int main(){
std::vector<Double_t> radii;
radii.push_back(2.0); // 1.
radii.push_back(3.0); // 3.5
radii.push_back(6.0);
radii.push_back(9.0);
radii.push_back(17.0);
radii.push_back(20.0);
radii.push_back(25.5);
radii.push_back(28.0); //Added!!!
radii.push_back(30.0);
radii.push_back(34.0);
radii.push_back(36.5); //Added!!!
radii.push_back(38.0);
radii.push_back(46.0);
radii.push_back(54.5); // 54.0
radii.push_back(57.0);
radii.push_back(61.5); // 61.0
radii.push_back(65.0);
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-26., 26., 1., 20.));
geoCuts.push_back(GeoCut(-66., 66., 20., 65.));
Double_t boxSize = 30.;
MatPlot myPlot("XY", -boxSize, boxSize, -boxSize, boxSize, 0.2, 0.05);
myPlot.SetEffRadii(&radii);
myPlot.SetGeoCuts(&geoCuts);
//
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
TChain *convmc = new TChain("ntupleR2S");
convmc->Add("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
convmc->Add("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04_v2.root");
niR2SforMatPlot convMC(convmc);
// niR2SforMatPlot convMC("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
myPlot.FillMC(&convMC); // All events
TChain *convsim = new TChain("ntupleS2R");
convsim->Add("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
convsim->Add("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04_v2.root");
niS2RforMatPlot convSim(convsim);
// niS2RforMatPlot convSim("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
// myPlot.responseTrain(&convSim, &convMC, 5000000, 20000000); //Remaining events
myPlot.FillSim(&convSim); // All events
niR2SforMatPlot convData("../7TeV/ntuple_nuclint_CMSSW358p3_goodcoll7TeV_2010-06-04.root");
convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
myPlot.FillData(&convData);
// myPlot.doUnfold();
myPlot.test();
myPlot.PlotAll();
}
int main(){
Double_t pi = 3.141592653589793;
std::vector<GeoCut> geoCuts;
Double_t thetaMax = 2.*atan(exp(1.));
Double_t thetaMin = 2.*atan(exp(-1.));
std::cout << " thetaMin " << thetaMin << " thetaMax " << thetaMax << std::endl;
// eta = -log(tan(theta/2.)) ==> theta= 2.*tan(exp(-eta))
geoCuts.push_back(GeoCut(thetaMin, thetaMax, 2., 13.));
Double_t binW = (thetaMax-thetaMin)/40.;
std::cout << " thetaMin " << thetaMin << " thetaMax " << thetaMax << " binW " << binW << std::endl;
MatPlot myPlot("Theta", thetaMin, thetaMax, binW, binW, -1.);
myPlot.SetGeoCuts(&geoCuts);
myPlot.SetUIndex(5, 5);
myPlot.SetVIndex(0, 4);
//
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
//MC Reco
//
#include "src/files_conv_minbias_reco.cxx"
convR2SforMatPlot convMC(mc);
myPlot.FillMC(&convMC);
//MC Sim
//
#include "src/files_conv_minbias_sim.cxx"
convS2RforMatPlot convSim(sim);
myPlot.FillSim(&convSim, 1, 10000000);
//Data
//
#include "src/files_conv_run2012ABCD.cxx"
convR2SforMatPlot convData(data);
// convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
//
// run2012D
// https://twiki.cern.ch/twiki/bin/viewauth/CMS/TkAlignmentPixelPosition
convData.SetCenterCoord(-0.10822, -0.376969, -0.410475);
myPlot.FillData(&convData);
myPlot.test();
myPlot.PlotAll();
}
int main(){
std::vector<Double_t> radii;
radii.push_back(1.0);
radii.push_back(6.0);
radii.push_back(9.0);
radii.push_back(17.0);
radii.push_back(20.0);
radii.push_back(25.5);
radii.push_back(30.0);
radii.push_back(34.0);
radii.push_back(38.0);
radii.push_back(46.0);
radii.push_back(54.0);
radii.push_back(57.0);
radii.push_back(61.0);
radii.push_back(65.0);
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-33., -29., 1., 30.));
Double_t boxSize = 30.;
MatPlot myPlot("XY", -boxSize, boxSize, -boxSize, boxSize, 0.2, 0.05);
myPlot.SetEffRadii(&radii);
myPlot.SetGeoCuts(&geoCuts);
/*
// Normalization factors
Float_t nDataEv = 10809460;
Float_t nSimEv = 6106513;
// Float_t nSimEv = 6106513*5./11.;
Float_t scaleFact = nDataEv/nSimEv;
myPlot.SetMCScaleFact(scaleFact);
myPlot.SetSimScaleFact(scaleFact);
myPlot.SetDataScaleFact(1.);
*/
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
niR2SforMatPlot convMC("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
myPlot.FillMC(&convMC); // All events
niS2RforMatPlot convSim("../7TeV/ntuple_nuclint_CMSSW358p3_minbias7TeV_2010-06-04.root");
// myPlot.responseTrain(&convSim, &convMC, 5000000, 20000000); //Remaining events
myPlot.FillSim(&convSim); // All events
niR2SforMatPlot convData("../7TeV/ntuple_nuclint_CMSSW358p3_goodcoll7TeV_2010-06-04.root");
convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
myPlot.FillData(&convData);
// myPlot.doUnfold();
myPlot.test();
myPlot.PlotAll();
}
int main(){
Double_t pi = 3.141592653589793;
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(13., 29., 26., 50.));
Double_t binW = 10.*pi/180.;
MatPlot myPlot("Phi", -pi, pi, binW, binW, -1.);
myPlot.SetGeoCuts(&geoCuts);
myPlot.SetUIndex(6, 3); //phi, Z
myPlot.SetVIndex(0, 4); //--, R
//
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
//MC Reco
//
#include "src/files_conv_minbias_reco.cxx"
convR2SforMatPlot convMC(mc);
myPlot.FillMC(&convMC);
//MC Sim
//
#include "src/files_conv_minbias_sim.cxx"
convS2RforMatPlot convSim(sim);
myPlot.FillSim(&convSim, 1, 10000000);
//Data
//
#include "src/files_conv_run2012ABCD.cxx"
convR2SforMatPlot convData(data);
// convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
//
// run2012D
// https://twiki.cern.ch/twiki/bin/viewauth/CMS/TkAlignmentPixelPosition
convData.SetCenterCoord(-0.10822, -0.376969, -0.410475);
myPlot.FillData(&convData);
myPlot.test();
myPlot.PlotAll();
}
int main(){
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-26., 26., 1., 65.));
MatPlot myPlotR("R", 1., 60., 0.5, 0.5);
myPlotR.SetGeoCuts(&geoCuts);
Float_t nDataEv = 10809460;
// Float_t nSimEv = 6106513;
Float_t nSimEv = 6106513*5./11.;
Float_t scaleFact = nDataEv/nSimEv;
//
// Assumo che il numero di eventi iniziale fosse 11000000
//
// I primi 5M si usano come pseudo dati
// i secondi 6M per il training...
//
//
myPlotR.SetMCScaleFact(scaleFact);
myPlotR.SetSimScaleFact(scaleFact);
myPlotR.SetDataScaleFact(1.);
// MatPlot myPlotEta("Eta", -3., 3., 0.1, 0.01);
// myPlotEta.SetGeoCuts(&geoCuts);
// Double_t boxSize = 60.;
// MatPlot myPlotXY("XY", -boxSize, boxSize, -boxSize, boxSize, 1., 0.1);
// myPlotXY.SetGeoCuts(&geoCuts);
convR2SforMatPlot convMC("../7TeV/ntuple_conversion_CMSSW356_minbias7TeV_2010-05-10.root");
myPlotR.FillMC(&convMC, 1, 5000000); // First 5M events
// myPlotXY.FillMC(&convMC);
convS2RforMatPlot convSim("../7TeV/ntuple_conversion_CMSSW356_minbias7TeV_2010-05-10.root");
myPlotR.responseTrain(&convSim, &convMC, 5000000, 20000000); //Remaining events
myPlotR.FillSim(&convSim, 1, 5000000); // First 5000000 events
// myPlotXY.FillSim(&convSim);
convR2SforMatPlot convData("../7TeV/ntuple_conversion_goodcoll7TeV_2010-05-10.root");
myPlotR.FillData(&convData);
myPlotR.doUnfold();
// myPlotXY.FillData(&convData);
myPlotR.PlotAll();
// myPlotXY.PlotAll();
}
int main(){
Double_t rMax = 65.;
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-26., 26., 2., 20.));
geoCuts.push_back(GeoCut(-66., 66., 20., rMax));
MatPlot myPlot("R", 1., rMax, 0.5, 0.5, -1.);
myPlot.SetGeoCuts(&geoCuts);
myPlot.SetUIndex(4, 3); //Radius for plot, z for cut
myPlot.SetVIndex(0, 4); //Plot is 1d, radius for cut
//
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
//MC Reco
//
#include "src/files_conv_minbias_reco.cxx"
convR2SforMatPlot convMC(mc);
myPlot.FillMC(&convMC);
//MC Sim
//
#include "src/files_conv_minbias_sim.cxx"
convS2RforMatPlot convSim(sim);
myPlot.FillSim(&convSim, 1, 10000000);
//Data
//
#include "src/files_conv_run2012ABCD.cxx"
convR2SforMatPlot convData(data);
// convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
//
// run2012D
// https://twiki.cern.ch/twiki/bin/viewauth/CMS/TkAlignmentPixelPosition
convData.SetCenterCoord(-0.10822, -0.376969, -0.410475);
myPlot.FillData(&convData);
myPlot.test();
myPlot.PlotAll();
}
int main(){
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-26., 26., 1., 20.));
geoCuts.push_back(GeoCut(-66., 66., 20., 54.));
geoCuts.push_back(GeoCut(-105., 105., 54., 120.));
Double_t boxSize = 120.;
//MatPlot myPlot("XY", -boxSize, boxSize, -boxSize, boxSize, 1., 0.1);
//binsize, binsizesim, binsizeeff
MatPlot myPlot("XY", -boxSize, boxSize, -boxSize, boxSize, 0.5, 0.2, -1.); // era 2
myPlot.SetGeoCuts(&geoCuts);
//
myPlot.SetMCScaleFact(-1.);
myPlot.SetSimScaleFact(-1.);
myPlot.SetDataScaleFact(1.);
//MC Reco
//
#include "src/files_conv_minbias_reco.cxx"
convR2SforMatPlot convMC(mc);
myPlot.FillMC(&convMC);
//MC Sim
//
#include "src/files_conv_minbias_sim.cxx"
convS2RforMatPlot convSim(sim);
myPlot.FillSim(&convSim, 1, 10000000);
//Data
//
#include "src/files_conv_run2012D.cxx"
convR2SforMatPlot convData(data);
// convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
//
// run2012D
// https://twiki.cern.ch/twiki/bin/viewauth/CMS/TkAlignmentPixelPosition
convData.SetCenterCoord(-0.10822, -0.376969, -0.410475);
myPlot.FillData(&convData);
myPlot.test();
myPlot.PlotAll();
}
matrix *calcWeights(matrix *m, int n, int k, int *knots) {
//double w[m->rows][m->cols][n];
matrix *w;
matrix *z;
w = new_matrix(m->rows, n * m->cols);
z =convData(m, n, k);
int i, j, t;
for (i = 0; i < m->rows; ++i) {
for (t = 0; t < n; ++t) {
for (j = 0; j < m->cols; ++j) {
w->m[i][t * m->cols + j] = BSpline(t, k, z->m[i][j], knots, n);
//if (w->m[i][t*n + j] > 1)
//printf("bad weight %lf\n", w->m[i][t*n +j]);
}
}
}
/*matrix *p;
p = new_matrix(m->rows, n);
//printf("p: %d, %d\n", p->rows, p->cols);
double sum;
for (i = 0; i < m->rows; ++i) {
for (t = 0; t < n; ++t) {
sum = 0;
for (j = 0; j < m->cols; ++j) {
sum += w[i][j][t];
}
sum /= n;
p->m[i][t] = sum;
}
}
*/
//printf("p2: %d, %d\n", p->rows, p->cols);
free_matrix(z);
return w;
}
byte *doConvert(iconv_t &ctx, byte *data, size_t nIn, size_t nOut, size_t &size) {
size_t inBytes = nIn;
size_t outBytes = nOut;
ScopedArray<byte> convData(new byte[outBytes]);
byte *outBuf = convData.get();
// Reset the converter's state
iconv(ctx, 0, 0, 0, 0);
// Convert
if (iconv(ctx, const_cast<ICONV_CONST char **>(reinterpret_cast<char **>(&data)), &inBytes,
reinterpret_cast<char **>(&outBuf), &outBytes) == ((size_t) -1)) {
warning("iconv() failed: %s", strerror(errno));
return 0;
}
size = nOut - outBytes;
return convData.release();
}
void mexFunction( int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[] )
{
double *x; /* input data, size N*n */
double *y; /* output data, size N*1 */
double C; /* upper bound for Lagrange multipliers */
double e; /* insensitivity zone epsilon */
long n; /* dimension of input space */
long N; /* number of input data */
long k; /* counter */
int d0,d1; /* true number of dimensions of arguments #0 and #1 */
int label1,label2; /* different class labels */
kernel ker; /* kernel function */
options opt; /* optimizer settings */
const mxArray *mlopt; /* mxArray for getOptionsStruct and getOptions */
struct svm_problem prob; /* LIBSVM problem (i.e. data) */
struct svm_parameter param; /* LIBSVM parameters */
struct svm_model *model; /* calculated LIBSVM model */
if (nrhs<4)
mexErrMsgTxt("Invalid number of input arguments.");
/* --- get input and output data --- */
if ( mxIsEmpty(prhs[0]) ||
!mxIsDouble(prhs[0]) ||
mxIsComplex(prhs[0]) )
mexErrMsgTxt("Invalid first argument (input data).");
d0 = mxGetNumberOfDimensions(prhs[0]); /* compute true number of dims #0 */
while ( mxGetDimensions(prhs[0])[d0-1] == 1 )
d0--;
if ( mxIsEmpty(prhs[1]) ) { /* one-class SVM */
n = mxGetDimensions(prhs[0])[d0-1];
N = mxGetNumberOfElements(prhs[0])/n;
}
else if ( !mxIsDouble(prhs[1]) ||
mxIsComplex(prhs[1]) ) {
mexErrMsgTxt("Invalid second argument (output data).");
}
else {
d1 = mxGetNumberOfDimensions(prhs[1]); /* compute true number of dims #1 */
while ( mxGetDimensions(prhs[1])[d1-1] == 1 )
d1--;
if ( d1 == d0 ) /* exatly 1 regressor */
n = 1;
else if ( d1 == d0-1 ) /* more than 1 regressor */
n = mxGetDimensions(prhs[0])[d1];
else
mexErrMsgTxt("Sizes of input and output data do not match.");
N = 1; /* get number of data */
for (k=0; k<d1; k++) {
if ( mxGetDimensions(prhs[1])[k] != mxGetDimensions(prhs[0])[k] )
mexErrMsgTxt("Sizes of first and second argument do not match.");
else
N *= mxGetDimensions(prhs[1])[k];
}
}
if ( mxGetNumberOfElements(prhs[2]) != 1 ||
!mxIsDouble(prhs[2]) ||
mxIsComplex(prhs[2]) ||
mxGetScalar(prhs[2]) <= 0 )
mexErrMsgTxt("Invalid third argument (upper bound).");
x = mxGetPr(prhs[0]); /* get the input arguments */
y = mxGetPr(prhs[1]);
C = mxGetScalar(prhs[2]);
/* set default values */
opt.tol = 1e-3; /* tolerance for KKT check */
opt.shrink = 1; /* enable shrinking */
opt.cache = 40.0; /* cache size in MB */
opt.weight = 1.0; /* weight for class wlabel */
opt.wlabel = -1; /* class to be weighted */
opt.verbose = 0; /* no verbosity */
opt.style = 0; /* C/eps style */
opt.prob = 0; /* no probability information */
/* --- SVM classification --- */
if ( mxGetNumberOfElements(prhs[3]) == 1 &&
mxIsStruct(prhs[3]) ) {
/* check lables for struct output (1 argument) */
if ( !mxIsEmpty(prhs[1]) && nlhs == 1 ) { /* allow different class labels */
label1 = (int)y[0];
for (k=0; k<N; k++) {
label2 = (int)y[k];
if (label1 != label2)
break;
}
for (k=0; k<N; k++)
if ( y[k]!=label1 && y[k]!=label2 )
mexErrMsgTxt("Only two different class labels are allowed.");
}
/* check lables for vector output (2 arguments) */
if ( !mxIsEmpty(prhs[1]) && nlhs>1 ) { /* class labels must be -1 or +1 */
for (k=0; k<N; k++)
if ( y[k]!=1 && y[k]!=-1 )
mexErrMsgTxt("Only class labels +1 and -1 are allowed.");
label1 = +1;
label2 = -1;
}
/* get kernel and options */
if ( getKernel(&ker,prhs[3],n) ||
ker.type == KERNEL_GAUSS )
mexErrMsgTxt("Invalid fourth argument (kernel function).");
if ( nrhs>4 ) {
getOptionsStruct(&mlopt,prhs+4,nrhs-4);
getOptions(&opt,mlopt,N);
}
/* compute probability information only if it can be returned */
if ( nlhs>1 )
opt.prob = 0;
/* check if weighting makes sense */
if ( !mxIsEmpty(prhs[1]) &&
opt.wlabel!=label1 && opt.wlabel!=label2 ) {
opt.weight = 1;
mexWarnMsgTxt("Class to be weighted does not exist.");
}
/* check nu value (C is treated as nu) */
if ( opt.style == 1 && C > 1 )
mexErrMsgTxt("nu must be in the range (0,1]");
/* solve the classification problem */
if ( mxIsEmpty(prhs[1]) ) {
if ( C > 1 )
mexErrMsgTxt("nu must be in the range (0,1]");
convOptions(¶m,C,0,&ker,&opt,2);
}
else {
convOptions(¶m,C,0,&ker,&opt,1);
}
convData(&prob,x,y,n,N);
/* dump information about options and settings into MATLAB window */
e = -1;
if (opt.verbose > 0) {
if ( mxIsEmpty(prhs[1]) )
dumpOptions(&ker,&opt,C,e,2);
else
dumpOptions(&ker,&opt,C,e,1);
}
/* compute the solution */
model = svm_train(&prob,¶m);
if ( mxIsEmpty(prhs[1]) )
buildSolution(plhs,prhs[3],model,&prob,&opt,nlhs,2,N);
else
buildSolution(plhs,prhs[3],model,&prob,&opt,nlhs,1,N);
/* dump information about solution into MATLAB window */
if (opt.verbose > 0) {
if ( mxIsEmpty(prhs[1]) )
dumpSolution(&opt,model,&prob,y,C,2,N,(nlhs>1));
else
dumpSolution(&opt,model,&prob,y,C,1,N,(nlhs>1));
}
/* the model is no longer needed */
svm_destroy_model(model);
}
/* --- SVM regression --- */
else if ( !mxIsEmpty(prhs[1]) && /* one-class SVM not allowed */
mxGetNumberOfElements(prhs[3]) == 1 &&
mxIsDouble(prhs[3]) &&
!mxIsComplex(prhs[3]) &&
mxGetScalar(prhs[3]) >= 0 ) {
if (nrhs<5)
mexErrMsgTxt("Invalid number of input arguments.");
if ( mxGetNumberOfElements(prhs[4]) != 1 ||
!mxIsStruct(prhs[4]) )
mexErrMsgTxt("Invalid fifth argument (kernel function).");
/* get epsilon, kernel and options */
e = mxGetScalar(prhs[3]);
if ( getKernel(&ker,prhs[4],n) ||
ker.type == KERNEL_GAUSS )
mexErrMsgTxt("Invalid fourth argument (kernel function).");
if ( nrhs>5 ) {
getOptionsStruct(&mlopt,prhs+5,nrhs-5);
getOptions(&opt,mlopt,N);
}
/* check nu value (e is treated as nu) */
if ( opt.style == 1 && e > 1 )
mexErrMsgTxt("Invalid fourth argument (nu).");
/* solve the regression problem */
convOptions(¶m,C,e,&ker,&opt,0);
convData(&prob,x,y,n,N);
/* dump information about options and settings into MATLAB window */
if (opt.verbose > 0)
dumpOptions(&ker,&opt,C,e,0);
model = svm_train(&prob,¶m);
buildSolution(plhs,prhs[4],model,&prob,&opt,nlhs,0,N);
/* dump information about solution into MATLAB window */
if (opt.verbose > 0)
dumpSolution(&opt,model,&prob,y,C,0,N,(nlhs>1));
/* the model is no longer needed */
svm_destroy_model(model);
}
else
mexErrMsgTxt("Invalid fourth argument (kernel function).");
}
int main(){
std::vector<Double_t> radii;
radii.push_back(2.0); // 1.
radii.push_back(3.0); // 3.5
radii.push_back(6.0);
radii.push_back(9.0);
radii.push_back(17.0);
radii.push_back(22.0); // 20.0
radii.push_back(25.5);
radii.push_back(30.0);
radii.push_back(34.0);
radii.push_back(38.0);
radii.push_back(45.5); // 46.0
radii.push_back(54.5); // 54.0
radii.push_back(57.0);
radii.push_back(61.5); // 61.0
radii.push_back(65.0);
Double_t rMax = 65.;
std::vector<GeoCut> geoCuts;
geoCuts.push_back(GeoCut(-26., 26., 2., 20.));
geoCuts.push_back(GeoCut(-66., 66., 20., rMax));
MatPlot myPlotR("R", 1., rMax, 0.5, 0.5);
myPlotR.SetEffRadii(&radii);
myPlotR.SetGeoCuts(&geoCuts);
Float_t nDataEv = 10809460;
// Float_t nSimEv = 6106513;
Float_t nSimEv = 6106513*5./11.;
Float_t scaleFact = nDataEv/nSimEv;
//
// Assumo che il numero di eventi iniziale fosse 11000000
//
// I primi 5M si usano come pseudo dati
// i secondi 6M per il training...
//
//
myPlotR.SetMCScaleFact(-1.);
myPlotR.SetSimScaleFact(-1.);
myPlotR.SetDataScaleFact(1.);
convR2SforMatPlot convMC("../7TeV/ntuple_conversion_CMSSW358p3_minbias7TeV_2010-06-04.root");
myPlotR.FillMC(&convMC, 5000000, 100000000); // First 5M events
convS2RforMatPlot convSim("../7TeV/ntuple_conversion_CMSSW358p3_minbias7TeV_2010-06-04.root");
myPlotR.responseTrain(&convSim, &convMC, 1, 5000000); //Remaining events
myPlotR.FillSim(&convSim, 5000000, 100000000); // First 5000000 events
convR2SforMatPlot convData("../7TeV/TIB1Int_Plus15_2.root");
// convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
myPlotR.FillData(&convData);
myPlotR.doUnfold();
/*
myPlotR.SetMCScaleFact(scaleFact);
myPlotR.SetSimScaleFact(scaleFact);
myPlotR.SetDataScaleFact(1.);
convR2SforMatPlot convMC("../7TeV/ntuple_conversion_CMSSW356_minbias7TeV_2010-05-10.root");
myPlotR.FillMC(&convMC, 1, 5000000); // First 5M events
convS2RforMatPlot convSim("../7TeV/ntuple_conversion_CMSSW356_minbias7TeV_2010-05-10.root");
myPlotR.responseTrain(&convSim, &convMC, 5000000, 20000000); //Remaining events
myPlotR.FillSim(&convSim, 1, 5000000); // First 5000000 events
convR2SforMatPlot convData("../7TeV/ntuple_conversion_goodcoll7TeV_2010-05-10.root");
convData.SetCenterCoord(-0.1475, -0.3782, -0.4847);
myPlotR.FillData(&convData);
myPlotR.doUnfold();
*/
myPlotR.PlotAll();
myPlotR.test();
}