1.561560000000e+00 -4.400000000000e-02 -1.774500000000e-01 -5.000000000000e-03 5.181540000000e+00 1.460000000000e-01 2.910180000000e+00 8.200000000000e-02 1.419600000000e+00 4.000000000000e-02 -1.206660000000e+00 -3.400000000000e-02 -3.265080000000e+00 -9.200000000000e-02 -1.455090000000e+00 -4.100000000000e-02 -7.098000000000e-01 -2.000000000000e-02 2.093910000000e+00 5.900000000000e-02 -7.098000000000e-02 -2.000000000000e-03 -9.937200000000e-01 -2.800000000000e-02 2.271360000000e+00 6.400000000000e-02 7.098000000000e-02 2.000000000000e-03 6.956040000000e+00 1.960000000000e-01 5.288010000000e+00 1.490000000000e-01 2.413320000000e+00 6.800000000000e-02 2.129400000000e-01 6.000000000000e-03 -9.937200000000e-01 -2.800000000000e-02 -1.064700000000e-01 -3.000000000000e-03 -3.194100000000e-01 -9.000000000000e-03 -3.903900000000e-01 -1.100000000000e-02 1.061151000000e+01 2.990000000000e-01 -1.774500000000e+00 -5.000000000000e-02 3.549000000000e-01 1.000000000000e-02 4.968600000000e-01 1.400000000000e-02 5.323500000000e-01 1.500000000000e-02 -8.517600000000e-01 -2.400000000000e-02 -8.872500000000e-01 -2.500000000000e-02 7.452900000000e-01 2.100000000000e-02 1.313130000000e+00 3.700000000000e-02 5.323500000000e-01 1.500000000000e-02 3.549000000000e-02 1.000000000000e-03 -5.323500000000e-01 -1.500000000000e-02 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 5.323500000000e-01 1.500000000000e-02 -1.419600000000e-01 -4.000000000000e-03 3.549000000000e-02 1.000000000000e-03 -7.098000000000e-02 -2.000000000000e-03 -2.839200000000e-01 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.484300000000e-01 7.000000000000e-03 -3.549000000000e-02 -1.000000000000e-03 7.098000000000e-02 2.000000000000e-03 -5.678400000000e-01 -1.600000000000e-02 2.129400000000e-01 6.000000000000e-03 -2.129400000000e-01 -6.000000000000e-03 -2.342340000000e+00 -6.600000000000e-02 -1.632540000000e+00 -4.600000000000e-02 -9.937200000000e-01 -2.800000000000e-02 0.000000000000e+00 0.000000000000e+00 -3.549000000000e-02 -1.000000000000e-03 1.064700000000e-01 3.000000000000e-03 -2.484300000000e-01 -7.000000000000e-03 1.526070000000e+00 4.300000000000e-02 1.135680000000e+00 3.200000000000e-02 9.227400000000e-01 2.600000000000e-02 2.484300000000e-01 7.000000000000e-03 1.206660000000e+00 3.400000000000e-02 -1.029210000000e+00 -2.900000000000e-02 -1.206660000000e+00 -3.400000000000e-02 -1.774500000000e-01 -5.000000000000e-03 -1.171170000000e+00 -3.300000000000e-02 -5.678400000000e-01 -1.600000000000e-02 -1.064700000000e-01 -3.000000000000e-03 7.098000000000e-01 2.000000000000e-02 6.388200000000e+01 1.800000000000e+00 4.871002500000e+00 1.372500000000e-01 + 3 EWK_RAP 1.000000000000e+00 3.136000000000e+03 7.000000000000e+03 3.411400000000e+03 3.320588532000e+01 1.651936336000e+01 4.842400000000e-01 -3.070260000000e-01 -9.000000000000e-03 2.353866000000e+00 6.900000000000e-02 6.345204000000e+00 1.860000000000e-01 7.505080000000e-01 2.200000000000e-02 5.117100000000e-01 1.500000000000e-02 -3.274944000000e+00 -9.600000000000e-02 6.822800000000e-02 2.000000000000e-03 4.980644000000e+00 1.460000000000e-01 -6.822800000000e-01 -2.000000000000e-02 -7.948562000000e+00 -2.330000000000e-01 8.664956000000e+00 2.540000000000e-01 4.298364000000e+00 1.260000000000e-01 3.411400000000e-02 1.000000000000e-03 1.705700000000e-01 5.000000000000e-03 1.078002400000e+01 3.160000000000e-01 3.070260000000e-01 9.000000000000e-03 9.893060000000e-01 2.900000000000e-02 2.387980000000e-01 7.000000000000e-03 1.364560000000e-01 4.000000000000e-03 9.893060000000e-01 2.900000000000e-02 -5.458240000000e-01 -1.600000000000e-02 3.411400000000e-01 1.000000000000e-02 -1.023420000000e-01 -3.000000000000e-03 -3.411400000000e-02 -1.000000000000e-03 -1.364560000000e-01 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.387980000000e-01 -7.000000000000e-03 1.705700000000e-01 5.000000000000e-03 -1.023420000000e-01 -3.000000000000e-03 -2.387980000000e-01 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.705700000000e-01 -5.000000000000e-03 -2.046840000000e-01 -6.000000000000e-03 6.822800000000e-02 2.000000000000e-03 -1.705700000000e-01 -5.000000000000e-03 3.752540000000e-01 1.100000000000e-02 -4.434820000000e-01 -1.300000000000e-02 6.822800000000e-02 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -6.822800000000e-01 -2.000000000000e-02 -3.070260000000e-01 -9.000000000000e-03 -4.434820000000e-01 -1.300000000000e-02 3.411400000000e-02 1.000000000000e-03 -1.364560000000e-01 -4.000000000000e-03 -4.093680000000e-01 -1.200000000000e-02 6.822800000000e-02 2.000000000000e-03 -7.163940000000e-01 -2.100000000000e-02 1.364560000000e-01 4.000000000000e-03 -6.481660000000e-01 -1.900000000000e-02 -6.822800000000e-02 -2.000000000000e-03 3.718426000000e+00 1.090000000000e-01 1.842156000000e+00 5.400000000000e-02 2.916747000000e+01 8.550000000000e-01 -2.592664000000e+00 -7.600000000000e-02 -3.377286000000e+00 -9.900000000000e-02 2.660892000000e+00 7.800000000000e-02 -1.808042000000e+00 -5.300000000000e-02 -4.093680000000e-01 -1.200000000000e-02 5.492354000000e+00 1.610000000000e-01 2.695006000000e+00 7.900000000000e-02 1.296332000000e+00 3.800000000000e-02 -2.012726000000e+00 -5.900000000000e-02 -3.070260000000e+00 -9.000000000000e-02 -1.535130000000e+00 -4.500000000000e-02 -1.023420000000e+00 -3.000000000000e-02 1.739814000000e+00 5.100000000000e-02 -1.023420000000e-01 -3.000000000000e-03 -2.729120000000e+00 -8.000000000000e-02 3.036146000000e+00 8.900000000000e-02 3.411400000000e-02 1.000000000000e-03 6.379318000000e+00 1.870000000000e-01 3.991338000000e+00 1.170000000000e-01 1.398674000000e+00 4.100000000000e-02 -1.023420000000e-01 -3.000000000000e-03 -5.799380000000e-01 -1.700000000000e-02 -1.705700000000e-01 -5.000000000000e-03 5.458240000000e-01 1.600000000000e-02 2.387980000000e-01 7.000000000000e-03 7.880334000000e+00 2.310000000000e-01 -3.411400000000e-02 -1.000000000000e-03 2.831462000000e+00 8.300000000000e-02 1.330446000000e+00 3.900000000000e-02 -1.364560000000e-01 -4.000000000000e-03 -4.093680000000e-01 -1.200000000000e-02 -7.163940000000e-01 -2.100000000000e-02 9.210780000000e-01 2.700000000000e-02 1.057534000000e+00 3.100000000000e-02 6.140520000000e-01 1.800000000000e-02 6.822800000000e-02 2.000000000000e-03 -3.070260000000e-01 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 1.364560000000e-01 4.000000000000e-03 5.117100000000e-01 1.500000000000e-02 1.023420000000e-01 3.000000000000e-03 6.822800000000e-02 2.000000000000e-03 -6.822800000000e-02 -2.000000000000e-03 -3.070260000000e-01 -9.000000000000e-03 6.822800000000e-02 2.000000000000e-03 3.752540000000e-01 1.100000000000e-02 2.046840000000e-01 6.000000000000e-03 1.023420000000e-01 3.000000000000e-03 -6.481660000000e-01 -1.900000000000e-02 1.364560000000e-01 4.000000000000e-03 -1.364560000000e-01 -4.000000000000e-03 -1.978612000000e+00 -5.800000000000e-02 -1.364560000000e+00 -4.000000000000e-02 -1.023420000000e+00 -3.000000000000e-02 1.023420000000e-01 3.000000000000e-03 3.411400000000e-02 1.000000000000e-03 2.387980000000e-01 7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.228104000000e+00 3.600000000000e-02 1.398674000000e+00 4.100000000000e-02 5.799380000000e-01 1.700000000000e-02 3.070260000000e-01 9.000000000000e-03 1.193990000000e+00 3.500000000000e-02 -7.505080000000e-01 -2.200000000000e-02 -1.398674000000e+00 -4.100000000000e-02 -1.364560000000e-01 -4.000000000000e-03 -1.364560000000e+00 -4.000000000000e-02 -4.434820000000e-01 -1.300000000000e-02 3.411400000000e-01 1.000000000000e-02 6.822800000000e-01 2.000000000000e-02 6.140520000000e+01 1.800000000000e+00 5.441183000000e+00 1.595000000000e-01 + 4 EWK_RAP 1.400000000000e+00 3.136000000000e+03 7.000000000000e+03 3.422800000000e+03 3.439914000000e+01 1.658038548000e+01 4.844100000000e-01 -1.711400000000e-01 -5.000000000000e-03 2.704012000000e+00 7.900000000000e-02 6.777144000000e+00 1.980000000000e-01 -1.642944000000e+00 -4.800000000000e-02 1.916768000000e+00 5.600000000000e-02 -4.723464000000e+00 -1.380000000000e-01 -1.300664000000e+00 -3.800000000000e-02 4.894604000000e+00 1.430000000000e-01 -2.122136000000e+00 -6.200000000000e-02 -8.317404000000e+00 -2.430000000000e-01 5.989900000000e+00 1.750000000000e-01 2.977836000000e+00 8.700000000000e-02 6.845600000000e-02 2.000000000000e-03 2.053680000000e-01 6.000000000000e-03 1.016571600000e+01 2.970000000000e-01 2.395960000000e-01 7.000000000000e-03 8.557000000000e-01 2.500000000000e-02 1.369120000000e-01 4.000000000000e-03 2.053680000000e-01 6.000000000000e-03 1.300664000000e+00 3.800000000000e-02 -5.818760000000e-01 -1.700000000000e-02 3.422800000000e-01 1.000000000000e-02 3.422800000000e-02 1.000000000000e-03 1.369120000000e-01 4.000000000000e-03 -1.711400000000e-01 -5.000000000000e-03 -1.369120000000e-01 -4.000000000000e-03 -3.765080000000e-01 -1.100000000000e-02 3.765080000000e-01 1.100000000000e-02 -1.711400000000e-01 -5.000000000000e-03 -2.053680000000e-01 -6.000000000000e-03 1.369120000000e-01 4.000000000000e-03 -3.765080000000e-01 -1.100000000000e-02 -4.107360000000e-01 -1.200000000000e-02 2.053680000000e-01 6.000000000000e-03 -1.026840000000e-01 -3.000000000000e-03 3.422800000000e-02 1.000000000000e-03 -7.187880000000e-01 -2.100000000000e-02 2.053680000000e-01 6.000000000000e-03 -2.053680000000e-01 -6.000000000000e-03 -1.026840000000e+00 -3.000000000000e-02 -3.422800000000e-01 -1.000000000000e-02 -3.422800000000e-01 -1.000000000000e-02 0.000000000000e+00 0.000000000000e+00 -2.053680000000e-01 -6.000000000000e-03 -6.503320000000e-01 -1.900000000000e-02 3.422800000000e-02 1.000000000000e-03 -6.503320000000e-01 -1.900000000000e-02 3.080520000000e-01 9.000000000000e-03 -7.872440000000e-01 -2.300000000000e-02 6.845600000000e-02 2.000000000000e-03 -1.095296000000e+00 -3.200000000000e-02 1.369120000000e-01 4.000000000000e-03 2.584214000000e+01 7.550000000000e-01 -1.950996000000e+00 -5.700000000000e-02 -2.293276000000e+00 -6.700000000000e-02 2.704012000000e+00 7.900000000000e-02 -1.642944000000e+00 -4.800000000000e-02 1.026840000000e-01 3.000000000000e-03 6.263724000000e+00 1.830000000000e-01 2.601328000000e+00 7.600000000000e-02 1.300664000000e+00 3.800000000000e-02 -2.053680000000e+00 -6.000000000000e-02 -3.662396000000e+00 -1.070000000000e-01 -1.334892000000e+00 -3.900000000000e-02 -7.872440000000e-01 -2.300000000000e-02 1.369120000000e+00 4.000000000000e-02 4.107360000000e-01 1.200000000000e-02 -1.403348000000e+00 -4.100000000000e-02 3.422800000000e+00 1.000000000000e-01 3.422800000000e-02 1.000000000000e-03 6.229496000000e+00 1.820000000000e-01 3.457028000000e+00 1.010000000000e-01 1.129524000000e+00 3.300000000000e-02 3.080520000000e-01 9.000000000000e-03 -7.187880000000e-01 -2.100000000000e-02 -2.738240000000e-01 -8.000000000000e-03 5.134200000000e-01 1.500000000000e-02 1.711400000000e-01 5.000000000000e-03 7.119424000000e+00 2.080000000000e-01 2.053680000000e-01 6.000000000000e-03 2.395960000000e+00 7.000000000000e-02 1.061068000000e+00 3.100000000000e-02 -3.422800000000e-01 -1.000000000000e-02 -1.711400000000e-01 -5.000000000000e-03 -5.818760000000e-01 -1.700000000000e-02 1.232208000000e+00 3.600000000000e-02 1.403348000000e+00 4.100000000000e-02 3.080520000000e-01 9.000000000000e-03 -3.765080000000e-01 -1.100000000000e-02 -2.053680000000e-01 -6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -5.476480000000e-01 -1.600000000000e-02 5.134200000000e-01 1.500000000000e-02 3.422800000000e-01 1.000000000000e-02 -3.422800000000e-02 -1.000000000000e-03 -2.395960000000e-01 -7.000000000000e-03 -3.422800000000e-01 -1.000000000000e-02 3.422800000000e-02 1.000000000000e-03 -2.738240000000e-01 -8.000000000000e-03 4.791920000000e-01 1.400000000000e-02 -1.026840000000e-01 -3.000000000000e-03 -7.530160000000e-01 -2.200000000000e-02 1.369120000000e-01 4.000000000000e-03 -3.422800000000e-02 -1.000000000000e-03 -2.087908000000e+00 -6.100000000000e-02 -1.129524000000e+00 -3.300000000000e-02 -1.437576000000e+00 -4.200000000000e-02 1.026840000000e-01 3.000000000000e-03 2.738240000000e-01 8.000000000000e-03 6.845600000000e-01 2.000000000000e-02 5.476480000000e-01 1.600000000000e-02 1.300664000000e+00 3.800000000000e-02 2.669784000000e+00 7.800000000000e-02 8.214720000000e-01 2.400000000000e-02 4.107360000000e-01 1.200000000000e-02 1.129524000000e+00 3.300000000000e-02 -8.214720000000e-01 -2.400000000000e-02 -1.711400000000e+00 -5.000000000000e-02 -2.738240000000e-01 -8.000000000000e-03 -1.814084000000e+00 -5.300000000000e-02 -7.872440000000e-01 -2.300000000000e-02 5.476480000000e-01 1.600000000000e-02 1.266436000000e+00 3.700000000000e-02 6.161040000000e+01 1.800000000000e+00 5.544936000000e+00 1.620000000000e-01 + 5 EWK_RAP 1.800000000000e+00 3.136000000000e+03 7.000000000000e+03 2.941700000000e+03 3.214983930000e+01 1.380775146000e+01 4.693800000000e-01 -5.883400000000e-02 -2.000000000000e-03 2.588696000000e+00 8.800000000000e-02 5.648064000000e+00 1.920000000000e-01 -6.765910000000e-01 -2.300000000000e-02 -8.530930000000e-01 -2.900000000000e-02 -3.147619000000e+00 -1.070000000000e-01 4.412550000000e-01 1.500000000000e-02 -1.029595000000e+00 -3.500000000000e-02 -1.000178000000e+00 -3.400000000000e-02 -8.060258000000e+00 -2.740000000000e-01 1.794437000000e+00 6.100000000000e-02 1.500267000000e+00 5.100000000000e-02 2.941700000000e-02 1.000000000000e-03 1.176680000000e-01 4.000000000000e-03 8.854517000000e+00 3.010000000000e-01 2.059190000000e-01 7.000000000000e-03 7.060080000000e-01 2.400000000000e-02 0.000000000000e+00 0.000000000000e+00 2.647530000000e-01 9.000000000000e-03 1.206097000000e+00 4.100000000000e-02 -6.765910000000e-01 -2.300000000000e-02 8.825100000000e-02 3.000000000000e-03 3.530040000000e-01 1.200000000000e-02 1.470850000000e-01 5.000000000000e-03 -5.589230000000e-01 -1.900000000000e-02 3.235870000000e-01 1.100000000000e-02 -5.589230000000e-01 -1.900000000000e-02 5.295060000000e-01 1.800000000000e-02 -1.176680000000e-01 -4.000000000000e-03 -1.176680000000e-01 -4.000000000000e-03 1.176680000000e-01 4.000000000000e-03 -2.059190000000e-01 -7.000000000000e-03 -5.000890000000e-01 -1.700000000000e-02 3.824210000000e-01 1.300000000000e-02 5.883400000000e-02 2.000000000000e-03 1.176680000000e-01 4.000000000000e-03 -6.765910000000e-01 -2.300000000000e-02 2.647530000000e-01 9.000000000000e-03 -5.883400000000e-02 -2.000000000000e-03 -7.942590000000e-01 -2.700000000000e-02 -5.000890000000e-01 -1.700000000000e-02 -2.941700000000e-01 -1.000000000000e-02 8.825100000000e-02 3.000000000000e-03 -1.470850000000e-01 -5.000000000000e-03 -7.060080000000e-01 -2.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -8.236760000000e-01 -2.800000000000e-02 2.353360000000e-01 8.000000000000e-03 -7.060080000000e-01 -2.400000000000e-02 8.825100000000e-02 3.000000000000e-03 -9.589942000000e+00 -3.260000000000e-01 2.412194000000e+00 8.200000000000e-02 2.085665300000e+01 7.090000000000e-01 -2.647530000000e+00 -9.000000000000e-02 -2.412194000000e+00 -8.200000000000e-02 2.265109000000e+00 7.700000000000e-02 -9.413440000000e-01 -3.200000000000e-02 -6.471740000000e-01 -2.200000000000e-02 3.441789000000e+00 1.170000000000e-01 1.941522000000e+00 6.600000000000e-02 1.176680000000e+00 4.000000000000e-02 -7.942590000000e-01 -2.700000000000e-02 -3.294704000000e+00 -1.120000000000e-01 -6.177570000000e-01 -2.100000000000e-02 -7.942590000000e-01 -2.700000000000e-02 9.707610000000e-01 3.300000000000e-02 3.235870000000e-01 1.100000000000e-02 1.470850000000e-01 5.000000000000e-03 1.706186000000e+00 5.800000000000e-02 2.941700000000e-02 1.000000000000e-03 5.795149000000e+00 1.970000000000e-01 2.971117000000e+00 1.010000000000e-01 2.941700000000e-01 1.000000000000e-02 6.177570000000e-01 2.100000000000e-02 -6.765910000000e-01 -2.300000000000e-02 -6.765910000000e-01 -2.300000000000e-02 2.941700000000e-01 1.000000000000e-02 1.176680000000e-01 4.000000000000e-03 5.912817000000e+00 2.010000000000e-01 -5.295060000000e-01 -1.800000000000e-02 1.029595000000e+00 3.500000000000e-02 5.000890000000e-01 1.700000000000e-02 -3.235870000000e-01 -1.100000000000e-02 3.530040000000e-01 1.200000000000e-02 -5.295060000000e-01 -1.800000000000e-02 1.206097000000e+00 4.100000000000e-02 1.500267000000e+00 5.100000000000e-02 -1.765020000000e-01 -6.000000000000e-03 -2.353360000000e-01 -8.000000000000e-03 -5.589230000000e-01 -1.900000000000e-02 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -3.235870000000e-01 -1.100000000000e-02 4.412550000000e-01 1.500000000000e-02 4.706720000000e-01 1.600000000000e-02 -1.470850000000e-01 -5.000000000000e-03 -2.941700000000e-01 -1.000000000000e-02 -1.176680000000e-01 -4.000000000000e-03 2.941700000000e-02 1.000000000000e-03 -5.883400000000e-02 -2.000000000000e-03 8.236760000000e-01 2.800000000000e-02 -2.353360000000e-01 -8.000000000000e-03 -5.883400000000e-01 -2.000000000000e-02 1.176680000000e-01 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.647352000000e+00 -5.600000000000e-02 -1.235514000000e+00 -4.200000000000e-02 -1.470850000000e+00 -5.000000000000e-02 5.883400000000e-02 2.000000000000e-03 1.765020000000e-01 6.000000000000e-03 4.706720000000e-01 1.600000000000e-02 2.941700000000e-01 1.000000000000e-02 1.029595000000e+00 3.500000000000e-02 2.618113000000e+00 8.900000000000e-02 5.295060000000e-01 1.800000000000e-02 4.118380000000e-01 1.400000000000e-02 1.235514000000e+00 4.200000000000e-02 -2.059190000000e-01 -7.000000000000e-03 -1.853271000000e+00 -6.300000000000e-02 -1.765020000000e-01 -6.000000000000e-03 -1.882688000000e+00 -6.400000000000e-02 -5.883400000000e-01 -2.000000000000e-02 1.264931000000e+00 4.300000000000e-02 4.706720000000e-01 1.600000000000e-02 5.295060000000e+01 1.800000000000e+00 6.074610500000e+00 2.065000000000e-01 + 6 EWK_RAP 2.200000000000e+00 3.136000000000e+03 7.000000000000e+03 1.541200000000e+03 2.530650400000e+01 9.321331720000e+00 6.048100000000e-01 -4.623600000000e-02 -3.000000000000e-03 1.340844000000e+00 8.700000000000e-02 2.404272000000e+00 1.560000000000e-01 -4.007120000000e-01 -2.600000000000e-02 -3.236520000000e-01 -2.100000000000e-02 -3.853000000000e-01 -2.500000000000e-02 -2.774160000000e-01 -1.800000000000e-02 -1.155900000000e+00 -7.500000000000e-02 4.007120000000e-01 2.600000000000e-02 -4.438656000000e+00 -2.880000000000e-01 -2.774160000000e-01 -1.800000000000e-02 4.007120000000e-01 2.600000000000e-02 0.000000000000e+00 0.000000000000e+00 4.623600000000e-02 3.000000000000e-03 4.392420000000e+00 2.850000000000e-01 9.247200000000e-02 6.000000000000e-03 2.928280000000e-01 1.900000000000e-02 -3.082400000000e-02 -2.000000000000e-03 1.387080000000e-01 9.000000000000e-03 5.856560000000e-01 3.800000000000e-02 -2.928280000000e-01 -1.900000000000e-02 -1.078840000000e-01 -7.000000000000e-03 2.311800000000e-01 1.500000000000e-02 7.706000000000e-02 5.000000000000e-03 -5.394200000000e-01 -3.500000000000e-02 2.157680000000e-01 1.400000000000e-02 -2.465920000000e-01 -1.600000000000e-02 2.157680000000e-01 1.400000000000e-02 -1.387080000000e-01 -9.000000000000e-03 -1.541200000000e-02 -1.000000000000e-03 7.706000000000e-02 5.000000000000e-03 -3.082400000000e-02 -2.000000000000e-03 -1.387080000000e-01 -9.000000000000e-03 2.928280000000e-01 1.900000000000e-02 6.164800000000e-02 4.000000000000e-03 -3.082400000000e-02 -2.000000000000e-03 -4.161240000000e-01 -2.700000000000e-02 1.387080000000e-01 9.000000000000e-03 -1.232960000000e-01 -8.000000000000e-03 -4.007120000000e-01 -2.600000000000e-02 -2.311800000000e-01 -1.500000000000e-02 -1.232960000000e-01 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.078840000000e-01 -7.000000000000e-03 -3.544760000000e-01 -2.300000000000e-02 4.623600000000e-02 3.000000000000e-03 -2.928280000000e-01 -1.900000000000e-02 7.706000000000e-02 5.000000000000e-03 -2.928280000000e-01 -1.900000000000e-02 9.247200000000e-02 6.000000000000e-03 6.010680000000e-01 3.900000000000e-02 6.858340000000e+00 4.450000000000e-01 1.054180800000e+01 6.840000000000e-01 3.082400000000e-02 2.000000000000e-03 -3.082400000000e-01 -2.000000000000e-02 1.325432000000e+00 8.600000000000e-02 -4.007120000000e-01 -2.600000000000e-02 -6.318920000000e-01 -4.100000000000e-02 1.032604000000e+00 6.700000000000e-02 5.702440000000e-01 3.700000000000e-02 9.709560000000e-01 6.300000000000e-02 -3.853000000000e-01 -2.500000000000e-02 -3.698880000000e-01 -2.400000000000e-02 -3.390640000000e-01 -2.200000000000e-02 -5.394200000000e-01 -3.500000000000e-02 4.007120000000e-01 2.600000000000e-02 3.853000000000e-01 2.500000000000e-02 2.157680000000e-01 1.400000000000e-02 2.049796000000e+00 1.330000000000e-01 1.541200000000e-02 1.000000000000e-03 2.959104000000e+00 1.920000000000e-01 6.935400000000e-01 4.500000000000e-02 6.627160000000e-01 4.300000000000e-02 3.236520000000e-01 2.100000000000e-02 -3.698880000000e-01 -2.400000000000e-02 -1.541200000000e-01 -1.000000000000e-02 -1.541200000000e-02 -1.000000000000e-03 1.078840000000e-01 7.000000000000e-03 2.774160000000e+00 1.800000000000e-01 3.082400000000e-01 2.000000000000e-02 3.236520000000e-01 2.100000000000e-02 4.161240000000e-01 2.700000000000e-02 0.000000000000e+00 0.000000000000e+00 -1.232960000000e-01 -8.000000000000e-03 -2.465920000000e-01 -1.600000000000e-02 7.706000000000e-01 5.000000000000e-02 8.938960000000e-01 5.800000000000e-02 -2.774160000000e-01 -1.800000000000e-02 -2.003560000000e-01 -1.300000000000e-02 -3.544760000000e-01 -2.300000000000e-02 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -2.928280000000e-01 -1.900000000000e-02 1.849440000000e-01 1.200000000000e-02 3.544760000000e-01 2.300000000000e-02 -3.082400000000e-02 -2.000000000000e-03 -2.003560000000e-01 -1.300000000000e-02 -3.082400000000e-02 -2.000000000000e-03 4.623600000000e-02 3.000000000000e-03 -2.465920000000e-01 -1.600000000000e-02 5.856560000000e-01 3.800000000000e-02 -9.247200000000e-02 -6.000000000000e-03 -2.620040000000e-01 -1.700000000000e-02 1.541200000000e-02 1.000000000000e-03 6.164800000000e-02 4.000000000000e-03 -6.935400000000e-01 -4.500000000000e-02 -4.931840000000e-01 -3.200000000000e-02 -8.168360000000e-01 -5.300000000000e-02 4.623600000000e-02 3.000000000000e-03 1.387080000000e-01 9.000000000000e-03 3.544760000000e-01 2.300000000000e-02 3.390640000000e-01 2.200000000000e-02 3.698880000000e-01 2.400000000000e-02 1.587436000000e+00 1.030000000000e-01 2.465920000000e-01 1.600000000000e-02 2.157680000000e-01 1.400000000000e-02 5.085960000000e-01 3.300000000000e-02 -1.541200000000e-02 -1.000000000000e-03 -9.863680000000e-01 -6.400000000000e-02 -1.078840000000e-01 -7.000000000000e-03 -1.140488000000e+00 -7.400000000000e-02 -3.390640000000e-01 -2.200000000000e-02 9.555440000000e-01 6.200000000000e-02 5.702440000000e-01 3.700000000000e-02 2.774160000000e+01 1.800000000000e+00 4.201696500000e+00 2.726250000000e-01 + 7 EWK_RAP 1.000000000000e-01 8.281000000000e+03 7.000000000000e+03 1.352200000000e+05 2.551601400000e+02 1.393712540000e+02 1.030700000000e-01 -5.544020000000e+01 -4.100000000000e-02 6.355340000000e+01 4.700000000000e-02 2.704400000000e+01 2.000000000000e-02 5.408800000000e+00 4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -3.921380000000e+01 -2.900000000000e-02 4.056600000000e+00 3.000000000000e-03 -1.352200000000e+01 -1.000000000000e-02 1.162892000000e+02 8.600000000000e-02 -1.338678000000e+02 -9.900000000000e-02 -5.408800000000e+00 -4.000000000000e-03 1.757860000000e+01 1.300000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.761000000000e+00 5.000000000000e-03 4.056600000000e+00 3.000000000000e-03 1.352200000000e+01 1.000000000000e-02 2.704400000000e+00 2.000000000000e-03 -1.352200000000e+00 -1.000000000000e-03 8.113200000000e+00 6.000000000000e-03 -2.704400000000e+00 -2.000000000000e-03 6.761000000000e+00 5.000000000000e-03 6.761000000000e+00 5.000000000000e-03 -5.408800000000e+00 -4.000000000000e-03 -1.352200000000e+00 -1.000000000000e-03 4.056600000000e+00 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.408800000000e+00 4.000000000000e-03 -2.704400000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.352200000000e+00 1.000000000000e-03 -4.056600000000e+00 -3.000000000000e-03 4.056600000000e+00 3.000000000000e-03 1.352200000000e+00 1.000000000000e-03 -2.704400000000e+00 -2.000000000000e-03 -1.352200000000e+00 -1.000000000000e-03 1.757860000000e+01 1.300000000000e-02 -8.113200000000e+00 -6.000000000000e-03 -8.113200000000e+00 -6.000000000000e-03 -5.408800000000e+00 -4.000000000000e-03 5.408800000000e+00 4.000000000000e-03 8.113200000000e+00 6.000000000000e-03 -6.761000000000e+00 -5.000000000000e-03 -1.352200000000e+00 -1.000000000000e-03 1.352200000000e+00 1.000000000000e-03 -2.704400000000e+00 -2.000000000000e-03 2.704400000000e+00 2.000000000000e-03 -1.352200000000e+01 -1.000000000000e-02 4.056600000000e+00 3.000000000000e-03 2.704400000000e+00 2.000000000000e-03 4.056600000000e+00 3.000000000000e-03 5.273580000000e+01 3.900000000000e-02 -2.569180000000e+01 -1.900000000000e-02 3.650940000000e+01 2.700000000000e-02 -4.191820000000e+01 -3.100000000000e-02 -3.786160000000e+01 -2.800000000000e-02 2.569180000000e+01 1.900000000000e-02 -8.113200000000e+00 -6.000000000000e-03 -5.408800000000e+00 -4.000000000000e-03 6.355340000000e+01 4.700000000000e-02 1.893080000000e+01 1.400000000000e-02 1.893080000000e+01 1.400000000000e-02 -1.216980000000e+01 -9.000000000000e-03 -2.974840000000e+01 -2.200000000000e-02 -2.704400000000e+00 -2.000000000000e-03 -1.216980000000e+01 -9.000000000000e-03 1.487420000000e+01 1.100000000000e-02 -6.761000000000e+00 -5.000000000000e-03 -2.569180000000e+01 -1.900000000000e-02 9.465400000000e+00 7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.406288000000e+02 1.040000000000e-01 8.924520000000e+01 6.600000000000e-02 4.056600000000e+01 3.000000000000e-02 -2.704400000000e+00 -2.000000000000e-03 -3.650940000000e+01 -2.700000000000e-02 -1.352200000000e+01 -1.000000000000e-02 -9.465400000000e+00 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.663206000000e+02 1.230000000000e-01 -8.113200000000e+00 -6.000000000000e-03 1.622640000000e+01 1.200000000000e-02 2.704400000000e+01 2.000000000000e-02 2.704400000000e+00 2.000000000000e-03 1.352200000000e+00 1.000000000000e-03 -6.761000000000e+00 -5.000000000000e-03 1.893080000000e+01 1.400000000000e-02 3.515720000000e+01 2.600000000000e-02 2.839620000000e+01 2.100000000000e-02 1.216980000000e+01 9.000000000000e-03 -1.216980000000e+01 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 8.113200000000e+00 6.000000000000e-03 1.487420000000e+01 1.100000000000e-02 -2.704400000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.352200000000e+00 -1.000000000000e-03 -8.113200000000e+00 -6.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.408800000000e+00 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.352200000000e+00 1.000000000000e-03 -1.216980000000e+01 -9.000000000000e-03 1.352200000000e+00 1.000000000000e-03 -6.761000000000e+00 -5.000000000000e-03 -8.113200000000e+01 -6.000000000000e-02 -3.245280000000e+01 -2.400000000000e-02 -4.462260000000e+01 -3.300000000000e-02 2.704400000000e+00 2.000000000000e-03 -1.352200000000e+00 -1.000000000000e-03 6.761000000000e+00 5.000000000000e-03 1.216980000000e+01 9.000000000000e-03 4.327040000000e+01 3.200000000000e-02 5.949680000000e+01 4.400000000000e-02 4.056600000000e+01 3.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.081760000000e+01 -8.000000000000e-03 -2.298740000000e+01 -1.700000000000e-02 -3.650940000000e+01 -2.700000000000e-02 -1.216980000000e+01 -9.000000000000e-03 -6.490560000000e+01 -4.800000000000e-02 -3.245280000000e+01 -2.400000000000e-02 -4.056600000000e+00 -3.000000000000e-03 5.408800000000e+01 4.000000000000e-02 2.433960000000e+03 1.800000000000e+00 7.572320000000e+01 5.600000000000e-02 + 8 EWK_RAP 3.000000000000e-01 8.281000000000e+03 7.000000000000e+03 1.347400000000e+05 2.606410560000e+02 1.304916478000e+02 9.684700000000e-02 -3.772720000000e+01 -2.800000000000e-02 6.737000000000e+01 5.000000000000e-02 3.099020000000e+01 2.300000000000e-02 -2.694800000000e+00 -2.000000000000e-03 5.389600000000e+00 4.000000000000e-03 -3.772720000000e+01 -2.800000000000e-02 -1.347400000000e+00 -1.000000000000e-03 -5.389600000000e+00 -4.000000000000e-03 1.104868000000e+02 8.200000000000e-02 -1.374348000000e+02 -1.020000000000e-01 -1.077920000000e+01 -8.000000000000e-03 1.616880000000e+01 1.200000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.737000000000e+00 5.000000000000e-03 4.042200000000e+00 3.000000000000e-03 1.347400000000e+01 1.000000000000e-02 2.694800000000e+00 2.000000000000e-03 -1.347400000000e+00 -1.000000000000e-03 8.084400000000e+00 6.000000000000e-03 -4.042200000000e+00 -3.000000000000e-03 8.084400000000e+00 6.000000000000e-03 4.042200000000e+00 3.000000000000e-03 -4.042200000000e+00 -3.000000000000e-03 -1.347400000000e+00 -1.000000000000e-03 2.694800000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 4.042200000000e+00 3.000000000000e-03 -2.694800000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.347400000000e+00 1.000000000000e-03 -2.694800000000e+00 -2.000000000000e-03 2.694800000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.347400000000e+00 -1.000000000000e-03 -1.347400000000e+00 -1.000000000000e-03 1.212660000000e+01 9.000000000000e-03 -6.737000000000e+00 -5.000000000000e-03 -5.389600000000e+00 -4.000000000000e-03 -2.694800000000e+00 -2.000000000000e-03 2.694800000000e+00 2.000000000000e-03 5.389600000000e+00 4.000000000000e-03 -4.042200000000e+00 -3.000000000000e-03 -2.694800000000e+00 -2.000000000000e-03 2.694800000000e+00 2.000000000000e-03 -2.694800000000e+00 -2.000000000000e-03 2.694800000000e+00 2.000000000000e-03 -1.212660000000e+01 -9.000000000000e-03 4.042200000000e+00 3.000000000000e-03 1.347400000000e+00 1.000000000000e-03 2.694800000000e+00 2.000000000000e-03 3.368500000000e+01 2.500000000000e-02 6.737000000000e+00 5.000000000000e-03 3.637980000000e+01 2.700000000000e-02 -3.907460000000e+01 -2.900000000000e-02 -3.368500000000e+01 -2.500000000000e-02 2.694800000000e+01 2.000000000000e-02 -1.212660000000e+01 -9.000000000000e-03 -6.737000000000e+00 -5.000000000000e-03 7.949660000000e+01 5.900000000000e-02 2.155840000000e+01 1.600000000000e-02 2.021100000000e+01 1.500000000000e-02 -1.212660000000e+01 -9.000000000000e-03 -3.099020000000e+01 -2.300000000000e-02 -5.389600000000e+00 -4.000000000000e-03 -1.347400000000e+01 -1.000000000000e-02 1.482140000000e+01 1.100000000000e-02 -6.737000000000e+00 -5.000000000000e-03 -2.560060000000e+01 -1.900000000000e-02 1.347400000000e+01 1.000000000000e-02 0.000000000000e+00 0.000000000000e+00 1.360874000000e+02 1.010000000000e-01 8.353880000000e+01 6.200000000000e-02 3.907460000000e+01 2.900000000000e-02 -1.347400000000e+00 -1.000000000000e-03 -3.503240000000e+01 -2.600000000000e-02 -1.482140000000e+01 -1.100000000000e-02 -5.389600000000e+00 -4.000000000000e-03 -5.389600000000e+00 -4.000000000000e-03 1.643828000000e+02 1.220000000000e-01 -1.616880000000e+01 -1.200000000000e-02 4.042200000000e+00 3.000000000000e-03 2.155840000000e+01 1.600000000000e-02 6.737000000000e+00 5.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -8.084400000000e+00 -6.000000000000e-03 2.155840000000e+01 1.600000000000e-02 3.637980000000e+01 2.700000000000e-02 2.694800000000e+01 2.000000000000e-02 6.737000000000e+00 5.000000000000e-03 -5.389600000000e+00 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 5.389600000000e+00 4.000000000000e-03 1.482140000000e+01 1.100000000000e-02 -1.347400000000e+00 -1.000000000000e-03 1.347400000000e+00 1.000000000000e-03 -1.347400000000e+00 -1.000000000000e-03 -5.389600000000e+00 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.694800000000e+00 2.000000000000e-03 2.694800000000e+00 2.000000000000e-03 1.347400000000e+00 1.000000000000e-03 -1.077920000000e+01 -8.000000000000e-03 1.347400000000e+00 1.000000000000e-03 -6.737000000000e+00 -5.000000000000e-03 -8.084400000000e+01 -6.000000000000e-02 -3.503240000000e+01 -2.600000000000e-02 -4.581160000000e+01 -3.400000000000e-02 2.694800000000e+00 2.000000000000e-03 -1.347400000000e+00 -1.000000000000e-03 8.084400000000e+00 6.000000000000e-03 1.212660000000e+01 9.000000000000e-03 4.446420000000e+01 3.300000000000e-02 6.063300000000e+01 4.500000000000e-02 4.042200000000e+01 3.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -9.431800000000e+00 -7.000000000000e-03 -2.021100000000e+01 -1.500000000000e-02 -3.907460000000e+01 -2.900000000000e-02 -1.212660000000e+01 -9.000000000000e-03 -6.602260000000e+01 -4.900000000000e-02 -3.368500000000e+01 -2.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 5.120120000000e+01 3.800000000000e-02 2.425320000000e+03 1.800000000000e+00 7.949660000000e+01 5.900000000000e-02 + 9 EWK_RAP 5.000000000000e-01 8.281000000000e+03 7.000000000000e+03 1.342400000000e+05 2.614860960000e+02 1.228819536000e+02 9.153900000000e-02 -4.295680000000e+01 -3.200000000000e-02 6.980480000000e+01 5.200000000000e-02 3.087520000000e+01 2.300000000000e-02 5.369600000000e+00 4.000000000000e-03 5.369600000000e+00 4.000000000000e-03 -3.624480000000e+01 -2.700000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -6.712000000000e+00 -5.000000000000e-03 1.154464000000e+02 8.600000000000e-02 -1.369248000000e+02 -1.020000000000e-01 -1.073920000000e+01 -8.000000000000e-03 1.610880000000e+01 1.200000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.712000000000e+00 5.000000000000e-03 4.027200000000e+00 3.000000000000e-03 1.342400000000e+01 1.000000000000e-02 2.684800000000e+00 2.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 8.054400000000e+00 6.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.369600000000e+00 4.000000000000e-03 5.369600000000e+00 4.000000000000e-03 -2.684800000000e+00 -2.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 4.027200000000e+00 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.684800000000e+00 2.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 1.342400000000e+00 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -2.684800000000e+00 -2.000000000000e-03 2.684800000000e+00 2.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.073920000000e+01 8.000000000000e-03 -6.712000000000e+00 -5.000000000000e-03 -4.027200000000e+00 -3.000000000000e-03 -5.369600000000e+00 -4.000000000000e-03 1.342400000000e+00 1.000000000000e-03 4.027200000000e+00 3.000000000000e-03 -5.369600000000e+00 -4.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 2.684800000000e+00 2.000000000000e-03 -2.684800000000e+00 -2.000000000000e-03 1.342400000000e+00 1.000000000000e-03 -1.208160000000e+01 -9.000000000000e-03 4.027200000000e+00 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.684800000000e+00 2.000000000000e-03 4.295680000000e+01 3.200000000000e-02 -5.369600000000e+00 -4.000000000000e-03 3.490240000000e+01 2.600000000000e-02 -4.027200000000e+01 -3.000000000000e-02 -4.161440000000e+01 -3.100000000000e-02 2.819040000000e+01 2.100000000000e-02 -9.396800000000e+00 -7.000000000000e-03 -9.396800000000e+00 -7.000000000000e-03 6.577760000000e+01 4.900000000000e-02 1.745120000000e+01 1.300000000000e-02 2.013600000000e+01 1.500000000000e-02 -1.073920000000e+01 -8.000000000000e-03 -3.356000000000e+01 -2.500000000000e-02 -2.684800000000e+00 -2.000000000000e-03 -1.342400000000e+01 -1.000000000000e-02 1.476640000000e+01 1.100000000000e-02 -5.369600000000e+00 -4.000000000000e-03 -2.953280000000e+01 -2.200000000000e-02 9.396800000000e+00 7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.382672000000e+02 1.030000000000e-01 7.785920000000e+01 5.800000000000e-02 2.953280000000e+01 2.200000000000e-02 -2.684800000000e+00 -2.000000000000e-03 -3.356000000000e+01 -2.500000000000e-02 -1.745120000000e+01 -1.300000000000e-02 -4.027200000000e+00 -3.000000000000e-03 -1.073920000000e+01 -8.000000000000e-03 1.691424000000e+02 1.260000000000e-01 -2.550560000000e+01 -1.900000000000e-02 4.027200000000e+00 3.000000000000e-03 1.610880000000e+01 1.200000000000e-02 1.208160000000e+01 9.000000000000e-03 6.712000000000e+00 5.000000000000e-03 -8.054400000000e+00 -6.000000000000e-03 2.147840000000e+01 1.600000000000e-02 4.027200000000e+01 3.000000000000e-02 2.013600000000e+01 1.500000000000e-02 -2.684800000000e+00 -2.000000000000e-03 4.027200000000e+00 3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 6.712000000000e+00 5.000000000000e-03 1.476640000000e+01 1.100000000000e-02 -1.342400000000e+00 -1.000000000000e-03 1.342400000000e+00 1.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 -5.369600000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.369600000000e+00 4.000000000000e-03 2.684800000000e+00 2.000000000000e-03 1.342400000000e+00 1.000000000000e-03 -1.073920000000e+01 -8.000000000000e-03 1.342400000000e+00 1.000000000000e-03 -6.712000000000e+00 -5.000000000000e-03 -7.785920000000e+01 -5.800000000000e-02 -3.356000000000e+01 -2.500000000000e-02 -4.295680000000e+01 -3.200000000000e-02 2.684800000000e+00 2.000000000000e-03 -1.342400000000e+00 -1.000000000000e-03 6.712000000000e+00 5.000000000000e-03 1.073920000000e+01 8.000000000000e-03 4.161440000000e+01 3.100000000000e-02 5.772320000000e+01 4.300000000000e-02 3.892960000000e+01 2.900000000000e-02 0.000000000000e+00 0.000000000000e+00 -1.073920000000e+01 -8.000000000000e-03 -1.879360000000e+01 -1.400000000000e-02 -3.892960000000e+01 -2.900000000000e-02 -1.208160000000e+01 -9.000000000000e-03 -6.309280000000e+01 -4.700000000000e-02 -3.356000000000e+01 -2.500000000000e-02 -0.000000000000e+00 -0.000000000000e+00 4.966880000000e+01 3.700000000000e-02 2.416320000000e+03 1.800000000000e+00 8.054400000000e+01 6.000000000000e-02 + 10 EWK_RAP 7.000000000000e-01 8.281000000000e+03 7.000000000000e+03 1.330800000000e+05 2.653615200000e+02 1.256514744000e+02 9.441800000000e-02 -3.726240000000e+01 -2.800000000000e-02 7.452480000000e+01 5.600000000000e-02 2.927760000000e+01 2.200000000000e-02 -6.654000000000e+00 -5.000000000000e-03 -1.197720000000e+01 -9.000000000000e-03 -4.258560000000e+01 -3.200000000000e-02 -6.654000000000e+00 -5.000000000000e-03 -1.330800000000e+01 -1.000000000000e-02 1.104564000000e+02 8.300000000000e-02 -1.384032000000e+02 -1.040000000000e-01 -1.863120000000e+01 -1.400000000000e-02 1.463880000000e+01 1.100000000000e-02 -0.000000000000e+00 -0.000000000000e+00 6.654000000000e+00 5.000000000000e-03 3.992400000000e+00 3.000000000000e-03 1.330800000000e+01 1.000000000000e-02 2.661600000000e+00 2.000000000000e-03 -2.661600000000e+00 -2.000000000000e-03 7.984800000000e+00 6.000000000000e-03 1.330800000000e+00 1.000000000000e-03 3.992400000000e+00 3.000000000000e-03 6.654000000000e+00 5.000000000000e-03 -2.661600000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.992400000000e+00 3.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 2.661600000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -1.330800000000e+00 -1.000000000000e-03 1.330800000000e+00 1.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.330800000000e+00 1.000000000000e-03 1.064640000000e+01 8.000000000000e-03 -7.984800000000e+00 -6.000000000000e-03 -5.323200000000e+00 -4.000000000000e-03 -5.323200000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.992400000000e+00 3.000000000000e-03 -5.323200000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.661600000000e+00 2.000000000000e-03 -3.992400000000e+00 -3.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 -1.197720000000e+01 -9.000000000000e-03 3.992400000000e+00 3.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 3.992400000000e+00 3.000000000000e-03 2.661600000000e+01 2.000000000000e-02 -1.463880000000e+01 -1.100000000000e-02 3.060840000000e+01 2.300000000000e-02 -3.460080000000e+01 -2.600000000000e-02 -3.327000000000e+01 -2.500000000000e-02 3.060840000000e+01 2.300000000000e-02 -9.315600000000e+00 -7.000000000000e-03 -9.315600000000e+00 -7.000000000000e-03 6.654000000000e+01 5.000000000000e-02 1.996200000000e+01 1.500000000000e-02 2.528520000000e+01 1.900000000000e-02 -1.197720000000e+01 -9.000000000000e-03 -2.927760000000e+01 -2.200000000000e-02 -3.992400000000e+00 -3.000000000000e-03 -1.463880000000e+01 -1.100000000000e-02 1.596960000000e+01 1.200000000000e-02 -3.992400000000e+00 -3.000000000000e-03 -2.395440000000e+01 -1.800000000000e-02 1.330800000000e+01 1.000000000000e-02 0.000000000000e+00 0.000000000000e+00 1.397340000000e+02 1.050000000000e-01 7.319400000000e+01 5.500000000000e-02 1.730040000000e+01 1.300000000000e-02 -2.661600000000e+00 -2.000000000000e-03 -2.927760000000e+01 -2.200000000000e-02 -1.064640000000e+01 -8.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 -5.323200000000e+00 -4.000000000000e-03 1.743348000000e+02 1.310000000000e-01 -4.125480000000e+01 -3.100000000000e-02 3.992400000000e+00 3.000000000000e-03 9.315600000000e+00 7.000000000000e-03 1.330800000000e+01 1.000000000000e-02 7.984800000000e+00 6.000000000000e-03 -9.315600000000e+00 -7.000000000000e-03 2.395440000000e+01 1.800000000000e-02 4.125480000000e+01 3.100000000000e-02 1.197720000000e+01 9.000000000000e-03 -1.330800000000e+01 -1.000000000000e-02 7.984800000000e+00 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 1.330800000000e+00 1.000000000000e-03 1.463880000000e+01 1.100000000000e-02 -2.661600000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.330800000000e+00 -1.000000000000e-03 -5.323200000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.330800000000e+00 1.000000000000e-03 2.661600000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.064640000000e+01 -8.000000000000e-03 2.661600000000e+00 2.000000000000e-03 -6.654000000000e+00 -5.000000000000e-03 -7.851720000000e+01 -5.900000000000e-02 -3.327000000000e+01 -2.500000000000e-02 -4.258560000000e+01 -3.200000000000e-02 2.661600000000e+00 2.000000000000e-03 -1.330800000000e+00 -1.000000000000e-03 7.984800000000e+00 6.000000000000e-03 1.197720000000e+01 9.000000000000e-03 4.258560000000e+01 3.200000000000e-02 5.855520000000e+01 4.400000000000e-02 3.992400000000e+01 3.000000000000e-02 1.330800000000e+00 1.000000000000e-03 -1.064640000000e+01 -8.000000000000e-03 -1.996200000000e+01 -1.500000000000e-02 -3.726240000000e+01 -2.800000000000e-02 -1.197720000000e+01 -9.000000000000e-03 -5.988600000000e+01 -4.500000000000e-02 -3.460080000000e+01 -2.600000000000e-02 -2.661600000000e+00 -2.000000000000e-03 4.923960000000e+01 3.700000000000e-02 2.395440000000e+03 1.800000000000e+00 7.851720000000e+01 5.900000000000e-02 + 11 EWK_RAP 9.000000000000e-01 8.281000000000e+03 7.000000000000e+03 1.324800000000e+05 2.613300480000e+02 1.328774400000e+02 1.003000000000e-01 -1.192320000000e+01 -9.000000000000e-03 8.876160000000e+01 6.700000000000e-02 2.649600000000e+01 2.000000000000e-02 -1.192320000000e+01 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.974400000000e+01 -3.000000000000e-02 9.273600000000e+00 7.000000000000e-03 2.517120000000e+01 1.900000000000e-02 1.073088000000e+02 8.100000000000e-02 -1.430784000000e+02 -1.080000000000e-01 -2.384640000000e+01 -1.800000000000e-02 1.324800000000e+01 1.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 5.299200000000e+00 4.000000000000e-03 2.649600000000e+00 2.000000000000e-03 1.324800000000e+01 1.000000000000e-02 2.649600000000e+00 2.000000000000e-03 -2.649600000000e+00 -2.000000000000e-03 7.948800000000e+00 6.000000000000e-03 1.324800000000e+00 1.000000000000e-03 2.649600000000e+00 2.000000000000e-03 6.624000000000e+00 5.000000000000e-03 -3.974400000000e+00 -3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.649600000000e+00 2.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 1.324800000000e+00 1.000000000000e-03 2.649600000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.649600000000e+00 -2.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -2.649600000000e+00 -2.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.192320000000e+01 9.000000000000e-03 -3.974400000000e+00 -3.000000000000e-03 -2.649600000000e+00 -2.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -3.974400000000e+00 -3.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -7.948800000000e+00 -6.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 -1.324800000000e+01 -1.000000000000e-02 3.974400000000e+00 3.000000000000e-03 -6.624000000000e+00 -5.000000000000e-03 2.649600000000e+00 2.000000000000e-03 4.636800000000e+01 3.500000000000e-02 -2.384640000000e+01 -1.800000000000e-02 3.576960000000e+01 2.700000000000e-02 -3.444480000000e+01 -2.600000000000e-02 -2.517120000000e+01 -1.900000000000e-02 2.782080000000e+01 2.100000000000e-02 -9.273600000000e+00 -7.000000000000e-03 -1.059840000000e+01 -8.000000000000e-03 5.961600000000e+01 4.500000000000e-02 1.589760000000e+01 1.200000000000e-02 2.119680000000e+01 1.600000000000e-02 -1.192320000000e+01 -9.000000000000e-03 -2.649600000000e+01 -2.000000000000e-02 -1.324800000000e+00 -1.000000000000e-03 -1.192320000000e+01 -9.000000000000e-03 1.192320000000e+01 9.000000000000e-03 -2.649600000000e+00 -2.000000000000e-03 -1.059840000000e+01 -8.000000000000e-03 9.273600000000e+00 7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.430784000000e+02 1.080000000000e-01 5.961600000000e+01 4.500000000000e-02 9.273600000000e+00 7.000000000000e-03 3.974400000000e+00 3.000000000000e-03 -2.384640000000e+01 -1.800000000000e-02 -9.273600000000e+00 -7.000000000000e-03 6.624000000000e+00 5.000000000000e-03 7.948800000000e+00 6.000000000000e-03 1.642752000000e+02 1.240000000000e-01 -4.636800000000e+01 -3.500000000000e-02 -5.299200000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.589760000000e+01 1.200000000000e-02 5.299200000000e+00 4.000000000000e-03 -1.457280000000e+01 -1.100000000000e-02 2.782080000000e+01 2.100000000000e-02 4.106880000000e+01 3.100000000000e-02 2.649600000000e+00 2.000000000000e-03 -1.589760000000e+01 -1.200000000000e-02 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -3.974400000000e+00 -3.000000000000e-03 1.324800000000e+01 1.000000000000e-02 -1.324800000000e+00 -1.000000000000e-03 -1.324800000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.649600000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.649600000000e+00 -2.000000000000e-03 2.649600000000e+00 2.000000000000e-03 -2.649600000000e+00 -2.000000000000e-03 -9.273600000000e+00 -7.000000000000e-03 1.324800000000e+00 1.000000000000e-03 -5.299200000000e+00 -4.000000000000e-03 -7.551360000000e+01 -5.700000000000e-02 -3.576960000000e+01 -2.700000000000e-02 -4.239360000000e+01 -3.200000000000e-02 0.000000000000e+00 0.000000000000e+00 -2.649600000000e+00 -2.000000000000e-03 7.948800000000e+00 6.000000000000e-03 7.948800000000e+00 6.000000000000e-03 4.239360000000e+01 3.200000000000e-02 5.696640000000e+01 4.300000000000e-02 3.576960000000e+01 2.700000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -7.948800000000e+00 -6.000000000000e-03 -1.589760000000e+01 -1.200000000000e-02 -3.576960000000e+01 -2.700000000000e-02 -1.192320000000e+01 -9.000000000000e-03 -5.299200000000e+01 -4.000000000000e-02 -3.312000000000e+01 -2.500000000000e-02 -3.974400000000e+00 -3.000000000000e-03 3.312000000000e+01 2.500000000000e-02 2.384640000000e+03 1.800000000000e+00 8.081280000000e+01 6.100000000000e-02 + 12 EWK_RAP 1.100000000000e+00 8.281000000000e+03 7.000000000000e+03 1.290600000000e+05 2.637341100000e+02 1.396558260000e+02 1.082100000000e-01 -1.161540000000e+01 -9.000000000000e-03 9.163260000000e+01 7.100000000000e-02 1.548720000000e+01 1.200000000000e-02 3.871800000000e+00 3.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 -4.258980000000e+01 -3.300000000000e-02 3.871800000000e+00 3.000000000000e-03 3.871800000000e+01 3.000000000000e-02 1.019574000000e+02 7.900000000000e-02 -1.406754000000e+02 -1.090000000000e-01 -3.097440000000e+01 -2.400000000000e-02 1.032480000000e+01 8.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.162400000000e+00 4.000000000000e-03 2.581200000000e+00 2.000000000000e-03 1.161540000000e+01 9.000000000000e-03 2.581200000000e+00 2.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 7.743600000000e+00 6.000000000000e-03 5.162400000000e+00 4.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 7.743600000000e+00 6.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 1.290600000000e+00 1.000000000000e-03 1.290600000000e+00 1.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.581200000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -2.581200000000e+00 -2.000000000000e-03 -2.581200000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.871800000000e+00 -3.000000000000e-03 1.290600000000e+00 1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 9.034200000000e+00 7.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 2.581200000000e+00 2.000000000000e-03 -2.581200000000e+00 -2.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 -2.581200000000e+00 -2.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 -9.034200000000e+00 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.290600000000e+01 -1.000000000000e-02 3.871800000000e+00 3.000000000000e-03 -6.453000000000e+00 -5.000000000000e-03 2.581200000000e+00 2.000000000000e-03 4.388040000000e+01 3.400000000000e-02 -4.517100000000e+01 -3.500000000000e-02 2.968380000000e+01 2.300000000000e-02 -2.968380000000e+01 -2.300000000000e-02 -2.323080000000e+01 -1.800000000000e-02 2.581200000000e+01 2.000000000000e-02 -7.743600000000e+00 -6.000000000000e-03 -1.032480000000e+01 -8.000000000000e-03 5.033340000000e+01 3.900000000000e-02 1.419660000000e+01 1.100000000000e-02 2.194020000000e+01 1.700000000000e-02 -9.034200000000e+00 -7.000000000000e-03 -1.935900000000e+01 -1.500000000000e-02 1.290600000000e+00 1.000000000000e-03 -1.032480000000e+01 -8.000000000000e-03 1.419660000000e+01 1.100000000000e-02 -5.162400000000e+00 -4.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 1.161540000000e+01 9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.445472000000e+02 1.120000000000e-01 4.646160000000e+01 3.600000000000e-02 6.453000000000e+00 5.000000000000e-03 6.453000000000e+00 5.000000000000e-03 -1.806840000000e+01 -1.400000000000e-02 -1.032480000000e+01 -8.000000000000e-03 1.032480000000e+01 8.000000000000e-03 6.453000000000e+00 5.000000000000e-03 1.561626000000e+02 1.210000000000e-01 -4.258980000000e+01 -3.300000000000e-02 -7.743600000000e+00 -6.000000000000e-03 -1.290600000000e+00 -1.000000000000e-03 1.548720000000e+01 1.200000000000e-02 9.034200000000e+00 7.000000000000e-03 -1.677780000000e+01 -1.300000000000e-02 2.968380000000e+01 2.300000000000e-02 3.871800000000e+01 3.000000000000e-02 -7.743600000000e+00 -6.000000000000e-03 -6.453000000000e+00 -5.000000000000e-03 -1.419660000000e+01 -1.100000000000e-02 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -5.162400000000e+00 -4.000000000000e-03 1.290600000000e+01 1.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -2.581200000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.581200000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -3.871800000000e+00 -3.000000000000e-03 2.581200000000e+00 2.000000000000e-03 -3.871800000000e+00 -3.000000000000e-03 -9.034200000000e+00 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -5.162400000000e+00 -4.000000000000e-03 -7.227360000000e+01 -5.600000000000e-02 -3.355560000000e+01 -2.600000000000e-02 -4.388040000000e+01 -3.400000000000e-02 0.000000000000e+00 0.000000000000e+00 -2.581200000000e+00 -2.000000000000e-03 9.034200000000e+00 7.000000000000e-03 9.034200000000e+00 7.000000000000e-03 4.129920000000e+01 3.200000000000e-02 5.936760000000e+01 4.600000000000e-02 3.484620000000e+01 2.700000000000e-02 -1.290600000000e+00 -1.000000000000e-03 -9.034200000000e+00 -7.000000000000e-03 -1.419660000000e+01 -1.100000000000e-02 -3.613680000000e+01 -2.800000000000e-02 -1.161540000000e+01 -9.000000000000e-03 -5.162400000000e+01 -4.000000000000e-02 -3.226500000000e+01 -2.500000000000e-02 -3.871800000000e+00 -3.000000000000e-03 3.097440000000e+01 2.400000000000e-02 2.323080000000e+03 1.800000000000e+00 7.743600000000e+01 6.000000000000e-02 + 13 EWK_RAP 1.300000000000e+00 8.281000000000e+03 7.000000000000e+03 1.199200000000e+05 2.506447920000e+02 1.128675048000e+02 9.411900000000e-02 -1.199200000000e+01 -1.000000000000e-02 9.113920000000e+01 7.600000000000e-02 1.199200000000e+00 1.000000000000e-03 1.199200000000e+00 1.000000000000e-03 7.195200000000e+00 6.000000000000e-03 -4.676880000000e+01 -3.900000000000e-02 -5.996000000000e+00 -5.000000000000e-03 -4.197200000000e+01 -3.500000000000e-02 8.874080000000e+01 7.400000000000e-02 -1.319120000000e+02 -1.100000000000e-01 -3.837440000000e+01 -3.200000000000e-02 8.394400000000e+00 7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 5.996000000000e+00 5.000000000000e-03 3.597600000000e+00 3.000000000000e-03 1.079280000000e+01 9.000000000000e-03 2.398400000000e+00 2.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 7.195200000000e+00 6.000000000000e-03 1.439040000000e+01 1.200000000000e-02 -7.195200000000e+00 -6.000000000000e-03 9.593600000000e+00 8.000000000000e-03 -3.597600000000e+00 -3.000000000000e-03 2.398400000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.398400000000e+00 -2.000000000000e-03 1.199200000000e+00 1.000000000000e-03 3.597600000000e+00 3.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -2.398400000000e+00 -2.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -4.796800000000e+00 -4.000000000000e-03 3.597600000000e+00 3.000000000000e-03 2.398400000000e+00 2.000000000000e-03 5.996000000000e+00 5.000000000000e-03 -7.195200000000e+00 -6.000000000000e-03 -2.398400000000e+00 -2.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -3.597600000000e+00 -3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.597600000000e+00 -3.000000000000e-03 -3.597600000000e+00 -3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -9.593600000000e+00 -8.000000000000e-03 1.199200000000e+00 1.000000000000e-03 -1.079280000000e+01 -9.000000000000e-03 2.398400000000e+00 2.000000000000e-03 -4.796800000000e+00 -4.000000000000e-03 5.996000000000e+00 5.000000000000e-03 -2.758160000000e+01 -2.300000000000e-02 3.117920000000e+01 2.600000000000e-02 3.597600000000e+01 3.000000000000e-02 -2.998000000000e+01 -2.500000000000e-02 -1.558960000000e+01 -1.300000000000e-02 2.278480000000e+01 1.900000000000e-02 -8.394400000000e+00 -7.000000000000e-03 -9.593600000000e+00 -8.000000000000e-03 4.197200000000e+01 3.500000000000e-02 1.439040000000e+01 1.200000000000e-02 1.918720000000e+01 1.600000000000e-02 -4.796800000000e+00 -4.000000000000e-03 -9.593600000000e+00 -8.000000000000e-03 -2.398400000000e+00 -2.000000000000e-03 -1.199200000000e+01 -1.000000000000e-02 1.079280000000e+01 9.000000000000e-03 -3.597600000000e+00 -3.000000000000e-03 5.996000000000e+00 5.000000000000e-03 2.398400000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.439040000000e+02 1.200000000000e-01 4.556960000000e+01 3.800000000000e-02 7.195200000000e+00 6.000000000000e-03 2.398400000000e+00 2.000000000000e-03 -1.079280000000e+01 -9.000000000000e-03 -4.796800000000e+00 -4.000000000000e-03 3.597600000000e+00 3.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 1.594936000000e+02 1.330000000000e-01 -2.998000000000e+01 -2.500000000000e-02 -8.394400000000e+00 -7.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.319120000000e+01 1.100000000000e-02 5.996000000000e+00 5.000000000000e-03 -1.439040000000e+01 -1.200000000000e-02 3.357760000000e+01 2.800000000000e-02 3.357760000000e+01 2.800000000000e-02 -7.195200000000e+00 -6.000000000000e-03 7.195200000000e+00 6.000000000000e-03 -9.593600000000e+00 -8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -4.796800000000e+00 -4.000000000000e-03 1.319120000000e+01 1.100000000000e-02 1.199200000000e+00 1.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 1.199200000000e+00 1.000000000000e-03 -4.796800000000e+00 -4.000000000000e-03 7.195200000000e+00 6.000000000000e-03 -2.398400000000e+00 -2.000000000000e-03 -8.394400000000e+00 -7.000000000000e-03 1.199200000000e+00 1.000000000000e-03 -4.796800000000e+00 -4.000000000000e-03 -7.075280000000e+01 -5.900000000000e-02 -3.117920000000e+01 -2.600000000000e-02 -4.317120000000e+01 -3.600000000000e-02 1.199200000000e+00 1.000000000000e-03 -1.199200000000e+00 -1.000000000000e-03 1.079280000000e+01 9.000000000000e-03 1.079280000000e+01 9.000000000000e-03 3.957360000000e+01 3.300000000000e-02 6.235840000000e+01 5.200000000000e-02 3.597600000000e+01 3.000000000000e-02 0.000000000000e+00 0.000000000000e+00 -8.394400000000e+00 -7.000000000000e-03 -1.079280000000e+01 -9.000000000000e-03 -3.837440000000e+01 -3.200000000000e-02 -1.199200000000e+01 -1.000000000000e-02 -5.876080000000e+01 -4.900000000000e-02 -3.357760000000e+01 -2.800000000000e-02 4.796800000000e+00 4.000000000000e-03 3.597600000000e+01 3.000000000000e-02 2.158560000000e+03 1.800000000000e+00 7.674880000000e+01 6.400000000000e-02 + 14 EWK_RAP 1.500000000000e+00 8.281000000000e+03 7.000000000000e+03 1.073200000000e+05 2.433373680000e+02 1.330446040000e+02 1.239700000000e-01 -6.439200000000e+00 -6.000000000000e-03 8.156320000000e+01 7.600000000000e-02 -1.502480000000e+01 -1.400000000000e-02 -1.073200000000e+00 -1.000000000000e-03 6.439200000000e+00 6.000000000000e-03 -3.648880000000e+01 -3.400000000000e-02 0.000000000000e+00 0.000000000000e+00 2.468360000000e+01 2.300000000000e-02 7.834360000000e+01 7.300000000000e-02 -1.191252000000e+02 -1.110000000000e-01 -4.078160000000e+01 -3.800000000000e-02 6.439200000000e+00 6.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 4.292800000000e+00 4.000000000000e-03 3.219600000000e+00 3.000000000000e-03 9.658800000000e+00 9.000000000000e-03 2.146400000000e+00 2.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 4.292800000000e+00 4.000000000000e-03 1.287840000000e+01 1.200000000000e-02 -7.512400000000e+00 -7.000000000000e-03 9.658800000000e+00 9.000000000000e-03 -3.219600000000e+00 -3.000000000000e-03 2.146400000000e+00 2.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 -3.219600000000e+00 -3.000000000000e-03 -2.146400000000e+00 -2.000000000000e-03 4.292800000000e+00 4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -3.219600000000e+00 -3.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 -2.146400000000e+00 -2.000000000000e-03 -5.366000000000e+00 -5.000000000000e-03 4.292800000000e+00 4.000000000000e-03 1.073200000000e+00 1.000000000000e-03 7.512400000000e+00 7.000000000000e-03 -4.292800000000e+00 -4.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 1.073200000000e+00 1.000000000000e-03 -3.219600000000e+00 -3.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 -5.366000000000e+00 -5.000000000000e-03 -2.146400000000e+00 -2.000000000000e-03 -3.219600000000e+00 -3.000000000000e-03 -7.512400000000e+00 -7.000000000000e-03 1.073200000000e+00 1.000000000000e-03 -1.073200000000e+01 -1.000000000000e-02 1.073200000000e+00 1.000000000000e-03 -5.366000000000e+00 -5.000000000000e-03 2.146400000000e+00 2.000000000000e-03 -1.287840000000e+01 -1.200000000000e-02 -7.834360000000e+01 -7.300000000000e-02 2.575680000000e+01 2.400000000000e-02 -2.253720000000e+01 -2.100000000000e-02 -8.585600000000e+00 -8.000000000000e-03 1.824440000000e+01 1.700000000000e-02 -5.366000000000e+00 -5.000000000000e-03 -9.658800000000e+00 -9.000000000000e-03 3.434240000000e+01 3.200000000000e-02 1.073200000000e+00 1.000000000000e-03 1.717120000000e+01 1.600000000000e-02 -4.292800000000e+00 -4.000000000000e-03 2.146400000000e+00 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.073200000000e+01 -1.000000000000e-02 2.146400000000e+00 2.000000000000e-03 -7.512400000000e+00 -7.000000000000e-03 -9.658800000000e+00 -9.000000000000e-03 8.585600000000e+00 8.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.298572000000e+02 1.210000000000e-01 2.253720000000e+01 2.100000000000e-02 8.585600000000e+00 8.000000000000e-03 4.292800000000e+00 4.000000000000e-03 -4.292800000000e+00 -4.000000000000e-03 4.292800000000e+00 4.000000000000e-03 6.439200000000e+00 6.000000000000e-03 1.073200000000e+00 1.000000000000e-03 1.352232000000e+02 1.260000000000e-01 -1.609800000000e+01 -1.500000000000e-02 3.219600000000e+00 3.000000000000e-03 2.146400000000e+00 2.000000000000e-03 1.609800000000e+01 1.500000000000e-02 1.073200000000e+00 1.000000000000e-03 -1.824440000000e+01 -1.700000000000e-02 3.541560000000e+01 3.300000000000e-02 2.790320000000e+01 2.600000000000e-02 -9.658800000000e+00 -9.000000000000e-03 1.502480000000e+01 1.400000000000e-02 2.146400000000e+00 2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -4.292800000000e+00 -4.000000000000e-03 1.073200000000e+01 1.000000000000e-02 1.073200000000e+00 1.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 -2.146400000000e+00 -2.000000000000e-03 1.073200000000e+00 1.000000000000e-03 -4.292800000000e+00 -4.000000000000e-03 5.366000000000e+00 5.000000000000e-03 -2.146400000000e+00 -2.000000000000e-03 -7.512400000000e+00 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -4.292800000000e+00 -4.000000000000e-03 -6.331880000000e+01 -5.900000000000e-02 -2.897640000000e+01 -2.700000000000e-02 -3.863520000000e+01 -3.600000000000e-02 1.073200000000e+00 1.000000000000e-03 -1.073200000000e+00 -1.000000000000e-03 9.658800000000e+00 9.000000000000e-03 9.658800000000e+00 9.000000000000e-03 3.434240000000e+01 3.200000000000e-02 5.366000000000e+01 5.000000000000e-02 3.004960000000e+01 2.800000000000e-02 -1.073200000000e+00 -1.000000000000e-03 -7.512400000000e+00 -7.000000000000e-03 -1.180520000000e+01 -1.100000000000e-02 -3.219600000000e+01 -3.000000000000e-02 -9.658800000000e+00 -9.000000000000e-03 -4.936720000000e+01 -4.600000000000e-02 -2.790320000000e+01 -2.600000000000e-02 2.146400000000e+00 2.000000000000e-03 3.219600000000e+01 3.000000000000e-02 1.931760000000e+03 1.800000000000e+00 7.941680000000e+01 7.400000000000e-02 + 15 EWK_RAP 1.700000000000e+00 8.281000000000e+03 7.000000000000e+03 8.986600000000e+04 2.230384254000e+02 1.016474326000e+02 1.131100000000e-01 -0.000000000000e+00 -0.000000000000e+00 8.087940000000e+01 9.000000000000e-02 -3.145310000000e+01 -3.500000000000e-02 -2.695980000000e+00 -3.000000000000e-03 -1.437856000000e+01 -1.600000000000e-02 -3.504774000000e+01 -3.900000000000e-02 2.695980000000e+00 3.000000000000e-03 -1.437856000000e+01 -1.600000000000e-02 6.380486000000e+01 7.100000000000e-02 -1.051432200000e+02 -1.170000000000e-01 -4.403434000000e+01 -4.900000000000e-02 4.493300000000e+00 5.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.594640000000e+00 4.000000000000e-03 2.695980000000e+00 3.000000000000e-03 8.087940000000e+00 9.000000000000e-03 1.797320000000e+00 2.000000000000e-03 -8.986600000000e-01 -1.000000000000e-03 1.797320000000e+00 2.000000000000e-03 1.168258000000e+01 1.300000000000e-02 -7.189280000000e+00 -8.000000000000e-03 8.087940000000e+00 9.000000000000e-03 8.986600000000e-01 1.000000000000e-03 3.594640000000e+00 4.000000000000e-03 -3.594640000000e+00 -4.000000000000e-03 -8.986600000000e-01 -1.000000000000e-03 -4.493300000000e+00 -5.000000000000e-03 5.391960000000e+00 6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.797320000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.797320000000e+00 -2.000000000000e-03 -7.189280000000e+00 -8.000000000000e-03 5.391960000000e+00 6.000000000000e-03 8.986600000000e-01 1.000000000000e-03 5.391960000000e+00 6.000000000000e-03 -3.594640000000e+00 -4.000000000000e-03 -1.797320000000e+00 -2.000000000000e-03 1.797320000000e+00 2.000000000000e-03 -2.695980000000e+00 -3.000000000000e-03 -1.797320000000e+00 -2.000000000000e-03 -1.797320000000e+00 -2.000000000000e-03 -1.797320000000e+00 -2.000000000000e-03 -8.986600000000e-01 -1.000000000000e-03 -4.493300000000e+00 -5.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -8.986600000000e+00 -1.000000000000e-02 1.797320000000e+00 2.000000000000e-03 -4.493300000000e+00 -5.000000000000e-03 2.695980000000e+00 3.000000000000e-03 -1.716440600000e+02 -1.910000000000e-01 -3.594640000000e+00 -4.000000000000e-03 1.887186000000e+01 2.100000000000e-02 -2.246650000000e+01 -2.500000000000e-02 -1.168258000000e+01 -1.300000000000e-02 1.258124000000e+01 1.400000000000e-02 -8.986600000000e-01 -1.000000000000e-03 -5.391960000000e+00 -6.000000000000e-03 2.516248000000e+01 2.800000000000e-02 5.391960000000e+00 6.000000000000e-03 1.168258000000e+01 1.300000000000e-02 -4.493300000000e+00 -5.000000000000e-03 3.594640000000e+00 4.000000000000e-03 1.797320000000e+00 2.000000000000e-03 -1.078392000000e+01 -1.200000000000e-02 5.391960000000e+00 6.000000000000e-03 -6.290620000000e+00 -7.000000000000e-03 -8.986600000000e+00 -1.000000000000e-02 -3.594640000000e+00 -4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 1.105351800000e+02 1.230000000000e-01 2.336516000000e+01 2.600000000000e-02 -3.594640000000e+00 -4.000000000000e-03 8.986600000000e+00 1.000000000000e-02 -2.695980000000e+00 -3.000000000000e-03 -2.695980000000e+00 -3.000000000000e-03 9.885260000000e+00 1.100000000000e-02 3.594640000000e+00 4.000000000000e-03 1.123325000000e+02 1.250000000000e-01 -2.785846000000e+01 -3.100000000000e-02 8.986600000000e-01 1.000000000000e-03 2.695980000000e+00 3.000000000000e-03 1.078392000000e+01 1.200000000000e-02 8.986600000000e+00 1.000000000000e-02 -1.977052000000e+01 -2.200000000000e-02 4.673032000000e+01 5.200000000000e-02 2.066918000000e+01 2.300000000000e-02 -3.594640000000e+00 -4.000000000000e-03 9.885260000000e+00 1.100000000000e-02 3.594640000000e+00 4.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.797320000000e+00 -2.000000000000e-03 9.885260000000e+00 1.100000000000e-02 3.594640000000e+00 4.000000000000e-03 8.986600000000e-01 1.000000000000e-03 -2.695980000000e+00 -3.000000000000e-03 8.986600000000e-01 1.000000000000e-03 1.797320000000e+00 2.000000000000e-03 -4.493300000000e+00 -5.000000000000e-03 1.258124000000e+01 1.400000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -5.391960000000e+00 -6.000000000000e-03 8.986600000000e-01 1.000000000000e-03 -2.695980000000e+00 -3.000000000000e-03 -5.571692000000e+01 -6.200000000000e-02 -3.055444000000e+01 -3.400000000000e-02 -3.684506000000e+01 -4.100000000000e-02 0.000000000000e+00 0.000000000000e+00 -1.797320000000e+00 -2.000000000000e-03 7.189280000000e+00 8.000000000000e-03 8.087940000000e+00 9.000000000000e-03 3.055444000000e+01 3.400000000000e-02 5.212228000000e+01 5.800000000000e-02 2.695980000000e+01 3.000000000000e-02 8.986600000000e-01 1.000000000000e-03 -4.493300000000e+00 -5.000000000000e-03 -5.391960000000e+00 -6.000000000000e-03 -3.594640000000e+01 -4.000000000000e-02 -8.986600000000e+00 -1.000000000000e-02 -5.302094000000e+01 -5.900000000000e-02 -2.516248000000e+01 -2.800000000000e-02 1.887186000000e+01 2.100000000000e-02 3.235176000000e+01 3.600000000000e-02 1.617588000000e+03 1.800000000000e+00 6.650084000000e+01 7.400000000000e-02 + 16 EWK_RAP 1.900000000000e+00 8.281000000000e+03 7.000000000000e+03 6.879800000000e+04 1.963907708000e+02 1.023714240000e+02 1.488000000000e-01 -2.063940000000e+00 -3.000000000000e-03 6.604608000000e+01 9.600000000000e-02 -3.439900000000e+01 -5.000000000000e-02 1.375960000000e+00 2.000000000000e-03 6.879800000000e+00 1.000000000000e-02 -3.095910000000e+01 -4.500000000000e-02 -5.503840000000e+00 -8.000000000000e-03 -1.788748000000e+01 -2.600000000000e-02 4.609466000000e+01 6.700000000000e-02 -7.980568000000e+01 -1.160000000000e-01 -3.852688000000e+01 -5.600000000000e-02 3.439900000000e+00 5.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 3.439900000000e+00 5.000000000000e-03 2.751920000000e+00 4.000000000000e-03 6.191820000000e+00 9.000000000000e-03 1.375960000000e+00 2.000000000000e-03 -1.375960000000e+00 -2.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 8.943740000000e+00 1.300000000000e-02 -6.191820000000e+00 -9.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 4.127880000000e+00 6.000000000000e-03 2.751920000000e+00 4.000000000000e-03 -6.879800000000e+00 -1.000000000000e-02 4.127880000000e+00 6.000000000000e-03 -4.127880000000e+00 -6.000000000000e-03 6.879800000000e+00 1.000000000000e-02 -6.879800000000e-01 -1.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 6.879800000000e-01 1.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 -5.503840000000e+00 -8.000000000000e-03 4.815860000000e+00 7.000000000000e-03 6.879800000000e-01 1.000000000000e-03 2.751920000000e+00 4.000000000000e-03 -4.127880000000e+00 -6.000000000000e-03 -1.375960000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.751920000000e+00 -4.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -1.375960000000e+00 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -3.439900000000e+00 -5.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -6.879800000000e+00 -1.000000000000e-02 1.375960000000e+00 2.000000000000e-03 -3.439900000000e+00 -5.000000000000e-03 2.751920000000e+00 4.000000000000e-03 -7.636578000000e+01 -1.110000000000e-01 -1.169566000000e+01 -1.700000000000e-02 1.582354000000e+01 2.300000000000e-02 -1.926344000000e+01 -2.800000000000e-02 -1.788748000000e+01 -2.600000000000e-02 7.567780000000e+00 1.100000000000e-02 -6.879800000000e-01 -1.000000000000e-03 -2.063940000000e+00 -3.000000000000e-03 1.788748000000e+01 2.600000000000e-02 4.815860000000e+00 7.000000000000e-03 8.255760000000e+00 1.200000000000e-02 -2.751920000000e+00 -4.000000000000e-03 -6.879800000000e+00 -1.000000000000e-02 2.063940000000e+00 3.000000000000e-03 -4.815860000000e+00 -7.000000000000e-03 4.127880000000e+00 6.000000000000e-03 -6.191820000000e+00 -9.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 8.668548000000e+01 1.260000000000e-01 6.191820000000e+00 9.000000000000e-03 -6.191820000000e+00 -9.000000000000e-03 8.943740000000e+00 1.300000000000e-02 -4.815860000000e+00 -7.000000000000e-03 -2.063940000000e+00 -3.000000000000e-03 4.127880000000e+00 6.000000000000e-03 -1.375960000000e+00 -2.000000000000e-03 7.774174000000e+01 1.130000000000e-01 -1.995142000000e+01 -2.900000000000e-02 -1.375960000000e+00 -2.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 9.631720000000e+00 1.400000000000e-02 9.631720000000e+00 1.400000000000e-02 -1.444758000000e+01 -2.100000000000e-02 4.265476000000e+01 6.200000000000e-02 1.307162000000e+01 1.900000000000e-02 1.375960000000e+00 2.000000000000e-03 4.815860000000e+00 7.000000000000e-03 2.063940000000e+00 3.000000000000e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.375960000000e+00 -2.000000000000e-03 7.567780000000e+00 1.100000000000e-02 2.751920000000e+00 4.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 -1.375960000000e+00 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 6.879800000000e-01 1.000000000000e-03 -2.063940000000e+00 -3.000000000000e-03 7.567780000000e+00 1.100000000000e-02 -2.063940000000e+00 -3.000000000000e-03 -4.815860000000e+00 -7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.063940000000e+00 -3.000000000000e-03 -3.990284000000e+01 -5.800000000000e-02 -1.788748000000e+01 -2.600000000000e-02 -2.683122000000e+01 -3.900000000000e-02 6.879800000000e-01 1.000000000000e-03 -6.879800000000e-01 -1.000000000000e-03 6.191820000000e+00 9.000000000000e-03 7.567780000000e+00 1.100000000000e-02 2.201536000000e+01 3.200000000000e-02 3.990284000000e+01 5.800000000000e-02 1.995142000000e+01 2.900000000000e-02 6.879800000000e-01 1.000000000000e-03 -5.503840000000e+00 -8.000000000000e-03 -2.751920000000e+00 -4.000000000000e-03 -2.545526000000e+01 -3.700000000000e-02 -6.879800000000e+00 -1.000000000000e-02 -3.783890000000e+01 -5.500000000000e-02 -1.926344000000e+01 -2.800000000000e-02 8.943740000000e+00 1.300000000000e-02 2.063940000000e+01 3.000000000000e-02 1.238364000000e+03 1.800000000000e+00 7.017396000000e+01 1.020000000000e-01 + 17 EWK_RAP 2.100000000000e+00 8.281000000000e+03 7.000000000000e+03 4.561500000000e+04 1.628866035000e+02 1.012744230000e+02 2.220200000000e-01 -1.824600000000e+00 -4.000000000000e-03 4.333425000000e+01 9.500000000000e-02 -2.554440000000e+01 -5.600000000000e-02 3.193050000000e+00 7.000000000000e-03 -1.824600000000e+00 -4.000000000000e-03 -2.508825000000e+01 -5.500000000000e-02 -9.123000000000e-01 -2.000000000000e-03 2.280750000000e+00 5.000000000000e-03 2.873745000000e+01 6.300000000000e-02 -4.972035000000e+01 -1.090000000000e-01 -2.508825000000e+01 -5.500000000000e-02 1.368450000000e+00 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.280750000000e+00 5.000000000000e-03 1.824600000000e+00 4.000000000000e-03 3.649200000000e+00 8.000000000000e-03 9.123000000000e-01 2.000000000000e-03 -9.123000000000e-01 -2.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 5.017650000000e+00 1.100000000000e-02 -4.105350000000e+00 -9.000000000000e-03 -1.368450000000e+00 -3.000000000000e-03 2.736900000000e+00 6.000000000000e-03 3.193050000000e+00 7.000000000000e-03 -8.210700000000e+00 -1.800000000000e-02 3.649200000000e+00 8.000000000000e-03 -3.193050000000e+00 -7.000000000000e-03 4.105350000000e+00 9.000000000000e-03 -1.824600000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 1.368450000000e+00 3.000000000000e-03 -2.280750000000e+00 -5.000000000000e-03 5.473800000000e+00 1.200000000000e-02 0.000000000000e+00 0.000000000000e+00 3.193050000000e+00 7.000000000000e-03 -2.736900000000e+00 -6.000000000000e-03 -9.123000000000e-01 -2.000000000000e-03 4.561500000000e-01 1.000000000000e-03 -1.824600000000e+00 -4.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -9.123000000000e-01 -2.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -2.736900000000e+00 -6.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -4.561500000000e+00 -1.000000000000e-02 9.123000000000e-01 2.000000000000e-03 -2.280750000000e+00 -5.000000000000e-03 1.368450000000e+00 3.000000000000e-03 1.824600000000e+01 4.000000000000e-02 -4.561500000000e-01 -1.000000000000e-03 6.386100000000e+00 1.400000000000e-02 -1.322835000000e+01 -2.900000000000e-02 -2.143905000000e+01 -4.700000000000e-02 1.824600000000e+00 4.000000000000e-03 -1.824600000000e+00 -4.000000000000e-03 -3.193050000000e+00 -7.000000000000e-03 1.505295000000e+01 3.300000000000e-02 3.649200000000e+00 8.000000000000e-03 4.105350000000e+00 9.000000000000e-03 -2.280750000000e+00 -5.000000000000e-03 -5.017650000000e+00 -1.100000000000e-02 2.736900000000e+00 6.000000000000e-03 -3.649200000000e+00 -8.000000000000e-03 1.368450000000e+00 3.000000000000e-03 4.561500000000e-01 1.000000000000e-03 -4.561500000000e+00 -1.000000000000e-02 7.298400000000e+00 1.600000000000e-02 0.000000000000e+00 0.000000000000e+00 6.066795000000e+01 1.330000000000e-01 -1.733370000000e+01 -3.800000000000e-02 3.193050000000e+00 7.000000000000e-03 4.561500000000e+00 1.000000000000e-02 -4.561500000000e+00 -1.000000000000e-02 4.561500000000e-01 1.000000000000e-03 1.368450000000e+00 3.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 4.196580000000e+01 9.200000000000e-02 -1.003530000000e+01 -2.200000000000e-02 -1.824600000000e+00 -4.000000000000e-03 -1.368450000000e+00 -3.000000000000e-03 1.094760000000e+01 2.400000000000e-02 4.561500000000e+00 1.000000000000e-02 -9.579150000000e+00 -2.100000000000e-02 4.059735000000e+01 8.900000000000e-02 2.736900000000e+00 6.000000000000e-03 8.210700000000e+00 1.800000000000e-02 -3.193050000000e+00 -7.000000000000e-03 -1.824600000000e+00 -4.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 1.824600000000e+00 4.000000000000e-03 5.017650000000e+00 1.100000000000e-02 2.280750000000e+00 5.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 4.561500000000e-01 1.000000000000e-03 9.123000000000e-01 2.000000000000e-03 5.473800000000e+00 1.200000000000e-02 -1.368450000000e+00 -3.000000000000e-03 -2.736900000000e+00 -6.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 -1.368450000000e+00 -3.000000000000e-03 -2.508825000000e+01 -5.500000000000e-02 -1.140375000000e+01 -2.500000000000e-02 -1.778985000000e+01 -3.900000000000e-02 4.561500000000e-01 1.000000000000e-03 -4.561500000000e-01 -1.000000000000e-03 3.193050000000e+00 7.000000000000e-03 4.105350000000e+00 9.000000000000e-03 1.322835000000e+01 2.900000000000e-02 2.554440000000e+01 5.600000000000e-02 1.140375000000e+01 2.500000000000e-02 -4.561500000000e-01 -1.000000000000e-03 -4.561500000000e+00 -1.000000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.642140000000e+01 -3.600000000000e-02 -4.105350000000e+00 -9.000000000000e-03 -2.463210000000e+01 -5.400000000000e-02 -1.140375000000e+01 -2.500000000000e-02 6.842250000000e+00 1.500000000000e-02 1.140375000000e+01 2.500000000000e-02 8.210700000000e+02 1.800000000000e+00 5.884335000000e+01 1.290000000000e-01 + 18 EWK_RAP 2.300000000000e+00 8.281000000000e+03 7.000000000000e+03 2.222800000000e+04 1.322210352000e+02 8.195685880000e+01 3.687100000000e-01 -0.000000000000e+00 -0.000000000000e+00 2.178344000000e+01 9.800000000000e-02 -1.333680000000e+01 -6.000000000000e-02 4.445600000000e-01 2.000000000000e-03 7.557520000000e+00 3.400000000000e-02 -1.022488000000e+01 -4.600000000000e-02 -1.333680000000e+00 -6.000000000000e-03 1.222540000000e+01 5.500000000000e-02 1.555960000000e+01 7.000000000000e-02 -2.511764000000e+01 -1.130000000000e-01 -1.178084000000e+01 -5.300000000000e-02 4.445600000000e-01 2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 1.111400000000e+00 5.000000000000e-03 8.891200000000e-01 4.000000000000e-03 1.778240000000e+00 8.000000000000e-03 2.222800000000e-01 1.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 2.222800000000e+00 1.000000000000e-02 -1.333680000000e+00 -6.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 1.333680000000e+00 6.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -6.890680000000e+00 -3.100000000000e-02 2.222800000000e-01 1.000000000000e-03 -2.000520000000e+00 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -8.891200000000e-01 -4.000000000000e-03 2.222800000000e-01 1.000000000000e-03 4.445600000000e-01 2.000000000000e-03 8.891200000000e-01 4.000000000000e-03 6.668400000000e-01 3.000000000000e-03 1.778240000000e+00 8.000000000000e-03 -2.222800000000e-01 -1.000000000000e-03 1.555960000000e+00 7.000000000000e-03 -8.891200000000e-01 -4.000000000000e-03 -2.222800000000e-01 -1.000000000000e-03 4.445600000000e-01 2.000000000000e-03 -1.111400000000e+00 -5.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -6.668400000000e-01 -3.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -8.891200000000e-01 -4.000000000000e-03 -1.111400000000e+00 -5.000000000000e-03 4.445600000000e-01 2.000000000000e-03 -1.778240000000e+00 -8.000000000000e-03 4.445600000000e-01 2.000000000000e-03 -1.333680000000e+00 -6.000000000000e-03 4.445600000000e-01 2.000000000000e-03 3.378656000000e+01 1.520000000000e-01 7.335240000000e+00 3.300000000000e-02 3.334200000000e+00 1.500000000000e-02 -1.333680000000e+00 -6.000000000000e-03 -5.334720000000e+00 -2.400000000000e-02 2.000520000000e+00 9.000000000000e-03 -1.111400000000e+00 -5.000000000000e-03 -1.555960000000e+00 -7.000000000000e-03 7.557520000000e+00 3.400000000000e-02 4.445600000000e-01 2.000000000000e-03 1.555960000000e+00 7.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 2.222800000000e+00 1.000000000000e-02 4.445600000000e-01 2.000000000000e-03 -1.778240000000e+00 -8.000000000000e-03 1.111400000000e+00 5.000000000000e-03 -2.222800000000e-01 -1.000000000000e-03 -4.890160000000e+00 -2.200000000000e-02 2.889640000000e+00 1.300000000000e-02 0.000000000000e+00 0.000000000000e+00 3.356428000000e+01 1.510000000000e-01 -2.511764000000e+01 -1.130000000000e-01 1.111400000000e+01 5.000000000000e-02 -6.668400000000e+00 -3.000000000000e-02 -3.111920000000e+00 -1.400000000000e-02 4.890160000000e+00 2.200000000000e-02 1.555960000000e+00 7.000000000000e-03 2.222800000000e-01 1.000000000000e-03 1.733784000000e+01 7.800000000000e-02 -3.334200000000e+00 -1.500000000000e-02 -1.778240000000e+00 -8.000000000000e-03 1.111400000000e+00 5.000000000000e-03 8.891200000000e+00 4.000000000000e-02 -8.891200000000e-01 -4.000000000000e-03 -2.889640000000e+00 -1.300000000000e-02 3.400884000000e+01 1.530000000000e-01 -5.557000000000e+00 -2.500000000000e-02 1.244768000000e+01 5.600000000000e-02 -1.044716000000e+01 -4.700000000000e-02 -8.446640000000e+00 -3.800000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 2.222800000000e-01 1.000000000000e-03 2.222800000000e+00 1.000000000000e-02 1.555960000000e+00 7.000000000000e-03 4.445600000000e-01 2.000000000000e-03 -6.668400000000e-01 -3.000000000000e-03 2.222800000000e-01 1.000000000000e-03 4.445600000000e-01 2.000000000000e-03 -1.111400000000e+00 -5.000000000000e-03 3.778760000000e+00 1.700000000000e-02 2.222800000000e-01 1.000000000000e-03 -1.111400000000e+00 -5.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -4.445600000000e-01 -2.000000000000e-03 -1.222540000000e+01 -5.500000000000e-02 -6.223840000000e+00 -2.800000000000e-02 -9.113480000000e+00 -4.100000000000e-02 2.222800000000e-01 1.000000000000e-03 2.222800000000e-01 1.000000000000e-03 2.000520000000e+00 9.000000000000e-03 2.445080000000e+00 1.100000000000e-02 5.779280000000e+00 2.600000000000e-02 1.311452000000e+01 5.900000000000e-02 5.334720000000e+00 2.400000000000e-02 -4.445600000000e-01 -2.000000000000e-03 -2.667360000000e+00 -1.200000000000e-02 0.000000000000e+00 0.000000000000e+00 -8.668920000000e+00 -3.900000000000e-02 -2.000520000000e+00 -9.000000000000e-03 -1.378136000000e+01 -6.200000000000e-02 -5.557000000000e+00 -2.500000000000e-02 6.446120000000e+00 2.900000000000e-02 8.891200000000e+00 4.000000000000e-02 4.001040000000e+02 1.800000000000e+00 4.779020000000e+01 2.150000000000e-01 + 19 EWK_RAP 2.000000000000e-01 1.768900000000e+04 7.000000000000e+03 1.510400000000e+03 2.127398400000e+01 1.360447488000e+01 9.007200000000e-01 -8.156160000000e-01 -5.400000000000e-02 9.666560000000e-01 6.400000000000e-02 -3.322880000000e-01 -2.200000000000e-02 -6.645760000000e-01 -4.400000000000e-02 4.078080000000e-01 2.700000000000e-02 2.205184000000e+00 1.460000000000e-01 -7.400960000000e-01 -4.900000000000e-02 1.465088000000e+00 9.700000000000e-02 -2.567680000000e+00 -1.700000000000e-01 -1.465088000000e+00 -9.700000000000e-02 2.673408000000e+00 1.770000000000e-01 6.434304000000e+00 4.260000000000e-01 0.000000000000e+00 0.000000000000e+00 -3.171840000000e-01 -2.100000000000e-02 4.531200000000e-02 3.000000000000e-03 3.322880000000e-01 2.200000000000e-02 1.253632000000e+00 8.300000000000e-02 8.458240000000e-01 5.600000000000e-02 -2.869760000000e-01 -1.900000000000e-02 1.510400000000e-01 1.000000000000e-02 1.057280000000e-01 7.000000000000e-03 -7.552000000000e-02 -5.000000000000e-03 -3.020800000000e-02 -2.000000000000e-03 1.510400000000e-02 1.000000000000e-03 -3.020800000000e-02 -2.000000000000e-03 1.510400000000e-02 1.000000000000e-03 -1.510400000000e-02 -1.000000000000e-03 1.510400000000e-02 1.000000000000e-03 0.000000000000e+00 0.000000000000e+00 4.531200000000e-02 3.000000000000e-03 4.531200000000e-02 3.000000000000e-03 -9.062400000000e-02 -6.000000000000e-03 3.020800000000e-02 2.000000000000e-03 -6.041600000000e-02 -4.000000000000e-03 -1.510400000000e-02 -1.000000000000e-03 -4.380160000000e-01 -2.900000000000e-02 -4.229120000000e-01 -2.800000000000e-02 3.624960000000e-01 2.400000000000e-02 -2.567680000000e-01 -1.700000000000e-02 -5.739520000000e-01 -3.800000000000e-02 -4.229120000000e-01 -2.800000000000e-02 -1.208320000000e-01 -8.000000000000e-03 3.020800000000e-01 2.000000000000e-02 -1.208320000000e-01 -8.000000000000e-03 -1.359360000000e-01 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 2.718720000000e-01 1.800000000000e-02 -1.510400000000e-02 -1.000000000000e-03 -1.812480000000e-01 -1.200000000000e-02 -2.265600000000e-01 -1.500000000000e-02 -1.223424000000e+00 -8.100000000000e-02 1.208320000000e-01 8.000000000000e-03 8.563968000000e+00 5.670000000000e-01 3.232256000000e+00 2.140000000000e-01 1.736960000000e+00 1.150000000000e-01 4.682240000000e-01 3.100000000000e-02 -2.416640000000e-01 -1.600000000000e-02 1.208320000000e-01 8.000000000000e-03 4.380160000000e-01 2.900000000000e-02 4.682240000000e-01 3.100000000000e-02 -1.057280000000e-01 -7.000000000000e-03 1.510400000000e-02 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2.567680000000e-01 1.700000000000e-02 1.510400000000e-02 1.000000000000e-03 -9.062400000000e-02 -6.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -8.005120000000e-01 -5.300000000000e-02 -5.588480000000e-01 -3.700000000000e-02 1.963520000000e-01 1.300000000000e-02 1.057280000000e-01 7.000000000000e-03 -1.661440000000e-01 -1.100000000000e-02 -1.510400000000e-01 -1.000000000000e-02 -9.062400000000e-02 -6.000000000000e-03 -3.322880000000e-01 -2.200000000000e-02 -1.510400000000e-01 -1.000000000000e-02 1.057280000000e-01 7.000000000000e-03 -9.062400000000e-02 -6.000000000000e-03 1.359360000000e-01 9.000000000000e-03 3.624960000000e-01 2.400000000000e-02 3.866624000000e+00 2.560000000000e-01 1.510400000000e+00 1.000000000000e-01 2.280704000000e+00 1.510000000000e-01 1.208320000000e-01 8.000000000000e-03 3.776000000000e-01 2.500000000000e-02 7.552000000000e-02 5.000000000000e-03 -3.927040000000e-01 -2.600000000000e-02 -2.008832000000e+00 -1.330000000000e-01 -2.326016000000e+00 -1.540000000000e-01 -2.114560000000e+00 -1.400000000000e-01 4.229120000000e-01 2.800000000000e-02 1.797376000000e+00 1.190000000000e-01 4.531200000000e-02 3.000000000000e-03 1.525504000000e+00 1.010000000000e-01 6.343680000000e-01 4.200000000000e-02 3.368192000000e+00 2.230000000000e-01 1.767168000000e+00 1.170000000000e-01 2.567680000000e-01 1.700000000000e-02 -1.465088000000e+00 -9.700000000000e-02 2.718720000000e+01 1.800000000000e+00 9.968640000000e-01 6.600000000000e-02 + 20 EWK_RAP 6.000000000000e-01 1.768900000000e+04 7.000000000000e+03 1.458100000000e+03 2.002408730000e+01 8.901992120000e+00 6.105200000000e-01 -2.916200000000e-01 -2.000000000000e-02 8.456980000000e-01 5.800000000000e-02 -2.624580000000e-01 -1.800000000000e-02 -5.540780000000e-01 -3.800000000000e-02 8.602790000000e-01 5.900000000000e-02 1.545586000000e+00 1.060000000000e-01 -5.540780000000e-01 -3.800000000000e-02 -2.055921000000e+00 -1.410000000000e-01 -3.309887000000e+00 -2.270000000000e-01 -1.166480000000e+00 -8.000000000000e-02 1.385195000000e+00 9.500000000000e-02 5.730333000000e+00 3.930000000000e-01 5.832400000000e-02 4.000000000000e-03 -2.916200000000e-01 -2.000000000000e-02 4.374300000000e-02 3.000000000000e-03 3.499440000000e-01 2.400000000000e-02 1.151899000000e+00 7.900000000000e-02 5.540780000000e-01 3.800000000000e-02 -2.770390000000e-01 -1.900000000000e-02 2.478770000000e-01 1.700000000000e-02 5.832400000000e-02 4.000000000000e-03 -5.832400000000e-02 -4.000000000000e-03 8.748600000000e-02 6.000000000000e-03 2.916200000000e-02 2.000000000000e-03 -8.748600000000e-02 -6.000000000000e-03 8.748600000000e-02 6.000000000000e-03 -4.374300000000e-02 -3.000000000000e-03 5.832400000000e-02 4.000000000000e-03 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2.080000000000e-01 -1.312290000000e-01 -9.000000000000e-03 -5.103350000000e-01 -3.500000000000e-02 2.770390000000e-01 1.900000000000e-02 7.290500000000e-02 5.000000000000e-03 -6.853070000000e-01 -4.700000000000e-02 -3.353630000000e-01 -2.300000000000e-02 -1.458100000000e-02 -1.000000000000e-03 1.020670000000e-01 7.000000000000e-03 1.458100000000e-01 1.000000000000e-02 1.458100000000e-02 1.000000000000e-03 -1.166480000000e-01 -8.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -1.166480000000e+00 -8.000000000000e-02 -5.249160000000e-01 -3.600000000000e-02 1.749720000000e-01 1.200000000000e-02 4.374300000000e-02 3.000000000000e-03 -1.458100000000e-01 -1.000000000000e-02 -1.749720000000e-01 -1.200000000000e-02 -1.166480000000e-01 -8.000000000000e-03 -6.707260000000e-01 -4.600000000000e-02 -2.624580000000e-01 -1.800000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -1.020670000000e-01 -7.000000000000e-03 1.166480000000e-01 8.000000000000e-03 3.499440000000e-01 2.400000000000e-02 3.353630000000e+00 2.300000000000e-01 1.195642000000e+00 8.200000000000e-02 2.041340000000e+00 1.400000000000e-01 7.290500000000e-02 5.000000000000e-03 3.499440000000e-01 2.400000000000e-02 2.041340000000e-01 1.400000000000e-02 -4.228490000000e-01 -2.900000000000e-02 -1.633072000000e+00 -1.120000000000e-01 -1.997597000000e+00 -1.370000000000e-01 -1.822625000000e+00 -1.250000000000e-01 4.082680000000e-01 2.800000000000e-02 1.939273000000e+00 1.330000000000e-01 -1.603910000000e-01 -1.100000000000e-02 1.487262000000e+00 1.020000000000e-01 5.540780000000e-01 3.800000000000e-02 3.280725000000e+00 2.250000000000e-01 1.574748000000e+00 1.080000000000e-01 -1.895530000000e-01 -1.300000000000e-02 -1.531005000000e+00 -1.050000000000e-01 2.624580000000e+01 1.800000000000e+00 9.769270000000e-01 6.700000000000e-02 + 21 EWK_RAP 1.000000000000e+00 1.768900000000e+04 7.000000000000e+03 1.349700000000e+03 1.960034340000e+01 9.900724350000e+00 7.335500000000e-01 -1.889580000000e-01 -1.400000000000e-02 9.582870000000e-01 7.100000000000e-02 -4.723950000000e-01 -3.500000000000e-02 -1.079760000000e-01 -8.000000000000e-03 -4.319040000000e-01 -3.200000000000e-02 1.754610000000e+00 1.300000000000e-01 5.533770000000e-01 4.100000000000e-02 1.430682000000e+00 1.060000000000e-01 -2.510442000000e+00 -1.860000000000e-01 -1.201233000000e+00 -8.900000000000e-02 9.447900000000e-01 7.000000000000e-02 4.008609000000e+00 2.970000000000e-01 8.098200000000e-02 6.000000000000e-03 -2.969340000000e-01 -2.200000000000e-02 6.748500000000e-02 5.000000000000e-03 3.239280000000e-01 2.400000000000e-02 9.717840000000e-01 7.200000000000e-02 3.644190000000e-01 2.700000000000e-02 -2.429460000000e-01 -1.800000000000e-02 9.447900000000e-02 7.000000000000e-03 -4.049100000000e-02 -3.000000000000e-03 -1.349700000000e-02 -1.000000000000e-03 -2.699400000000e-02 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -9.447900000000e-02 -7.000000000000e-03 9.447900000000e-02 7.000000000000e-03 -9.447900000000e-02 -7.000000000000e-03 5.398800000000e-02 4.000000000000e-03 5.398800000000e-02 4.000000000000e-03 1.349700000000e-02 1.000000000000e-03 -1.349700000000e-02 -1.000000000000e-03 -2.699400000000e-02 -2.000000000000e-03 -4.049100000000e-02 -3.000000000000e-03 -2.699400000000e-02 -2.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -2.159520000000e-01 -1.600000000000e-02 -2.564430000000e-01 -1.900000000000e-02 3.914130000000e-01 2.900000000000e-02 2.699400000000e-02 2.000000000000e-03 -4.588980000000e-01 -3.400000000000e-02 -5.128860000000e-01 -3.800000000000e-02 -1.619640000000e-01 -1.200000000000e-02 2.969340000000e-01 2.200000000000e-02 -1.079760000000e-01 -8.000000000000e-03 -2.024550000000e-01 -1.500000000000e-02 -8.098200000000e-02 -6.000000000000e-03 2.699400000000e-02 2.000000000000e-03 -2.699400000000e-02 -2.000000000000e-03 -2.834370000000e-01 -2.100000000000e-02 -2.699400000000e-01 -2.000000000000e-02 5.263830000000e-01 3.900000000000e-02 2.793879000000e+00 2.070000000000e-01 5.938680000000e+00 4.400000000000e-01 3.131304000000e+00 2.320000000000e-01 2.523939000000e+00 1.870000000000e-01 5.938680000000e-01 4.400000000000e-02 1.484670000000e-01 1.100000000000e-02 8.098200000000e-02 6.000000000000e-03 -1.012275000000e+00 -7.500000000000e-02 2.024550000000e-01 1.500000000000e-02 -2.429460000000e-01 -1.800000000000e-02 2.159520000000e-01 1.600000000000e-02 4.723950000000e-01 3.500000000000e-02 -4.184070000000e-01 -3.100000000000e-02 1.214730000000e-01 9.000000000000e-03 1.349700000000e-01 1.000000000000e-02 4.723950000000e-01 3.500000000000e-02 1.417185000000e+00 1.050000000000e-01 2.564430000000e+00 1.900000000000e-01 1.349700000000e-02 1.000000000000e-03 1.633137000000e+00 1.210000000000e-01 1.066263000000e+00 7.900000000000e-02 1.309209000000e+00 9.700000000000e-02 3.239280000000e-01 2.400000000000e-02 5.398800000000e-02 4.000000000000e-03 1.889580000000e-01 1.400000000000e-02 2.699400000000e-01 2.000000000000e-02 -1.484670000000e-01 -1.100000000000e-02 2.523939000000e+00 1.870000000000e-01 -6.748500000000e-02 -5.000000000000e-03 -3.509220000000e-01 -2.600000000000e-02 2.969340000000e-01 2.200000000000e-02 -2.699400000000e-02 -2.000000000000e-03 -5.398800000000e-01 -4.000000000000e-02 -3.779160000000e-01 -2.800000000000e-02 3.374250000000e-01 2.500000000000e-02 -6.748500000000e-02 -5.000000000000e-03 1.349700000000e-01 1.000000000000e-02 -6.748500000000e-02 -5.000000000000e-03 6.748500000000e-02 5.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -9.582870000000e-01 -7.100000000000e-02 -4.858920000000e-01 -3.600000000000e-02 2.024550000000e-01 1.500000000000e-02 5.398800000000e-02 4.000000000000e-03 -1.889580000000e-01 -1.400000000000e-02 -9.447900000000e-02 -7.000000000000e-03 -8.098200000000e-02 -6.000000000000e-03 -5.533770000000e-01 -4.100000000000e-02 -6.748500000000e-02 -5.000000000000e-03 2.699400000000e-02 2.000000000000e-03 -5.398800000000e-02 -4.000000000000e-03 1.214730000000e-01 9.000000000000e-03 3.374250000000e-01 2.500000000000e-02 3.225783000000e+00 2.390000000000e-01 8.638080000000e-01 6.400000000000e-02 1.795101000000e+00 1.330000000000e-01 -0.000000000000e+00 -0.000000000000e+00 2.564430000000e-01 1.900000000000e-02 5.398800000000e-02 4.000000000000e-03 -4.993890000000e-01 -3.700000000000e-02 -1.633137000000e+00 -1.210000000000e-01 -1.916574000000e+00 -1.420000000000e-01 -1.903077000000e+00 -1.410000000000e-01 3.644190000000e-01 2.700000000000e-02 1.849089000000e+00 1.370000000000e-01 -1.349700000000e-02 -1.000000000000e-03 1.255221000000e+00 9.300000000000e-02 5.803710000000e-01 4.300000000000e-02 3.023328000000e+00 2.240000000000e-01 1.606143000000e+00 1.190000000000e-01 2.564430000000e-01 1.900000000000e-02 -1.592646000000e+00 -1.180000000000e-01 2.429460000000e+01 1.800000000000e+00 9.717840000000e-01 7.200000000000e-02 + 22 EWK_RAP 1.400000000000e+00 1.768900000000e+04 7.000000000000e+03 1.182900000000e+03 1.823085480000e+01 8.893278780000e+00 7.518200000000e-01 -1.301190000000e-01 -1.100000000000e-02 1.052781000000e+00 8.900000000000e-02 -7.097400000000e-01 -6.000000000000e-02 1.407651000000e+00 1.190000000000e-01 1.407651000000e+00 1.190000000000e-01 2.200194000000e+00 1.860000000000e-01 8.398590000000e-01 7.100000000000e-02 6.269370000000e-01 5.300000000000e-02 -1.620573000000e+00 -1.370000000000e-01 -1.301190000000e+00 -1.100000000000e-01 2.720670000000e-01 2.300000000000e-02 2.318484000000e+00 1.960000000000e-01 7.097400000000e-02 6.000000000000e-03 -2.602380000000e-01 -2.200000000000e-02 3.548700000000e-02 3.000000000000e-03 2.247510000000e-01 1.900000000000e-02 7.333980000000e-01 6.200000000000e-02 2.602380000000e-01 2.200000000000e-02 -2.602380000000e-01 -2.200000000000e-02 1.774350000000e-01 1.500000000000e-02 -1.182900000000e-01 -1.000000000000e-02 4.731600000000e-02 4.000000000000e-03 -2.365800000000e-02 -2.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -1.064610000000e-01 -9.000000000000e-03 1.419480000000e-01 1.200000000000e-02 -1.064610000000e-01 -9.000000000000e-03 8.280300000000e-02 7.000000000000e-03 3.548700000000e-02 3.000000000000e-03 -2.365800000000e-02 -2.000000000000e-03 -2.365800000000e-02 -2.000000000000e-03 -3.548700000000e-02 -3.000000000000e-03 -5.914500000000e-02 -5.000000000000e-03 3.548700000000e-02 3.000000000000e-03 1.182900000000e-02 1.000000000000e-03 -2.247510000000e-01 -1.900000000000e-02 -2.010930000000e-01 -1.700000000000e-02 4.021860000000e-01 3.400000000000e-02 7.097400000000e-02 6.000000000000e-03 -4.021860000000e-01 -3.400000000000e-02 -5.086470000000e-01 -4.300000000000e-02 -1.182900000000e-01 -1.000000000000e-02 2.957250000000e-01 2.500000000000e-02 -1.064610000000e-01 -9.000000000000e-03 -2.129220000000e-01 -1.800000000000e-02 -5.914500000000e-02 -5.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -4.731600000000e-02 -4.000000000000e-03 -2.838960000000e-01 -2.400000000000e-02 -2.838960000000e-01 -2.400000000000e-02 2.838960000000e-01 2.400000000000e-02 -1.738863000000e+00 -1.470000000000e-01 4.376730000000e+00 3.700000000000e-01 3.394923000000e+00 2.870000000000e-01 2.093733000000e+00 1.770000000000e-01 2.838960000000e-01 2.400000000000e-02 2.484090000000e-01 2.100000000000e-02 3.193830000000e-01 2.700000000000e-02 -1.005465000000e+00 -8.500000000000e-02 -3.903570000000e-01 -3.300000000000e-02 -2.484090000000e-01 -2.100000000000e-02 7.452270000000e-01 6.300000000000e-02 8.990040000000e-01 7.600000000000e-02 -2.247510000000e-01 -1.900000000000e-02 2.720670000000e-01 2.300000000000e-02 1.419480000000e-01 1.200000000000e-02 2.957250000000e-01 2.500000000000e-02 2.720670000000e-01 2.300000000000e-02 2.176536000000e+00 1.840000000000e-01 1.182900000000e-02 1.000000000000e-03 1.632402000000e+00 1.380000000000e-01 6.742530000000e-01 5.700000000000e-02 9.699780000000e-01 8.200000000000e-02 3.903570000000e-01 3.300000000000e-02 7.097400000000e-02 6.000000000000e-03 3.666990000000e-01 3.100000000000e-02 2.602380000000e-01 2.200000000000e-02 -1.182900000000e-01 -1.000000000000e-02 2.188365000000e+00 1.850000000000e-01 -4.731600000000e-02 -4.000000000000e-03 -2.720670000000e-01 -2.300000000000e-02 4.731600000000e-02 4.000000000000e-03 7.097400000000e-02 6.000000000000e-03 -5.204760000000e-01 -4.400000000000e-02 -3.903570000000e-01 -3.300000000000e-02 3.430410000000e-01 2.900000000000e-02 -9.463200000000e-02 -8.000000000000e-03 5.914500000000e-02 5.000000000000e-03 -4.731600000000e-02 -4.000000000000e-03 3.548700000000e-02 3.000000000000e-03 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -8.990040000000e-01 -7.600000000000e-02 -4.495020000000e-01 -3.800000000000e-02 1.537770000000e-01 1.300000000000e-02 1.182900000000e-01 1.000000000000e-02 -9.463200000000e-02 -8.000000000000e-03 -9.463200000000e-02 -8.000000000000e-03 -5.914500000000e-02 -5.000000000000e-03 -5.204760000000e-01 -4.400000000000e-02 -1.774350000000e-01 -1.500000000000e-02 9.463200000000e-02 8.000000000000e-03 -4.731600000000e-02 -4.000000000000e-03 4.731600000000e-02 4.000000000000e-03 2.957250000000e-01 2.500000000000e-02 2.898105000000e+00 2.450000000000e-01 7.215690000000e-01 6.100000000000e-02 1.703376000000e+00 1.440000000000e-01 1.182900000000e-02 1.000000000000e-03 2.010930000000e-01 1.700000000000e-02 5.914500000000e-02 5.000000000000e-03 -5.086470000000e-01 -4.300000000000e-02 -1.490454000000e+00 -1.260000000000e-01 -1.975443000000e+00 -1.670000000000e-01 -1.786179000000e+00 -1.510000000000e-01 2.484090000000e-01 2.100000000000e-02 1.596915000000e+00 1.350000000000e-01 -3.548700000000e-02 -3.000000000000e-03 1.277532000000e+00 1.080000000000e-01 5.323050000000e-01 4.500000000000e-02 2.921763000000e+00 2.470000000000e-01 1.478625000000e+00 1.250000000000e-01 8.280300000000e-02 7.000000000000e-03 -1.466796000000e+00 -1.240000000000e-01 2.129220000000e+01 1.800000000000e+00 1.005465000000e+00 8.500000000000e-02 + 23 EWK_RAP 1.800000000000e+00 1.768900000000e+04 7.000000000000e+03 7.704600000000e+02 1.564650168000e+01 7.596350370000e+00 9.859500000000e-01 1.540920000000e-02 2.000000000000e-03 8.398014000000e-01 1.090000000000e-01 -5.624358000000e-01 -7.300000000000e-02 -3.312978000000e-01 -4.300000000000e-02 1.463874000000e-01 1.900000000000e-02 1.718125800000e+00 2.230000000000e-01 -3.621162000000e-01 -4.700000000000e-02 -2.157288000000e-01 -2.800000000000e-02 -9.707796000000e-01 -1.260000000000e-01 -1.255849800000e+00 -1.630000000000e-01 -6.934140000000e-02 -9.000000000000e-03 8.320968000000e-01 1.080000000000e-01 2.311380000000e-02 3.000000000000e-03 -1.772058000000e-01 -2.300000000000e-02 1.540920000000e-02 2.000000000000e-03 1.309782000000e-01 1.700000000000e-02 3.621162000000e-01 4.700000000000e-02 8.475060000000e-02 1.100000000000e-02 -2.003196000000e-01 -2.600000000000e-02 2.157288000000e-01 2.800000000000e-02 -3.852300000000e-02 -5.000000000000e-03 -6.934140000000e-02 -9.000000000000e-03 7.704600000000e-02 1.000000000000e-02 1.540920000000e-02 2.000000000000e-03 -9.245520000000e-02 -1.200000000000e-02 1.078644000000e-01 1.400000000000e-02 -7.704600000000e-02 -1.000000000000e-02 9.245520000000e-02 1.200000000000e-02 1.540920000000e-02 2.000000000000e-03 -7.704600000000e-03 -1.000000000000e-03 3.852300000000e-02 5.000000000000e-03 -6.163680000000e-02 -8.000000000000e-03 -5.393220000000e-02 -7.000000000000e-03 5.393220000000e-02 7.000000000000e-03 3.081840000000e-02 4.000000000000e-03 -2.850702000000e-01 -3.700000000000e-02 -2.465472000000e-01 -3.200000000000e-02 2.311380000000e-01 3.000000000000e-02 -1.001598000000e-01 -1.300000000000e-02 -3.467070000000e-01 -4.500000000000e-02 -2.773656000000e-01 -3.600000000000e-02 -0.000000000000e+00 -0.000000000000e+00 1.386828000000e-01 1.800000000000e-02 -5.393220000000e-02 -7.000000000000e-03 -1.155690000000e-01 -1.500000000000e-02 -2.311380000000e-02 -3.000000000000e-03 1.540920000000e-01 2.000000000000e-02 -2.311380000000e-02 -3.000000000000e-03 -1.232736000000e-01 -1.600000000000e-02 -8.475060000000e-02 -1.100000000000e-02 -1.571738400000e+00 -2.040000000000e-01 4.052619600000e+00 5.260000000000e-01 1.879922400000e+00 2.440000000000e-01 2.488585800000e+00 3.230000000000e-01 1.987786800000e+00 2.580000000000e-01 2.157288000000e-01 2.800000000000e-02 -1.463874000000e-01 -1.900000000000e-02 1.695012000000e-01 2.200000000000e-02 -5.932542000000e-01 -7.700000000000e-02 -4.622760000000e-02 -6.000000000000e-03 -3.081840000000e-01 -4.000000000000e-02 5.007990000000e-01 6.500000000000e-02 8.552106000000e-01 1.110000000000e-01 -5.624358000000e-01 -7.300000000000e-02 6.934140000000e-02 9.000000000000e-03 1.155690000000e-01 1.500000000000e-02 4.468668000000e-01 5.800000000000e-02 -1.302077400000e+00 -1.690000000000e-01 1.163394600000e+00 1.510000000000e-01 1.540920000000e-02 2.000000000000e-03 1.171099200000e+00 1.520000000000e-01 3.775254000000e-01 4.900000000000e-02 5.701404000000e-01 7.400000000000e-02 8.243922000000e-01 1.070000000000e-01 3.081840000000e-02 4.000000000000e-03 4.083438000000e-01 5.300000000000e-02 2.003196000000e-01 2.600000000000e-02 -2.311380000000e-02 -3.000000000000e-03 1.540920000000e+00 2.000000000000e-01 -7.704600000000e-02 -1.000000000000e-02 -2.542518000000e-01 -3.300000000000e-02 -2.619564000000e-01 -3.400000000000e-02 -1.926150000000e-01 -2.500000000000e-02 -3.775254000000e-01 -4.900000000000e-02 -4.622760000000e-01 -6.000000000000e-02 5.855496000000e-01 7.600000000000e-02 -1.463874000000e-01 -1.900000000000e-02 1.695012000000e-01 2.200000000000e-02 -1.463874000000e-01 -1.900000000000e-02 -6.934140000000e-02 -9.000000000000e-03 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 -0.000000000000e+00 -0.000000000000e+00 -6.394818000000e-01 -8.300000000000e-02 -2.773656000000e-01 -3.600000000000e-02 1.463874000000e-01 1.900000000000e-02 2.773656000000e-01 3.600000000000e-02 -1.386828000000e-01 -1.800000000000e-02 -1.540920000000e-02 -2.000000000000e-03 1.540920000000e-02 2.000000000000e-03 -5.547312000000e-01 -7.200000000000e-02 6.163680000000e-02 8.000000000000e-03 2.927748000000e-01 3.800000000000e-02 -3.081840000000e-02 -4.000000000000e-03 3.852300000000e-02 5.000000000000e-03 2.234334000000e-01 2.900000000000e-02 1.764353400000e+00 2.290000000000e-01 3.467070000000e-01 4.500000000000e-02 1.132576200000e+00 1.470000000000e-01 6.163680000000e-02 8.000000000000e-03 1.463874000000e-01 1.900000000000e-02 1.617966000000e-01 2.100000000000e-02 -2.003196000000e-01 -2.600000000000e-02 -9.476658000000e-01 -1.230000000000e-01 -1.171099200000e+00 -1.520000000000e-01 -1.001598000000e+00 -1.300000000000e-01 2.157288000000e-01 2.800000000000e-02 1.024711800000e+00 1.330000000000e-01 -1.001598000000e-01 -1.300000000000e-02 6.548910000000e-01 8.500000000000e-02 2.927748000000e-01 3.800000000000e-02 1.571738400000e+00 2.040000000000e-01 8.629152000000e-01 1.120000000000e-01 6.009588000000e-01 7.800000000000e-02 -1.078644000000e-01 -1.400000000000e-02 1.386828000000e+01 1.800000000000e+00 9.476658000000e-01 1.230000000000e-01 + 24 EWK_RAP 2.200000000000e+00 1.768900000000e+04 7.000000000000e+03 3.287100000000e+02 1.041681990000e+01 4.306429710000e+00 1.310100000000e+00 6.574200000000e-03 2.000000000000e-03 3.615810000000e-01 1.100000000000e-01 -2.498196000000e-01 -7.600000000000e-02 2.005131000000e-01 6.100000000000e-02 6.935781000000e-01 2.110000000000e-01 4.634811000000e-01 1.410000000000e-01 3.221358000000e-01 9.800000000000e-02 -9.138138000000e-01 -2.780000000000e-01 -5.292231000000e-01 -1.610000000000e-01 -3.089874000000e-01 -9.400000000000e-02 -1.249098000000e-01 -3.800000000000e-02 1.281969000000e-01 3.900000000000e-02 -0.000000000000e+00 -0.000000000000e+00 -7.231620000000e-02 -2.200000000000e-02 1.643550000000e-02 5.000000000000e-03 5.259360000000e-02 1.600000000000e-02 1.314840000000e-01 4.000000000000e-02 1.643550000000e-02 5.000000000000e-03 -8.217750000000e-02 -2.500000000000e-02 7.231620000000e-02 2.200000000000e-02 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-1.200000000000e-01 + 2 EWK_RAP 6.000000000000e-01 8.315178393760e+03 7.000000000000e+03 1.318605280000e+05 1.938349761600e+03 6.593026400000e+02 5.000000000000e-01 4.615118480000e+03 3.500000000000e+00 3.823955312000e+02 2.900000000000e-01 1.186744752000e+02 9.000000000000e-02 5.274421120000e+01 4.000000000000e-02 2.505350032000e+02 1.900000000000e-01 9.230236960000e+01 7.000000000000e-02 -1.318605280000e+02 -1.000000000000e-01 5.274421120000e+01 4.000000000000e-02 -1.186744752000e+02 -9.000000000000e-02 -2.637210560000e+01 -2.000000000000e-02 1.714186864000e+02 1.300000000000e-01 -1.318605280000e+02 -1.000000000000e-01 7.911631680000e+01 6.000000000000e-02 -3.823955312000e+02 -2.900000000000e-01 1.318605280000e+01 1.000000000000e-02 7.911631680000e+01 6.000000000000e-02 -1.054884224000e+02 -8.000000000000e-02 -7.252329040000e+02 -5.500000000000e-01 2.637210560000e+01 2.000000000000e-02 -2.109768448000e+02 -1.600000000000e-01 4.219536896000e+02 3.200000000000e-01 -2.241628976000e+02 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1.565731713000e+02 1.300000000000e-01 -1.445290812000e+02 -1.200000000000e-01 + 5 EWK_RAP 1.800000000000e+00 8.315178393760e+03 7.000000000000e+03 1.154900190000e+05 2.125016349600e+03 7.275871197000e+02 6.300000000000e-01 4.042150665000e+03 3.500000000000e+00 3.349210551000e+02 2.900000000000e-01 1.039410171000e+02 9.000000000000e-02 4.619600760000e+01 4.000000000000e-02 2.194310361000e+02 1.900000000000e-01 1.154900190000e+01 1.000000000000e-02 -4.619600760000e+01 -4.000000000000e-02 5.774500950000e+01 5.000000000000e-02 -9.239201520000e+01 -8.000000000000e-02 5.774500950000e+01 5.000000000000e-02 3.464700570000e+01 3.000000000000e-02 1.154900190000e+01 1.000000000000e-02 3.811170627000e+02 3.300000000000e-01 1.732350285000e+02 1.500000000000e-01 -1.154900190000e+01 -1.000000000000e-02 2.309800380000e+01 2.000000000000e-02 -1.039410171000e+02 -9.000000000000e-02 -4.273130703000e+02 -3.700000000000e-01 1.963330323000e+02 1.700000000000e-01 -8.084301330000e+01 -7.000000000000e-02 4.735090779000e+02 4.100000000000e-01 4.619600760000e+01 4.000000000000e-02 -5.197050855000e+02 -4.500000000000e-01 -5.659010931000e+02 -4.900000000000e-01 0.000000000000e+00 0.000000000000e+00 9.239201520000e+01 8.000000000000e-02 2.771760456000e+02 2.400000000000e-01 -6.929401140000e+01 -6.000000000000e-02 7.622341254000e+02 6.600000000000e-01 -6.929401140000e+01 -6.000000000000e-02 -1.270390209000e+02 -1.100000000000e-01 + 6 EWK_RAP 2.200000000000e+00 8.315178393760e+03 7.000000000000e+03 1.072283620000e+05 2.755768903400e+03 1.469028559400e+03 1.370000000000e+00 3.752992670000e+03 3.500000000000e+00 3.109622498000e+02 2.900000000000e-01 9.650552580000e+01 9.000000000000e-02 4.289134480000e+01 4.000000000000e-02 2.037338878000e+02 1.900000000000e-01 0.000000000000e+00 0.000000000000e+00 -7.505985340000e+01 -7.000000000000e-02 9.650552580000e+01 9.000000000000e-02 -2.037338878000e+02 -1.900000000000e-01 1.930110516000e+02 1.800000000000e-01 -5.361418100000e+01 -5.000000000000e-02 1.393968706000e+02 1.300000000000e-01 8.149355512000e+02 7.600000000000e-01 1.930110516000e+02 1.800000000000e-01 2.466252326000e+02 2.300000000000e-01 2.466252326000e+02 2.300000000000e-01 4.289134480000e+01 4.000000000000e-02 -6.219244996000e+02 -5.800000000000e-01 1.822882154000e+02 1.700000000000e-01 -6.433701720000e+01 -6.000000000000e-02 7.077071892000e+02 6.600000000000e-01 1.393968706000e+02 1.300000000000e-01 -1.233126163000e+03 -1.150000000000e+00 -9.114410770000e+02 -8.500000000000e-01 1.608425430000e+02 1.500000000000e-01 1.072283620000e+01 1.000000000000e-02 7.398756978000e+02 6.900000000000e-01 -2.144567240000e+02 -2.000000000000e-01 6.648158444000e+02 6.200000000000e-01 -1.501197068000e+02 -1.400000000000e-01 -2.144567240000e+02 -2.000000000000e-01 + 7 EWK_RAP 2.600000000000e+00 8.315178393760e+03 7.000000000000e+03 9.390376600000e+04 3.042482018400e+03 3.577733484600e+03 3.810000000000e+00 3.286631810000e+03 3.500000000000e+00 2.723209214000e+02 2.900000000000e-01 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-1.900000000000e-01 6.573263620000e+02 7.000000000000e-01 -1.577583268800e+03 -1.680000000000e+00 -1.971979086000e+02 -2.100000000000e-01 + 8 EWK_RAP 3.200000000000e+00 8.315178393760e+03 7.000000000000e+03 5.437820600000e+04 2.289322472600e+03 2.376327602200e+03 4.370000000000e+00 1.903237210000e+03 3.500000000000e+00 1.576967974000e+02 2.900000000000e-01 4.894038540000e+01 9.000000000000e-02 2.175128240000e+01 4.000000000000e-02 9.788077080000e+01 1.800000000000e-01 9.788077080000e+01 1.800000000000e-01 -1.631346180000e+01 -3.000000000000e-02 9.570564256000e+02 1.760000000000e+00 -6.307871896000e+02 -1.160000000000e+00 6.960410368000e+02 1.280000000000e+00 -5.057173158000e+02 -9.300000000000e-01 1.016872452200e+03 1.870000000000e+00 2.702596838200e+03 4.970000000000e+00 -2.120750034000e+02 -3.900000000000e-01 1.734664771400e+03 3.190000000000e+00 1.468211562000e+03 2.700000000000e+00 8.918025784000e+02 1.640000000000e+00 -1.060375017000e+03 -1.950000000000e+00 3.045179536000e+02 5.600000000000e-01 2.011993622000e+02 3.700000000000e-01 -4.513391098000e+02 -8.300000000000e-01 -1.631346180000e+01 -3.000000000000e-02 7.558570634000e+02 1.390000000000e+00 4.241500068000e+02 7.800000000000e-01 1.522589768000e+02 2.800000000000e-01 1.413833356000e+02 2.600000000000e-01 -6.144737278000e+02 -1.130000000000e+00 -2.175128240000e+01 -4.000000000000e-02 1.413833356000e+02 2.600000000000e-01 -2.501397476000e+02 -4.600000000000e-01 -1.141942326000e+02 -2.100000000000e-01 diff --git a/nnpdfcpp/data/commondata/DATA_ATLAS_W_TOT_13TEV.dat b/nnpdfcpp/data/commondata/DATA_ATLAS_W_TOT_13TEV.dat new file mode 100644 index 0000000000..09f73eb223 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_ATLAS_W_TOT_13TEV.dat @@ -0,0 +1,3 @@ +ATLAS_W_TOT_13TEV 4 2 + 1 INC 0.000000000000e+00 8.038500000000e+01 1.300000000000e+01 3.500000000000e+06 1.000000000000e+04 6.804831649279e+04 1.944237614080e+00 1.641421688915e+04 4.689776254043e-01 -1.031564236735e+01 -2.947326390672e-04 7.000000000000e+04 2.000000000000e+00 + 2 INC 0.000000000000e+00 8.038500000000e+01 1.300000000000e+01 4.530000000000e+06 1.000000000000e+04 8.912329915071e+04 1.967401747256e+00 -1.253128092916e+04 -2.766287180831e-01 -6.742972668559e+01 -1.488514937872e-03 1.000000000000e+05 2.207505518764e+00 diff --git a/nnpdfcpp/data/commondata/DATA_ATLAS_Z_TOT_13TEV.dat b/nnpdfcpp/data/commondata/DATA_ATLAS_Z_TOT_13TEV.dat new file mode 100644 index 0000000000..4976500e86 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_ATLAS_Z_TOT_13TEV.dat @@ -0,0 +1,2 @@ +ATLAS_Z_TOT_13TEV 4 1 + 1 INC 0.000000000000e+00 9.118760000000e+01 1.300000000000e+01 7.790000000000e+05 3.000000000000e+03 1.139539991217e+03 1.462824122230e-01 -1.147189778108e+02 -1.472644131076e-02 5.889676405758e+03 7.560560212783e-01 1.600000000000e+04 2.053915275995e+00 diff --git a/nnpdfcpp/data/commondata/DATA_LHCBWMU7TEV.dat b/nnpdfcpp/data/commondata/DATA_LHCBWMU7TEV.dat new file mode 100644 index 0000000000..c63f8b3489 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_LHCBWMU7TEV.dat @@ -0,0 +1,17 @@ +LHCBWMU7TEV 35 16 + 1 EWK_RAP 2.125000000000e+00 6.463838404000e+03 7.000000000000e+03 1.922000000000e+05 1.200000000000e+03 2.989058480120e+03 1.555181311197e+00 1.741235273420e+03 9.059496739957e-01 -2.502509253267e+02 -1.302033950711e-01 1.923129135381e+02 1.000587479387e-01 1.091852381188e+02 5.680813637815e-02 -1.025660890279e+02 -5.336425027466e-02 -1.104461653422e+02 -5.746418592204e-02 -9.069732310441e+01 -4.718903387326e-02 -1.302139122911e+02 -6.774917392879e-02 -3.443802792048e+02 -1.791780849141e-01 -5.222339273468e+01 -2.717138019494e-02 5.306781238154e+01 2.761072444409e-02 1.434556533549e+00 7.463873743749e-04 -6.801894197503e+00 -3.538966804112e-03 2.441106994931e+00 1.270086886020e-03 1.524675578507e+00 7.932755351234e-04 4.789441759398e-01 2.491905181789e-04 -3.726763257367e-02 -1.939002735363e-05 6.207631613405e-05 3.229777114155e-08 5.144752523450e-05 2.676770303564e-08 -4.978535045625e-04 -2.590288785445e-07 -1.332543857629e-03 -6.933110601606e-07 3.153912505699e-02 1.640953436888e-05 1.090011576442e-03 5.671236089708e-07 5.255700735596e-04 2.734495700102e-07 -8.821259852596e-04 -4.589625313526e-07 -1.956012480794e-02 -1.017696399997e-05 -2.273515254326e-02 -1.182890350846e-05 7.187191336324e-02 3.739433577692e-05 -7.576816752144e-03 -3.942152316412e-06 1.146778633281e-03 5.966590183562e-07 -5.970827174256e-02 -3.106569809706e-05 -6.654182936885e-03 -3.462113910970e-06 2.000000000000e+03 1.040582726327e+00 3.300000000000e+03 1.716961498439e+00 + 2 EWK_RAP 2.375000000000e+00 6.463838404000e+03 7.000000000000e+03 1.788000000000e+05 9.000000000000e+02 -1.771220332867e+03 -9.906153986954e-01 2.177614555246e+03 1.217905232241e+00 1.184982769207e+03 6.627420409437e-01 4.615478923378e+02 2.581364051106e-01 1.337658587596e+02 7.481312011165e-02 -2.271367328176e+01 -1.270339669002e-02 -2.089766517340e+01 -1.168773219989e-02 -7.501098488920e+00 -4.195245239888e-03 1.304455757005e+01 7.295613853496e-03 -2.233613584480e+02 -1.249224599821e-01 1.959079428952e+02 1.095682007244e-01 -3.482826694483e+01 -1.947889650158e-02 -6.349481139807e+01 -3.551163948438e-02 2.814939334331e+01 1.574350858127e-02 1.179622725077e+01 6.597442533989e-03 6.619959021199e+00 3.702437931319e-03 4.660844529208e-01 2.606736313875e-04 -2.452777622605e-02 -1.371799565215e-05 6.435082314041e-05 3.599039325526e-08 1.532612796747e-04 8.571659937061e-08 -4.990479802595e-04 -2.791096086463e-07 -3.561554370899e-03 -1.991920789094e-06 -9.260786790773e-03 -5.179410956808e-06 3.726237000544e-03 2.084025168089e-06 7.849551180122e-03 4.390129295370e-06 -3.652881697629e-02 -2.042998712320e-05 -1.176959484568e-02 -6.582547452840e-06 4.908830761368e-03 2.745431074591e-06 2.144099412842e-02 1.199160745438e-05 -1.149407568064e-02 -6.428453960090e-06 1.316935152189e-02 7.365409128575e-06 -6.059498306499e-02 -3.388981155760e-05 2.772306047150e-02 1.550506737779e-05 1.900000000000e+03 1.062639821029e+00 3.100000000000e+03 1.733780760626e+00 + 3 EWK_RAP 2.625000000000e+00 6.463838404000e+03 7.000000000000e+03 1.543000000000e+05 8.000000000000e+02 -4.576423183868e+02 -2.965925589027e-01 8.102620334429e+02 5.251212141561e-01 -1.155296667958e+01 -7.487340686701e-03 -1.818587804309e+03 -1.178605187498e+00 3.510991721698e+02 2.275432094425e-01 -1.095741310016e+02 -7.101369475154e-02 -5.948870207152e+01 -3.855392227578e-02 -3.995856993978e+01 -2.589667526882e-02 -3.092842563875e+01 -2.004434584494e-02 -5.642192277027e+01 -3.656637898267e-02 -2.098423901684e+02 -1.359963643346e-01 -1.971176054834e+02 -1.277495822964e-01 -8.766815367247e+01 -5.681669064969e-02 3.495502658944e+01 2.265393816555e-02 1.364098039849e+01 8.840557614055e-03 1.040630935059e+01 6.744205671155e-03 2.102782614228e-01 1.362788473252e-04 9.349020488857e-02 6.058989299324e-05 1.569549779935e-04 1.017206597495e-07 -1.512604916090e-04 -9.803013066040e-08 -4.488871631265e-04 -2.909184466147e-07 1.540468282218e-03 9.983592237315e-07 -6.142634454431e-03 -3.980968538192e-06 2.520891253966e-03 1.633759723892e-06 6.458823244352e-03 4.185886742937e-06 -5.292251395058e-03 -3.429845362967e-06 -1.655491247243e-03 -1.072904243190e-06 -3.891746499557e-03 -2.522194750199e-06 -1.159883451701e-02 -7.517067088144e-06 1.835668883996e-02 1.189675232661e-05 -2.111903605138e-02 -1.368699679286e-05 -4.574055894155e-03 -2.964391376640e-06 2.447135548580e-03 1.585959525975e-06 1.600000000000e+03 1.036941023979e+00 2.600000000000e+03 1.685029163966e+00 + 4 EWK_RAP 2.875000000000e+00 6.463838404000e+03 7.000000000000e+03 1.228000000000e+05 7.000000000000e+02 4.394366915739e+02 3.578474687084e-01 4.762649345625e+01 3.878378945948e-02 3.951470343649e+02 3.217809726099e-01 -3.201665755766e+02 -2.607219670819e-01 -1.354648278639e+03 -1.103133777394e+00 -3.322987152617e+02 -2.706015596594e-01 -1.177891074280e+02 -9.591946858957e-02 -8.324115448246e+01 -6.778595641894e-02 -7.473780927882e+01 -6.086140820751e-02 2.411626008280e+01 1.963864827589e-02 1.679651742934e+02 1.367794578937e-01 -3.004888602396e+02 -2.446977689248e-01 1.067870758964e+02 8.696015952472e-02 -5.871616154918e+01 -4.781446380226e-02 1.251659817384e+01 1.019266952267e-02 7.086159625744e-01 5.770488294580e-04 3.062737334365e-01 2.494085777170e-04 1.196466526096e-01 9.743212753221e-05 2.979868643353e-04 2.426603129766e-07 6.937506320305e-05 5.649435114255e-08 4.997181998828e-04 4.069366448557e-07 2.610989408866e-03 2.126212873669e-06 -3.638286984318e-03 -2.962774417197e-06 1.370512003667e-03 1.116052120250e-06 -1.199940979315e-02 -9.771506346217e-06 -5.999996447727e-02 -4.885990592612e-05 1.466067985028e-02 1.193866437320e-05 -2.676307209742e-03 -2.179403265262e-06 -1.488632204947e-02 -1.212241209240e-05 6.579970173707e-03 5.358281900413e-06 3.430374709980e-02 2.793464747540e-05 1.391503242380e-02 1.133145962850e-05 1.918461581069e-02 1.562265131164e-05 1.300000000000e+03 1.058631921824e+00 2.100000000000e+03 1.710097719870e+00 + 5 EWK_RAP 3.125000000000e+00 6.463838404000e+03 7.000000000000e+03 9.430000000000e+04 6.000000000000e+02 -2.480143699037e+02 -2.630056944896e-01 4.044526266707e+02 4.288999222383e-01 -3.251636827425e+01 -3.448183274046e-02 -1.673874232398e+02 -1.775052208269e-01 -2.565823885633e+02 -2.720916103535e-01 1.079538553819e+03 1.144791679554e+00 -1.676189474192e+02 -1.777507395750e-01 -6.130136217664e+01 -6.500674674087e-02 -4.428445403691e+01 -4.696124500202e-02 -8.248578437702e+01 -8.747166954085e-02 -9.474052086833e+01 -1.004671483227e-01 9.929809238617e+00 1.053002040150e-02 3.714846574035e+02 3.939391913080e-01 1.299800239433e+02 1.378367168010e-01 1.810371837383e+00 1.919800463821e-03 7.471091210112e-01 7.922684210087e-04 4.214025328085e-01 4.468743720133e-04 1.864689192430e-01 1.977401052418e-04 2.585137555144e-04 2.741397195274e-07 -2.686626754804e-04 -2.849020948891e-07 2.282232695397e-03 2.420183134037e-06 4.871900744122e-03 5.166384670331e-06 6.226501355942e-03 6.602864640448e-06 -1.038314900457e-02 -1.101076246508e-05 -1.807841434328e-02 -1.917117109574e-05 2.014717840695e-02 2.136498240397e-05 2.079639175233e-02 2.205343770130e-05 3.580261145077e-02 3.796671415776e-05 -5.079231305694e-02 -5.386247407947e-05 2.245470721011e-02 2.381199067880e-05 3.034541572969e-02 3.217965612904e-05 6.074075639357e-02 6.441225492425e-05 -3.312993954191e-02 -3.513249156088e-05 1.000000000000e+03 1.060445387063e+00 1.600000000000e+03 1.696712619300e+00 + 6 EWK_RAP 3.375000000000e+00 6.463838404000e+03 7.000000000000e+03 6.160000000000e+04 5.000000000000e+02 -2.949456461177e+02 -4.788078670742e-01 2.955199869993e+02 4.797402386352e-01 -1.025970883509e+02 -1.665537148554e-01 -5.426177319059e+01 -8.808729414057e-02 -9.647469105130e+01 -1.566147582002e-01 7.128275501730e+01 1.157187581450e-01 7.938038167913e+01 1.288642559726e-01 1.353508088116e+02 2.197253389799e-01 5.539962584105e+02 8.993445753418e-01 -2.053779905758e+02 -3.334058288567e-01 -1.560822901884e+02 -2.533803412150e-01 4.951882509019e+01 8.038770306849e-02 1.176773581820e+02 1.910346723734e-01 -4.305461136826e+02 -6.989384962379e-01 8.982562355331e+01 1.458208174567e-01 1.532178156461e+00 2.487302202048e-03 3.070352733829e-01 4.984338853619e-04 1.140221544526e-01 1.851009000854e-04 1.040765834683e-04 1.689554926433e-07 2.739372589337e-04 4.447033424248e-07 1.859797550420e-04 3.019151867564e-07 4.813306838651e-03 7.813809803005e-06 -9.659092259346e-03 -1.568034457686e-05 -1.474431202718e-02 -2.393557147269e-05 -5.971694635339e-02 -9.694309472952e-05 5.667357161732e-02 9.200255132682e-05 2.756891290459e-02 4.475472874122e-05 6.756965202421e-02 1.096909935458e-04 -1.243421472897e-02 -2.018541352106e-05 4.258458900406e-02 6.913082630529e-05 1.286711853948e-01 2.088817944721e-04 4.053603386903e-02 6.580524978739e-05 -3.886516500356e-02 -6.309280033045e-05 7.000000000000e+02 1.136363636364e+00 1.100000000000e+03 1.785714285714e+00 + 7 EWK_RAP 3.750000000000e+00 6.463838404000e+03 7.000000000000e+03 6.000000000000e+04 5.000000000000e+02 -5.215832457246e+01 -8.693054095410e-02 1.451742117800e+02 2.419570196333e-01 2.506909095215e+01 4.178181825358e-02 -7.241121212245e+01 -1.206853535374e-01 -7.203684627811e+01 -1.200614104635e-01 7.437215030877e+01 1.239535838480e-01 2.533756341324e+02 4.222927235540e-01 3.510314038080e+02 5.850523396801e-01 -1.237208583937e+02 -2.062014306562e-01 -9.359255615563e+01 -1.559875935927e-01 -2.939175309319e+01 -4.898625515532e-02 -3.320333897179e+01 -5.533889828632e-02 2.010470175527e+01 3.350783625879e-02 -9.692472202516e+01 -1.615412033753e-01 -4.757595604893e+02 -7.929326008154e-01 -3.262631985572e+00 -5.437719975953e-03 2.864055062154e-01 4.773425103591e-04 1.666453127670e-01 2.777421879450e-04 -1.127344020794e-03 -1.878906701323e-06 2.392934653373e-04 3.988224422289e-07 3.928978181555e-03 6.548296969259e-06 9.329597580319e-03 1.554932930053e-05 3.175092411472e-03 5.291820685787e-06 -3.148695227275e-02 -5.247825378792e-05 -4.929865689624e-02 -8.216442816041e-05 4.485024408868e-02 7.475040681447e-05 1.198041017363e-02 1.996735028938e-05 1.547081675185e-01 2.578469458642e-04 -2.694235501937e-02 -4.490392503228e-05 8.426679128530e-02 1.404446521422e-04 1.394803788448e-01 2.324672980747e-04 7.062926208545e-02 1.177154368091e-04 3.443581374865e-02 5.739302291441e-05 6.000000000000e+02 1.000000000000e+00 1.000000000000e+03 1.666666666667e+00 + 8 EWK_RAP 4.250000000000e+00 6.463838404000e+03 7.000000000000e+03 1.430000000000e+04 4.000000000000e+02 -4.472911199275e+01 -3.127909929563e-01 7.035727027289e+01 4.920088830272e-01 -8.053619187950e+00 -5.631901530035e-02 -2.409900730299e+01 -1.685245265944e-01 -1.134947405395e+01 -7.936695142623e-02 1.941148834440e+01 1.357446737371e-01 5.222811490581e+01 3.652315727679e-01 -9.673620787604e+00 -6.764769781541e-02 -8.719120366096e+00 -6.097286969298e-02 -2.256659133422e+01 -1.578083310085e-01 -1.113933997221e+01 -7.789748232313e-02 -1.812566959417e+01 -1.267529342249e-01 -1.501157291554e+01 -1.049760343744e-01 2.825573537002e+00 1.975925550351e-02 1.216397883308e+01 8.506278904254e-02 -3.842619544658e+02 -2.687146534726e+00 -1.439278870582e-01 -1.006488720687e-03 -1.913452738465e-02 -1.338078838087e-04 -2.974835675338e-03 -2.080304668068e-05 1.825311137101e-03 1.276441354616e-05 1.159388107007e-02 8.107609139906e-05 4.869941879566e-02 3.405553761934e-04 1.507043127186e-02 1.053876312717e-04 -8.632193188214e-02 -6.036498733016e-04 -1.147278406427e-01 -8.022925919067e-04 1.600804922779e-02 1.119444001943e-04 -3.154824090745e-03 -2.206170692829e-05 3.944091393484e-02 2.758105869569e-04 -3.331582531284e-03 -2.329777993905e-05 1.654679477204e-01 1.157118515527e-03 1.960328803927e-01 1.370859303446e-03 8.161126080518e-02 5.707081175188e-04 -7.681146337356e-02 -5.371431005144e-04 2.000000000000e+02 1.398601398601e+00 2.000000000000e+02 1.398601398601e+00 + 9 EWK_RAP 2.125000000000e+00 6.463838404000e+03 7.000000000000e+03 1.111000000000e+05 9.000000000000e+02 1.697271027136e+02 1.527696694092e-01 1.695620741811e+03 1.526211288758e+00 -9.226299247770e+02 -8.304499772970e-01 1.147016070505e+02 1.032417705225e-01 -2.363814175180e+01 -2.127645522215e-02 1.046214570985e+02 9.416872826148e-02 1.764558657093e+02 1.588261617545e-01 1.615250550357e+02 1.453870882410e-01 2.460318289767e+02 2.214507911581e-01 6.992073391140e+02 6.293495401566e-01 1.069522264237e+02 9.626663044437e-02 -1.085553578188e+02 -9.770959299620e-02 -3.192076522214e+00 -2.873156185611e-03 1.643157516042e+01 1.478989663404e-02 -1.702094217597e+00 -1.532037999637e-03 1.360465577589e-01 1.224541473978e-04 6.432655935964e-01 5.789969339302e-04 3.846019076528e-03 3.461763345209e-06 -1.981221480453e-04 -1.783277660173e-07 -1.197906751754e-04 -1.078223898968e-07 1.498562221319e-03 1.348840883276e-06 2.948478342616e-03 2.653895897944e-06 4.609159724683e-02 4.148658618076e-05 9.436141795372e-03 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-1.621861591122e-02 -1.687681156214e-05 -6.016930657788e-02 -6.261114108000e-05 -2.616854501701e-02 -2.723053591780e-05 -3.533295596205e-04 -3.676686364417e-07 -6.470390123464e-02 -6.732976195072e-05 -1.656188673225e-02 -1.723401324896e-05 7.049892336858e-02 7.335996188197e-05 -6.240251334834e-02 -6.493497746966e-05 -3.712912607412e-03 -3.863592723633e-06 9.000000000000e+02 9.365244536941e-01 1.600000000000e+03 1.664932362123e+00 + 12 EWK_RAP 2.875000000000e+00 6.463838404000e+03 7.000000000000e+03 8.840000000000e+04 7.000000000000e+02 -7.255903980378e+02 -8.208036176898e-01 6.741142052359e+02 7.625726303574e-01 -3.134170975631e+02 -3.545442280125e-01 -1.582176567420e+02 -1.789792497081e-01 -8.907824338260e+02 -1.007672436455e+00 -1.177926661394e+02 -1.332496223297e-01 -5.098346380045e+00 -5.767360158422e-03 7.079723382443e+00 8.008736857967e-03 2.214184613364e+01 2.504733725525e-02 3.808583541311e-01 4.308352422297e-04 -2.626596996926e+02 -2.971263571184e-01 4.731748678206e+02 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8.060000000000e+04 6.000000000000e+02 7.581798133410e+02 9.406697435992e-01 -2.611823656853e+02 -3.240476001058e-01 5.272236305984e+02 6.541236111642e-01 -1.748439666286e+02 -2.169279982985e-01 -1.773662841460e+02 -2.200574244988e-01 8.378081595822e+02 1.039464217844e+00 -1.385014661035e+02 -1.718380472749e-01 -6.669263216258e+01 -8.274520119427e-02 -4.259250149667e+01 -5.284429466088e-02 1.228735857163e+02 1.524486175140e-01 1.110637954599e+02 1.377962722828e-01 -1.546693595600e+01 -1.918974684367e-02 -4.443253250738e+02 -5.512721154762e-01 -1.564122520595e+02 -1.940598660788e-01 3.008432543382e+00 3.732546579879e-03 3.832444124288e+00 4.754893454451e-03 3.126363025333e-01 3.878862314309e-04 1.802198625226e-01 2.235978443208e-04 5.335950985568e-05 6.620286582591e-08 3.782102293862e-04 4.692434607769e-07 -2.000780693369e-03 -2.482358180359e-06 3.751416681898e-03 4.654363128906e-06 -1.080812786758e-02 -1.340958792504e-05 -6.723009037401e-03 -8.341202279653e-06 -2.139251565042e-02 -2.654158269283e-05 -1.685059039254e-02 -2.090643969298e-05 3.237234334788e-02 4.016419770208e-05 4.935692375712e-02 6.123687811058e-05 1.898158734498e-02 2.355035650742e-05 3.767798406520e-02 4.674687849281e-05 5.157280203480e-02 6.398610674292e-05 3.183112541268e-02 3.949271143013e-05 3.697637550457e-02 4.587639640766e-05 7.000000000000e+02 8.684863523573e-01 1.400000000000e+03 1.736972704715e+00 + 14 EWK_RAP 3.375000000000e+00 6.463838404000e+03 7.000000000000e+03 6.860000000000e+04 6.000000000000e+02 9.326502014910e+02 1.359548398675e+00 -4.444005886406e+02 -6.478142691554e-01 6.141380061287e+02 8.952449068931e-01 -1.310228683014e+02 -1.909954348417e-01 -7.257197028127e+01 -1.057900441418e-01 2.150109182940e+01 3.134269945976e-02 1.022650746649e+02 1.490744528643e-01 1.690826785571e+02 2.464762078092e-01 7.987202483881e+02 1.164315230886e+00 -1.299109392438e+02 -1.893745470026e-01 3.800772180443e+01 5.540484228051e-02 -4.548627883016e+01 -6.630652890694e-02 -6.010745132287e+01 -8.762019143275e-02 2.800551773826e+02 4.082436988084e-01 -5.633331797816e+01 -8.211853932676e-02 -1.167157863049e+00 -1.701396301821e-03 1.948884804545e-01 2.840939948316e-04 1.265316707685e-01 1.844484996625e-04 -2.988588455624e-04 -4.356542938228e-07 -2.795114872830e-04 -4.074511476429e-07 2.377810315069e-03 3.466195794561e-06 1.342362017431e-03 1.956795943776e-06 4.404106214022e-03 6.419979903823e-06 -4.275478568418e-03 -6.232476047257e-06 1.771193560292e-02 2.581914810922e-05 2.444613714157e-02 3.563576842794e-05 1.219593907555e-02 1.777833684483e-05 5.823941875838e-02 8.489711189268e-05 -1.434006881667e-02 -2.090389040330e-05 8.587811147052e-03 1.251867514147e-05 -1.290248760599e-02 -1.880829097084e-05 3.469714922785e-02 5.057893473447e-05 3.725089162310e-02 5.430159128731e-05 6.000000000000e+02 8.746355685131e-01 1.200000000000e+03 1.749271137026e+00 + 15 EWK_RAP 3.750000000000e+00 6.463838404000e+03 7.000000000000e+03 9.590000000000e+04 7.000000000000e+02 3.968000721375e+02 4.137644130735e-01 -5.351658354307e+01 -5.580457095210e-02 3.314558511117e+02 3.456265392198e-01 -1.577062525130e+02 -1.644486470417e-01 -1.251738766502e+02 -1.305254188219e-01 1.230127851305e+02 1.282719344427e-01 5.995143389946e+02 6.251452961362e-01 7.843730567738e+02 8.179072541959e-01 -2.979314190589e+02 -3.106688415629e-01 -7.712695782982e+01 -8.042435644402e-02 1.888754466578e-01 1.969504136160e-04 7.916586562811e+00 8.255043339740e-03 2.316270009449e+00 2.415297194421e-03 3.718866788404e+01 3.877859007720e-02 2.078504538556e+02 2.167366567838e-01 1.129661792542e+01 1.177958073558e-02 1.320522949673e-01 1.376979092464e-04 1.022973973374e-01 1.066709044186e-04 -5.654626102173e-04 -5.896377583080e-07 2.734327577674e-04 2.851227922496e-07 1.798648722034e-03 1.875546112653e-06 4.752701240113e-03 4.955892846833e-06 -7.255705247004e-04 -7.565907452559e-07 -1.550315094142e-02 -1.616595510054e-05 -2.311414294422e-02 -2.410233883651e-05 1.436118654730e-02 1.497516845391e-05 3.795445403138e-03 3.957711577829e-06 1.130500988979e-01 1.178833148049e-04 -1.351761513442e-02 -1.409553194413e-05 3.340450560300e-02 3.483264400730e-05 1.163811640522e-01 1.213567925466e-04 7.161470115145e-02 7.467643498587e-05 -2.270027997254e-02 -2.367078203602e-05 9.000000000000e+02 9.384775808133e-01 1.600000000000e+03 1.668404588113e+00 + 16 EWK_RAP 4.250000000000e+00 6.463838404000e+03 7.000000000000e+03 4.380000000000e+04 8.000000000000e+02 1.180403910891e+02 2.694986097924e-01 4.489255154510e+01 1.024944099203e-01 1.140768673104e+02 2.604494687451e-01 -8.872082538814e+01 -2.025589620734e-01 -7.301875251111e+01 -1.667094806190e-01 1.134345900900e+02 2.589830823974e-01 9.484935405413e+02 2.165510366533e+00 -6.955046935341e+02 -1.587910259210e+00 7.178292123392e-01 1.638879480226e-03 -3.413590098555e+01 -7.793584699897e-02 7.243064790250e-01 1.653667760331e-03 3.935320666192e+00 8.984750379434e-03 1.133299314770e+01 2.587441357923e-02 -4.871279725857e+00 -1.112164320972e-02 -4.361282518296e+00 -9.957266023507e-03 1.572501182602e+01 3.590185348407e-02 1.240026394395e-01 2.831110489486e-04 5.713029250391e-02 1.304344577715e-04 -1.436770291157e-03 -3.280297468396e-06 5.777315326641e-04 1.319021764073e-06 4.904587524079e-03 1.119768841114e-05 1.852438115586e-02 4.229310766177e-05 1.614126719025e-03 3.685220819693e-06 -3.116585543023e-02 -7.115492107358e-05 -5.681395516433e-02 -1.297122264026e-04 -6.927373076339e-03 -1.581592026562e-05 -8.883483901942e-03 -2.028192671676e-05 2.305038082044e-02 5.262644022931e-05 -9.608860269080e-03 -2.193803714402e-05 8.633516535934e-02 1.971122496789e-04 8.323499885858e-02 1.900342439694e-04 2.010964580188e-02 4.591243333762e-05 -2.714092597291e-02 -6.196558441303e-05 4.000000000000e+02 9.132420091324e-01 7.000000000000e+02 1.598173515982e+00 diff --git a/nnpdfcpp/data/commondata/DATA_LHCBWMU8TEV.dat b/nnpdfcpp/data/commondata/DATA_LHCBWMU8TEV.dat new file mode 100644 index 0000000000..edbe564e50 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_LHCBWMU8TEV.dat @@ -0,0 +1,17 @@ +LHCBWMU8TEV 36 16 + 1 EWK_RAP 2.125000000000e+00 6.463838404000e+03 8.000000000000e+03 2.365000000000e+05 1.200000000000e+03 3.038579301980e+03 1.284811544177e+00 7.681516197290e+02 3.247998392089e-01 4.851095075129e+02 2.051202991598e-01 -5.308972426746e+01 -2.244808637102e-02 7.850087868618e+00 3.319276054384e-03 -8.807520308797e+01 -3.724110067145e-02 -1.372555607165e+02 -5.803617789281e-02 2.835081811025e+02 1.198766093457e-01 2.394261818068e+02 1.012372861762e-01 1.149282210891e+02 4.859544232099e-02 8.422450321819e+00 3.561289776667e-03 3.198627693876e+01 1.352485282823e-02 1.507174843915e+00 6.372832320995e-04 -6.896281410681e+00 -2.915975226504e-03 7.595533001147e+00 3.211641860950e-03 7.633120097777e+00 3.227534925064e-03 1.019554927280e+00 4.311014491672e-04 3.415602574189e-03 1.444229418262e-06 -1.133910367561e-03 -4.794547008716e-07 -7.284609808370e-07 -3.080173280495e-10 1.677835558232e-05 7.094442106689e-09 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2.606014116692e-06 2.100000000000e+03 1.007677543186e+00 2.400000000000e+03 1.151631477927e+00 + 3 EWK_RAP 2.625000000000e+00 6.463838404000e+03 8.000000000000e+03 1.820000000000e+05 8.000000000000e+02 5.391116598567e+02 2.962151977235e-01 -1.082196953898e+03 -5.946137109330e-01 -1.392653826342e+02 -7.651944100780e-02 -2.590007882802e+02 -1.423081254287e-01 -1.235363886048e+03 -6.787713659604e-01 -1.478992484251e+02 -8.126332331052e-02 3.097196513909e+01 1.701756326323e-02 6.612783421119e+01 3.633397484131e-02 -7.927645225016e+01 -4.355849024734e-02 -6.108339536541e+00 -3.356230514583e-03 2.988256052266e+02 1.641898929816e-01 -1.603305281460e+02 -8.809369678353e-02 1.237444832951e+02 6.799147433797e-02 3.243971184140e+01 1.782401749528e-02 1.181103744601e+01 6.489581014290e-03 2.392189941106e+01 1.314390077531e-02 5.767811158596e-01 3.169127010218e-04 -1.379628806295e-04 -7.580378056568e-08 4.789353762500e-04 2.631513056319e-07 2.877751006089e-06 1.581181871478e-09 1.774625906249e-05 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-3.408814568530e-05 -2.144640092330e-02 -1.398982447704e-05 1.500000000000e+03 9.784735812133e-01 1.800000000000e+03 1.174168297456e+00 + 5 EWK_RAP 3.125000000000e+00 6.463838404000e+03 8.000000000000e+03 1.195000000000e+05 6.000000000000e+02 2.748755548246e+02 2.300213847904e-01 -7.128587225878e+02 -5.965344958894e-01 -9.424364874673e+00 -7.886497803073e-03 3.108102674355e+02 2.600922740046e-01 1.626361173239e+02 1.360971693087e-01 7.287752580650e+02 6.098537724393e-01 7.645444548335e+01 6.397861546724e-02 5.080244085137e+02 4.251250280450e-01 -1.582720758281e+02 -1.324452517390e-01 -4.722082110865e+01 -3.951533147167e-02 3.417774149118e+01 2.860062049471e-02 1.315272958056e+01 1.100646826825e-02 -1.177021162615e+02 -9.849549477949e-02 3.771740405636e+02 3.156268121871e-01 -4.851723655536e+01 -4.060019795428e-02 -3.156153128981e+01 -2.641132325508e-02 9.822152491275e-01 8.219374469686e-04 6.347847483483e-03 5.312006262329e-06 -1.815465250726e-03 -1.519217783034e-06 2.461999837111e-06 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-2.085073751547e-05 3.433469192100e-02 4.068091459835e-05 -9.203113870856e-03 -1.090416335409e-05 8.000000000000e+02 9.478672985782e-01 1.000000000000e+03 1.184834123223e+00 + 7 EWK_RAP 3.750000000000e+00 6.463838404000e+03 8.000000000000e+03 8.640000000000e+04 5.000000000000e+02 1.882022891019e+02 2.178267234976e-01 -7.777968807962e+02 -9.002278712918e-01 8.352314957183e+01 9.667031200443e-02 2.196902172849e+02 2.542710848204e-01 1.184340249288e+02 1.370764177416e-01 2.527137844344e+02 2.924928060583e-01 -2.943555458082e+02 -3.406892891298e-01 -3.709454328088e+02 -4.293349916769e-01 2.091045510062e+02 2.420191562571e-01 1.304239378292e+02 1.509536317467e-01 3.656282260301e+02 4.231808171645e-01 4.806203850588e+02 5.562735938181e-01 2.007994775874e+01 2.324068027632e-02 -6.706685990861e+01 -7.762368044978e-02 -6.532932344673e+01 -7.561264287817e-02 -8.747120757017e+01 -1.012398235766e-01 -9.826105456668e-02 -1.137280724151e-04 2.061594320153e-02 2.386104537214e-05 8.413697309130e-03 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-3.478190276644e-05 -1.345409740231e-01 -5.849607566224e-04 8.854643213536e-02 3.849844875451e-04 -3.573913246434e-02 -1.553875324537e-04 2.000000000000e+02 8.695652173913e-01 3.000000000000e+02 1.304347826087e+00 + 9 EWK_RAP 2.125000000000e+00 6.463838404000e+03 8.000000000000e+03 1.340000000000e+05 9.000000000000e+02 1.418566028696e+03 1.058631364699e+00 -3.008361897603e+02 -2.245046192241e-01 3.721785778299e+02 2.777452073357e-01 -1.108522907735e+02 -8.272559012947e-02 2.130729456719e+02 1.590096609492e-01 1.920356083581e+02 1.433101554911e-01 3.150880721533e+02 2.351403523532e-01 -6.883892318077e+02 -5.137233073192e-01 -5.379263076607e+02 -4.014375430304e-01 -1.882713964977e+02 -1.405010421625e-01 -4.637284914904e+01 -3.460660384257e-02 -5.869340052789e+01 -4.380104517007e-02 -1.450487641934e+01 -1.082453464130e-02 1.474470779206e+01 1.100351327766e-02 -3.880705575242e+00 -2.896048936747e-03 -8.664528816324e+00 -6.466066280839e-03 8.337970308503e-01 6.222365901868e-04 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2.140499465966e-05 2.770793057262e-02 2.312848962656e-05 -3.939296565434e-02 -3.288227517057e-05 8.744923901338e-03 7.299602588763e-06 5.484652229037e-03 4.578173813887e-06 1.000000000000e+03 8.347245409015e-01 1.400000000000e+03 1.168614357262e+00 + 11 EWK_RAP 2.625000000000e+00 6.463838404000e+03 8.000000000000e+03 1.106000000000e+05 6.000000000000e+02 2.396134926211e+02 2.166487275055e-01 -6.788206626587e+02 -6.137619011381e-01 -4.304893366922e+01 -3.892308650020e-02 5.583800780749e+01 5.048644467224e-02 -6.344991542700e+02 -5.736882045841e-01 -2.594755426812e+01 -2.346071814478e-02 -4.142790442248e+01 -3.745741810351e-02 -5.405330881160e+01 -4.887279277721e-02 1.636237924361e+01 1.479419461447e-02 1.293827349946e+02 1.169825813695e-01 -5.927873743873e+02 -5.359741178908e-01 2.563760680903e+02 2.318047631920e-01 -2.655698980460e+02 -2.401174485045e-01 -4.329483884631e+01 -3.914542391167e-02 1.621153875102e+00 1.465781080562e-03 -4.876481505905e+01 -4.409115285629e-02 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-4.679293401071e-05 -6.819233827444e-02 -6.659408034613e-05 -4.485150499449e-02 -4.380029784618e-05 2.893751825512e-05 2.825929517102e-08 2.477697819845e-03 2.419626777193e-06 1.624354351429e-02 1.586283546318e-05 9.000000000000e+02 8.789062500000e-01 1.200000000000e+03 1.171875000000e+00 + 13 EWK_RAP 3.125000000000e+00 6.463838404000e+03 8.000000000000e+03 9.250000000000e+04 6.000000000000e+02 2.210340648033e+02 2.389557457333e-01 -5.987026972314e+02 -6.472461591690e-01 -7.879832997777e+00 -8.518738375975e-03 2.184763315198e+02 2.361906286700e-01 1.197980553229e+02 1.295114111599e-01 5.400535716311e+02 5.838416990606e-01 1.433569796840e+01 1.549805185773e-02 3.703375464348e+02 4.003649150646e-01 -1.565632398287e+02 -1.692575565716e-01 -4.885089017217e+01 -5.281177315911e-02 -7.225805431862e+01 -7.811681547959e-02 -6.023608515279e+01 -6.512009205707e-02 1.662409610003e+02 1.797199578381e-01 -4.960419192105e+02 -5.362615342816e-01 4.290701380970e+01 4.638596087535e-02 1.603726295711e+01 1.733758157526e-02 4.785205369484e-01 5.173194994037e-04 4.502053808522e-03 4.867085198403e-06 5.305379878289e-03 5.735545814366e-06 4.710614020287e-06 5.092555697607e-09 9.205968158778e-05 9.952398009490e-08 1.289444818082e-03 1.393994397927e-06 -9.383386501247e-03 -1.014420162297e-05 -1.241067869379e-01 -1.341694993923e-04 3.652483327628e-02 3.948630624462e-05 2.612495440402e-02 2.824319395030e-05 2.700475754578e-02 2.919433248192e-05 -2.217773972682e-02 -2.397593483981e-05 -4.456292446838e-02 -4.817613456041e-05 -2.875750635452e-02 -3.108919605894e-05 -5.203761053451e-02 -5.625687625352e-05 5.860786606371e-02 6.335985520401e-05 -5.914759281177e-02 -6.394334358030e-05 3.348043001920e-03 3.619505948022e-06 8.000000000000e+02 8.648648648649e-01 1.100000000000e+03 1.189189189189e+00 + 14 EWK_RAP 3.375000000000e+00 6.463838404000e+03 8.000000000000e+03 7.990000000000e+04 5.000000000000e+02 1.759523483065e+02 2.202157050144e-01 -4.582971920159e+02 -5.735884756144e-01 2.522158009032e+01 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-1.799505617142e-01 -2.252197268012e-04 2.169242324782e-02 2.714946589214e-05 7.009667327654e-03 8.773050472659e-06 3.717354123810e-02 4.652508290125e-05 -1.204396633561e-01 -1.507380016973e-04 1.543371412091e-02 1.931628801115e-05 7.000000000000e+02 8.760951188986e-01 9.000000000000e+02 1.126408010013e+00 + 15 EWK_RAP 3.750000000000e+00 6.463838404000e+03 8.000000000000e+03 1.193000000000e+05 6.000000000000e+02 1.831471323643e+02 1.535181327446e-01 5.673613770804e+02 4.755753370330e-01 -4.685631214610e+02 -3.927603700427e-01 9.425696139986e+02 7.900834987415e-01 -3.097732932894e+02 -2.596590890943e-01 1.936845903929e+02 1.623508720812e-01 -7.112139889473e+02 -5.961559002073e-01 -2.815128856875e+02 -2.359705663768e-01 -1.082139143905e+02 -9.070738842459e-02 -7.790499127010e+01 -6.530175295063e-02 -5.804127429123e+01 -4.865152916281e-02 -1.985639555860e+02 -1.664408680520e-01 2.354786254953e+01 1.973835922006e-02 4.382890699206e+01 3.673839647281e-02 2.050657414286e+01 1.718908142737e-02 6.743375805284e+01 5.652452477187e-02 1.419006487505e+00 1.189443828588e-03 1.435099886471e-02 1.202933685223e-05 5.908187636419e-03 4.952378572019e-06 3.892991343643e-06 3.263194755778e-09 1.779767176782e-04 1.491841724042e-07 1.774422933193e-03 1.487362056322e-06 -2.762243269223e-02 -2.315375749558e-05 -1.875036051463e-01 -1.571698282869e-04 5.462605794530e-02 4.578881638332e-05 -1.028457841930e-02 -8.620769840149e-06 -4.081526804414e-02 -3.421229509148e-05 -3.921710742970e-02 -3.287268015901e-05 -1.371256172369e-01 -1.149418417744e-04 -1.775950055693e-02 -1.488642125476e-05 -6.695235138006e-02 -5.612099864213e-05 -3.746692428422e-03 -3.140563644947e-06 -6.196728952751e-02 -5.194240530386e-05 -1.928733465502e-02 -1.616708688602e-05 1.000000000000e+03 8.382229673093e-01 1.400000000000e+03 1.173512154233e+00 + 16 EWK_RAP 4.250000000000e+00 6.463838404000e+03 8.000000000000e+03 6.000000000000e+04 7.000000000000e+02 1.085711870211e+02 1.809519783684e-01 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3.920811234591e-05 -4.847116685695e-02 -8.078527809492e-05 -3.684786732394e-02 -6.141311220657e-05 7.012670525561e-03 1.168778420927e-05 -1.275766566595e-02 -2.126277610992e-05 2.273651715641e-02 3.789419526068e-05 -4.112496966631e-02 -6.854161611052e-05 1.846240957404e-02 3.077068262340e-05 5.000000000000e+02 8.333333333333e-01 7.000000000000e+02 1.166666666667e+00 diff --git a/nnpdfcpp/data/commondata/DATA_LHCBZMU7TEV.dat b/nnpdfcpp/data/commondata/DATA_LHCBZMU7TEV.dat new file mode 100644 index 0000000000..d7a09aee76 --- /dev/null +++ b/nnpdfcpp/data/commondata/DATA_LHCBZMU7TEV.dat @@ -0,0 +1,18 @@ +LHCBZMU7TEV 35 17 + 1 EWK_RAP 2.062500000000e+00 8.315178393760e+03 7.000000000000e+03 9.690000000000e+02 3.900000000000e+01 5.144425552739e+00 5.309004698389e-01 6.572983562411e+00 6.783264770290e-01 -1.901231466028e+00 -1.962055176499e-01 4.518921666484e-01 4.663489851893e-02 5.594228802133e-02 5.773197938218e-03 3.604304421115e-01 3.719612405692e-02 2.843587009219e-01 2.934558317048e-02 2.158969946147e-01 2.228039160111e-02 3.940396089457e-01 4.066456232670e-02 9.963074820243e-01 1.028181096000e-01 2.729184708433e-01 2.816496087134e-02 -1.725003121682e-01 -1.780188980064e-02 2.412067740461e-01 2.489233994283e-02 1.656016888830e-01 1.708995757307e-02 -1.104936410749e-01 -1.140285253611e-02 -7.783131982623e-02 -8.032127949043e-03 -5.551997533968e+00 -5.729615618130e-01 -1.116984809926e-01 -1.152719102091e-02 -1.658810316311e-02 -1.711878551405e-03 3.904571434612e-03 4.029485484636e-04 -2.895258007054e-03 -2.987882360221e-04 6.694374851694e-02 6.908539578632e-03 -3.000232601652e+01 -3.096215275182e+00 -1.865445346433e+00 -1.925124196525e-01 3.731119418276e-01 3.850484435785e-02 5.424011750467e-01 5.597535346199e-02 4.732682414679e-01 4.884089179235e-02 2.268287138718e-01 2.340853600328e-02 -3.378319602398e+00 -3.486397938491e-01 1.527578158907e-01 1.576448048407e-02 -5.151443949292e-01 -5.316247625689e-02 1.411560590879e+00 1.456718876036e-01 1.757247150542e-01 1.813464551643e-02 1.200000000000e+01 1.238390092879e+00 1.700000000000e+01 1.754385964912e+00 + 2 EWK_RAP 2.187500000000e+00 8.315178393760e+03 7.000000000000e+03 2.840000000000e+03 6.300000000000e+01 7.297911572460e+00 2.569687173402e-01 1.300086912702e+01 4.577770819374e-01 1.042212440323e+00 3.669762113815e-02 1.735444785864e+00 6.110721076985e-02 4.746267757321e-01 1.671221041310e-02 -9.573237207650e-03 -3.370858171708e-04 -1.221800703845e-01 -4.302115154385e-03 -2.543064571411e-02 -8.954452716237e-04 5.399448945847e-01 1.901214417552e-02 2.136848343480e+00 7.524113885492e-02 8.943324783832e-04 3.149058022476e-05 -5.360948474574e-01 -1.887657913582e-02 -4.443972829327e-01 -1.564779165256e-02 -3.095894348283e-01 -1.090103643762e-02 1.081782410242e-01 3.809092993811e-03 2.420685014488e-01 8.523538783409e-03 -1.424152877077e+01 -5.014622806609e-01 -2.174093835900e-01 -7.655259985563e-03 -5.916154160698e-03 -2.083152873485e-04 1.292787122406e-03 4.552067332417e-05 3.415644742627e-02 1.202691810784e-03 9.648547898626e-02 3.397376020643e-03 2.607404943233e+00 9.181003321245e-02 -4.122313900568e-02 -1.451518979073e-03 -3.998287194514e-01 -1.407847603702e-02 1.651638915368e+00 5.815629983689e-02 1.963402041598e+00 6.913387470416e-02 1.539976122969e+00 5.422451137216e-02 -4.480936472069e+01 -1.577794532419e+00 1.184274038094e+00 4.169979007372e-02 -1.487023835470e+00 -5.235999420668e-02 6.129738977371e+00 2.158358794849e-01 1.011997356133e-01 3.563370972298e-03 3.600000000000e+01 1.267605633803e+00 4.900000000000e+01 1.725352112676e+00 + 3 EWK_RAP 2.312500000000e+00 8.315178393760e+03 7.000000000000e+03 4.428000000000e+03 7.700000000000e+01 7.699157805059e+00 1.738743858414e-01 1.771474186844e+01 4.000619211482e-01 5.635692680353e+00 1.272739991046e-01 5.396681593615e-01 1.218762780852e-02 1.198463911290e+00 2.706558065245e-02 -7.177770158017e-01 -1.620995970645e-02 -4.247910820243e-01 -9.593294535326e-03 -3.091214924304e-01 -6.981063514687e-03 4.698710408480e-01 1.061136045276e-02 2.605356064192e+00 5.883821283179e-02 4.066246734901e-01 9.183032373308e-03 6.905443288022e-01 1.559494870827e-02 1.065586789781e+00 2.406474231665e-02 -4.122883510640e-01 -9.310938370912e-03 -2.222918868605e-03 -5.020141979687e-05 2.111637371373e-01 4.768828751972e-03 -4.526100377543e+01 -1.022154556807e+00 5.958871381355e+01 1.345725244209e+00 -5.003254483911e-03 -1.129912936746e-04 1.014292746329e-03 2.290634025134e-05 -6.825287451754e-03 -1.541392830116e-04 -2.769392323918e-02 -6.254273540917e-04 6.852271010188e-01 1.547486678001e-02 -4.406223106422e-02 -9.950820023536e-04 -9.996058489347e-02 -2.257465783502e-03 -4.316724639363e+00 -9.748700630901e-02 -3.101131179780e+00 -7.003457948917e-02 -4.029424219011e-01 -9.099874026675e-03 3.231381514043e+00 7.297609561975e-02 -4.929906955107e-02 -1.113348454180e-03 2.520226453000e+00 5.691568322041e-02 -4.750051696163e+00 -1.072730735357e-01 4.819160671156e-02 1.088338001616e-03 5.500000000000e+01 1.242095754291e+00 7.600000000000e+01 1.716350496838e+00 + 4 EWK_RAP 2.437500000000e+00 8.315178393760e+03 7.000000000000e+03 5.823000000000e+03 8.800000000000e+01 5.838278576612e+00 1.002623832494e-01 1.439097310940e+01 2.471401873502e-01 5.566035904089e+00 9.558708404755e-02 -2.391986214651e+00 -4.107824514255e-02 -3.551921928468e-01 -6.099814405749e-03 -1.737443068735e-02 -2.983759348678e-04 -3.296774884858e-01 -5.661643285005e-03 -4.550736904528e-01 -7.815107169033e-03 6.014060984872e-01 1.032811434805e-02 2.095698384753e+00 3.599001175945e-02 8.035075574423e-01 1.379885896346e-02 1.005424051139e+00 1.726642711899e-02 7.408314091395e-01 1.272250402094e-02 -5.331301450047e-01 -9.155592392318e-03 -1.443900304104e-01 -2.479650187367e-03 4.857155411278e-01 8.341328200717e-03 -2.253807456375e+01 -3.870526286063e-01 -4.141360551526e+00 -7.112073761851e-02 -2.563392326853e-03 -4.402185002324e-05 -3.141318628169e-04 -5.394673927818e-06 1.038453870984e-02 1.783365740999e-04 -1.791503264108e-02 -3.076598427114e-04 9.487168334078e-01 1.629257828281e-02 -3.297155395541e-02 -5.662296746593e-04 -5.617137822940e-01 -9.646467152567e-03 3.677621647866e+00 6.315682033087e-02 3.466288787994e+00 5.952754229768e-02 -5.761160003537e-02 -9.893800452579e-04 7.426141561134e+00 1.275311963101e-01 2.739325236364e+00 4.704319485427e-02 -1.021972090034e+01 -1.755061119757e-01 5.074646898191e+01 8.714832385697e-01 4.471619432744e+00 7.679236532276e-02 7.300000000000e+01 1.253649321656e+00 1.000000000000e+02 1.717327837884e+00 + 5 EWK_RAP 2.562500000000e+00 8.315178393760e+03 7.000000000000e+03 6.877000000000e+03 9.500000000000e+01 5.996893917219e+00 8.720217997992e-02 1.484301497729e+01 2.158356111283e-01 5.269489895299e+00 7.662483488875e-02 -3.594970337236e+00 -5.227527028117e-02 -2.741187219997e+00 -3.986021840914e-02 1.246993725811e+00 1.813281555636e-02 -4.892499106280e-01 -7.114292723978e-03 -5.005765425755e-01 -7.278995820495e-03 7.965903106528e-01 1.158339843904e-02 2.585917906466e+00 3.760241248314e-02 1.796022833475e-01 2.611637099717e-03 8.595719321260e-01 1.249922832814e-02 5.897927826985e-01 8.576309185670e-03 1.133989273312e-01 1.648959245763e-03 -1.249790192327e-01 -1.817347960342e-03 5.870502811290e-01 8.536429855010e-03 -3.116440970132e+01 -4.531686738596e-01 -1.245548443193e+01 -1.811179937753e-01 -1.358414400409e-03 -1.975300858527e-05 -6.272593525656e-04 -9.121118984522e-06 9.692372147240e-04 1.409389580811e-05 5.617481071959e-02 8.168505266772e-04 6.423520184264e-01 9.340584825163e-03 -1.830675052535e-01 -2.662025668947e-03 -7.933777125670e-01 -1.153668332946e-02 2.196384251372e+01 3.193811620434e-01 4.451969291625e+01 6.473708436274e-01 2.246957677473e+01 3.267351574048e-01 3.752631298142e+00 5.456785368827e-02 1.081366240440e+00 1.572438912956e-02 1.125368066835e+01 1.636422955991e-01 -8.368031529335e+00 -1.216814240124e-01 -6.105904367428e-02 -8.878732539521e-04 8.600000000000e+01 1.250545295914e+00 1.180000000000e+02 1.715864475789e+00 + 6 EWK_RAP 2.687500000000e+00 8.315178393760e+03 7.000000000000e+03 7.669000000000e+03 1.000000000000e+02 5.949907003475e+00 7.758387017179e-02 1.413708255814e+01 1.843406253507e-01 5.277680065465e+00 6.881836048330e-02 -4.324795651635e+00 -5.639321491244e-02 -3.881762419546e+00 -5.061627877880e-02 3.050024424577e+00 3.977082311354e-02 -3.601690663545e-01 -4.696428039568e-03 1.059092272240e-01 1.381004397235e-03 1.365437369674e+00 1.780463384632e-02 2.029811904786e+00 2.646775205094e-02 5.096533176950e-01 6.645629387078e-03 2.471867974655e-01 3.223194646831e-03 4.315757865303e-01 5.627536660977e-03 -2.819219297349e-01 -3.676123741491e-03 -2.760050884899e-01 -3.598971032598e-03 6.540969041576e-01 8.529102935945e-03 -3.286048530825e+01 -4.284846173980e-01 -1.769822854830e+01 -2.307762230839e-01 -1.256896513772e-05 -1.638931430137e-07 -1.263697281219e-03 -1.647799297456e-05 2.834729980282e-02 3.696348911569e-04 1.264931117016e-01 1.649408158842e-03 5.245922592698e-01 6.840425860866e-03 -3.328874883915e-01 -4.340689638695e-03 -5.689330600890e-01 -7.418608163893e-03 2.922100600365e+01 3.810275916502e-01 -4.238654839833e+01 -5.526998096014e-01 1.709617534083e+01 2.229257444365e-01 2.252150437953e+00 2.936693751406e-02 1.602360084831e+00 2.089398989218e-02 8.884046829058e+00 1.158436149310e-01 -4.695198903532e+00 -6.122309171380e-02 -1.566783623812e+00 -2.043009028311e-02 9.600000000000e+01 1.251792932586e+00 1.320000000000e+02 1.721215282305e+00 + 7 EWK_RAP 2.812500000000e+00 8.315178393760e+03 7.000000000000e+03 8.306000000000e+03 1.040000000000e+02 5.835444039374e+00 7.025576738953e-02 1.308828552662e+01 1.575762765064e-01 5.492704668225e+00 6.612936032055e-02 -4.021133143361e+00 -4.841239036072e-02 -3.912196688307e+00 -4.710085105113e-02 3.486660073697e+00 4.197760743676e-02 2.117924831785e-01 2.549873382837e-03 8.777885622213e-01 1.056812620059e-02 1.878636012772e+00 2.261781859827e-02 9.027896072396e-01 1.086912602022e-02 -1.183085707080e+00 -1.424374797833e-02 1.140197903034e+00 1.372740071074e-02 4.738053765137e-01 5.704374867730e-03 -3.155168234501e-01 -3.798661491092e-03 -6.446447044376e-01 -7.761193166839e-03 5.576028659724e-01 6.713253864344e-03 -3.436525962411e+01 -4.137401832905e-01 -2.288666792955e+01 -2.755437988147e-01 4.724214571572e-04 5.687713185134e-06 -1.347815966577e-03 -1.622701621210e-05 2.537502237640e-02 3.055023161136e-04 1.123918942704e-01 1.353141033836e-03 4.070390546187e-01 4.900542434610e-03 -2.853761232434e-01 -3.435782846658e-03 -9.633357122381e-01 -1.159807021717e-02 -5.080381634416e+01 -6.116520147382e-01 -4.120146803768e+00 -4.960446428808e-02 1.412750180240e+01 1.700879099735e-01 1.845178331846e+00 2.221500519920e-02 1.495579517246e+00 1.800601393265e-02 9.740693365026e+00 1.172729757407e-01 -2.787873471685e+00 -3.356457346117e-02 2.992023172942e-01 3.602243165112e-03 1.040000000000e+02 1.252106910667e+00 1.430000000000e+02 1.721647002167e+00 + 8 EWK_RAP 2.937500000000e+00 8.315178393760e+03 7.000000000000e+03 8.241000000000e+03 1.030000000000e+02 4.578463173209e+00 5.555713109100e-02 1.149297540280e+01 1.394609319597e-01 5.342727368766e+00 6.483105653156e-02 -4.126356809329e+00 -5.007106915822e-02 -3.992260887375e+00 -4.844388893793e-02 3.659835297394e+00 4.441008733641e-02 1.241780764646e+00 1.506832623038e-02 2.207417830905e+00 2.678580064198e-02 1.554592021193e+00 1.886411868940e-02 6.499439295901e-01 7.886711923191e-03 -2.024145569790e-01 -2.456189260757e-03 7.346344891239e-01 8.914385258147e-03 1.501660626415e-01 1.822182534177e-03 -1.871901022181e-01 -2.271448880210e-03 -9.502953125299e-01 -1.153131067261e-02 6.382116555838e-01 7.744347234362e-03 -2.802284174040e+01 -3.400417636258e-01 -1.536037063964e+01 -1.863896449417e-01 -1.010497871591e-02 -1.226183559751e-04 4.262158936433e-03 5.171895323908e-05 5.849862498121e-02 7.098486225120e-04 2.142649251588e-01 2.599986957394e-03 4.065927686351e-01 4.933779500486e-03 -5.178959102669e-01 -6.284381874371e-03 -1.054833331548e+00 -1.279982200641e-02 5.178392681818e+00 6.283694553838e-02 3.829689715120e+00 4.647117722509e-02 -5.120257865708e+01 -6.213151153632e-01 1.098105440925e+00 1.332490524117e-02 3.038890187922e+00 3.687526013738e-02 2.030107936111e+01 2.463424264180e-01 -2.839324583945e+00 -3.445364135353e-02 4.512831009069e-01 5.476072089636e-03 1.030000000000e+02 1.249848319379e+00 1.420000000000e+02 1.723091857784e+00 + 9 EWK_RAP 3.062500000000e+00 8.315178393760e+03 7.000000000000e+03 7.783000000000e+03 9.900000000000e+01 3.946085893979e+00 5.070134773196e-02 9.331747682826e+00 1.198991093772e-01 4.502646795677e+00 5.785232938040e-02 -3.526619992171e+00 -4.531183338264e-02 -3.639029666607e+00 -4.675613088278e-02 3.225984386534e+00 4.144911199453e-02 2.158848236182e+00 2.773799609639e-02 2.236535199328e+00 2.873615828508e-02 1.213648254249e+00 1.559357900872e-02 2.967678491359e-01 3.813026456840e-03 8.236260631450e-01 1.058237264737e-02 3.484094277138e-01 4.476544105278e-03 8.854711601839e-02 1.137699036598e-03 -9.344478855826e-01 -1.200626860571e-02 -1.053365235501e+00 -1.353418007839e-02 -8.875471213300e-02 -1.140366338597e-03 -2.005967984288e+01 -2.577371173439e-01 -8.695726652384e+00 -1.117271829935e-01 -1.042377464094e-02 -1.339300352171e-04 4.045355376677e-03 5.197681326837e-05 6.267162582013e-02 8.052373868704e-04 2.381279322202e-01 3.059590546321e-03 3.754999968959e-01 4.824617716766e-03 -6.042913104888e-01 -7.764246569302e-03 -2.189527828655e+00 -2.813218333104e-02 3.262907577218e-01 4.192352020067e-03 2.665093396520e+00 3.424249513710e-02 -7.492399150283e+00 -9.626621033384e-02 1.845347179457e+00 2.370997275417e-02 6.137185313168e+00 7.885372366913e-02 -3.440405226289e+01 -4.420410158409e-01 -8.058504970994e+00 -1.035398300269e-01 -3.836148149358e+01 -4.928881086159e-01 9.700000000000e+01 1.246306051651e+00 1.340000000000e+02 1.721701143518e+00 + 10 EWK_RAP 3.187500000000e+00 8.315178393760e+03 7.000000000000e+03 7.094000000000e+03 9.600000000000e+01 3.329647992192e+00 4.693611491672e-02 7.588394300457e+00 1.069691894623e-01 3.714550452723e+00 5.236186147059e-02 -3.355035483932e+00 -4.729398765058e-02 -3.621024089380e+00 -5.104347461770e-02 3.303344767856e+00 4.656533363203e-02 2.778731234034e+00 3.917016117894e-02 1.790874580344e+00 2.524491937332e-02 6.991734741610e-01 9.855842601649e-03 2.116857061311e-01 2.984010517777e-03 -4.193254329695e-01 -5.910987214118e-03 1.034664667892e+00 1.458506721021e-02 9.249825327155e-01 1.303894182007e-02 -1.151342889063e+00 -1.622981236345e-02 -3.175887779463e-01 -4.476864645423e-03 -8.103817316899e-01 -1.142348085269e-02 -1.765115184322e+01 -2.488180412070e-01 -8.468050345075e+00 -1.193691900913e-01 -2.284100993512e-02 -3.219764580649e-04 3.460528125958e-03 4.878105618773e-05 1.033576253892e-01 1.456972446986e-03 3.639258931235e-01 5.130052059818e-03 4.209886404778e-01 5.934432484886e-03 -9.238706063651e-01 -1.302326763977e-02 -2.541392203981e+00 -3.582453064535e-02 1.439461394709e+00 2.029125168747e-02 5.679517012299e-01 8.006085441640e-03 -6.136048179722e+00 -8.649630927153e-02 1.193661271391e+00 1.682635003371e-02 7.949020796080e+00 1.120527318308e-01 -3.306818546504e+01 -4.661430147313e-01 -1.423410830257e+01 -2.006499619759e-01 3.793320406535e+01 5.347223578426e-01 8.900000000000e+01 1.254581336341e+00 1.220000000000e+02 1.719763180152e+00 + 11 EWK_RAP 3.312500000000e+00 8.315178393760e+03 7.000000000000e+03 5.894000000000e+03 8.700000000000e+01 2.264497044802e+00 3.842037741436e-02 5.303611386018e+00 8.998322677329e-02 2.996558016485e+00 5.084082145376e-02 -2.980807370554e+00 -5.057358959203e-02 -2.671718796563e+00 -4.532946719652e-02 2.820379868591e+00 4.785171137753e-02 3.075916761244e+00 5.218725417788e-02 6.002068928431e-01 1.018335413714e-02 5.652411860656e-01 9.590111741866e-03 -1.566211518698e-01 -2.657298131486e-03 -5.227061713302e-01 -8.868445390739e-03 2.012909067865e-01 3.415183352333e-03 -5.896119165051e-03 -1.000359546157e-04 -7.277698680109e-01 -1.234763943011e-02 -8.209984498231e-01 -1.392939344797e-02 -1.141179059817e+00 -1.936170783538e-02 -1.131013888738e+01 -1.918924141055e-01 -5.191444509732e+00 -8.808015795270e-02 -2.707280314159e-02 -4.593281836035e-04 1.224337898487e-02 2.077261449758e-04 1.243196398124e-01 2.109257546868e-03 6.384437220314e-01 1.083209572500e-02 2.366452339608e-01 4.015019239240e-03 -1.418444272579e+00 -2.406590214759e-02 -6.182965470300e+00 -1.049027056379e-01 7.831071066216e-01 1.328651351581e-02 3.367636386205e-01 5.713668792340e-03 -3.607855843972e+00 -6.121234889671e-02 2.585577771625e-02 4.386796354979e-04 -4.518748682643e+01 -7.666692708929e-01 -8.204394050542e+00 -1.391990846716e-01 -8.109805549899e-01 -1.375942577180e-02 1.608490642009e+00 2.729030610806e-02 7.400000000000e+01 1.255514082117e+00 1.010000000000e+02 1.713607058025e+00 + 12 EWK_RAP 3.437500000000e+00 8.315178393760e+03 7.000000000000e+03 4.160000000000e+03 7.300000000000e+01 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b/nnpdfcpp/data/commondata/DATA_LHCBZMU8TEV.dat @@ -0,0 +1,19 @@ +LHCBZMU8TEV 36 18 + 1 EWK_RAP 2.062500000000e+00 8.315178393760e+03 8.000000000000e+03 1.223000000000e+03 3.300000000000e+01 1.312937135745e+01 1.073538132252e+00 6.853465481115e-01 5.603814784231e-02 1.813615312414e+00 1.482923395269e-01 1.637891956526e+00 1.339241174592e-01 1.005644788150e+00 8.222770140226e-02 9.250488794403e-01 7.563768433690e-02 6.130610634101e-01 5.012764214310e-02 -1.033777871097e+00 -8.452803524917e-02 -9.022978319043e-01 -7.377741879839e-02 -5.049756150291e-01 -4.128991128611e-02 -8.765726686087e-01 -7.167397126808e-02 5.378206330644e-01 4.397552191859e-02 -1.089552309328e-01 -8.908849626557e-03 4.881555518108e-01 3.991459949394e-02 2.655680538396e-01 2.171447701060e-02 -3.401879609855e-02 -2.781585944281e-03 -1.151594407699e+01 -9.416143971373e-01 8.061168467579e-02 6.591307005380e-03 5.449798823334e-02 4.456090615972e-03 9.944936568493e-05 8.131591634091e-06 7.574441556976e-03 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-4.904694970248e+00 -1.503124416257e-01 -1.446277076600e+00 -4.432353897026e-02 3.800000000000e+01 1.164572479314e+00 3.800000000000e+01 1.164572479314e+00 + 3 EWK_RAP 2.312500000000e+00 8.315178393760e+03 8.000000000000e+03 4.983000000000e+03 6.200000000000e+01 2.106803631144e+01 4.227982402457e-01 -2.818726360958e+00 -5.656685452454e-02 -7.429751053130e+00 -1.491019677530e-01 1.236385409231e+00 2.481206921997e-02 4.400202992756e-01 8.830429445628e-03 8.285805636547e-01 1.662814697280e-02 1.833307684412e-01 3.679124391756e-03 -1.886683246120e+00 -3.786239707246e-02 -1.074860104126e+00 -2.157054192506e-02 9.841457536128e-01 1.975006529426e-02 -2.226573863378e+00 -4.468340083038e-02 -5.655169182101e-01 -1.134892470821e-02 -4.881568704057e-01 -9.796445322209e-03 7.820357793523e-01 1.569407544355e-02 5.919509595143e-02 1.187940918150e-03 1.109725097614e+00 2.227022070268e-02 -2.469985819748e+01 -4.956824843965e-01 2.846572509886e-02 5.712567750123e-04 3.260600131398e-02 6.543447985948e-04 3.105265933389e-05 6.231719713805e-07 -2.763372642623e-03 -5.545600326356e-05 1.714976905992e-02 3.441655440482e-04 1.467691264232e-01 2.945396877849e-03 -1.256580518240e+01 -2.521734935260e-01 6.256157595738e-01 1.255500219895e-02 3.587946103171e+00 7.200373476160e-02 3.192536187497e+01 6.406855684320e-01 -4.075747797835e+01 -8.179305233464e-01 -8.403699350567e+00 -1.686473881310e-01 2.152584070890e+00 4.319855650993e-02 -1.111898663890e+00 -2.231384033493e-02 3.401419929564e+00 6.826048423768e-02 -4.750919333405e+00 -9.534255134267e-02 -1.094803557002e+00 -2.197077176403e-02 5.700000000000e+01 1.143889223359e+00 5.800000000000e+01 1.163957455348e+00 + 4 EWK_RAP 2.437500000000e+00 8.315178393760e+03 8.000000000000e+03 6.719000000000e+03 7.000000000000e+01 2.333879393521e+01 3.473551709363e-01 -5.015020292076e+00 -7.463938520726e-02 -8.195207361706e+00 -1.219706408946e-01 3.616794632949e+00 5.382935902589e-02 -1.537589695146e+00 -2.288420442247e-02 -5.055645332319e-01 -7.524401447119e-03 1.656605444021e-01 2.465553570504e-03 -1.367423699519e+00 -2.035159546837e-02 -9.863174769317e-01 -1.467952786027e-02 1.168914762977e-01 1.739715378742e-03 -2.762797963782e+00 -4.111918386341e-02 -7.334770006817e-01 -1.091646079300e-02 -3.971020272107e-01 -5.910135841802e-03 9.513343420516e-01 1.415886801684e-02 5.236614050230e-01 7.793740214661e-03 -1.432810303335e-01 -2.132475522154e-03 -3.310807446118e+01 -4.927530058219e-01 -3.803307862355e-03 -5.660526659257e-05 4.012076569188e-02 5.971240614954e-04 1.167698609016e-05 1.737905356475e-07 5.199428393584e-03 7.738396180360e-05 -3.020457034224e-03 -4.495396687340e-05 -1.382310113905e-01 -2.057315246175e-03 -2.018490057863e+01 -3.004152489750e-01 7.835344757734e-01 1.166147456129e-02 1.542861258893e+00 2.296266198680e-02 2.911339229778e+00 4.332994835211e-02 1.987734374494e+01 2.958378292147e-01 -1.881752249516e+01 -2.800643324179e-01 -5.171011463680e+00 -7.696102788630e-02 -3.266548144615e+00 -4.861658200052e-02 4.533543603498e+01 6.747348717813e-01 -6.762197326304e+00 -1.006429130273e-01 -1.077789565837e+01 -1.604092224792e-01 7.700000000000e+01 1.146003869623e+00 7.800000000000e+01 1.160887036761e+00 + 5 EWK_RAP 2.562500000000e+00 8.315178393760e+03 8.000000000000e+03 8.051000000000e+03 7.600000000000e+01 2.362879238802e+01 2.934889130297e-01 -6.871934369335e+00 -8.535504122886e-02 -8.838236802398e+00 -1.097781244864e-01 5.753727209186e+00 7.146599440052e-02 -1.540298433635e+00 -1.913176541591e-02 -3.451192706498e-01 -4.286663403923e-03 -4.131058166845e-01 -5.131111870383e-03 5.073510714926e-01 6.301714960782e-03 -1.578894111876e+00 -1.961115528351e-02 -7.607246969865e-01 -9.448822469090e-03 -2.673007365634e+00 -3.320093610277e-02 -1.241747481749e+00 -1.542351859085e-02 -7.432869137168e-01 -9.232230949159e-03 5.989974516239e-01 7.440037903663e-03 6.637383592046e-02 8.244172887898e-04 -7.411626588090e-01 -9.205845967073e-03 -3.649951097455e+01 -4.533537569811e-01 1.532856339107e-01 1.903932851953e-03 5.044391052271e-02 6.265545959844e-04 -5.846611289619e-06 -7.261969059271e-08 1.752413952334e-04 2.176641351800e-06 8.085268741457e-03 1.004256457764e-04 -4.911013493766e-01 -6.099880131370e-03 -1.763914440712e+01 -2.190925898289e-01 1.555577025693e+00 1.932153801631e-02 2.941962686747e-01 3.654158100543e-03 1.451310044454e+00 1.802645689299e-02 1.299733153219e+01 1.614374802160e-01 -2.222192546156e+01 -2.760144759851e-01 -7.424115260800e+00 -9.221357919265e-02 1.012457166503e+01 1.257554547886e-01 -2.284933790302e+01 -2.838074512858e-01 -1.078810436100e+01 -1.339970731710e-01 4.044768877868e+01 5.023933521138e-01 9.300000000000e+01 1.155136007949e+00 9.400000000000e+01 1.167556825239e+00 + 6 EWK_RAP 2.687500000000e+00 8.315178393760e+03 8.000000000000e+03 8.967000000000e+03 7.900000000000e+01 2.330563882218e+01 2.599045257297e-01 -7.893736699339e+00 -8.803096575599e-02 -9.253795984806e+00 -1.031983493343e-01 7.241905559105e+00 8.076174371702e-02 -1.912372224724e+00 -2.132677846240e-02 5.912138549586e-01 6.593217965414e-03 -4.652249383991e-02 -5.188189343137e-04 7.199048005799e-01 8.028379620607e-03 -1.828692488405e+00 -2.039358189366e-02 -2.183225702046e+00 -2.434733692479e-02 -2.015036523294e+00 -2.247169090325e-02 -1.835374982911e+00 -2.046810508432e-02 1.518734723204e-03 1.693693234309e-05 4.820989621951e-01 5.376368486618e-03 -1.213798569671e+00 -1.353628381478e-02 -1.121115480524e+00 -1.250268183924e-02 -3.692425033444e+01 -4.117793056143e-01 2.127352107076e-01 2.372423449399e-03 9.023808536278e-02 1.006335288979e-03 -1.418860172918e-05 -1.582313118008e-07 8.850403418054e-03 9.869971471009e-05 2.487825307335e-02 2.774423226648e-04 -5.683465667233e-01 -6.338201926210e-03 -9.560426327352e+00 -1.066178914615e-01 1.683538823935e+00 1.877482796850e-02 6.834505876370e-01 7.621842172823e-03 6.825047571967e-01 7.611294270065e-03 7.890847045524e+00 8.799874033148e-02 -1.445530599396e+01 -1.612055982375e-01 -1.042790997024e+01 -1.162920705949e-01 2.656207575694e+00 2.962203162366e-02 -2.980150469562e+01 -3.323464335410e-01 1.883353500367e+01 2.100316159660e-01 -4.025708269327e+01 -4.489470580269e-01 1.030000000000e+02 1.148656183785e+00 1.050000000000e+02 1.170960187354e+00 + 7 EWK_RAP 2.812500000000e+00 8.315178393760e+03 8.000000000000e+03 9.561000000000e+03 8.100000000000e+01 2.312287055366e+01 2.418457332251e-01 -8.472992295351e+00 -8.862035660863e-02 -9.978884071327e+00 -1.043707151064e-01 8.191892596978e+00 8.568029073295e-02 -2.170985058689e+00 -2.270667355600e-02 1.192720228358e+00 1.247484811587e-02 -1.027768527952e+00 -1.074959238523e-02 1.322256330842e+00 1.382968654787e-02 -3.390668514565e-01 -3.546353430149e-03 -2.559980432575e+00 -2.677523724061e-02 -1.607483272459e+00 -1.681291990858e-02 -1.614987442947e+00 -1.689140720581e-02 -1.816302646114e-01 -1.899699452059e-03 1.317510032847e+00 1.378004427201e-02 -1.293720350513e+00 -1.353122424969e-02 -4.372359769180e-01 -4.573119725113e-03 -3.900203494075e+01 -4.079284064507e-01 2.942383397581e-01 3.077484988580e-03 5.958653229903e-02 6.232248959212e-04 -1.548696283131e-05 -1.619805755811e-07 6.718922393634e-03 7.027426413172e-05 1.818785300700e-02 1.902296099467e-04 -8.058671737706e-01 -8.428691285123e-03 -7.740143059286e+00 -8.095537139719e-02 2.274379055527e+00 2.378808760095e-02 9.438822433667e-01 9.872212565283e-03 2.354691524266e-01 2.462808831991e-03 4.673162285710e+00 4.887733799509e-02 3.163416661777e+01 3.308667149647e-01 -4.348764566811e+00 -4.548441132529e-02 -4.720725640418e+01 -4.937481058904e-01 -6.675227803606e+00 -6.981725555493e-02 -7.705400922725e+00 -8.059199793667e-02 4.070133303428e+00 4.257016319870e-02 1.100000000000e+02 1.150507269114e+00 1.120000000000e+02 1.171425583098e+00 + 8 EWK_RAP 2.937500000000e+00 8.315178393760e+03 8.000000000000e+03 9.822000000000e+03 8.200000000000e+01 2.085999640062e+01 2.123803339505e-01 -8.242540680871e+00 -8.391916799909e-02 -8.961204056550e+00 -9.123604211515e-02 8.614385898952e+00 8.770500813431e-02 -2.306048360099e+00 -2.347839910506e-02 1.379918925231e+00 1.404926619051e-02 -1.763104057565e+00 -1.795056055351e-02 1.204438762600e+00 1.226266302790e-02 2.922352968786e-02 2.975313549975e-04 -3.021580237130e+00 -3.076339072623e-02 -1.414299254216e+00 -1.439930008365e-02 -1.188972363053e+00 -1.210519612150e-02 9.257611979898e-01 9.425383811747e-03 6.372331880604e-01 6.487814987379e-03 -3.263646033902e-01 -3.322791726636e-03 -8.296699988914e-01 -8.447057614452e-03 -3.431148751935e+01 -3.493330026405e-01 4.318081034914e-01 4.396335812374e-03 1.217992677226e-01 1.240065849344e-03 -2.223371221677e-05 -2.263664448867e-07 4.079579657238e-03 4.153512173934e-05 4.109755671296e-02 4.184235055280e-04 -1.238366902775e+00 -1.260809308466e-02 5.553499113305e-01 5.654142856145e-03 3.847663593633e+00 3.917393192459e-02 -1.214500716627e+00 -1.236510605404e-02 -1.089658879005e+00 -1.109406311347e-02 5.220822383000e+00 5.315437164529e-02 4.056607732585e+00 4.130123938693e-02 5.373393248419e+01 5.470773007960e-01 5.961938629068e+00 6.069984350507e-02 1.723904769556e-01 1.755146375031e-03 1.369996479874e+01 1.394824353364e-01 2.433988169905e+00 2.478098320001e-02 1.130000000000e+02 1.150478517614e+00 1.150000000000e+02 1.170840969253e+00 + 9 EWK_RAP 3.062500000000e+00 8.315178393760e+03 8.000000000000e+03 9.721000000000e+03 8.100000000000e+01 2.022398325060e+01 2.080442675713e-01 -8.154175836436e+00 -8.388206806333e-02 -9.263273566379e+00 -9.529136474003e-02 9.718752686920e+00 9.997688187347e-02 -2.815203846765e+00 -2.896002311249e-02 1.870230536609e+00 1.923907557462e-02 -1.642208435164e+00 -1.689341050472e-02 -1.622478671960e-01 -1.669045028248e-03 2.245271174694e-01 2.309712143498e-03 -3.572768532873e+00 -3.675309672743e-02 -1.807628621364e+00 -1.859508920239e-02 -9.629409377418e-01 -9.905780657769e-03 5.171356641658e-01 5.319778460712e-03 6.176549011257e-01 6.353820606170e-03 -2.939686520237e-01 -3.024057730930e-03 -1.922811023104e-01 -1.977997143405e-03 -3.597332885136e+01 -3.700579040362e-01 4.367334843617e-01 4.492680633286e-03 2.029827971103e-01 2.088085558177e-03 -2.103031895222e-05 -2.163390489890e-07 1.573421063355e-02 1.618579429436e-04 3.959349841839e-02 4.072986155579e-04 -1.222881890842e+00 -1.257979519434e-02 8.050128059305e+00 8.281172779863e-02 3.706780158718e+00 3.813167532886e-02 -2.856448791761e-01 -2.938431017139e-03 3.134908927481e-01 3.224883167864e-03 1.831682047644e+00 1.884252697915e-02 3.211772042507e+01 3.303952312012e-01 -6.005329354851e+00 -6.177686817047e-02 3.591989545512e+01 3.695082342878e-01 -2.011206048262e-02 -2.068929172165e-04 -3.062631510529e+01 -3.150531334769e-01 -1.070501425116e+01 -1.101225619912e-01 1.120000000000e+02 1.152144841066e+00 1.140000000000e+02 1.172718856085e+00 + 10 EWK_RAP 3.187500000000e+00 8.315178393760e+03 8.000000000000e+03 9.030000000000e+03 7.800000000000e+01 1.704123512386e+01 1.887179969419e-01 -7.918393116786e+00 -8.768984625455e-02 -8.440143768235e+00 -9.346781581655e-02 1.002402010797e+01 1.110079746176e-01 -2.684703450732e+00 -2.973093522406e-02 2.067166924945e+00 2.289221400825e-02 -1.837279687306e+00 -2.034639742311e-02 3.650568659959e-01 4.042711694307e-03 4.904354192348e-01 5.431178507583e-03 -3.056868456895e+00 -3.385236386374e-02 -1.063880157349e+00 -1.178161857529e-02 -1.358245619266e+00 -1.504147972609e-02 7.169286786160e-02 7.939409508483e-04 2.199043557753e-01 2.435264183558e-03 -1.574430445433e+00 -1.743555310558e-02 1.329240667376e-03 1.472027317139e-05 -3.211721511436e+01 -3.556723711447e-01 6.435224332446e-01 7.126494277349e-03 2.132859532475e-01 2.361970689341e-03 -1.563925465248e-05 -1.731921888425e-07 1.602557329814e-02 1.774703576760e-04 6.980990577093e-02 7.730886574853e-04 -1.968944344839e+00 -2.180447779446e-02 1.289965278862e+01 1.428532977699e-01 5.004417879946e+00 5.541991007692e-02 -4.905581183298e-01 -5.432537301548e-03 -6.767901157596e-01 -7.494907151269e-03 -5.192725175081e+00 -5.750526218252e-02 1.590697875224e+01 1.761570182972e-01 -2.016293066604e+01 -2.232882687269e-01 1.198733158974e+01 1.327500729761e-01 1.425514530242e+01 1.578642890634e-01 4.378533938226e+01 4.848874793163e-01 1.753546136519e+01 1.941911557607e-01 1.040000000000e+02 1.151716500554e+00 1.050000000000e+02 1.162790697674e+00 + 11 EWK_RAP 3.312500000000e+00 8.315178393760e+03 8.000000000000e+03 7.748000000000e+03 7.200000000000e+01 1.494965869166e+01 1.929486150189e-01 -7.165496747474e+00 -9.248188884194e-02 -7.808477726717e+00 -1.007805591987e-01 9.563054093267e+00 1.234260982611e-01 -2.670729336857e+00 -3.446991916438e-02 1.870910013083e+00 2.414700584774e-02 -1.134378485773e+00 -1.464092005386e-02 5.731050576351e-01 7.396812824408e-03 8.237338552005e-01 1.063156756841e-02 -3.475192583360e+00 -4.485276953226e-02 -1.385142283775e-01 -1.787741718863e-03 -1.002361602276e-01 -1.293703668400e-03 -2.975667575736e-01 -3.840562178286e-03 1.650093308799e-02 2.129702257097e-04 -6.964491524517e-01 -8.988760356889e-03 -2.065417319098e-02 -2.665742538846e-04 -2.991414324734e+01 -3.860885808898e-01 6.436033819978e-01 8.306703433115e-03 1.988462861960e-01 2.566420833711e-03 2.595663656500e-06 3.350107971735e-08 2.076869363903e-02 2.680523185213e-04 5.834119476439e-02 7.529839282961e-04 -1.616593825386e+00 -2.086465959456e-02 5.683115477670e+01 7.334945118315e-01 4.207755805619e+00 5.430763817268e-02 -1.354616593848e-01 -1.748343564594e-03 1.679456788096e-01 2.167600397646e-03 -1.254823525198e+00 -1.619545076404e-02 -2.391565302609e+01 -3.086687277502e-01 -1.316650496015e+00 -1.699342405802e-02 -1.259376213707e+01 -1.625421029565e-01 1.475379610023e+00 1.904207034103e-02 -1.188261280170e+01 -1.533636138578e-01 -6.558219352411e-01 -8.464402881274e-03 8.900000000000e+01 1.148683531234e+00 9.000000000000e+01 1.161590087765e+00 + 12 EWK_RAP 3.437500000000e+00 8.315178393760e+03 8.000000000000e+03 6.059000000000e+03 6.300000000000e+01 9.149049767315e+00 1.509993359847e-01 -4.972284733299e+00 -8.206444517741e-02 -4.934501253784e+00 -8.144085251335e-02 7.146715955713e+00 1.179520705680e-01 -2.480683242649e+00 -4.094212316634e-02 1.671603651748e+00 2.758877127823e-02 -3.731925008924e-01 -6.159308481472e-03 4.690692536356e-01 7.741694233959e-03 1.087081450232e+00 1.794159845241e-02 -2.186426049623e+00 -3.608559250080e-02 -8.527632330601e-02 -1.407432304110e-03 -1.252636370982e-02 -2.067397872556e-04 4.243834079319e-01 7.004182339197e-03 1.345657962147e-01 2.220924182451e-03 -4.790045408799e-01 -7.905669927049e-03 1.534041916905e-01 2.531840100520e-03 -1.487981063298e+01 -2.455819546621e-01 1.204788925465e+00 1.988428660613e-02 4.495879379658e-01 7.420167320775e-03 2.456468050259e-04 4.054246658292e-06 4.544359342930e-02 7.500180463657e-04 1.251769557362e-01 2.065967250969e-03 -6.991666808012e+00 -1.153930814988e-01 5.151973939331e+00 8.503010297625e-02 -4.564159328049e+01 -7.532859098942e-01 1.378443477905e+00 2.275034622718e-02 1.565294265897e+00 2.583420145069e-02 1.409320903182e+00 2.325995879159e-02 2.328009122842e+00 3.842233244498e-02 7.987670255568e-01 1.318314945629e-02 1.492549105843e+00 2.463358814727e-02 1.634737023741e-01 2.698031067405e-03 2.022897365248e+00 3.338665398990e-02 1.008066369713e+00 1.663750403883e-02 7.000000000000e+01 1.155306156131e+00 7.100000000000e+01 1.171810529790e+00 + 13 EWK_RAP 3.562500000000e+00 8.315178393760e+03 8.000000000000e+03 4.385000000000e+03 5.400000000000e+01 6.326085258886e+00 1.442664825287e-01 -3.439415506883e+00 -7.843592946141e-02 -3.341327737674e+00 -7.619903620693e-02 5.541898966162e+00 1.263831007107e-01 -1.666176480785e+00 -3.799718314218e-02 9.793752178742e-01 2.233466859462e-02 -2.485455876128e-04 -5.668086376575e-06 -8.187806243714e-02 -1.867230614302e-03 4.333148438936e-01 9.881752426307e-03 -1.768835651967e+00 -4.033832729686e-02 1.673892047972e-01 3.817313678386e-03 1.105532568097e-01 2.521168912421e-03 4.269058132515e-01 9.735594372897e-03 1.138800538387e-01 2.597036575568e-03 -9.613977606948e-01 -2.192469237617e-02 1.382052895681e-02 3.151773992430e-04 -9.506358516912e+00 -2.167926685727e-01 1.947072274655e+00 4.440301652577e-02 5.827172665109e-01 1.328887722944e-02 3.224919588650e-04 7.354434637742e-06 4.499426072411e-02 1.026094885385e-03 1.375554489632e-01 3.136954366322e-03 3.751338943830e+01 8.554934877605e-01 3.666147114227e+00 8.360654764485e-02 -7.529167532070e+00 -1.717027943459e-01 6.017477237189e-01 1.372286713156e-02 1.699317696165e-01 3.875296912577e-03 8.185166967642e-01 1.866628726942e-02 1.513953963948e+00 3.452574604214e-02 2.381249692410e-01 5.430443996375e-03 8.615737285413e-01 1.964820361554e-02 9.807293782638e-02 2.236555024547e-03 1.548883383250e+00 3.532231204674e-02 7.674261131263e-01 1.750116563572e-02 5.000000000000e+01 1.140250855188e+00 5.100000000000e+01 1.163055872292e+00 + 14 EWK_RAP 3.687500000000e+00 8.315178393760e+03 8.000000000000e+03 2.724000000000e+03 4.200000000000e+01 3.581622334817e+00 1.314839329962e-01 -1.595201474768e+00 -5.856099393422e-02 -1.696419758224e+00 -6.227678994948e-02 3.146991276460e+00 1.155283141138e-01 -8.213111707131e-01 -3.015092403499e-02 8.751706472028e-01 3.212814417044e-02 -2.206946879338e-01 -8.101860790520e-03 -1.039628140716e-01 -3.816549708944e-03 6.365967085277e-01 2.336992322055e-02 -9.100948097627e-01 -3.341023530700e-02 1.302544404313e-01 4.781734230225e-03 3.485205805134e-01 1.279444128169e-02 9.634194009991e-04 3.536781941994e-05 2.441540783404e-02 8.963071892087e-04 -2.368312662368e-01 -8.694246190780e-03 2.131235182572e-01 7.823917704009e-03 -4.887880950067e+00 -1.794376266544e-01 -2.560581500776e+01 -9.400078930895e-01 1.590603225067e+00 5.839218887911e-02 9.666121424544e-05 3.548502725603e-06 8.679639349475e-02 3.186358057810e-03 2.179591422002e-01 8.001436938332e-03 2.280210781652e+00 8.370817847474e-02 2.064997634263e+00 7.580754898174e-02 -2.190450694894e+00 -8.041302110478e-02 3.157588836555e-01 1.159173581702e-02 1.359336155772e-01 4.990220836169e-03 2.645398552229e-01 9.711448429622e-03 7.254250538684e-01 2.663087569267e-02 1.487361196764e-01 5.460209973438e-03 3.472172709894e-01 1.274659585130e-02 -6.366415037864e-02 -2.337156768672e-03 7.056752902129e-01 2.590584765833e-02 3.418947995636e-01 1.255120409558e-02 3.100000000000e+01 1.138032305433e+00 3.200000000000e+01 1.174743024963e+00 + 15 EWK_RAP 3.812500000000e+00 8.315178393760e+03 8.000000000000e+03 1.584000000000e+03 3.200000000000e+01 1.927044395121e+00 1.216568431263e-01 -8.906975447978e-01 -5.623090560592e-02 -9.859044565823e-01 -6.224144296605e-02 1.900006590187e+00 1.199499109967e-01 -5.000615975386e-01 -3.156954529916e-02 4.696847671780e-01 2.965181610972e-02 -2.656750900700e-02 -1.677241730240e-03 -2.464415131886e-01 -1.555817633767e-02 2.541442287433e-01 1.604445888531e-02 -5.977450748892e-01 -3.773643149553e-02 1.246114710530e-01 7.866885798803e-03 2.210648954705e-01 1.395611713829e-02 2.600996773551e-03 1.642043417646e-04 -1.856731584096e-01 -1.172179030364e-02 -1.188075652932e-01 -7.500477606895e-03 1.856799910382e-01 1.172222165645e-02 -2.827258869382e+00 -1.784885649862e-01 -1.979298289528e+00 -1.249557000965e-01 -1.933064816977e+01 -1.220369202637e+00 1.990574440578e-04 1.256675783193e-05 1.121901030963e-01 7.082708528805e-03 3.620340097657e-01 2.285568243470e-02 1.076070580397e+00 6.793374876246e-02 9.794399369759e-01 6.183332935454e-02 -1.269039719858e+00 -8.011614393041e-02 1.107756833672e-01 6.993414353990e-03 -4.550177309559e-02 -2.872586685328e-03 1.470947299450e-02 9.286283456121e-04 3.343664195544e-01 2.110899113349e-02 -1.154124894713e-02 -7.286142012077e-04 3.839086612902e-01 2.423665790974e-02 6.978441016574e-02 4.405581449857e-03 2.652311021248e-01 1.674438776041e-02 6.515123857761e-02 4.113083243536e-03 1.800000000000e+01 1.136363636364e+00 1.900000000000e+01 1.199494949495e+00 + 16 EWK_RAP 3.937500000000e+00 8.315178393760e+03 8.000000000000e+03 7.490000000000e+02 2.200000000000e+01 8.296601388640e-01 1.107690439071e-01 -3.805251722783e-01 -5.080442887560e-02 -4.256454984305e-01 -5.682850446336e-02 8.640659174103e-01 1.153626057958e-01 -3.029421108714e-01 -4.044620972917e-02 2.176950458025e-01 2.906475911916e-02 5.130151104931e-02 6.849333918466e-03 -1.291910301868e-01 -1.724846864978e-02 1.072104716032e-01 1.431381463327e-02 -1.529847335093e-01 -2.042519806533e-02 1.748760490121e-01 2.334793711778e-02 -1.248019049424e-02 -1.666247061981e-03 4.226511417813e-02 5.642872386934e-03 -7.817088485424e-02 -1.043670024756e-02 -7.360831837475e-02 -9.827545844426e-03 1.096321972416e-01 1.463714248886e-02 -1.212004225354e+00 -1.618163184718e-01 -4.778721145844e-01 -6.380135041180e-02 -5.401002869185e-01 -7.210951761262e-02 4.648904008981e-04 6.206814431217e-05 2.580363395866e-01 3.445077965108e-02 -1.179583433424e+01 -1.574877748230e+00 4.012872851790e-01 5.357640656596e-02 4.773980799993e-01 6.373806141513e-02 -5.578977015712e-01 -7.448567444208e-02 -1.591031666170e-02 -2.124207832002e-03 3.931534009798e-02 5.249044071826e-03 -3.491699302092e-02 -4.661814822553e-03 1.507933437772e-01 2.013262266718e-02 2.544812746286e-02 3.397613813465e-03 1.294786911407e-01 1.728687465163e-02 3.045495351607e-03 4.066081911358e-04 2.153979208948e-01 2.875806687514e-02 5.043277234420e-02 6.733347442483e-03 9.000000000000e+00 1.201602136182e+00 9.000000000000e+00 1.201602136182e+00 + 17 EWK_RAP 4.125000000000e+00 8.315178393760e+03 8.000000000000e+03 3.830000000000e+02 1.600000000000e+01 4.239372855009e-01 1.106885862927e-01 -1.489439685955e-01 -3.888876464634e-02 -1.981748571053e-01 -5.174278253402e-02 3.993023179385e-01 1.042564798795e-01 -1.176551557811e-01 -3.071936182274e-02 1.069448812314e-01 2.792294549122e-02 7.370908109907e-02 1.924519088749e-02 -1.344175518288e-01 -3.509596653494e-02 1.153604910917e-01 3.012023266101e-02 -4.875973725734e-02 -1.273100189487e-02 4.521689153204e-02 1.180597690131e-02 1.013038956877e-01 2.645010331272e-02 4.322115716787e-02 1.128489743286e-02 -2.813618535346e-02 -7.346262494376e-03 -4.731362627783e-03 -1.235342722659e-03 1.151605510201e-01 3.006802898698e-02 -6.185243817055e-01 -1.614946166333e-01 -3.020038060079e-01 -7.885216867046e-02 -2.667253838685e-01 -6.964109239385e-02 8.188847909514e-04 2.138080394129e-04 -7.911038971978e+00 -2.065545423493e+00 -3.752800559584e-01 -9.798434881421e-02 2.136989781424e-01 5.579607784396e-02 2.553303274367e-01 6.666588183725e-02 -3.315218861762e-01 -8.655923921050e-02 3.180232046119e-02 8.303477927204e-03 -4.502654465664e-02 -1.175627797824e-02 1.586101551858e-02 4.141257315557e-03 6.645220360766e-02 1.735044480618e-02 -3.990159797845e-02 -1.041817179594e-02 5.325010135976e-02 1.390342072057e-02 2.819711947909e-02 7.362172187753e-03 4.831256818403e-02 1.261424756763e-02 -1.828330837240e-02 -4.773709757807e-03 4.000000000000e+00 1.044386422977e+00 4.000000000000e+00 1.044386422977e+00 + 18 EWK_RAP 4.375000000000e+00 8.315178393760e+03 8.000000000000e+03 1.100000000000e+01 3.000000000000e+00 1.341418481095e-02 1.219471346450e-01 -3.796080264343e-03 -3.450982058494e-02 -7.050325110555e-03 -6.409386464141e-02 1.279367884201e-02 1.163061712910e-01 -6.988237873417e-03 -6.352943521288e-02 -1.152730392232e-03 -1.047936720211e-02 3.828274413001e-03 3.480249466364e-02 5.803516665110e-03 5.275924241009e-02 -1.011089292324e-02 -9.191720839308e-02 -6.099701507314e-03 -5.545183188467e-02 -2.713842573770e-03 -2.467129612518e-02 3.884474841333e-03 3.531340764848e-02 -2.192947913701e-04 -1.993589012456e-03 5.673249488264e-05 5.157499534785e-04 5.283439658297e-03 4.803126962088e-02 1.041343514448e-02 9.466759222252e-02 -9.022711855029e-03 -8.202465322753e-02 -2.448050388056e-03 -2.225500352778e-02 -3.870372245120e-03 -3.518520222836e-02 -9.993144938596e-01 -9.084677216906e+00 -6.305972549479e-03 -5.732702317708e-02 -5.629159396334e-03 -5.117417633031e-02 1.128119646006e-02 1.025563314551e-01 1.603895525081e-03 1.458086840983e-02 -1.500122302195e-02 -1.363747547450e-01 2.858815829938e-03 2.598923481762e-02 -3.202429830490e-03 -2.911299845900e-02 -3.789582290619e-03 -3.445074809653e-02 -1.281017022983e-03 -1.164560929985e-02 -2.095213867030e-04 -1.904739879118e-03 2.487670121814e-04 2.261518292558e-03 1.599311417493e-03 1.453919470448e-02 1.836099148958e-05 1.669181044507e-04 4.537969396256e-04 4.125426723869e-03 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 0.000000000000e+00 diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASDY2D8TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASDY2D8TEV.yaml index e0e348734a..62c3a1be80 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASDY2D8TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASDY2D8TEV.yaml @@ -9,4 +9,4 @@ x_label: '$|y_{\ell\ell}|$' kinematics_override: ewk_rap_sqrt_scale experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASLOMASSDY11EXT.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASLOMASSDY11EXT.yaml index 7de7755c8b..8f81988d5f 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASLOMASSDY11EXT.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASLOMASSDY11EXT.yaml @@ -3,4 +3,4 @@ x: k2 y_label: '$d\sigma_{Z/\gamma^{*}}/dM_{ll}$ (fb)' experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWPT31PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWPT31PB.yaml index a0ad9ced8c..32f91f2799 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASWPT31PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWPT31PB.yaml @@ -7,4 +7,4 @@ y_label: '$d\sigma_{W}/dp_T$' kinematics_override: ewk_pt_sqrt_scale experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP11CC.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP11CC.yaml new file mode 100644 index 0000000000..c4d9b39df9 --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP11CC.yaml @@ -0,0 +1,26 @@ +dataset_label: "ATLAS $W$ 7 TeV 2011 Central selection" +x: k1 + +x_label: '$\left\|\eta/y\right|$' + +y_label: '$d\sigma/dy$ (fb)' + +line_by: + - Boson + +normalize: + line_by: [] + figure_by: + - Boson + + +extra_labels: + Boson: ['$W^+$', '$W^+$', '$W^+$', '$W^+$', '$W^+$', '$W^+$', + '$W^+$', '$W^+$', '$W^+$', '$W^+$', '$W^+$', '$W^-$', '$W^-$', + '$W^-$', '$W^-$', '$W^-$', '$W^-$', '$W^-$', '$W^-$', '$W^-$', + '$W^-$', '$W^-$'] + + +experiment: "ATLAS" + +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP36PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP36PB.yaml new file mode 100644 index 0000000000..063bedb6b8 --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWRAP36PB.yaml @@ -0,0 +1,20 @@ +dataset_label: "ATLAS $W$ 7 TeV 2010" +x: k1 + +x_label: '$\left\|\eta/y\right|$' + +y_label: '$d\sigma/dy$ (fb)' + +line_by: + - Boson + +normalize: + figure_by: + - Boson + +extra_labels: + Boson: ["$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$"] + +experiment: "ATLAS" + +nnpdf31_process: DY CC \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11.yaml index 8da266f15a..0da5c2151a 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11.yaml @@ -19,4 +19,4 @@ extra_labels: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11CF.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11CF.yaml index 66c083a7b8..c109494e2e 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11CF.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP11CF.yaml @@ -23,4 +23,4 @@ extra_labels: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP36PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP36PB.yaml index 0ff36b94c4..15c5e0dabe 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP36PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZRAP36PB.yaml @@ -17,4 +17,4 @@ extra_labels: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZTOT13TEV81PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZTOT13TEV81PB.yaml index c05aa86e87..a7600022e2 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASWZTOT13TEV81PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASWZTOT13TEV81PB.yaml @@ -17,4 +17,4 @@ extra_labels: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZHIGHMASS49FB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZHIGHMASS49FB.yaml index fcf04cd516..f0b0c7b824 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASZHIGHMASS49FB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZHIGHMASS49FB.yaml @@ -7,4 +7,4 @@ kinematics_override: ewk_mll_sqrt_scale experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT7TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT7TEV.yaml index 951a54052a..3f84d7b7dd 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT7TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT7TEV.yaml @@ -10,4 +10,4 @@ kinematics_override: jet_sqrt_scale experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVMDIST.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVMDIST.yaml index 711cd15def..c54223ac65 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVMDIST.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVMDIST.yaml @@ -6,4 +6,4 @@ figure_by: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVYDIST.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVYDIST.yaml index 61c17476dc..41140acf3c 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVYDIST.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZPT8TEVYDIST.yaml @@ -8,4 +8,4 @@ kinematics_override: jet_sqrt_scale experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP11CC.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP11CC.yaml new file mode 100644 index 0000000000..c07827d50e --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP11CC.yaml @@ -0,0 +1,29 @@ +dataset_label: "ATLAS $Z$ 7 TeV 2011 Central selection" +x: k1 + +x_label: '$\left\|\eta/y\right|$' + +y_label: '$d\sigma/dy$ (fb)' + +line_by: + - Boson + +normalize: + line_by: [] + figure_by: + - Boson + + +extra_labels: + Boson: ['$Z_{low}$', '$Z_{low}$', '$Z_{low}$', + '$Z_{low}$', '$Z_{low}$', '$Z_{low}$', '$Z_{peak}$', + '$Z_{peak}$', '$Z_{peak}$', '$Z_{peak}$', '$Z_{peak}$', + '$Z_{peak}$', '$Z_{peak}$', '$Z_{peak}$', '$Z_{peak}$', + '$Z_{peak}$', '$Z_{peak}$', '$Z_{peak}$', '$Z_{high}$', + '$Z_{high}$', '$Z_{high}$', '$Z_{high}$', '$Z_{high}$', + '$Z_{high}$'] + + +experiment: "ATLAS" + +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP36PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP36PB.yaml new file mode 100644 index 0000000000..e9ee71340b --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLASZRAP36PB.yaml @@ -0,0 +1,20 @@ +dataset_label: "ATLAS $Z$ 7 TeV 2010" +x: k1 + +x_label: '$\left\|\eta/y\right|$' + +y_label: '$d\sigma/dy$ (fb)' + +line_by: + - Boson + +normalize: + figure_by: + - Boson + +extra_labels: + Boson: ["$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$"] + +experiment: "ATLAS" + +nnpdf31_process: DY NC \ No newline at end of file diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_DY_2D_8TEV_LOWMASS.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_DY_2D_8TEV_LOWMASS.yaml index 8b53ee46b8..a471b7f29e 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_DY_2D_8TEV_LOWMASS.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_DY_2D_8TEV_LOWMASS.yaml @@ -7,4 +7,4 @@ figure_by: x_label: '$|y_{\ell\ell}|$' experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WM_DIFF_7TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WM_DIFF_7TEV.yaml index cccd62ea82..dfd2f915f2 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WM_DIFF_7TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WM_DIFF_7TEV.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma(W^-+c)/d|\eta^\ell|$ (fb)' x_label: '$|\eta^\ell|$' experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WP_DIFF_7TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WP_DIFF_7TEV.yaml index 2489bf0c67..74675379e1 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WP_DIFF_7TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WCHARM_WP_DIFF_7TEV.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma(W^++\bar{c})/d|\eta^\ell|$ (fb)' x_label: '$|\eta^\ell|$' experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WMU_8TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WMU_8TEV.yaml index 075c518353..b88f170c89 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WMU_8TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WMU_8TEV.yaml @@ -21,4 +21,4 @@ extra_labels: experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PT.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PT.yaml index 44d0c7638b..23a7377c2e 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PT.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PT.yaml @@ -7,4 +7,4 @@ y_scale: log experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PTJ.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PTJ.yaml index 2f47c29832..7bdaa632d6 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PTJ.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WM_JET_8TEV_PTJ.yaml @@ -7,4 +7,4 @@ y_scale: log experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PT.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PT.yaml index a02daba1bb..598f067d17 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PT.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PT.yaml @@ -7,4 +7,4 @@ y_scale: log experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PTJ.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PTJ.yaml index 7de64cd8ce..799e6c4fba 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PTJ.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WP_JET_8TEV_PTJ.yaml @@ -7,4 +7,4 @@ y_scale: log experiment: "ATLAS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WZ_TOT_13TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WZ_TOT_13TEV.yaml index c05aa86e87..5d2ee46291 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WZ_TOT_13TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_WZ_TOT_13TEV.yaml @@ -3,8 +3,7 @@ dataset_label: "ATLAS $W,Z$ inclusive 13 TeV" x: " " y_label: $\sigma^{fid}$ (fb) -figure_by: - - boson + extra_labels: " ": - $W^-$ @@ -18,3 +17,4 @@ extra_labels: experiment: "ATLAS" nnpdf31_process: DY + diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_W_TOT_13TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_W_TOT_13TEV.yaml new file mode 100644 index 0000000000..1bd30f5f4c --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_W_TOT_13TEV.yaml @@ -0,0 +1,19 @@ +dataset_label: "ATLAS $W$ inclusive 13 TeV" + +x: " " + +y_label: $\sigma^{fid}$ (fb) +figure_by: + - boson +extra_labels: + " ": + - $W^-$ + - $W^+$ + boson: + - W + - W + +experiment: "ATLAS" + +nnpdf31_process: DY CC + diff --git a/nnpdfcpp/data/commondata/PLOTTING_ATLAS_Z_TOT_13TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_Z_TOT_13TEV.yaml new file mode 100644 index 0000000000..cb834a8e5c --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_ATLAS_Z_TOT_13TEV.yaml @@ -0,0 +1,17 @@ +dataset_label: "ATLAS $Z$ inclusive 13 TeV" + +x: " " + +y_label: $\sigma^{fid}$ (fb) +figure_by: + - boson +extra_labels: + " ": + - Z + boson: + - Z + +experiment: "ATLAS" + +nnpdf31_process: DY CC + diff --git a/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP.yaml b/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP.yaml index 63c729a730..e7215c7ba2 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z/\gamma^{*}}/dy$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "CDF" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP_NEW.yaml b/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP_NEW.yaml index 0f24efcd40..73fa3aec4d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP_NEW.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CDFZRAP_NEW.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z/\gamma^{*}}/dy$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "CDF" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D11.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D11.yaml index 9b4535b103..59cf625453 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D11.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D11.yaml @@ -8,4 +8,4 @@ kinematics_override: ewk_mll_sqrt_scale experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D12.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D12.yaml index eef80749b8..b2d44bc1b3 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D12.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSDY2D12.yaml @@ -6,4 +6,4 @@ figure_by: experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMRAT.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMRAT.yaml index 7a81bfd166..3d79f76de9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMRAT.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMRAT.yaml @@ -4,4 +4,4 @@ y_label: '$\sigma(W^+ + \bar{c})/\sigma(W^- + c)$' #x_label: 'Boson rapidity $|y|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMTOT.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMTOT.yaml index 9cef298672..3e619d672e 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMTOT.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSWCHARMTOT.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma(W+c)/d|\eta_l|$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSWEASY840PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSWEASY840PB.yaml index 2882456dc4..dd5d94a176 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSWEASY840PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSWEASY840PB.yaml @@ -4,4 +4,4 @@ y_label: '$dA_{e}/dy$' #x_label: 'Boson rapidity $|y|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSWMASY47FB.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSWMASY47FB.yaml index 8fb168a843..894bf0a5d8 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSWMASY47FB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSWMASY47FB.yaml @@ -4,4 +4,4 @@ y_label: '$dA_{\mu}/dy$' #x_label: 'Boson rapidity $|y|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSWMU8TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSWMU8TEV.yaml index afcc365969..145aa93931 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSWMU8TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSWMU8TEV.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma(W\to l\nu)/dy_l$' #x_label: 'Lepton rapidity $|y_l|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMSZDIFF12.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMSZDIFF12.yaml index d76a9e2013..2fce34db17 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMSZDIFF12.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMSZDIFF12.yaml @@ -6,4 +6,4 @@ figure_by: experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_CMS_WCHARM_DIFF_UNNORM_13TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_CMS_WCHARM_DIFF_UNNORM_13TEV.yaml index 3cdedfdf4e..65df1624f4 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_CMS_WCHARM_DIFF_UNNORM_13TEV.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_CMS_WCHARM_DIFF_UNNORM_13TEV.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma(W+c)/d|\eta^\mu|$ (fb)' x_label: '$|\eta^\mu|$' experiment: "CMS" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_D0WEASY.yaml b/nnpdfcpp/data/commondata/PLOTTING_D0WEASY.yaml index 3d23348171..cfe6327851 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_D0WEASY.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_D0WEASY.yaml @@ -4,4 +4,4 @@ y_label: '$dA_{e}/dy$' #x_label: 'Boson rapidity $|y|$' experiment: "D0" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_D0WMASY.yaml b/nnpdfcpp/data/commondata/PLOTTING_D0WMASY.yaml index 4cccad254a..6106b64db9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_D0WMASY.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_D0WMASY.yaml @@ -4,4 +4,4 @@ y_label: '$dA_{\mu}/dy$' #x_label: 'Boson rapidity $|y|$' experiment: "D0" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP.yaml b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP.yaml index 36fee913cc..42fb285454 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP.yaml @@ -4,4 +4,4 @@ y_label: '$1/\sigma\;d\sigma_{Z/\gamma^{*}}/dy$' #x_label: 'Boson rapidity $|y|$' experiment: "D0" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_40.yaml b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_40.yaml index a3f5d7264c..d8660dd6bb 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_40.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_40.yaml @@ -5,4 +5,4 @@ y_label: '$1/\sigma\;d\sigma_{Z/\gamma^{*}}/dy$' experiment: "D0" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_SF.yaml b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_SF.yaml index a3f5d7264c..d8660dd6bb 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_SF.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_D0ZRAP_SF.yaml @@ -5,4 +5,4 @@ y_label: '$1/\sigma\;d\sigma_{Z/\gamma^{*}}/dy$' experiment: "D0" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE605.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE605.yaml index 83334fae71..79de5a2f7a 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE605.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE605.yaml @@ -9,4 +9,4 @@ line_by: - k1 experiment: "DYE605" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw.yaml index afcc3847a9..f4e1ae3a6d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw.yaml @@ -9,4 +9,4 @@ line_by: - k1 experiment: "NUCLEAR" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw_ite.yaml index afcc3847a9..f4e1ae3a6d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE605_dw_ite.yaml @@ -9,4 +9,4 @@ line_by: - k1 experiment: "NUCLEAR" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh.yaml index afcc3847a9..f4e1ae3a6d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh.yaml @@ -9,4 +9,4 @@ line_by: - k1 experiment: "NUCLEAR" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh_ite.yaml index afcc3847a9..f4e1ae3a6d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE605_sh_ite.yaml @@ -9,4 +9,4 @@ line_by: - k1 experiment: "NUCLEAR" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886P.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886P.yaml index 10ec11b5d9..594c9f7b5d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886P.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886P.yaml @@ -47,4 +47,4 @@ extra_labels: experiment: "DYE886" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886R.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886R.yaml index 7537f8c245..f43cc1ddb3 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886R.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886R.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DYE886" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw.yaml index 98e6b4c4e5..46d5d8a3b9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw_ite.yaml index 98e6b4c4e5..46d5d8a3b9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_dw_ite.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh.yaml index 98e6b4c4e5..46d5d8a3b9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh_ite.yaml index 98e6b4c4e5..46d5d8a3b9 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886R_sh_ite.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE886_D.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE886_D.yaml index 13c3331601..fa7b5d872d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE886_D.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE886_D.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R.yaml index 7261a315b6..ed67905296 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DYE906" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN01.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN01.yml index 8a8a7b9e35..5066c966e2 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN01.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN01.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN02.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN02.yml index ef9b4bb3de..596ca710b5 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN02.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN02.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN03.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN03.yml index e158923009..c8af2662e3 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN03.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN03.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN04.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN04.yml index a28c8492e9..6456a4ad1c 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN04.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN04.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN05.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN05.yml index ea829dd716..8b71da16df 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN05.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN05.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN06.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN06.yml index 8f8af7b7c7..18e44b898b 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN06.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN06.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN07.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN07.yml index ce17caa9e9..101b6b6132 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN07.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN07.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN08.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN08.yml index 3a82c23eb5..4394055eac 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN08.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN08.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN09.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN09.yml index 6230bb3f14..73b885351b 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN09.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN09.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN10.yml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN10.yml index aa3eb93d78..e5b23d9e38 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN10.yml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_BIN10.yml @@ -8,4 +8,4 @@ extra_labels: experiment: "AUXILIARY" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_dw_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_dw_ite.yaml index e6d4ee8ddf..286446f963 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_dw_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_dw_ite.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_sh_ite.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_sh_ite.yaml index e6d4ee8ddf..286446f963 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906R_sh_ite.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906R_sh_ite.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_DYE906_D.yaml b/nnpdfcpp/data/commondata/PLOTTING_DYE906_D.yaml index d3ca3ee121..d1eff98df1 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_DYE906_D.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_DYE906_D.yaml @@ -8,4 +8,4 @@ extra_labels: experiment: "DEUTERON" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB.yaml index b4ba2a3ed1..0480755a48 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB.yaml @@ -12,4 +12,4 @@ extra_labels: experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB_40.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB_40.yaml index b4ba2a3ed1..85a9bf55db 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB_40.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBW36PB_40.yaml @@ -12,4 +12,4 @@ extra_labels: experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU7TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU7TEV.yaml new file mode 100644 index 0000000000..e12a9452ea --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU7TEV.yaml @@ -0,0 +1,16 @@ +dataset_label: "LHCb $W \\to \\mu$ 7 TeV" +x: k1 + +y_label: '$d\sigma/dy$ (fb)' + +kinematics_override: ewk_pseudorapity_sqrt_scale + +figure_by: + - Boson + +extra_labels: + Boson: ["$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$", "$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$"] + +experiment: "LHCb" + +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU8TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU8TEV.yaml new file mode 100644 index 0000000000..8f354c5606 --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBWMU8TEV.yaml @@ -0,0 +1,16 @@ +dataset_label: "LHCb $W \\to \\mu$ 8 TeV" +x: k1 + +y_label: '$d\sigma/dy$ (fb)' + +kinematics_override: ewk_pseudorapity_sqrt_scale + +figure_by: + - Boson + +extra_labels: + Boson: ["$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$","$W^+$", "$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$","$W^-$"] + +experiment: "LHCb" + +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBZ940PB.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBZ940PB.yaml index 6c03662edd..adc530193b 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCBZ940PB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBZ940PB.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z/\gamma^{*}}/dy$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB.yaml index 4bf4524a4d..224163bb79 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z/\gamma^{*}}/dy$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB_40.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB_40.yaml index 4bf4524a4d..224163bb79 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB_40.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBZEE2FB_40.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z/\gamma^{*}}/dy$ (fb)' #x_label: 'Boson rapidity $|y|$' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU7TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU7TEV.yaml new file mode 100644 index 0000000000..899384d3dd --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU7TEV.yaml @@ -0,0 +1,16 @@ +dataset_label: "LHCb $Z \\to \\mu$ 7 TeV" +x: k1 + +y_label: '$d\sigma/dy$ (fb)' + +kinematics_override: ewk_pseudorapity_sqrt_scale + +figure_by: + - Boson + +extra_labels: + Boson: ["$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$"] + +experiment: "LHCb" + +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU8TEV.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU8TEV.yaml new file mode 100644 index 0000000000..6f98a01f5a --- /dev/null +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCBZMU8TEV.yaml @@ -0,0 +1,16 @@ +dataset_label: "LHCb $Z \\to \\mu$ 8 TeV" +x: k1 + +y_label: '$d\sigma/dy$ (fb)' + +kinematics_override: ewk_pseudorapity_sqrt_scale + +figure_by: + - Boson + +extra_labels: + Boson: ["$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$","$Z$"] + +experiment: "LHCb" + +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_A.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_A.yaml index 642392b1ce..9a3ae07d3d 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_A.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_A.yaml @@ -6,4 +6,4 @@ x_label: '$\eta^e$' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_R.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_R.yaml index c62cbafb5e..d1814d6c07 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_R.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCB_WENU_8TEV_R.yaml @@ -6,4 +6,4 @@ x_label: '$\eta^e$' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY CC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIELECTRON.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIELECTRON.yaml index 482efe038e..ec7ae88c01 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIELECTRON.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIELECTRON.yaml @@ -5,4 +5,4 @@ x_label: 'y' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIMUON.yaml b/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIMUON.yaml index 6e333339b8..2a45a9ee84 100644 --- a/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIMUON.yaml +++ b/nnpdfcpp/data/commondata/PLOTTING_LHCB_Z_13TEV_DIMUON.yaml @@ -4,4 +4,4 @@ y_label: '$d\sigma_{Z}/dy$ (fb)' x_label: 'y' experiment: "LHCb" -nnpdf31_process: DY +nnpdf31_process: DY NC diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP11CC_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP11CC_DEFAULT.dat new file mode 100644 index 0000000000..362d8ef98a --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP11CC_DEFAULT.dat @@ -0,0 +1,134 @@ +133 +1 MULT UNCORR +2 MULT ATLASWZRAP11_1001 +3 MULT ATLASWZRAP11_1002 +4 MULT ATLASWZRAP11_1003 +5 MULT ATLASWZRAP11_1004 +6 MULT ATLASWZRAP11_1005 +7 MULT ATLASWZRAP11_1006 +8 MULT ATLASWZRAP11_1007 +9 MULT ATLASWZRAP11_1008 +10 MULT ATLASWZRAP11_1009 +11 MULT ATLASWZRAP11_1010 +12 MULT ATLASWZRAP11_1011 +13 MULT ATLASWZRAP11_1012 +14 MULT ATLASWZRAP11_1013 +15 MULT ATLASWZRAP11_1014 +16 MULT ATLASWZRAP11_1015 +17 MULT ATLASWZRAP11_1016 +18 MULT ATLASWZRAP11_1017 +19 MULT ATLASWZRAP11_1018 +20 MULT ATLASWZRAP11_1019 +21 MULT ATLASWZRAP11_1020 +22 MULT ATLASWZRAP11_1021 +23 MULT ATLASWZRAP11_1022 +24 MULT ATLASWZRAP11_1023 +25 MULT ATLASWZRAP11_1024 +26 MULT ATLASWZRAP11_1025 +27 MULT ATLASWZRAP11_1026 +28 MULT ATLASWZRAP11_1027 +29 MULT ATLASWZRAP11_1028 +30 MULT ATLASWZRAP11_1029 +31 MULT ATLASWZRAP11_1030 +32 MULT ATLASWZRAP11_1031 +33 MULT ATLASWZRAP11_1032 +34 MULT ATLASWZRAP11_1033 +35 MULT ATLASWZRAP11_1034 +36 MULT ATLASWZRAP11_1035 +37 MULT ATLASWZRAP11_1036 +38 MULT ATLASWZRAP11_1037 +39 MULT ATLASWZRAP11_1038 +40 MULT ATLASWZRAP11_1039 +41 MULT ATLASWZRAP11_1040 +42 MULT ATLASWZRAP11_1041 +43 MULT ATLASWZRAP11_1042 +44 MULT ATLASWZRAP11_1043 +45 MULT ATLASWZRAP11_1044 +46 MULT ATLASWZRAP11_1045 +47 MULT ATLASWZRAP11_1046 +48 MULT ATLASWZRAP11_1047 +49 MULT ATLASWZRAP11_1048 +50 MULT ATLASWZRAP11_1049 +51 MULT ATLASWZRAP11_1050 +52 MULT ATLASWZRAP11_1051 +53 MULT ATLASWZRAP11_1052 +54 MULT ATLASWZRAP11_1053 +55 MULT ATLASWZRAP11_1054 +56 MULT ATLASWZRAP11_1055 +57 MULT ATLASWZRAP11_1056 +58 MULT ATLASWZRAP11_1057 +59 MULT ATLASWZRAP11_1058 +60 MULT ATLASWZRAP11_1059 +61 MULT ATLASWZRAP11_1060 +62 MULT ATLASWZRAP11_1061 +63 MULT ATLASWZRAP11_1062 +64 MULT ATLASWZRAP11_1063 +65 MULT ATLASWZRAP11_1064 +66 MULT ATLASWZRAP11_1065 +67 MULT ATLASWZRAP11_1066 +68 MULT ATLASWZRAP11_1067 +69 MULT ATLASWZRAP11_1068 +70 MULT ATLASWZRAP11_1069 +71 MULT ATLASWZRAP11_1070 +72 MULT ATLASWZRAP11_1071 +73 MULT ATLASWZRAP11_1072 +74 MULT ATLASWZRAP11_1073 +75 MULT ATLASWZRAP11_1074 +76 MULT ATLASWZRAP11_1075 +77 MULT ATLASWZRAP11_1076 +78 MULT ATLASWZRAP11_1077 +79 MULT ATLASWZRAP11_1078 +80 MULT ATLASWZRAP11_1079 +81 MULT ATLASWZRAP11_1080 +82 MULT ATLASWZRAP11_1081 +83 MULT ATLASWZRAP11_1082 +84 MULT ATLASWZRAP11_1083 +85 MULT ATLASWZRAP11_1084 +86 MULT ATLASWZRAP11_1085 +87 MULT ATLASWZRAP11_1086 +88 MULT ATLASWZRAP11_1087 +89 MULT ATLASWZRAP11_1088 +90 MULT ATLASWZRAP11_1089 +91 MULT ATLASWZRAP11_1090 +92 MULT ATLASWZRAP11_1091 +93 MULT ATLASWZRAP11_1092 +94 MULT ATLASWZRAP11_1093 +95 MULT ATLASWZRAP11_1094 +96 MULT ATLASWZRAP11_1095 +97 MULT ATLASWZRAP11_1096 +98 MULT ATLASWZRAP11_1097 +99 MULT ATLASWZRAP11_1098 +100 MULT ATLASWZRAP11_1099 +101 MULT ATLASWZRAP11_1100 +102 MULT ATLASWZRAP11_1101 +103 MULT ATLASWZRAP11_1102 +104 MULT ATLASWZRAP11_1103 +105 MULT ATLASWZRAP11_1104 +106 MULT ATLASWZRAP11_1105 +107 MULT ATLASWZRAP11_1106 +108 MULT ATLASWZRAP11_1107 +109 MULT ATLASWZRAP11_1108 +110 MULT ATLASWZRAP11_1109 +111 MULT ATLASWZRAP11_1110 +112 MULT ATLASWZRAP11_1111 +113 MULT ATLASWZRAP11_1112 +114 MULT ATLASWZRAP11_1113 +115 MULT ATLASWZRAP11_1114 +116 MULT ATLASWZRAP11_1115 +117 MULT ATLASWZRAP11_1116 +118 MULT ATLASWZRAP11_1117 +119 MULT ATLASWZRAP11_1118 +120 MULT ATLASWZRAP11_1119 +121 MULT ATLASWZRAP11_1120 +122 MULT ATLASWZRAP11_1121 +123 MULT ATLASWZRAP11_1122 +124 MULT ATLASWZRAP11_1123 +125 MULT ATLASWZRAP11_1124 +126 MULT ATLASWZRAP11_1125 +127 MULT ATLASWZRAP11_1126 +128 MULT ATLASWZRAP11_1127 +129 MULT ATLASWZRAP11_1128 +130 MULT ATLASWZRAP11_1129 +131 MULT ATLASWZRAP11_1130 +132 MULT ATLASLUMI11 +133 MULT UNCORR diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP36PB_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP36PB_DEFAULT.dat new file mode 100644 index 0000000000..e65eb78ac1 --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASWRAP36PB_DEFAULT.dat @@ -0,0 +1,33 @@ +32 +1 MULT UNCORR +2 MULT ATLASLUMI10 +3 MULT ATLASWZRAP36PB_0 +4 MULT ATLASWZRAP36PB_1 +5 MULT ATLASWZRAP36PB_2 +6 MULT ATLASWZRAP36PB_3 +7 MULT ATLASWZRAP36PB_4 +8 MULT ATLASWZRAP36PB_5 +9 MULT ATLASWZRAP36PB_6 +10 MULT ATLASWZRAP36PB_7 +11 MULT ATLASWZRAP36PB_8 +12 MULT ATLASWZRAP36PB_9 +13 MULT ATLASWZRAP36PB_10 +14 MULT ATLASWZRAP36PB_11 +15 MULT ATLASWZRAP36PB_12 +16 MULT ATLASWZRAP36PB_13 +17 MULT ATLASWZRAP36PB_14 +18 MULT ATLASWZRAP36PB_15 +19 MULT ATLASWZRAP36PB_16 +20 MULT ATLASWZRAP36PB_17 +21 MULT ATLASWZRAP36PB_18 +22 MULT ATLASWZRAP36PB_19 +23 MULT ATLASWZRAP36PB_20 +24 MULT ATLASWZRAP36PB_21 +25 MULT ATLASWZRAP36PB_22 +26 MULT ATLASWZRAP36PB_23 +27 MULT ATLASWZRAP36PB_24 +28 MULT ATLASWZRAP36PB_25 +29 MULT ATLASWZRAP36PB_26 +30 MULT ATLASWZRAP36PB_27 +31 MULT ATLASWZRAP36PB_28 +32 MULT ATLASWZRAP36PB_29 diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP11CC_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP11CC_DEFAULT.dat new file mode 100644 index 0000000000..362d8ef98a --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP11CC_DEFAULT.dat @@ -0,0 +1,134 @@ +133 +1 MULT UNCORR +2 MULT ATLASWZRAP11_1001 +3 MULT ATLASWZRAP11_1002 +4 MULT ATLASWZRAP11_1003 +5 MULT ATLASWZRAP11_1004 +6 MULT ATLASWZRAP11_1005 +7 MULT ATLASWZRAP11_1006 +8 MULT ATLASWZRAP11_1007 +9 MULT ATLASWZRAP11_1008 +10 MULT ATLASWZRAP11_1009 +11 MULT ATLASWZRAP11_1010 +12 MULT ATLASWZRAP11_1011 +13 MULT ATLASWZRAP11_1012 +14 MULT ATLASWZRAP11_1013 +15 MULT ATLASWZRAP11_1014 +16 MULT ATLASWZRAP11_1015 +17 MULT ATLASWZRAP11_1016 +18 MULT ATLASWZRAP11_1017 +19 MULT ATLASWZRAP11_1018 +20 MULT ATLASWZRAP11_1019 +21 MULT ATLASWZRAP11_1020 +22 MULT ATLASWZRAP11_1021 +23 MULT ATLASWZRAP11_1022 +24 MULT ATLASWZRAP11_1023 +25 MULT ATLASWZRAP11_1024 +26 MULT ATLASWZRAP11_1025 +27 MULT ATLASWZRAP11_1026 +28 MULT ATLASWZRAP11_1027 +29 MULT ATLASWZRAP11_1028 +30 MULT ATLASWZRAP11_1029 +31 MULT ATLASWZRAP11_1030 +32 MULT ATLASWZRAP11_1031 +33 MULT ATLASWZRAP11_1032 +34 MULT ATLASWZRAP11_1033 +35 MULT ATLASWZRAP11_1034 +36 MULT ATLASWZRAP11_1035 +37 MULT ATLASWZRAP11_1036 +38 MULT ATLASWZRAP11_1037 +39 MULT ATLASWZRAP11_1038 +40 MULT ATLASWZRAP11_1039 +41 MULT ATLASWZRAP11_1040 +42 MULT ATLASWZRAP11_1041 +43 MULT ATLASWZRAP11_1042 +44 MULT ATLASWZRAP11_1043 +45 MULT ATLASWZRAP11_1044 +46 MULT ATLASWZRAP11_1045 +47 MULT ATLASWZRAP11_1046 +48 MULT ATLASWZRAP11_1047 +49 MULT ATLASWZRAP11_1048 +50 MULT ATLASWZRAP11_1049 +51 MULT ATLASWZRAP11_1050 +52 MULT ATLASWZRAP11_1051 +53 MULT ATLASWZRAP11_1052 +54 MULT ATLASWZRAP11_1053 +55 MULT ATLASWZRAP11_1054 +56 MULT ATLASWZRAP11_1055 +57 MULT ATLASWZRAP11_1056 +58 MULT ATLASWZRAP11_1057 +59 MULT ATLASWZRAP11_1058 +60 MULT ATLASWZRAP11_1059 +61 MULT ATLASWZRAP11_1060 +62 MULT ATLASWZRAP11_1061 +63 MULT ATLASWZRAP11_1062 +64 MULT ATLASWZRAP11_1063 +65 MULT ATLASWZRAP11_1064 +66 MULT ATLASWZRAP11_1065 +67 MULT ATLASWZRAP11_1066 +68 MULT ATLASWZRAP11_1067 +69 MULT ATLASWZRAP11_1068 +70 MULT ATLASWZRAP11_1069 +71 MULT ATLASWZRAP11_1070 +72 MULT ATLASWZRAP11_1071 +73 MULT ATLASWZRAP11_1072 +74 MULT ATLASWZRAP11_1073 +75 MULT ATLASWZRAP11_1074 +76 MULT ATLASWZRAP11_1075 +77 MULT ATLASWZRAP11_1076 +78 MULT ATLASWZRAP11_1077 +79 MULT ATLASWZRAP11_1078 +80 MULT ATLASWZRAP11_1079 +81 MULT ATLASWZRAP11_1080 +82 MULT ATLASWZRAP11_1081 +83 MULT ATLASWZRAP11_1082 +84 MULT ATLASWZRAP11_1083 +85 MULT ATLASWZRAP11_1084 +86 MULT ATLASWZRAP11_1085 +87 MULT ATLASWZRAP11_1086 +88 MULT ATLASWZRAP11_1087 +89 MULT ATLASWZRAP11_1088 +90 MULT ATLASWZRAP11_1089 +91 MULT ATLASWZRAP11_1090 +92 MULT ATLASWZRAP11_1091 +93 MULT ATLASWZRAP11_1092 +94 MULT ATLASWZRAP11_1093 +95 MULT ATLASWZRAP11_1094 +96 MULT ATLASWZRAP11_1095 +97 MULT ATLASWZRAP11_1096 +98 MULT ATLASWZRAP11_1097 +99 MULT ATLASWZRAP11_1098 +100 MULT ATLASWZRAP11_1099 +101 MULT ATLASWZRAP11_1100 +102 MULT ATLASWZRAP11_1101 +103 MULT ATLASWZRAP11_1102 +104 MULT ATLASWZRAP11_1103 +105 MULT ATLASWZRAP11_1104 +106 MULT ATLASWZRAP11_1105 +107 MULT ATLASWZRAP11_1106 +108 MULT ATLASWZRAP11_1107 +109 MULT ATLASWZRAP11_1108 +110 MULT ATLASWZRAP11_1109 +111 MULT ATLASWZRAP11_1110 +112 MULT ATLASWZRAP11_1111 +113 MULT ATLASWZRAP11_1112 +114 MULT ATLASWZRAP11_1113 +115 MULT ATLASWZRAP11_1114 +116 MULT ATLASWZRAP11_1115 +117 MULT ATLASWZRAP11_1116 +118 MULT ATLASWZRAP11_1117 +119 MULT ATLASWZRAP11_1118 +120 MULT ATLASWZRAP11_1119 +121 MULT ATLASWZRAP11_1120 +122 MULT ATLASWZRAP11_1121 +123 MULT ATLASWZRAP11_1122 +124 MULT ATLASWZRAP11_1123 +125 MULT ATLASWZRAP11_1124 +126 MULT ATLASWZRAP11_1125 +127 MULT ATLASWZRAP11_1126 +128 MULT ATLASWZRAP11_1127 +129 MULT ATLASWZRAP11_1128 +130 MULT ATLASWZRAP11_1129 +131 MULT ATLASWZRAP11_1130 +132 MULT ATLASLUMI11 +133 MULT UNCORR diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP36PB_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP36PB_DEFAULT.dat new file mode 100644 index 0000000000..e65eb78ac1 --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLASZRAP36PB_DEFAULT.dat @@ -0,0 +1,33 @@ +32 +1 MULT UNCORR +2 MULT ATLASLUMI10 +3 MULT ATLASWZRAP36PB_0 +4 MULT ATLASWZRAP36PB_1 +5 MULT ATLASWZRAP36PB_2 +6 MULT ATLASWZRAP36PB_3 +7 MULT ATLASWZRAP36PB_4 +8 MULT ATLASWZRAP36PB_5 +9 MULT ATLASWZRAP36PB_6 +10 MULT ATLASWZRAP36PB_7 +11 MULT ATLASWZRAP36PB_8 +12 MULT ATLASWZRAP36PB_9 +13 MULT ATLASWZRAP36PB_10 +14 MULT ATLASWZRAP36PB_11 +15 MULT ATLASWZRAP36PB_12 +16 MULT ATLASWZRAP36PB_13 +17 MULT ATLASWZRAP36PB_14 +18 MULT ATLASWZRAP36PB_15 +19 MULT ATLASWZRAP36PB_16 +20 MULT ATLASWZRAP36PB_17 +21 MULT ATLASWZRAP36PB_18 +22 MULT ATLASWZRAP36PB_19 +23 MULT ATLASWZRAP36PB_20 +24 MULT ATLASWZRAP36PB_21 +25 MULT ATLASWZRAP36PB_22 +26 MULT ATLASWZRAP36PB_23 +27 MULT ATLASWZRAP36PB_24 +28 MULT ATLASWZRAP36PB_25 +29 MULT ATLASWZRAP36PB_26 +30 MULT ATLASWZRAP36PB_27 +31 MULT ATLASWZRAP36PB_28 +32 MULT ATLASWZRAP36PB_29 diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_W_TOT_13TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_W_TOT_13TEV_DEFAULT.dat new file mode 100644 index 0000000000..0d79f337cf --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_W_TOT_13TEV_DEFAULT.dat @@ -0,0 +1,5 @@ +4 +1 ADD ATLAS_WZ_TOT_13TEV_0 +2 ADD ATLAS_WZ_TOT_13TEV_1 +3 ADD ATLAS_WZ_TOT_13TEV_2 +4 MULT ATLASLUMI13 diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_Z_TOT_13TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_Z_TOT_13TEV_DEFAULT.dat new file mode 100644 index 0000000000..0d79f337cf --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_ATLAS_Z_TOT_13TEV_DEFAULT.dat @@ -0,0 +1,5 @@ +4 +1 ADD ATLAS_WZ_TOT_13TEV_0 +2 ADD ATLAS_WZ_TOT_13TEV_1 +3 ADD ATLAS_WZ_TOT_13TEV_2 +4 MULT ATLASLUMI13 diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU7TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU7TEV_DEFAULT.dat new file mode 100644 index 0000000000..9d9f7de09e --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU7TEV_DEFAULT.dat @@ -0,0 +1,36 @@ +35 +1 MULT LHCBWZMU7TEV_0 +2 MULT LHCBWZMU7TEV_1 +3 MULT LHCBWZMU7TEV_2 +4 MULT LHCBWZMU7TEV_3 +5 MULT LHCBWZMU7TEV_4 +6 MULT LHCBWZMU7TEV_5 +7 MULT LHCBWZMU7TEV_6 +8 MULT LHCBWZMU7TEV_7 +9 MULT LHCBWZMU7TEV_8 +10 MULT LHCBWZMU7TEV_9 +11 MULT LHCBWZMU7TEV_10 +12 MULT LHCBWZMU7TEV_11 +13 MULT LHCBWZMU7TEV_12 +14 MULT LHCBWZMU7TEV_13 +15 MULT LHCBWZMU7TEV_14 +16 MULT LHCBWZMU7TEV_15 +17 MULT LHCBWZMU7TEV_16 +18 MULT LHCBWZMU7TEV_17 +19 MULT LHCBWZMU7TEV_18 +20 MULT LHCBWZMU7TEV_19 +21 MULT LHCBWZMU7TEV_20 +22 MULT LHCBWZMU7TEV_21 +23 MULT LHCBWZMU7TEV_22 +24 MULT LHCBWZMU7TEV_23 +25 MULT LHCBWZMU7TEV_24 +26 MULT LHCBWZMU7TEV_25 +27 MULT LHCBWZMU7TEV_26 +28 MULT LHCBWZMU7TEV_27 +29 MULT LHCBWZMU7TEV_28 +30 MULT LHCBWZMU7TEV_29 +31 MULT LHCBWZMU7TEV_30 +32 MULT LHCBWZMU7TEV_31 +33 MULT LHCBWZMU7TEV_32 +34 MULT LHCBBEAM7TEV +35 MULT LHCBLUMI7TEV diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU8TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU8TEV_DEFAULT.dat new file mode 100644 index 0000000000..62ba4f6680 --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBWMU8TEV_DEFAULT.dat @@ -0,0 +1,37 @@ +36 +1 MULT LHCBWZMU8TEV_0 +2 MULT LHCBWZMU8TEV_1 +3 MULT LHCBWZMU8TEV_2 +4 MULT LHCBWZMU8TEV_3 +5 MULT LHCBWZMU8TEV_4 +6 MULT LHCBWZMU8TEV_5 +7 MULT LHCBWZMU8TEV_6 +8 MULT LHCBWZMU8TEV_7 +9 MULT LHCBWZMU8TEV_8 +10 MULT LHCBWZMU8TEV_9 +11 MULT LHCBWZMU8TEV_10 +12 MULT LHCBWZMU8TEV_11 +13 MULT LHCBWZMU8TEV_12 +14 MULT LHCBWZMU8TEV_13 +15 MULT LHCBWZMU8TEV_14 +16 MULT LHCBWZMU8TEV_15 +17 MULT LHCBWZMU8TEV_16 +18 MULT LHCBWZMU8TEV_17 +19 MULT LHCBWZMU8TEV_18 +20 MULT LHCBWZMU8TEV_19 +21 MULT LHCBWZMU8TEV_20 +22 MULT LHCBWZMU8TEV_21 +23 MULT LHCBWZMU8TEV_22 +24 MULT LHCBWZMU8TEV_23 +25 MULT LHCBWZMU8TEV_24 +26 MULT LHCBWZMU8TEV_25 +27 MULT LHCBWZMU8TEV_26 +28 MULT LHCBWZMU8TEV_27 +29 MULT LHCBWZMU8TEV_28 +30 MULT LHCBWZMU8TEV_29 +31 MULT LHCBWZMU8TEV_30 +32 MULT LHCBWZMU8TEV_31 +33 MULT LHCBWZMU8TEV_32 +34 MULT LHCBWZMU8TEV_33 +35 MULT LHCBBEAM8TEV +36 MULT LHCBLUMI8TEV diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU7TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU7TEV_DEFAULT.dat new file mode 100644 index 0000000000..9d9f7de09e --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU7TEV_DEFAULT.dat @@ -0,0 +1,36 @@ +35 +1 MULT LHCBWZMU7TEV_0 +2 MULT LHCBWZMU7TEV_1 +3 MULT LHCBWZMU7TEV_2 +4 MULT LHCBWZMU7TEV_3 +5 MULT LHCBWZMU7TEV_4 +6 MULT LHCBWZMU7TEV_5 +7 MULT LHCBWZMU7TEV_6 +8 MULT LHCBWZMU7TEV_7 +9 MULT LHCBWZMU7TEV_8 +10 MULT LHCBWZMU7TEV_9 +11 MULT LHCBWZMU7TEV_10 +12 MULT LHCBWZMU7TEV_11 +13 MULT LHCBWZMU7TEV_12 +14 MULT LHCBWZMU7TEV_13 +15 MULT LHCBWZMU7TEV_14 +16 MULT LHCBWZMU7TEV_15 +17 MULT LHCBWZMU7TEV_16 +18 MULT LHCBWZMU7TEV_17 +19 MULT LHCBWZMU7TEV_18 +20 MULT LHCBWZMU7TEV_19 +21 MULT LHCBWZMU7TEV_20 +22 MULT LHCBWZMU7TEV_21 +23 MULT LHCBWZMU7TEV_22 +24 MULT LHCBWZMU7TEV_23 +25 MULT LHCBWZMU7TEV_24 +26 MULT LHCBWZMU7TEV_25 +27 MULT LHCBWZMU7TEV_26 +28 MULT LHCBWZMU7TEV_27 +29 MULT LHCBWZMU7TEV_28 +30 MULT LHCBWZMU7TEV_29 +31 MULT LHCBWZMU7TEV_30 +32 MULT LHCBWZMU7TEV_31 +33 MULT LHCBWZMU7TEV_32 +34 MULT LHCBBEAM7TEV +35 MULT LHCBLUMI7TEV diff --git a/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU8TEV_DEFAULT.dat b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU8TEV_DEFAULT.dat new file mode 100644 index 0000000000..62ba4f6680 --- /dev/null +++ b/nnpdfcpp/data/commondata/systypes/SYSTYPE_LHCBZMU8TEV_DEFAULT.dat @@ -0,0 +1,37 @@ +36 +1 MULT LHCBWZMU8TEV_0 +2 MULT LHCBWZMU8TEV_1 +3 MULT LHCBWZMU8TEV_2 +4 MULT LHCBWZMU8TEV_3 +5 MULT LHCBWZMU8TEV_4 +6 MULT LHCBWZMU8TEV_5 +7 MULT LHCBWZMU8TEV_6 +8 MULT LHCBWZMU8TEV_7 +9 MULT LHCBWZMU8TEV_8 +10 MULT LHCBWZMU8TEV_9 +11 MULT LHCBWZMU8TEV_10 +12 MULT LHCBWZMU8TEV_11 +13 MULT LHCBWZMU8TEV_12 +14 MULT LHCBWZMU8TEV_13 +15 MULT LHCBWZMU8TEV_14 +16 MULT LHCBWZMU8TEV_15 +17 MULT LHCBWZMU8TEV_16 +18 MULT LHCBWZMU8TEV_17 +19 MULT LHCBWZMU8TEV_18 +20 MULT LHCBWZMU8TEV_19 +21 MULT LHCBWZMU8TEV_20 +22 MULT LHCBWZMU8TEV_21 +23 MULT LHCBWZMU8TEV_22 +24 MULT LHCBWZMU8TEV_23 +25 MULT LHCBWZMU8TEV_24 +26 MULT LHCBWZMU8TEV_25 +27 MULT LHCBWZMU8TEV_26 +28 MULT LHCBWZMU8TEV_27 +29 MULT LHCBWZMU8TEV_28 +30 MULT LHCBWZMU8TEV_29 +31 MULT LHCBWZMU8TEV_30 +32 MULT LHCBWZMU8TEV_31 +33 MULT LHCBWZMU8TEV_32 +34 MULT LHCBWZMU8TEV_33 +35 MULT LHCBBEAM8TEV +36 MULT LHCBLUMI8TEV diff --git a/nnpdfcpp/data/theory.db b/nnpdfcpp/data/theory.db index 4bc4113daa..410e2ed89b 100644 Binary files a/nnpdfcpp/data/theory.db and b/nnpdfcpp/data/theory.db differ diff --git a/validphys2/examples/pdf_lumi_plots.yaml b/validphys2/examples/pdf_lumi_plots.yaml index 67d046dba7..c570249a83 100644 --- a/validphys2/examples/pdf_lumi_plots.yaml +++ b/validphys2/examples/pdf_lumi_plots.yaml @@ -13,7 +13,8 @@ pdf: {id: "NNPDF40_nlo_as_01180", label: "4.0 NLO"} sqrts: 13000 # GeV lumi_channel: "gg" # one of [gg, gq, qqbar, qq, ddbar, uubar, ssbar, - # ccbar, bbbar, dubar, udbar, scbar, csbar, pp, gp] + # ccbar, bbbar, dubar, udbar, scbar, csbar, pp, gp, + # wlum1, zlum1] PDFscalespecs: - xscale: log diff --git a/validphys2/src/validphys/cuts/filters.yaml b/validphys2/src/validphys/cuts/filters.yaml index 0e103fce04..8374fb7b56 100644 --- a/validphys2/src/validphys/cuts/filters.yaml +++ b/validphys2/src/validphys/cuts/filters.yaml @@ -76,6 +76,24 @@ PTO: NNLO rule: "etay >= 2.25" +- dataset: LHCBWMU8TEV + reason: | + The first two bins in rapidity have unnaturally large K-factors which we + don't understand, and theory calculations are unstable here, so we remove + these points at NNLO. + # Only evaluate rule if PTO matches + PTO: NNLO + rule: "etay >= 2.25" + +- dataset: LHCBZMU8TEV + reason: | + The first two bins in rapidity have unnaturally large K-factors which we + don't understand, and theory calculations are unstable here, so we remove + these points at NNLO. + # Only evaluate rule if PTO matches + PTO: NNLO + rule: "etay >= 2.25" + - dataset: LHCBWZMU7TEV reason: | The first two bins in rapidity have unnaturally large K-factors which we @@ -84,6 +102,22 @@ PTO: NNLO rule: "etay >= 2.25" +- dataset: LHCBWMU7TEV + reason: | + The first two bins in rapidity have unnaturally large K-factors which we + don't understand, and theory calculations are unstable here, so we remove + these points at NNLO. + PTO: NNLO + rule: "etay >= 2.25" + +- dataset: LHCBZMU7TEV + reason: | + The first two bins in rapidity have unnaturally large K-factors which we + don't understand, and theory calculations are unstable here, so we remove + these points at NNLO. + PTO: NNLO + rule: "etay >= 2.25" + - dataset: LHCB_Z_13TEV_DIELECTRON reason: | The first two bins in rapidity have unnaturally large K-factors which we diff --git a/validphys2/src/validphys/dataplots.py b/validphys2/src/validphys/dataplots.py index 8ae5fe1012..7a8088ed31 100644 --- a/validphys2/src/validphys/dataplots.py +++ b/validphys2/src/validphys/dataplots.py @@ -387,6 +387,7 @@ def _plot_fancy_impl( lb = labellist[normalize_to] ax.set_ylabel(f"Ratio to {lb if lb else norm_result.label}") + ax.legend().set_zorder(100000) ax.set_xlabel(info.xlabel) fig.tight_layout() @@ -879,7 +880,6 @@ def plot_smpdf(pdf, dataset, obs_pdf_correlations, mark_threshold: float = 0.9): info = get_info(dataset) table = kitable(dataset, info) - figby = sane_groupby_iter(table, info.figure_by) basis = obs_pdf_correlations.basis @@ -891,54 +891,83 @@ def plot_smpdf(pdf, dataset, obs_pdf_correlations, mark_threshold: float = 0.9): plotting_var = info.get_xcol(table) - # TODO: vmin vmax should be global or by figure? - vmin, vmax = min(plotting_var), max(plotting_var) - if info.x_scale == 'log': - norm = mcolors.LogNorm(vmin, vmax) + categorical = not np.issubdtype(plotting_var.dtype, np.number) + if categorical: + # Plot lines using a categorical color map (for a reasonable number of + # categories), and set up the categorical labels (used below). + categorical_keys, values = np.unique(plotting_var, return_inverse=True) + plotting_var = values + num_categories = len(categorical_keys) + if num_categories <= len(cm.Set2.colors): + cmap = mcolors.ListedColormap(cm.Set2.colors[:num_categories]) + else: + cmap = cm.viridis.resample(num_categories) + bins = np.linspace(0, num_categories, num_categories + 1) + norm = mcolors.BoundaryNorm(bins, num_categories) + else: - norm = mcolors.Normalize(vmin, vmax) - # http://stackoverflow.com/a/11558629/1007990 - sm = cm.ScalarMappable(cmap=cm.viridis, norm=norm) + cmap = cm.viridis + #TODO: vmin vmax should be global or by figure? + vmin, vmax = min(plotting_var), max(plotting_var) + if info.x_scale == 'log': + norm = mcolors.LogNorm(vmin, vmax) + else: + norm = mcolors.Normalize(vmin, vmax) + + + table["__plotting_var"] = plotting_var + sm = cm.ScalarMappable(cmap=cmap, norm=norm) + + figby = sane_groupby_iter(table, info.figure_by) for same_vals, fb in figby: - grid = fullgrid[np.asarray(fb.index), ...] + grid = fullgrid[ np.asarray(fb.index),...] - # Use the maximum absolute correlation for plotting purposes + + #Use the maximum absolute correlation for plotting purposes absgrid = np.max(np.abs(grid), axis=0) - mark_mask = absgrid > np.max(absgrid) * mark_threshold + mark_mask = absgrid > np.max(absgrid)*mark_threshold label = info.group_label(same_vals, info.figure_by) - # TODO: PY36ScalarMappable - # TODO Improve title? - title = "%s %s\n[%s]" % (info.dataset_label, '(%s)' % label if label else '', pdf.label) - - # Start plotting - w, h = mpl.rcParams["figure.figsize"] - h *= 2.5 - fig, axes = plotutils.subplots(nrows=nf, sharex=True, figsize=(w, h), sharey=True) + #TODO: PY36ScalarMappable + #TODO Improve title? + title = f"{info.dataset_label} {label if label else ''}\n[{pdf.label}]" + + #Start plotting + w,h = mpl.rcParams["figure.figsize"] + h*=2.5 + fig, axes = plotutils.subplots(nrows=nf, sharex=True, figsize=(w,h), sharey=True) fig.suptitle(title) - colors = sm.to_rgba(info.get_xcol(fb)) + colors = sm.to_rgba(fb["__plotting_var"]) for flindex, (ax, fl) in enumerate(zip(axes, fls)): - for i, color in enumerate(colors): - ax.plot(x, grid[i, flindex, :].T, color=color) + for i,color in enumerate(colors): + ax.plot(x, grid[i,flindex,:].T, color=color) + - flmask = mark_mask[flindex, :] + flmask = mark_mask[flindex,:] ranges = split_ranges(x, flmask, filter_falses=True) for r in ranges: ax.axvspan(r[0], r[-1], color='#eeeeff') - ax.set_ylabel("$%s$" % basis.elementlabel(fl)) + ax.set_ylabel("$%s$"%basis.elementlabel(fl)) ax.set_xscale(scale_from_grid(obs_pdf_correlations)) - ax.set_ylim(-1, 1) + ax.set_ylim(-1,1) ax.set_xlim(x[0], x[-1]) ax.set_xlabel('$x$') - # fig.subplots_adjust(hspace=0) - fig.colorbar(sm, ax=axes.ravel().tolist(), label=info.xlabel, aspect=100) - # TODO: Fix title for this - # fig.tight_layout() - yield fig + cbar = fig.colorbar( + sm, + ax=axes.ravel().tolist(), + label=info.xlabel, + aspect=100, + ) + if categorical: + cbar.set_ticks(np.linspace(0.5, num_categories - 0.5, num_categories)) + cbar.ax.set_yticklabels(categorical_keys) + #TODO: Fix title for this + #fig.tight_layout() + yield fig @figure def plot_obscorrs(corrpair_datasets, obs_obs_correlations, pdf): @@ -1225,14 +1254,14 @@ def plot_xq2( highlight_datasets = set() def next_options(): - # Get the colors + #Get the colors prop_settings = mpl.rcParams['axes.prop_cycle'] - # Apparently calling the object gives us an infinite cycler + #Apparently calling the object gives us an infinite cycler settings_cycler = prop_settings() - # So far, I don't understand how this is done with mpl "cycler" - # objects, or wether I like it. So far this is godd enough - for markeropts, settings in zip(plotutils.marker_iter_plot(), settings_cycler): - # Override last with first + #So far, I don't understand how this is done with mpl "cycler" + #objects, or wether I like it. So far this is godd enough + for markeropts, settings in zip(plotutils.marker_iter_plot(), settings_cycler): + #Override last with first options = { 'linestyle': 'none', **markeropts, @@ -1243,7 +1272,7 @@ def next_options(): next_opts = next_options() key_options = {} - for experiment, commondata, fitted, masked, group in dataset_inputs_by_groups_xq2map: + for (experiment, commondata, fitted, masked, group) in dataset_inputs_by_groups_xq2map: info = get_info(commondata) if marker_by == 'process type': key = info.process_description diff --git a/validphys2/src/validphys/eff_exponents.py b/validphys2/src/validphys/eff_exponents.py index 0a3a6c7a1f..6ed9b168e1 100644 --- a/validphys2/src/validphys/eff_exponents.py +++ b/validphys2/src/validphys/eff_exponents.py @@ -599,5 +599,8 @@ def iterated_runcard_yaml(fit, update_runcard_description_yaml): closuretest_data = filtermap["closuretest"] if "filterseed" in closuretest_data: closuretest_data["filterseed"] = random.randrange(0, maxint) + + if "fiatlux" in filtermap: + filtermap['fiatlux']['luxset'] = fit.name return yaml.dump(filtermap, Dumper=yaml.RoundTripDumper) diff --git a/validphys2/src/validphys/gridvalues.py b/validphys2/src/validphys/gridvalues.py index 83628a9997..96d2e3aacb 100644 --- a/validphys2/src/validphys/gridvalues.py +++ b/validphys2/src/validphys/gridvalues.py @@ -32,6 +32,8 @@ 'csbar': r'c\bar{s}', 'pp': r'\gamma\gamma', 'gp': r'g\gamma', + 'zlum1': r'u\bar{u} + d\bar{d}', + 'wlum1': r'u\bar{d} + d\bar{u}', } QUARK_COMBINATIONS = { @@ -115,6 +117,15 @@ def central_grid_values(pdf: PDF, flmat, xmat, qmat): # TODO: Investigate writting these in cython/cffi/numba/... +def _parton_pair_lumi_inner(pdf_set, n, mx, x1, x2, i, j): + """Helper to evaluate lumis for pairs of partons.""" + # fmt: off + return ( + pdf_set.xfxQ(x1, mx, n, i)*pdf_set.xfxQ(x2, mx, n, j) + + pdf_set.xfxQ(x1, mx, n, j)*pdf_set.xfxQ(x2, mx, n, i) + ) + + def evaluate_luminosity( pdf_set: LHAPDFSet, n: int, s: float, mx: float, x1: float, x2: float, channel ): @@ -155,11 +166,24 @@ def evaluate_luminosity( # as in the second of Eq.(4) in arXiv:1607.01831 res = sum(a*b for a,b in itertools.product(r1,r2)) + elif channel == 'zlum1': + u, ubar = 2, -2 + d, dbar = -1, 1 + res = ( + _parton_pair_lumi_inner(pdf_set=pdf_set, n=n, mx=mx, x1=x1, x2=x2, i=u, j=ubar) + + _parton_pair_lumi_inner(pdf_set=pdf_set, n=n, mx=mx, x1=x1, x2=x2, i=d, j=dbar) + ) + elif channel == 'wlum1': + u, dbar = 2, -1 + d, ubar = 1, -2 + res = ( + _parton_pair_lumi_inner(pdf_set=pdf_set, n=n, mx=mx, x1=x1, x2=x2, i=u, j=dbar) + + _parton_pair_lumi_inner(pdf_set=pdf_set, n=n, mx=mx, x1=x1, x2=x2, i=d, j=ubar) + ) + elif channel in QUARK_COMBINATIONS.keys(): i, j = QUARK_COMBINATIONS[channel] - res = (pdf_set.xfxQ(x1, mx, n, i) * pdf_set.xfxQ(x2, mx, n, j) - + pdf_set.xfxQ(x1, mx, n, j) * pdf_set.xfxQ(x2, mx, n, i)) - + res = _parton_pair_lumi_inner(pdf_set=pdf_set, n=n, mx=mx, x1=x1, x2=x2, i=i, j=j) else: raise ValueError("Bad channel") # fmt: on diff --git a/validphys2/src/validphys/pdfplots.py b/validphys2/src/validphys/pdfplots.py index 07cc497f4c..3c6a74fffd 100644 --- a/validphys2/src/validphys/pdfplots.py +++ b/validphys2/src/validphys/pdfplots.py @@ -824,7 +824,7 @@ def plot_lumi1d( ax.set_title( f"${LUMI_CHANNELS[lumi_channel]}$ luminosity\n" f"$\\sqrt{{s}}={format_number(sqrts/1000)}$ TeV " - f"$\\|y|<{format_number(y_cut)}$" + f"$\\|y\\|<{format_number(y_cut)}$" ) return fig diff --git a/validphys2/src/validphys/photon/compute.py b/validphys2/src/validphys/photon/compute.py index 657e807ba2..7a0c1638b7 100644 --- a/validphys2/src/validphys/photon/compute.py +++ b/validphys2/src/validphys/photon/compute.py @@ -17,9 +17,9 @@ log = logging.getLogger(__name__) +# not the complete fiatlux runcard since some parameters are set in the code FIATLUX_DEFAULT = { "apfel": False, - "eps_base": 1e-5, # precision on final integration of double integral. "eps_rel": 1e-1, # extra precision on any single integration. "mum_proton": 2.792847356, # proton magnetic moment, from # http://pdglive.lbl.gov/DataBlock.action?node=S016MM which itself @@ -59,6 +59,15 @@ def __init__(self, theoryid, lux_params, replicas): # This is going to be changed in favor of a bool em_running # in the runcard fiatlux_runcard["mproton"] = theory["MP"] + + # precision on final integration of double integral + if "eps_base" in lux_params: + fiatlux_runcard["eps_base"] = lux_params["eps_base"] + log.warning(f"Using fiatlux parameter eps_base from runcard") + else: + fiatlux_runcard["eps_base"] = 1e-5 + log.info(f"Using default value for fiatlux parameter eps_base") + self.replicas = replicas # structure functions @@ -66,13 +75,11 @@ def __init__(self, theoryid, lux_params, replicas): self.additional_errors = lux_params["additional_errors"] self.luxseed = lux_params["luxseed"] - # TODO : maybe find a different name for fiatlux_dis_F2 - path_to_F2 = theoryid.path / "fastkernel/fiatlux_dis_F2.pineappl.lz4" - path_to_FL = theoryid.path / "fastkernel/fiatlux_dis_FL.pineappl.lz4" + path_to_F2 = theoryid.path / "fastkernel/FIATLUX_DIS_F2.pineappl.lz4" + path_to_FL = theoryid.path / "fastkernel/FIATLUX_DIS_FL.pineappl.lz4" self.path_to_eko_photon = theoryid.path / "eko_photon.tar" with EKO.read(self.path_to_eko_photon) as eko: self.q_in = np.sqrt(eko.mu20) - # set fiatlux self.lux = {} @@ -89,7 +96,7 @@ def __init__(self, theoryid, lux_params, replicas): fl = sf.InterpStructureFunction(path_to_FL, self.luxpdfset.members[replica]) if not np.isclose(f2.q2_max, fl.q2_max): log.error( - "FKtables for fiatlux_dis_F2 and fiatlux_dis_FL have two different q2_max" + "FKtables for FIATLUX_DIS_F2 and FIATLUX_DIS_FL have two different q2_max" ) fiatlux_runcard["q2_max"] = float(f2.q2_max) @@ -112,7 +119,9 @@ def __init__(self, theoryid, lux_params, replicas): self.lux[replica].PlugStructureFunctions(f2.fxq, fl.fxq, f2lo.fxq) photon_array = self.compute_photon_array(replica) - self.interpolator.append(interp1d(XGRID, photon_array, fill_value=0.0, kind="cubic")) + self.interpolator.append( + interp1d(XGRID, photon_array, fill_value="extrapolate", kind="cubic") + ) self.integral.append(trapezoid(photon_array, XGRID)) def compute_photon_array(self, replica): @@ -131,7 +140,9 @@ def compute_photon_array(self, replica): """ # Compute photon PDF log.info(f"Computing photon") - photon_qin = np.array([self.lux[replica].EvaluatePhoton(x, self.q_in**2).total for x in XGRID]) + photon_qin = np.array( + [self.lux[replica].EvaluatePhoton(x, self.q_in**2).total for x in XGRID] + ) photon_qin += self.generate_errors(replica) # fiatlux computes x * gamma(x) photon_qin /= XGRID diff --git a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml index a1f7b7c681..a74805c98c 100644 --- a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml +++ b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml @@ -24,6 +24,32 @@ scale_variations_for: (2, 1): 408 (2, 2): 409 +#alpha=0.117 + - theoryid: 528 + variations: + (0.5, 0.5): 401 + (0.5, 1): 402 + (0.5, 2): 403 + (1, 0.5): 404 + (1, 1): 405 + (1, 2): 406 + (2, 0.5): 407 + (2, 1): 408 + (2, 2): 409 + +#alpha=0.119 + - theoryid: 529 + variations: + (0.5, 0.5): 401 + (0.5, 1): 402 + (0.5, 2): 403 + (1, 0.5): 404 + (1, 1): 405 + (1, 2): 406 + (2, 0.5): 407 + (2, 1): 408 + (2, 2): 409 + - theoryid: 414 variations: (0.5, 0.5): 410 @@ -48,6 +74,32 @@ scale_variations_for: (2, 1): 427 (2, 2): 428 +#alpha=0.117 + - theoryid: 530 + variations: + (0.5, 0.5): 420 + (0.5, 1): 421 + (0.5, 2): 422 + (1, 0.5): 423 + (1, 1): 424 + (1, 2): 425 + (2, 0.5): 426 + (2, 1): 427 + (2, 2): 428 + +#alpha=0.119 + - theoryid: 531 + variations: + (0.5, 0.5): 420 + (0.5, 1): 421 + (0.5, 2): 422 + (1, 0.5): 423 + (1, 1): 424 + (1, 2): 425 + (2, 0.5): 426 + (2, 1): 427 + (2, 2): 428 + - theoryid: 434 variations: (0.5, 0.5): 430 diff --git a/validphys2/src/validphys/tests/baseline/test_plot_smpdf.png b/validphys2/src/validphys/tests/baseline/test_plot_smpdf.png index 7274fa0469..883dc4d077 100644 Binary files a/validphys2/src/validphys/tests/baseline/test_plot_smpdf.png and b/validphys2/src/validphys/tests/baseline/test_plot_smpdf.png differ diff --git a/validphys2/src/validphys/tests/baseline/test_plot_smpdf_categorical.png b/validphys2/src/validphys/tests/baseline/test_plot_smpdf_categorical.png new file mode 100644 index 0000000000..42349bad95 Binary files /dev/null and b/validphys2/src/validphys/tests/baseline/test_plot_smpdf_categorical.png differ diff --git a/validphys2/src/validphys/tests/conftest.py b/validphys2/src/validphys/tests/conftest.py index 0f36cd2455..75d35c718c 100644 --- a/validphys2/src/validphys/tests/conftest.py +++ b/validphys2/src/validphys/tests/conftest.py @@ -27,6 +27,8 @@ def tmp(tmpdir): SINGLE_DATASET = {'dataset': 'NMC'} +SINGLE_CATEGORICAL = {"dataset": "ATLAS_WZ_TOT_13TEV", 'cfac': ["QCD"]} + DATA = [ {'dataset': 'NMC'}, {'dataset': 'ATLASTTBARTOT', 'cfac':['QCD']}, @@ -54,6 +56,7 @@ def tmp(tmpdir): HESSIAN_PDF = "NNPDF40_nnlo_as_01180_hessian" THEORYID = 162 THEORYID_NEW = 399 +THEORY_QED = 398 FIT = "NNPDF40_nnlo_lowprecision" FIT_3REPLICAS = "Basic_runcard_3replicas_lowprec_221130" FIT_3REPLICAS_DCUTS = "Basic_runcard_3replicas_diffcuts_230221" @@ -95,6 +98,16 @@ def single_data_internal_cuts_config(data_internal_cuts_config): config_dict.update(dataset_input=DATA[0]) return config_dict +@pytest.fixture(scope='module') +def single_data_categorical_internal_cuts_config(data_internal_cuts_config): + """Test dataset with categorical plotting variables""" + return { + **data_internal_cuts_config, + 'dataset_input': SINGLE_CATEGORICAL, + # NOTE: The old theory is currently bugged for this dataset + 'theoryid': THEORYID_NEW, + } + @pytest.fixture(scope='module') def single_data_single_point_internal_cuts_config(single_data_internal_cuts_config): config_dict = dict(single_data_internal_cuts_config) diff --git a/validphys2/src/validphys/tests/photon/test_compute.py b/validphys2/src/validphys/tests/photon/test_compute.py index f61b13a6bd..bd7a65c862 100644 --- a/validphys2/src/validphys/tests/photon/test_compute.py +++ b/validphys2/src/validphys/tests/photon/test_compute.py @@ -1,158 +1,86 @@ -from collections import namedtuple -from pathlib import Path +import tempfile import fiatlux import numpy as np -from validphys.photon import structure_functions -from validphys.photon.compute import Photon, Alpha -from validphys.core import PDF as PDFset +import yaml -from ..conftest import PDF from eko.io import EKO +from n3fit.io.writer import XGRID +from validphys.api import API +from validphys.core import PDF as PDFset +from validphys.loader import FallbackLoader +from validphys.photon import structure_functions as sf +from validphys.photon.compute import FIATLUX_DEFAULT, Alpha, Photon +from ..conftest import PDF, THEORY_QED -class FakeTheory: - def __init__(self): - self.path = Path("/fake/path/") - - def get_description(self): - return { - "alphaqed": 0.01, - "Qref": 91.2, - "Qedref": 91.2, - "mc": 1.3, - "mb": 4.92, - "mt": 172.0, - "kcThr": 1.0, - "kbThr": 1.0, - "ktThr": 1.0, - "MaxNfAs": 5, - "MaxNfPdf": 5, - "MP": 0.938 - } - - -fiatlux_runcard = { - "luxset": PDFset(PDF), - "additional_errors": False, - "luxseed": 123456789 -} - -photon = namedtuple("photon", ["total", "elastic", "inelastic"]) - - -class FakeFiatlux: - def __init__(self, runcard): - self.runcard = runcard - self.alphaem = None - self.qref = None - self.trash1 = None - self.trash2 = None - self.f2 = None - self.fl = None - self.f2lo = None - self.res = photon(0., 0., 0.) - - def PlugAlphaQED(self, alphaem, qref): - self.alphaem = alphaem - self.qref = qref - - def InsertInelasticSplitQ(self, args): - self.trash1 = args[0] - self.trash2 = args[1] - - def PlugStructureFunctions(self, f2, fl, f2lo): - self.f2 = f2 - self.fl = fl - self.f2lo = f2lo - - def EvaluatePhoton(self, x, q): - return self.res - -class FakeEKO: - def __init__(self, path): - self.path = path - self.mu20 = 100**2 - - def __enter__(self): - return self - - def __exit__(self, exc_type: type, _exc_value, _traceback): - pass - - -class FakeStructureFunction: - def __init__(self, path, pdfs): - self.path = path - self.pdfs = pdfs - self.q2_max = 1e8 - - def fxq(self): - return 0 - - -class FakeF2LO: - def __init__(self, pdfs, theory): - self.pdfs = pdfs - self.theory = theory - - def fxq(self): - return 0 - - -def test_parameters_init(monkeypatch): - monkeypatch.setattr( - structure_functions, "InterpStructureFunction", FakeStructureFunction - ) - monkeypatch.setattr(structure_functions, "F2LO", FakeF2LO) - monkeypatch.setattr(fiatlux, "FiatLux", FakeFiatlux) - monkeypatch.setattr(Photon, "compute_photon_array", lambda *args: np.zeros(196)) - monkeypatch.setattr(EKO, "read", FakeEKO) - photon = Photon(FakeTheory(), fiatlux_runcard, [1, 2, 3]) - alpha = Alpha(FakeTheory().get_description()) +def generate_fiatlux_runcard(): + return { + "luxset": PDFset(PDF), + # check if "LUXqed17_plus_PDF4LHC15_nnlo_100" is installed + "additional_errors": FallbackLoader().check_pdf("LUXqed17_plus_PDF4LHC15_nnlo_100"), + "luxseed": 123456789, + "eps_base": 1e-2, # using low precision to speed up tests + } + + +def test_parameters_init(): + "test initailization of the parameters from Photon class" + fiatlux_runcard = generate_fiatlux_runcard() + test_theory = API.theoryid(theoryid=THEORY_QED) + + # we are not testing the photon here so we make it faster + fiatlux_runcard['eps_base'] = 1e-1 + + photon = Photon(test_theory, fiatlux_runcard, [1, 2, 3]) np.testing.assert_equal(photon.replicas, [1, 2, 3]) np.testing.assert_equal(photon.luxpdfset._name, fiatlux_runcard["luxset"].name) - np.testing.assert_equal(photon.additional_errors, fiatlux_runcard["additional_errors"]) + np.testing.assert_equal(photon.additional_errors.name, "LUXqed17_plus_PDF4LHC15_nnlo_100") np.testing.assert_equal(photon.luxseed, fiatlux_runcard["luxseed"]) - np.testing.assert_almost_equal( - alpha.alpha_em_ref, FakeTheory().get_description()["alphaqed"] - ) + np.testing.assert_equal(photon.path_to_eko_photon, test_theory.path / "eko_photon.tar") + np.testing.assert_equal(photon.q_in, 100.0) + def test_masses_init(): - alpha = Alpha(FakeTheory().get_description()) + "test thresholds values in Alpha class" + test_theory = API.theoryid(theoryid=THEORY_QED) + theory = test_theory.get_description() + alpha = Alpha(theory) np.testing.assert_equal(alpha.thresh_t, np.inf) - np.testing.assert_almost_equal(alpha.thresh_b, 4.92) - np.testing.assert_almost_equal(alpha.thresh_c, 1.3) + np.testing.assert_almost_equal(alpha.thresh_b, theory["mb"]) + np.testing.assert_almost_equal(alpha.thresh_c, theory["mc"]) -def test_set_thresholds_alpha_em(monkeypatch): - monkeypatch.setattr( - structure_functions, "InterpStructureFunction", FakeStructureFunction - ) - monkeypatch.setattr(structure_functions, "F2LO", FakeF2LO) - monkeypatch.setattr(fiatlux, "FiatLux", FakeFiatlux) - monkeypatch.setattr(Photon, "compute_photon_array", lambda *args: np.zeros(196)) +def test_set_thresholds_alpha_em(): + "test value of alpha_em at threshold values" + test_theory = API.theoryid(theoryid=THEORY_QED) + theory = test_theory.get_description() - alpha = Alpha(FakeTheory().get_description()) + alpha = Alpha(theory) - np.testing.assert_almost_equal(alpha.thresh[5], 91.2) - np.testing.assert_almost_equal(alpha.thresh[4], 4.92) - np.testing.assert_almost_equal(alpha.thresh[3], 1.3) - np.testing.assert_almost_equal(alpha.alpha_thresh[5], 0.01) + np.testing.assert_almost_equal(alpha.alpha_em_ref, theory["alphaqed"]) + np.testing.assert_almost_equal(alpha.thresh[5], theory["Qedref"]) + np.testing.assert_almost_equal(alpha.thresh[4], theory["mb"]) + np.testing.assert_almost_equal(alpha.thresh[3], theory["mc"]) + np.testing.assert_almost_equal(alpha.alpha_thresh[5], theory["alphaqed"]) np.testing.assert_almost_equal( - alpha.alpha_thresh[4], alpha.alpha_em_fixed_flavor(4.92, 0.01, 91.2, 5) + alpha.alpha_thresh[4], + alpha.alpha_em_fixed_flavor(theory["mb"], theory["alphaqed"], theory["Qedref"], 5), ) np.testing.assert_almost_equal( alpha.alpha_thresh[3], - alpha.alpha_em_fixed_flavor(1.3, alpha.alpha_thresh[4], 4.92, 4), + alpha.alpha_em_fixed_flavor(theory["mc"], alpha.alpha_thresh[4], theory["mb"], 4), ) np.testing.assert_equal(len(alpha.alpha_thresh), 3) np.testing.assert_equal(len(alpha.thresh), 3) + def test_betas(): - alpha = Alpha(FakeTheory().get_description()) + "test betas for different nf" + test_theory = API.theoryid(theoryid=THEORY_QED) + alpha = Alpha(test_theory.get_description()) vec_beta0 = [ -0.5305164769729844, -0.6719875374991137, @@ -168,3 +96,75 @@ def test_betas(): for nf in range(3, 6 + 1): np.testing.assert_allclose(alpha.beta0[nf], vec_beta0[nf - 3], rtol=1e-7) np.testing.assert_allclose(alpha.b1[nf], vec_b1[nf - 3], rtol=1e-7) + + +def test_photon(): + """test that photon coming out of Photon interpolator matches the photon array + for XGRID points + """ + fiatlux_runcard = generate_fiatlux_runcard() + fiatlux_runcard["additional_errors"] = False + test_theory = API.theoryid(theoryid=THEORY_QED) + theory = test_theory.get_description() + + for replica in [1, 2, 3]: + photon = Photon(test_theory, fiatlux_runcard, [replica]) + + # set up fiatlux + path_to_F2 = test_theory.path / "fastkernel/FIATLUX_DIS_F2.pineappl.lz4" + path_to_FL = test_theory.path / "fastkernel/FIATLUX_DIS_FL.pineappl.lz4" + pdfs = fiatlux_runcard["luxset"].load() + f2 = sf.InterpStructureFunction(path_to_F2, pdfs.members[replica]) + fl = sf.InterpStructureFunction(path_to_FL, pdfs.members[replica]) + f2lo = sf.F2LO(pdfs.members[replica], theory) + + # runcard + fiatlux_default = FIATLUX_DEFAULT.copy() + fiatlux_default['mproton'] = theory['MP'] + fiatlux_default["qed_running"] = bool(np.isclose(theory["Qedref"], theory["Qref"])) + fiatlux_default["q2_max"] = float(f2.q2_max) + fiatlux_default["eps_base"] = fiatlux_runcard["eps_base"] + + # load fiatlux + with tempfile.NamedTemporaryFile(mode="w") as tmp: + with tmp.file as tmp_file: + tmp_file.write(yaml.dump(FIATLUX_DEFAULT)) + lux = fiatlux.FiatLux(tmp.name) + + alpha = Alpha(theory) + + lux.PlugAlphaQED(alpha.alpha_em, alpha.qref) + lux.InsertInelasticSplitQ( + [ + theory["kbThr"] * theory["mb"], + theory["ktThr"] * theory["mt"] if theory["MaxNfPdf"] == 6 else 1e100, + ] + ) + lux.PlugStructureFunctions(f2.fxq, fl.fxq, f2lo.fxq) + path_to_eko_photon = test_theory.path / "eko_photon.tar" + with EKO.read(path_to_eko_photon) as eko: + photon_fiatlux_qin = np.array([lux.EvaluatePhoton(x, eko.mu20).total for x in XGRID]) + photon_fiatlux_qin /= XGRID + # construct PDFs + pdfs_init = np.zeros((len(eko.bases.inputpids), len(XGRID))) + for j, pid in enumerate(eko.bases.inputpids): + if pid == 22: + pdfs_init[j] = photon_fiatlux_qin + ph_id = j + else: + if pid not in pdfs.flavors: + continue + pdfs_init[j] = np.array( + [pdfs.xfxQ(x, np.sqrt(eko.mu20), replica, pid) / x for x in XGRID] + ) + + # Apply EKO to PDFs + for _, elem in eko.items(): + pdfs_final = np.einsum("ajbk,bk", elem.operator, pdfs_init) + + photon_Q0 = pdfs_final[ph_id] + photon_fiatlux = XGRID * photon_Q0 + + photon_validphys = photon(XGRID[np.newaxis, :, np.newaxis])[0][0, :, 0] + + np.testing.assert_allclose(photon_fiatlux, photon_validphys, rtol=1e-7) diff --git a/validphys2/src/validphys/tests/photon/test_structurefunctions.py b/validphys2/src/validphys/tests/photon/test_structurefunctions.py index 984eb2eecd..879f552c73 100644 --- a/validphys2/src/validphys/tests/photon/test_structurefunctions.py +++ b/validphys2/src/validphys/tests/photon/test_structurefunctions.py @@ -1,7 +1,11 @@ import numpy as np import pineappl + +from validphys.api import API +from validphys.core import PDF as PDFset import validphys.photon.structure_functions as sf -from validphys.lhapdfset import LHAPDFSet + +from ..conftest import PDF, THEORY_QED class ZeroPdfs: @@ -9,35 +13,12 @@ def xfxQ(self, x, Q): res = {} for i in range(1, 6 + 1): res[i] = res[-i] = 0.0 + res[21] = 0.0 + res[22] = 0.0 return res - -def test_zero_pdfs(): - - pdfs = ZeroPdfs() - - fake_theory = { - "mc": 1.3, - "mb": 5.0, - "mt": 172.0, - "kcThr": 1.0, - "kbThr": 1.0, - "ktThr": 1.0, - "MaxNfPdf": 5, - } - - f2lo = sf.F2LO(pdfs, fake_theory) - - np.testing.assert_equal(f2lo.thresh_t, np.inf) - - for x in np.geomspace(1e-4, 1.0, 10): - for Q in np.geomspace(10, 1000000, 10): - np.testing.assert_allclose(f2lo.fxq(x, Q), 0.0) - - -class FakeSet: - def get_entry(self, string): - return 0 + def xfxQ2(self, i, x, Q2): + return self.xfxQ(x, np.sqrt(Q2))[i] class ZeroFKTable: @@ -58,70 +39,72 @@ def convolute_with_one(self, pdgid, xfxQ2): return np.zeros((10, 10)) -class OnePdf: - def __init__(self): - self.ao = 1 - - def xfxQ(self, x, Q): - return 1.0 - - def xfxQ2(self, x, Q): - return 1.0**2 - - def set(self): - return FakeSet() - - -class OneFKTable: - def __init__(self, path): - self.path = path - self.xgrid = np.geomspace(1e-4, 1.0, 10) - self.qgrid = np.geomspace(1.65, 1000, 10) - - def bin_left(self, i): - if i == 1: - return self.xgrid - if i == 0: - return self.qgrid - else: - return 0 - - def convolute_with_one(self, pdgid, xfxQ2): - return np.zeros((10, 10)) - - -class ZeroPdf: - def __init__(self): - self.ao = 1 +def test_zero_pdfs(): + "test that a zero PDF gives a zero structure function" + pdfs = ZeroPdfs() + test_theory = API.theoryid(theoryid=THEORY_QED) + theory = test_theory.get_description() + path_to_F2 = test_theory.path / "fastkernel/FIATLUX_DIS_F2.pineappl.lz4" + path_to_FL = test_theory.path / "fastkernel/FIATLUX_DIS_FL.pineappl.lz4" - def xfxQ(self, x, Q): - return 1.0 + f2 = sf.InterpStructureFunction(path_to_F2, pdfs) + fl = sf.InterpStructureFunction(path_to_FL, pdfs) + f2lo = sf.F2LO(pdfs, theory) - def xfxQ2(self, x, Q): - return 1.0**2 + np.testing.assert_equal(f2lo.thresh_t, np.inf) - def set(self): - return FakeSet() + for x in np.geomspace(1e-4, 1.0, 10): + for Q in np.geomspace(10, 1000000, 10): + np.testing.assert_allclose(f2lo.fxq(x, Q), 0.0) + np.testing.assert_allclose(f2.fxq(x, Q), 0.0) + np.testing.assert_allclose(fl.fxq(x, Q), 0.0) -def test_F2(monkeypatch): - # grid put to 0 and pdf put to 1 +def test_zero_grid(monkeypatch): + "test that a zero grid gives a zero structure function" + # patching pineappl.fk_table.FkTable to use ZeroFKTable monkeypatch.setattr(pineappl.fk_table.FkTable, "read", ZeroFKTable) - structurefunc = sf.InterpStructureFunction("", OnePdf()) + pdfs = PDFset(PDF).load() + structurefunc = sf.InterpStructureFunction("", pdfs.central_member) for x in np.geomspace(1e-4, 1.0, 10): for Q in np.geomspace(10, 1000000, 10): np.testing.assert_allclose(structurefunc.fxq(x, Q), 0.0, rtol=1e-5) - # grid put to 0 and real pdf - pdf = LHAPDFSet("NNPDF40_nnlo_as_01180", "replicas") - structurefunc = sf.InterpStructureFunction("", pdf.central_member) - for x in np.geomspace(1e-4, 1.0, 10): - for Q in np.geomspace(10, 1000000, 10): - np.testing.assert_allclose(structurefunc.fxq(x, Q), 0.0, rtol=1e-5) - # grid put to 1 and pdf put to 0 - monkeypatch.setattr(pineappl.fk_table.FkTable, "read", OneFKTable) - structurefunc = sf.InterpStructureFunction("", ZeroPdf()) - for x in np.geomspace(1e-4, 1.0, 10): - for Q in np.geomspace(10, 1000000, 10): - np.testing.assert_allclose(structurefunc.fxq(x, Q), 0.0, rtol=1e-5) +def test_params(): + "test initialization of parameters" + pdfs = PDFset(PDF).load() + replica = 1 + test_theory = API.theoryid(theoryid=THEORY_QED) + theory = test_theory.get_description() + for channel in ["F2", "FL"]: + tmp = "fastkernel/FIATLUX_DIS_" + channel + ".pineappl.lz4" + path_to_fktable = test_theory.path / tmp + struct_func = sf.InterpStructureFunction(path_to_fktable, pdfs.members[replica]) + np.testing.assert_allclose(struct_func.q2_max, 1e8) + f2lo = sf.F2LO(pdfs.members[replica], theory) + np.testing.assert_allclose(f2lo.thresh_c, theory["mc"]) + np.testing.assert_allclose(f2lo.thresh_b, theory["mb"]) + np.testing.assert_allclose(f2lo.thresh_t, np.inf) + + +def test_interpolation_grid(): + """test that the values coming out of InterpStructureFunction match the grid ones""" + pdfs = PDFset(PDF).load() + test_theory = API.theoryid(theoryid=THEORY_QED) + for replica in [1, 2, 3]: + for channel in ["F2", "FL"]: + tmp = "fastkernel/FIATLUX_DIS_" + channel + ".pineappl.lz4" + path_to_fktable = test_theory.path / tmp + fktable = pineappl.fk_table.FkTable.read(path_to_fktable) + x = np.unique(fktable.bin_left(1)) + q2 = np.unique(fktable.bin_left(0)) + predictions = fktable.convolute_with_one(2212, pdfs.members[replica].xfxQ2) + grid2D = predictions.reshape(len(x), len(q2)) + + struct_func = sf.InterpStructureFunction(path_to_fktable, pdfs.members[replica]) + for i, x_ in enumerate(x): + for j, q2_ in enumerate(q2): + np.testing.assert_allclose( + struct_func.fxq(x_, np.sqrt(q2_)), grid2D[i, j], rtol=1e-5 + ) diff --git a/validphys2/src/validphys/tests/test_plots.py b/validphys2/src/validphys/tests/test_plots.py index 004514c71b..da85cc5cd5 100644 --- a/validphys2/src/validphys/tests/test_plots.py +++ b/validphys2/src/validphys/tests/test_plots.py @@ -40,6 +40,11 @@ def test_dataspecschi2(): def test_plot_smpdf(single_data_internal_cuts_config): return next(API.plot_smpdf(**single_data_internal_cuts_config)) +@pytest.mark.linux +@pytest.mark.mpl_image_compare +def test_plot_smpdf_categorical(single_data_categorical_internal_cuts_config): + return next(API.plot_smpdf(**single_data_categorical_internal_cuts_config)) + @pytest.mark.linux @pytest.mark.mpl_image_compare def test_plot_obscorrs(single_data_internal_cuts_config): diff --git a/validphys2/src/validphys/theorycovariance/output.py b/validphys2/src/validphys/theorycovariance/output.py index 2eab9d20c3..7299579863 100644 --- a/validphys2/src/validphys/theorycovariance/output.py +++ b/validphys2/src/validphys/theorycovariance/output.py @@ -128,7 +128,7 @@ def plot_covmat_heatmap(covmat, title): return fig -_procorder = ("DIS NC", "DIS CC", "DY", "JETS", "TOP") +_procorder = ("DIS NC", "DIS CC", "TOP", "DY NC", "DY CC", "SINGLETOP", "JETS", "PHOTON", "DIJET") _dsorder = ( "BCDMSP",