//------------------------------------------------------------------------------
std::pair<float,float>
PlotAlignmentValidation::fitGauss(TH1 *hist,int color)
{
//1. fits a Gauss function to the inner range of abs(2 rms)
//2. repeates the Gauss fit in a 2 sigma range around mean of first fit
//returns mean and sigma from fit in micron
std::pair<float,float> fitResult(9999., 9999.);
if (!hist || hist->GetEntries() < 20) return fitResult;
float mean = hist->GetMean();
float sigma = hist->GetRMS();
TF1 func("tmp", "gaus", mean - 2.*sigma, mean + 2.*sigma);
func.SetLineColor(color);
func.SetLineStyle(2);
if (0 == hist->Fit(&func,"QNR")) { // N: do not blow up file by storing fit!
mean = func.GetParameter(1);
sigma = func.GetParameter(2);
// second fit: three sigma of first fit around mean of first fit
func.SetRange(mean - 2.*sigma, mean + 2.*sigma);
// I: integral gives more correct results if binning is too wide
// L: Likelihood can treat empty bins correctly (if hist not weighted...)
if (0 == hist->Fit(&func, "Q0ILR")) {
if (hist->GetFunction(func.GetName())) { // Take care that it is later on drawn:
//hist->GetFunction(func.GetName())->ResetBit(TF1::kNotDraw);
}
fitResult.first = func.GetParameter(1)*10000;//convert from cm to micron
fitResult.second = func.GetParameter(2)*10000;//convert from cm to micron
}
}
return fitResult;
}
ASMFitResult ASMModel::fit(const cv::Mat& img, int verbose)
{
ASMFitResult fitResult(this);
// Step 2: Ensure it is a grayscale image
Mat grayImg;
if (img.channels() == 3){
cv::cvtColor(img, grayImg, CV_BGR2GRAY);
}
else
grayImg = img;
// Step 3: Resize each face image
Mat resizedImg;
// Resize the image to proper size
double ratio;
ratio = sqrt( double(40000) / (grayImg.rows * grayImg.cols));
cv::resize(grayImg, resizedImg, Size(grayImg.cols*ratio, grayImg.rows*ratio));
ModelImage curSearch;
curSearch.setShapeInfo( &shapeInfo );
curSearch.loadTrainImage(resizedImg);
fitResult.params = Mat_<double>::zeros(nShapeParams, 1);
ShapeVec &sv = curSearch.shapeVec;
ShapeVec shape_old;
projectParamToShape(fitResult.params, sv);
SimilarityTrans st = sv.getShapeTransformFitingSize(resizedImg.size(),
searchScaleRatio,
searchInitXOffset,
searchInitYOffset);
fitResult.transformation = st;
curSearch.buildFromShapeVec(st);
pyramidLevel = 2;
int k=localFeatureRad;
ns=4;
// sum of offsets of current iteration.
int totalOffset;
if (verbose >= ASM_FIT_VERBOSE_AT_LEVEL)
curSearch.show();
// Update each point
vector< Point_< int > > V;
for (int l=this->pyramidLevel; l>=0; l--){
if (verbose >= ASM_FIT_VERBOSE_AT_LEVEL)
printf("Level %d\n", l);
Mat_<double> img=curSearch.getDerivImage(l);
// printf("Image size: %dx%d\n", img.cols, img.rows);
// at most 5 iterations for each level
int runT;
double avgMov;
for (runT=0; runT<10; runT++){
// Backup current shape
shape_old.fromPointList(curSearch.points);
totalOffset = 0;
vector< Point_< int > > bestEP(nMarkPoints);
for (int i=0; i<this->nMarkPoints; i++){
if (verbose >= ASM_FIT_VERBOSE_AT_POINT)
printf("Dealing point %d...\n", i);
Mat_< double > nrmV(2*k+1, 1);
double curBest=-1, ct;
int bestI = 0;
double absSum;
for (int e=ns; e>=-ns; e--){
curSearch.getPointsOnNorm(i, k, l, V, 2*searchStepAreaRatio, e);
absSum = 0;
for (int j=-k;j<=k;j++){
nrmV(j+k, 0) = img(V[j+k]);
absSum += fabs(nrmV(j+k, 0));
}
nrmV *= 1/absSum;
ct = cv::Mahalanobis(nrmV, this->meanG[l][i], this->iCovarG[l][i]);
// printf("absSum: %lf, ct: %lf\n", absSum, ct);
if (verbose >= ASM_FIT_VERBOSE_AT_POINT)
curSearch.show(l, i, true, e);
if (ct<curBest || curBest<0){
curBest = ct;
bestI = e;
bestEP[i] = V[k];
}
}
// printf("best e: %d\n", bestI);
// bestEP[i] = V[bestI+(ns+k)];
totalOffset += abs(bestI);
if (verbose >= ASM_FIT_VERBOSE_AT_POINT)
curSearch.show(l, i, true, bestI);
}
for (int i=0;i<nMarkPoints;i++){
curSearch.points[i] = bestEP[i];
curSearch.points[i].x <<= l;
if (l>0) curSearch.points[i].x += (1<<(l-1));
curSearch.points[i].y <<= l;
if (l>0) curSearch.points[i].y += (1<<(l-1));
}
curSearch.shapeVec.fromPointList(curSearch.points);
if (verbose >= ASM_FIT_VERBOSE_AT_ITERATION)
curSearch.show(l);
// Project to PCA model and then back
//findParamForShape(curSearch.shapeVec, fitResult);
findParamForShapeBTSM(curSearch.shapeVec, shape_old, fitResult, fitResult, l);
pcaPyr[l].backProject(fitResult.params, sv);
// Reconstruct new shape
curSearch.buildFromShapeVec(fitResult.transformation);
avgMov = (double)totalOffset/nMarkPoints;
if (verbose >= ASM_FIT_VERBOSE_AT_ITERATION){
printf("Iter %d: Average offset: %.3f\n", runT+1, avgMov);
curSearch.show(l);
}
if (avgMov < 1.3){
runT++;
break;
}
}
if (verbose == ASM_FIT_VERBOSE_AT_LEVEL){
printf("%d iterations. average offset for last iter: %.3f\n", runT, avgMov);
curSearch.show(l);
}
}
SimilarityTrans s2;
s2.a = 1/ratio;
fitResult.transformation = s2 * fitResult.transformation;
return fitResult;
}
bool fitCharmoniaMassModel( RooWorkspace& myws, // Local Workspace
const RooWorkspace& inputWorkspace, // Workspace with all the input RooDatasets
struct KinCuts& cut, // Variable containing all kinematic cuts
map<string, string>& parIni, // Variable containing all initial parameters
struct InputOpt& opt, // Variable with run information (kept for legacy purpose)
string outputDir, // Path to output directory
// Select the type of datasets to fit
string DSTAG, // Specifies the type of datasets: i.e, DATA, MCJPSINP, ...
bool isPbPb = false, // isPbPb = false for pp, true for PbPb
bool importDS = true, // Select if the dataset is imported in the local workspace
// Select the type of object to fit
bool incJpsi = true, // Includes Jpsi model
bool incPsi2S = true, // Includes Psi(2S) model
bool incBkg = true, // Includes Background model
// Select the fitting options
bool doFit = true, // Flag to indicate if we want to perform the fit
bool cutCtau = false, // Apply prompt ctau cuts
bool doConstrFit = false, // Do constrained fit
bool doSimulFit = false, // Do simultaneous fit
bool wantPureSMC = false, // Flag to indicate if we want to fit pure signal MC
const char* applyCorr ="", // Flag to indicate if we want corrected dataset and which correction
uint loadFitResult = false, // Load previous fit results
string inputFitDir = "", // Location of the fit results
int numCores = 2, // Number of cores used for fitting
// Select the drawing options
bool setLogScale = true, // Draw plot with log scale
bool incSS = false, // Include Same Sign data
bool zoomPsi = false, // Zoom Psi(2S) peak on extra pad
double binWidth = 0.05, // Bin width used for plotting
bool getMeanPT = false // Compute the mean PT (NEED TO FIX)
)
{
if (DSTAG.find("_")!=std::string::npos) DSTAG.erase(DSTAG.find("_"));
// Check if input dataset is MC
bool isMC = false;
if (DSTAG.find("MC")!=std::string::npos) {
if (incJpsi && incPsi2S) {
cout << "[ERROR] We can only fit one type of signal using MC" << endl; return false;
}
isMC = true;
}
wantPureSMC = (isMC && wantPureSMC);
bool cutSideBand = (incBkg && (!incPsi2S && !incJpsi));
bool applyWeight_Corr = ( strcmp(applyCorr,"") );
// Define the mass range
setMassCutParameters(cut, incJpsi, incPsi2S, isMC);
parIni["invMassNorm"] = Form("RooFormulaVar::%s('( -1.0 + 2.0*( @0 - @1 )/( @2 - @1) )', {%s, mMin[%.6f], mMax[%.6f]})", "invMassNorm", "invMass", cut.dMuon.M.Min, cut.dMuon.M.Max );
// Apply the ctau cuts to reject non-prompt charmonia
if (cutCtau) { setCtauCuts(cut, isPbPb); }
string COLL = (isPbPb ? "PbPb" : "PP" );
string plotLabelPbPb, plotLabelPP;
if (doSimulFit || !isPbPb) {
// Set models based on initial parameters
struct OniaModel model;
if (!setMassModel(model, parIni, false, incJpsi, incPsi2S, incBkg)) { return false; }
// Import the local datasets
double numEntries = 1000000;
string label = ((DSTAG.find("PP")!=std::string::npos) ? DSTAG.c_str() : Form("%s_%s", DSTAG.c_str(), "PP"));
if (wantPureSMC) label += "_NoBkg";
if (applyWeight_Corr) label += Form("_%s",applyCorr);
string dsName = Form("dOS_%s", label.c_str());
if (importDS) {
if ( !(myws.data(dsName.c_str())) ) {
int importID = importDataset(myws, inputWorkspace, cut, label, cutSideBand);
if (importID<0) { return false; }
else if (importID==0) { doFit = false; }
}
numEntries = myws.data(dsName.c_str())->sumEntries(); if (numEntries<=0) { doFit = false; }
}
else if (doFit && !(myws.data(dsName.c_str()))) { cout << "[ERROR] No local dataset was found to perform the fit!" << endl; return false; }
if (myws.data(dsName.c_str())) numEntries = myws.data(dsName.c_str())->sumEntries();
// Set global parameters
setMassGlobalParameterRange(myws, parIni, cut, incJpsi, incPsi2S, incBkg, wantPureSMC);
// Build the Fit Model
if (!buildCharmoniaMassModel(myws, model.PP, parIni, false, doConstrFit, doSimulFit, incBkg, incJpsi, incPsi2S, numEntries)) { return false; }
// Define plot names
if (incJpsi) { plotLabelPP += Form("_Jpsi_%s", parIni["Model_Jpsi_PP"].c_str()); }
if (incPsi2S) { plotLabelPP += Form("_Psi2S_%s", parIni["Model_Psi2S_PP"].c_str()); }
if (incBkg) { plotLabelPP += Form("_Bkg_%s", parIni["Model_Bkg_PP"].c_str()); }
if (wantPureSMC) plotLabelPP +="_NoBkg";
if (applyWeight_Corr) plotLabelPP +=Form("_%s",applyCorr);
}
if (doSimulFit || isPbPb) {
// Set models based on initial parameters
struct OniaModel model;
if (!setMassModel(model, parIni, true, incJpsi, incPsi2S, incBkg)) { return false; }
// Import the local datasets
double numEntries = 1000000;
string label = ((DSTAG.find("PbPb")!=std::string::npos) ? DSTAG.c_str() : Form("%s_%s", DSTAG.c_str(), "PbPb"));
if (wantPureSMC) label += "_NoBkg";
if (applyWeight_Corr) label += Form("_%s",applyCorr);
string dsName = Form("dOS_%s", label.c_str());
if (importDS) {
if ( !(myws.data(dsName.c_str())) ) {
int importID = importDataset(myws, inputWorkspace, cut, label, cutSideBand);
if (importID<0) { return false; }
else if (importID==0) { doFit = false; }
}
numEntries = myws.data(dsName.c_str())->sumEntries(); if (numEntries<=0) { doFit = false; }
}
else if (doFit && !(myws.data(dsName.c_str()))) { cout << "[ERROR] No local dataset was found to perform the fit!" << endl; return false; }
if (myws.data(dsName.c_str())) numEntries = myws.data(dsName.c_str())->sumEntries();
// Set global parameters
setMassGlobalParameterRange(myws, parIni, cut, incJpsi, incPsi2S, incBkg, wantPureSMC);
// Build the Fit Model
if (!buildCharmoniaMassModel(myws, model.PbPb, parIni, true, doConstrFit, doSimulFit, incBkg, incJpsi, incPsi2S, numEntries)) { return false; }
// Define plot names
if (incJpsi) { plotLabelPbPb += Form("_Jpsi_%s", parIni["Model_Jpsi_PbPb"].c_str()); }
if (incPsi2S) { plotLabelPbPb += Form("_Psi2S_%s", parIni["Model_Psi2S_PbPb"].c_str()); }
if (incBkg) { plotLabelPbPb += Form("_Bkg_%s", parIni["Model_Bkg_PbPb"].c_str()); }
if (wantPureSMC) plotLabelPbPb += "_NoBkg";
if (applyWeight_Corr) plotLabelPbPb += Form("_%s",applyCorr);
}
if (doSimulFit) {
// Create the combided datasets
RooCategory* sample = new RooCategory("sample","sample"); sample->defineType("PbPb"); sample->defineType("PP");
RooDataSet* combData = new RooDataSet("combData","combined data", *myws.var("invMass"), Index(*sample),
Import("PbPb", *((RooDataSet*)myws.data("dOS_DATA_PbPb"))),
Import("PP", *((RooDataSet*)myws.data("dOS_DATA_PP")))
);
myws.import(*sample);
// Create the combided models
RooSimultaneous* simPdf = new RooSimultaneous("simPdf", "simultaneous pdf", *sample);
simPdf->addPdf(*myws.pdf("pdfMASS_Tot_PbPb"), "PbPb"); simPdf->addPdf(*myws.pdf("pdfMASS_Tot_PP"), "PP");
myws.import(*simPdf);
// check if we have already done this fit. If yes, do nothing and return true.
string FileName = "";
setMassFileName(FileName, (inputFitDir=="" ? outputDir : inputFitDir), DSTAG, (plotLabelPP + plotLabelPbPb), cut, isPbPb, cutSideBand, doSimulFit);
if (gSystem->AccessPathName(FileName.c_str()) && inputFitDir!="") {
cout << "[WARNING] User Input File : " << FileName << " was not found!" << endl;
if (loadFitResult) return false;
setMassFileName(FileName, outputDir, DSTAG, (plotLabelPP + plotLabelPbPb), cut, isPbPb, cutSideBand, doSimulFit);
}
bool found = true; bool skipFit = !doFit;
RooArgSet *newpars = myws.pdf("simPdf")->getParameters(*(myws.var("invMass")));
myws.saveSnapshot("simPdf_parIni", *newpars, kTRUE);
found = found && isFitAlreadyFound(newpars, FileName, "simPdf");
if (loadFitResult) {
if ( loadPreviousFitResult(myws, FileName, DSTAG, false, (!isMC && !cutSideBand && loadFitResult==1), loadFitResult==1) ) { skipFit = true; } else { skipFit = false; }
if ( loadPreviousFitResult(myws, FileName, DSTAG, true, (!isMC && !cutSideBand && loadFitResult==1), loadFitResult==1) ) { skipFit = true; } else { skipFit = false; }
if (skipFit) { cout << "[INFO] This simultaneous mass fit was already done, so I'll load the fit results." << endl; }
myws.saveSnapshot("simPdf_parLoad", *newpars, kTRUE);
} else if (found) {
cout << "[INFO] This simultaneous mass fit was already done, so I'll just go to the next one." << endl;
return true;
}
// Do the simultaneous fit
if (skipFit==false) {
RooFitResult* fitResult = simPdf->fitTo(*combData, Offset(kTRUE), Extended(kTRUE), NumCPU(numCores), Range("MassWindow"), Save()); //, Minimizer("Minuit2","Migrad")
fitResult->Print("v");
myws.import(*fitResult, "fitResult_simPdf");
// Create the output files
int nBins = min(int( round((cut.dMuon.M.Max - cut.dMuon.M.Min)/binWidth) ), 1000);
drawMassPlot(myws, outputDir, opt, cut, parIni, plotLabelPP, DSTAG, false, incJpsi, incPsi2S, incBkg, cutCtau, doSimulFit, false, setLogScale, incSS, zoomPsi, nBins, getMeanPT);
drawMassPlot(myws, outputDir, opt, cut, parIni, plotLabelPbPb, DSTAG, true, incJpsi, incPsi2S, incBkg, cutCtau, doSimulFit, false, setLogScale, incSS, zoomPsi, nBins, getMeanPT);
// Save the results
string FileName = ""; setMassFileName(FileName, outputDir, DSTAG, (plotLabelPP + plotLabelPbPb), cut, isPbPb, cutSideBand, doSimulFit);
myws.saveSnapshot("simPdf_parFit", *newpars, kTRUE);
saveWorkSpace(myws, Form("%smass%s/%s/result", outputDir.c_str(), (cutSideBand?"SB":""), DSTAG.c_str()), FileName);
// Delete the objects used during the simultaneous fit
delete sample; delete combData; delete simPdf;
}
}
else {
// Define pdf and plot names
string pdfName = Form("pdfMASS_Tot_%s", COLL.c_str());
string plotLabel = (isPbPb ? plotLabelPbPb : plotLabelPP);
// Import the local datasets
string label = ((DSTAG.find(COLL.c_str())!=std::string::npos) ? DSTAG.c_str() : Form("%s_%s", DSTAG.c_str(), COLL.c_str()));
if (wantPureSMC) label += "_NoBkg";
if (applyWeight_Corr) label += Form("_%s",applyCorr);
string dsName = Form("dOS_%s", label.c_str());
// check if we have already done this fit. If yes, do nothing and return true.
string FileName = "";
setMassFileName(FileName, (inputFitDir=="" ? outputDir : inputFitDir), DSTAG, plotLabel, cut, isPbPb, cutSideBand);
if (gSystem->AccessPathName(FileName.c_str()) && inputFitDir!="") {
cout << "[WARNING] User Input File : " << FileName << " was not found!" << endl;
if (loadFitResult) return false;
setMassFileName(FileName, outputDir, DSTAG, plotLabel, cut, isPbPb, cutSideBand);
}
bool found = true; bool skipFit = !doFit;
RooArgSet *newpars = myws.pdf(pdfName.c_str())->getParameters(*(myws.var("invMass")));
found = found && isFitAlreadyFound(newpars, FileName, pdfName.c_str());
if (loadFitResult) {
if ( loadPreviousFitResult(myws, FileName, DSTAG, isPbPb, (!isMC && !cutSideBand && loadFitResult==1), loadFitResult==1) ) { skipFit = true; } else { skipFit = false; }
if (skipFit) { cout << "[INFO] This mass fit was already done, so I'll load the fit results." << endl; }
myws.saveSnapshot(Form("%s_parLoad", pdfName.c_str()), *newpars, kTRUE);
} else if (found) {
cout << "[INFO] This mass fit was already done, so I'll just go to the next one." << endl;
return true;
}
// Fit the Datasets
if (skipFit==false) {
bool isWeighted = myws.data(dsName.c_str())->isWeighted();
RooFitResult* fitResult(0x0);
if (doConstrFit)
{
cout << "[INFO] Performing constrained fit" << endl;
if (isPbPb) {
cout << "[INFO] Constrained variables: alpha, n, ratio of sigmas" << endl;
fitResult = myws.pdf(pdfName.c_str())->fitTo(*myws.data(dsName.c_str()), Extended(kTRUE), SumW2Error(isWeighted), Range(cutSideBand ? parIni["BkgMassRange_FULL_Label"].c_str() : "MassWindow"), ExternalConstraints(RooArgSet(*(myws.pdf("sigmaAlphaConstr")),*(myws.pdf("sigmaNConstr")),*(myws.pdf("sigmaRSigmaConstr")))), NumCPU(numCores), Save());
}
else {
cout << "[INFO] Constrained variables: alpha, n, ratio of sigmas" << endl;
fitResult = myws.pdf(pdfName.c_str())->fitTo(*myws.data(dsName.c_str()), Extended(kTRUE), SumW2Error(isWeighted), Range(cutSideBand ? parIni["BkgMassRange_FULL_Label"].c_str() : "MassWindow"), ExternalConstraints(RooArgSet(*(myws.pdf("sigmaAlphaConstr")),*(myws.pdf("sigmaNConstr")))), NumCPU(numCores), Save());
}
}
else
{
fitResult = myws.pdf(pdfName.c_str())->fitTo(*myws.data(dsName.c_str()), Extended(kTRUE), SumW2Error(isWeighted), Range(cutSideBand ? parIni["BkgMassRange_FULL_Label"].c_str() : "MassWindow"), NumCPU(numCores), Save());
}
fitResult->Print("v");
myws.import(*fitResult, Form("fitResult_%s", pdfName.c_str()));
// Create the output files
int nBins = min(int( round((cut.dMuon.M.Max - cut.dMuon.M.Min)/binWidth) ), 1000);
drawMassPlot(myws, outputDir, opt, cut, parIni, plotLabel, DSTAG, isPbPb, incJpsi, incPsi2S, incBkg, cutCtau, doSimulFit, wantPureSMC, setLogScale, incSS, zoomPsi, nBins, getMeanPT);
// Save the results
string FileName = ""; setMassFileName(FileName, outputDir, DSTAG, plotLabel, cut, isPbPb, cutSideBand);
myws.saveSnapshot(Form("%s_parFit", pdfName.c_str()), *newpars, kTRUE);
saveWorkSpace(myws, Form("%smass%s/%s/result", outputDir.c_str(), (cutSideBand?"SB":""), DSTAG.c_str()), FileName);
}
}
return true;
};
