[v628][RF] Backports of RooFit PRs to v6-28-00-patches: Part 3

roofit/hs3/src/RooJSONFactoryWSTool.cxx

@@ -311,7 +311,7 @@ inline bool checkRegularBins(const TAxis &ax)
    double w = ax.GetXmax() - ax.GetXmin();
    double bw = w / ax.GetNbins();
    for (int i = 0; i <= ax.GetNbins(); ++i) {
-      if (fabs(ax.GetBinUpEdge(i) - (ax.GetXmin() + (bw * i))) > w * 1e-6)
+      if (std::abs(ax.GetBinUpEdge(i) - (ax.GetXmin() + (bw * i))) > w * 1e-6)
          return false;
    }
    return true;

roofit/multiprocess/test/utils.h

@@ -53,7 +53,7 @@ generate_ND_gaussian_pdf_nll(RooWorkspace &w, unsigned int n, unsigned long N_ev
    double mean[n], sigma[n];
    for (unsigned ix = 0; ix < n; ++ix) {
       mean[ix] = RooRandom::randomGenerator()->Gaus(0, 2);
-      sigma[ix] = 0.1 + abs(RooRandom::randomGenerator()->Gaus(0, 2));
+      sigma[ix] = 0.1 + std::abs(RooRandom::randomGenerator()->Gaus(0, 2));
    }
 
    // create gaussians and also the observables and parameters they depend on
@@ -126,7 +126,7 @@ generate_ND_gaussian_pdf_nll(RooWorkspace &w, unsigned int n, unsigned long N_ev
          std::ostringstream os;
          os << "s" << ix;
          dynamic_cast<RooRealVar *>(w.arg(os.str().c_str()))
-            ->setVal(0.1 + abs(RooRandom::randomGenerator()->Gaus(0, 2)));
+            ->setVal(0.1 + std::abs(RooRandom::randomGenerator()->Gaus(0, 2)));
       }
    }
 

roofit/roofit/src/RooBCPEffDecay.cxx

@@ -225,7 +225,7 @@ void RooBCPEffDecay::generateEvent(Int_t code)
     // Accept event if T is in generated range
     double maxDil = 1.0 ;
     double al2 = _absLambda*_absLambda ;
-    double maxAcceptProb = (1+al2) + fabs(maxDil*_CPeigenval*_absLambda*_argLambda) + fabs(maxDil*(1-al2)/2);
+    double maxAcceptProb = (1+al2) + std::abs(maxDil*_CPeigenval*_absLambda*_argLambda) + std::abs(maxDil*(1-al2)/2);
     double acceptProb    = (1+al2)/2*(1-_tag*_delMistag)
                            - (_tag*(1-2*_avgMistag))*(_CPeigenval*_absLambda*_argLambda)*sin(_dm*tval)
                            - (_tag*(1-2*_avgMistag))*(1-al2)/2*cos(_dm*tval);

roofit/roofit/src/RooBCPGenDecay.cxx

@@ -224,7 +224,7 @@ void RooBCPGenDecay::generateEvent(Int_t code)
     // Accept event if T is in generated range
     double maxDil = 1.0 ;
 // 2 in next line is conservative and inefficient - allows for delMistag=1!
-    double maxAcceptProb = 2 + fabs(maxDil*_avgS) + fabs(maxDil*_avgC);
+    double maxAcceptProb = 2 + std::abs(maxDil*_avgS) + std::abs(maxDil*_avgC);
     double acceptProb    = (1-_tag*_delMistag + _mu*_tag*(1. - 2.*_avgMistag))
                            + (_tag*(1-2*_avgMistag) + _mu*(1. - _tag*_delMistag))*_avgS*sin(_dm*tval)
                            - (_tag*(1-2*_avgMistag) + _mu*(1. - _tag*_delMistag))*_avgC*cos(_dm*tval);

roofit/roofit/src/RooBDecay.cxx

@@ -223,7 +223,7 @@ void RooBDecay::generateEvent(Int_t code)
 
     double dgt = _dgamma*t/2;
     double dmt = _dm*t;
-    double ft = fabs(t);
+    double ft = std::abs(t);
     double f = exp(-ft/_tau)*(_f0*cosh(dgt)+_f1*sinh(dgt)+_f2*cos(dmt)+_f3*sin(dmt));
     if(f < 0) {
       cout << "RooBDecay::generateEvent(" << GetName() << ") ERROR: PDF value less than zero" << endl;

roofit/roofit/src/RooBukinPdf.cxx

@@ -96,7 +96,7 @@ double RooBukinPdf::evaluate() const
   r4=sqrt(xi*xi+1);
   r1=xi/r4;
 
-  if(fabs(xi) > exp(-6.)){
+  if(std::abs(xi) > exp(-6.)){
     r5=xi/log(r4+xi);
   }
   else
@@ -113,7 +113,7 @@ double RooBukinPdf::evaluate() const
 
   //--- Center
   else if(x < x2) {
-    if(fabs(xi) > exp(-6.)) {
+    if(std::abs(xi) > exp(-6.)) {
       r2=log(1 + 4 * xi * r4 * (x-Xp)/hp)/log(1+2*xi*(xi-r4));
       r2=-r3*r2*r2;
     }
@@ -128,7 +128,7 @@ double RooBukinPdf::evaluate() const
     r2=rho2*(x-x2)*(x-x2)/(Xp-x2)/(Xp-x2)-r3 - 4 * r3 * (x-x2)/hp * r5 * r4/(r4+xi)/(r4+xi);
   }
 
-  if(fabs(r2) > 100){
+  if(std::abs(r2) > 100){
     fit_result = 0;
   }
   else{

roofit/roofit/src/RooCBShape.cxx

@@ -76,7 +76,7 @@ double RooCBShape::evaluate() const {
   double t = (m-m0)/sigma;
   if (alpha < 0) t = -t;
 
-  double absAlpha = fabs((double)alpha);
+  double absAlpha = std::abs((double)alpha);
 
   if (t >= -absAlpha) {
     return exp(-0.5*t*t);
@@ -119,10 +119,10 @@ double RooCBShape::analyticalIntegral(Int_t code, const char* rangeName) const
   double result = 0.0;
   bool useLog = false;
 
-  if( fabs(n-1.0) < 1.0e-05 )
+  if( std::abs(n-1.0) < 1.0e-05 )
     useLog = true;
 
-  double sig = fabs((double)sigma);
+  double sig = std::abs((double)sigma);
 
   double tmin = (m.min(rangeName)-m0)/sig;
   double tmax = (m.max(rangeName)-m0)/sig;
@@ -133,7 +133,7 @@ double RooCBShape::analyticalIntegral(Int_t code, const char* rangeName) const
     tmax = -tmp;
   }
 
-  double absAlpha = fabs((double)alpha);
+  double absAlpha = std::abs((double)alpha);
 
   if( tmin >= -absAlpha ) {
     result += sig*sqrtPiOver2*(   ApproxErf(tmax/sqrt2)

roofit/roofit/src/RooGExpModel.cxx

@@ -211,7 +211,7 @@ namespace {
 double logErfC(double xx)
 {
   double t,z,ans;
-  z=fabs(xx);
+  z=std::abs(xx);
   t=1.0/(1.0+0.5*z);
 
   if(xx >= 0.0)
@@ -469,10 +469,10 @@ double RooGExpModel::calcDecayConv(double sign, double tau, double sig, double r
   sign *= fsign ;  // modified FMV,08/13/03
 
   double cFly;
-  if ((sign<0)&&(fabs(tau-rtau)<tau/260)) {
+  if ((sign<0)&&(std::abs(tau-rtau)<tau/260)) {
 
     double MeanTau=0.5*(tau+rtau);
-    if (fabs(xp/MeanTau)>300) {
+    if (std::abs(xp/MeanTau)>300) {
       return 0 ;
     }
 
@@ -848,7 +848,7 @@ double RooGExpModel::calcSinConvNorm(double sign, double tau, double sig, double
   double term2 = evalCerfInt(-fsign, rtau, fsign*umin2, fsign*umax2, c2)*fsign*sign;
 
   // WVE Handle 0/0 numeric divergence
-  if (fabs(tau-rtau)<1e-10 && fabs(term1+term2)<1e-10) {
+  if (std::abs(tau-rtau)<1e-10 && std::abs(term1+term2)<1e-10) {
     cout << "epsilon method" << endl ;
     static double epsilon = 1e-4 ;
     return calcSinConvNorm(sign,tau+epsilon,sig,rtau-epsilon,fsign,rangeName) ;

roofit/roofit/src/RooIntegralMorph.cxx

@@ -389,7 +389,7 @@ void RooIntegralMorph::MorphCacheElem::calculate(TIterator* dIter)
     // Calculate additional offset to apply if bin ixlo does not have X value calculated at bin center
     double xBinC = xmin + (i+0.5)*binw ;
     double xOffset = xBinC-_calcX[i] ;
-    if (fabs(xOffset/binw)>1e-3) {
+    if (std::abs(xOffset/binw)>1e-3) {
       double slope = (_yatX[i+1]-_yatX[i-1])/(_calcX[i+1]-_calcX[i-1]) ;
       double newY = _yatX[i] + slope*xOffset ;
       //cout << "bin " << i << " needs to be re-centered " << xOffset/binw << " slope = " << slope << " origY = " << _yatX[i] << " newY = " << newY << endl ;
@@ -481,7 +481,7 @@ void RooIntegralMorph::MorphCacheElem::fillGap(Int_t ixlo, Int_t ixhi, double sp
 
 
   // Policy: If centration quality is better than 1% OR better than 1/10 of a bin, fill interval with linear interpolation
-  if (fabs(cq)<0.01 || fabs(cq*(ixhi-ixlo))<0.1 || ymid<_ycutoff ) {
+  if (std::abs(cq)<0.01 || std::abs(cq*(ixhi-ixlo))<0.1 || ymid<_ycutoff ) {
 
     // Fill remaining gaps on either side with linear interpolation
     if (iX-ixlo>1) {
@@ -584,7 +584,7 @@ void RooIntegralMorph::MorphCacheElem::findRange()
 
     // Terminate if value of X no longer moves by >0.1 bin size
     double X = _alpha->getVal()*x1 + (1-_alpha->getVal())*x2 ;
-    if (fabs(X-Xlast)/(xmax-xmin)<0.0001) {
+    if (std::abs(X-Xlast)/(xmax-xmin)<0.0001) {
       break ;
     }
     Xlast=X ;
@@ -621,7 +621,7 @@ void RooIntegralMorph::MorphCacheElem::findRange()
 
     // Terminate if value of X no longer moves by >0.1 bin size
     double X = _alpha->getVal()*x1 + (1-_alpha->getVal())*x2 ;
-    if (fabs(X-Xlast)/(xmax-xmin)<0.0001) {
+    if (std::abs(X-Xlast)/(xmax-xmin)<0.0001) {
       break ;
     }
     Xlast=X ;

roofit/roofit/src/RooLagrangianMorphFunc.cxx

@@ -317,7 +317,7 @@ inline double invertMatrix(const Matrix &matrix, Matrix &inverse)
    // sanitize numeric problems
    for (size_t i = 0; i < n; ++i)
       for (size_t j = 0; j < n; ++j)
-         if (fabs(inverse(i, j)) < 1e-9)
+         if (std::abs(inverse(i, j)) < 1e-9)
             inverse(i, j) = 0;
    return condition;
 }
@@ -1060,8 +1060,8 @@ inline void inverseSanity(const Matrix &matrix, const Matrix &inverse, double &u
          if (inverse(i, j) > largestWeight) {
             largestWeight = (double)inverse(i, j);
          }
-         if (fabs(unity(i, j) - static_cast<int>(i == j)) > unityDeviation) {
-            unityDeviation = fabs((double)unity(i, j)) - static_cast<int>(i == j);
+         if (std::abs(unity(i, j) - static_cast<int>(i == j)) > unityDeviation) {
+            unityDeviation = std::abs((double)unity(i, j)) - static_cast<int>(i == j);
          }
       }
    }

roofit/roofit/src/RooNDKeysPdf.cxx

@@ -1242,9 +1242,9 @@ double RooNDKeysPdf::analyticalIntegral(Int_t code, const char* rangeName) const
      chi[j] = (bi->xVarHi[j]-x[j])/weight[j];
 
    if (chi[j]>0) // inVarRange
-     prob *= (0.5 + TMath::Erf(fabs(chi[j])/sqrt(2.))/2.);
+     prob *= (0.5 + TMath::Erf(std::abs(chi[j])/sqrt(2.))/2.);
    else // outside Var range
-     prob *= (0.5 - TMath::Erf(fabs(chi[j])/sqrt(2.))/2.);
+     prob *= (0.5 - TMath::Erf(std::abs(chi[j])/sqrt(2.))/2.);
       }
 
       norm += prob * _wMap.at(_idx[bi->sIdcs[i]]);

roofit/roofit/test/testRooBernstein.cxx

@@ -55,8 +55,8 @@ void IntegrationChecker(double a0, double a1, double a2, double a3)
   auto numInt_full = bern.createIntegral(x, "FULL");
 
   // closure
-  EXPECT_LT(fabs(int_full->getVal() - int_range1->getVal() - int_range2->getVal() - int_range3->getVal()), 1e-10);
-  EXPECT_LT(fabs(numInt_full->getVal() - numInt_range1->getVal() - numInt_range2->getVal() - numInt_range3->getVal()), 1e-10);
+  EXPECT_LT(std::abs(int_full->getVal() - int_range1->getVal() - int_range2->getVal() - int_range3->getVal()), 1e-10);
+  EXPECT_LT(std::abs(numInt_full->getVal() - numInt_range1->getVal() - numInt_range2->getVal() - numInt_range3->getVal()), 1e-10);
 
   // comparision with polynomial
   double accAnaVsNum = 1.;

roofit/roofitcore/inc/RooAbsPdf.h

@@ -299,9 +299,9 @@ class RooAbsPdf : public RooAbsReal {
   static void verboseEval(Int_t stat) ;
   static int verboseEval() ;
 
-  double extendedTerm(double sumEntries, double expected, double sumEntriesW2=0.0) const;
-  double extendedTerm(double sumEntries, RooArgSet const* nset, double sumEntriesW2=0.0) const;
-  double extendedTerm(RooAbsData const& data, bool weightSquared) const;
+  double extendedTerm(double sumEntries, double expected, double sumEntriesW2=0.0, bool doOffset=false) const;
+  double extendedTerm(double sumEntries, RooArgSet const* nset, double sumEntriesW2=0.0, bool doOffset=false) const;
+  double extendedTerm(RooAbsData const& data, bool weightSquared, bool doOffset=false) const;
 
   void setNormRange(const char* rangeName) ;
   const char* normRange() const {

roofit/roofitcore/inc/RooGlobalFunc.h

@@ -70,7 +70,7 @@ enum class BatchModeOption { Off, Cpu, Cuda, Old };
 
 /// For setting the offset mode with the Offset() command argument to
 /// RooAbsPdf::fitTo()
-enum class OffsetMode { Off, Initial, Bin };
+enum class OffsetMode { None, Initial, Bin };
 
 namespace Experimental {
 

roofit/roofitcore/inc/RooNLLVar.h

@@ -61,8 +61,8 @@ class RooNLLVar : public RooAbsOptTestStatistic {
     _batchEvaluations = on;
   }
 
-  void templateRatioOffset(bool on = true) {
-    _templateRatioOffset = on;
+  void enableBinOffsetting(bool on = true) {
+    _doBinOffset = on;
   }
 
   using ComputeResult = std::pair<ROOT::Math::KahanSum<double>, double>;
@@ -73,7 +73,7 @@ class RooNLLVar : public RooAbsOptTestStatistic {
                                                  std::size_t firstEvent, std::size_t lastEvent);
   static RooNLLVar::ComputeResult computeScalarFunc(const RooAbsPdf *pdfClone, RooAbsData *dataClone, RooArgSet *normSet,
                                                 bool weightSq, std::size_t stepSize, std::size_t firstEvent,
-                                                std::size_t lastEvent, bool templateRatioOffset=false);
+                                                std::size_t lastEvent, bool doBinOffset=false);
 
 protected:
 
@@ -88,7 +88,7 @@ class RooNLLVar : public RooAbsOptTestStatistic {
 
   bool _extended{false};
   bool _batchEvaluations{false};
-  bool _templateRatioOffset{false};
+  bool _doBinOffset{false};
   bool _weightSq{false}; ///< Apply weights squared?
   mutable bool _first{true}; ///<!
   ROOT::Math::KahanSum<double> _offsetSaveW2{0.0}; ///<!

roofit/roofitcore/inc/RooPlot.h

@@ -204,6 +204,8 @@ class RooPlot : public TNamed, public RooPrintable {
 
   static void fillItemsFromTList(Items & items, TList const& tlist);
 
+  void createInternalPlotVarClone();
+
 protected:
 
   RooPlot(const RooPlot& other) = delete; // cannot be copied

roofit/roofitcore/src/BatchModeDataHelpers.cxx

@@ -12,6 +12,7 @@
 
 #include "RooFit/BatchModeDataHelpers.h"
 #include <RooAbsData.h>
+#include <RooDataHist.h>
 #include "RooNLLVarNew.h"
 
 #include <ROOT/StringUtils.hxx>
@@ -23,7 +24,9 @@
 /// Spans with the weights and squared weights will be also stored in the map,
 /// keyed with the names `_weight` and the `_weight_sumW2`. If the dataset is
 /// unweighted, these weight spans will only contain the single value `1.0`.
-/// Entries with zero weight will be skipped.
+/// Entries with zero weight will be skipped. If the input dataset is a
+/// RooDataHist, the output map will also contain an item for the key
+/// `_bin_volume` with the bin volumes.
 ///
 /// \return A `std::map` with spans keyed to name pointers.
 /// \param[in] data The input dataset.
@@ -110,6 +113,21 @@ RooFit::BatchModeDataHelpers::getDataSpans(RooAbsData const &data, std::string_v
       insert(RooNLLVarNew::weightVarNameSumW2, weightSumW2);
    }
 
+   // Add also bin volume information if we are dealing with a RooDataHist
+   if (auto dataHist = dynamic_cast<RooDataHist const *>(&data)) {
+      buffers.emplace();
+      auto &buffer = buffers.top();
+      buffer.reserve(nNonZeroWeight);
+
+      for (std::size_t i = 0; i < nEvents; ++i) {
+         if (!hasZeroWeight[i]) {
+            buffer.push_back(dataHist->binVolume(i));
+         }
+      }
+
+      insert("_bin_volume", {buffer.data(), buffer.size()});
+   }
+
    // Get the real-valued batches and cast the also to double branches to put in
    // the data map
    for (auto const &item : data.getBatches(0, nEvents)) {

roofit/roofitcore/src/RooAbsCategory.cxx

@@ -665,7 +665,7 @@ bool RooAbsCategory::isSignType(bool mustHaveZero) const
   if (mustHaveZero && theStateNames.size() != 3) return false;
 
   for (const auto& type : theStateNames) {
-    if (abs(type.second)>1)
+    if (std::abs(type.second)>1)
       return false;
   }