[RF] Don't double-scale pdfs plotted by RooSimultaneous::plotOn()

roofit/roofitcore/src/RooPlot.cxx

@@ -898,22 +898,28 @@ bool RooPlot::drawAfter(const char *after, const char *target)
 /// methods to change the drawing style attributes of a contained
 /// object directly.
 
-TObject *RooPlot::findObject(const char *name, const TClass* tClass) const
+TObject *RooPlot::findObject(const char *name, const TClass *tClass) const
 {
-  TObject *ret = nullptr;
+   TObject *ret = nullptr;
 
-  for(auto const& item : _items) {
-    TObject &obj = *item.first;
-    if ((!name || name[0] == '\0' || !TString(name).CompareTo(obj.GetName()))
-        && (!tClass || (obj.IsA()==tClass))) {
-      ret = &obj ;
-    }
-  }
+   for (auto const &item : _items) {
+      TObject &obj = *item.first;
+      if ((!name || name[0] == '\0' || !TString(name).CompareTo(obj.GetName())) && (!tClass || (obj.IsA() == tClass))) {
+         ret = &obj;
+      }
+   }
 
-  if (ret == nullptr) {
-    coutE(InputArguments) << "RooPlot::findObject(" << GetName() << ") cannot find object " << (name?name:"<last>") << std::endl ;
-  }
-  return ret ;
+   if (ret == nullptr) {
+      std::stringstream error;
+      error << "RooPlot::findObject(" << GetName() << ") cannot find object " << (name ? name : "<last>") << "\n"
+            << "Available objects are:\n";
+      for (auto const &item : _items) {
+         TObject &obj = *item.first;
+         error << "  - " << obj.IsA()->GetName() << " \"" << obj.GetName() << "\"\n";
+      }
+      coutE(InputArguments) << error.str();
+   }
+   return ret;
 }
 
 

roofit/roofitcore/src/RooSimultaneous.cxx

@@ -777,7 +777,7 @@ RooPlot* RooSimultaneous::plotOn(RooPlot *frame, RooLinkedList& cmdList) const
        projDataTmp(projData->reduce(RooFit::SelectVars(projDataVars), RooFit::Cut(cutString.c_str())));
 
     // Override normalization and projection dataset
-    RooCmdArg tmp1 = RooFit::Normalization(scaleFactor*wTable->getFrac(idxCatClone->getCurrentLabel()),stype) ;
+    RooCmdArg tmp1 = RooFit::Normalization(scaleFactor*wTable->get(idxCatClone->getCurrentLabel()),RooAbsReal::NumEvent) ;
     RooCmdArg tmp2 = RooFit::ProjWData(*projDataSet,*projDataTmp) ;
 
     // WVE -- do not adjust normalization for asymmetry plots

roofit/roofitcore/test/stressRooFit_tests.h

@@ -2974,22 +2974,21 @@ class TestBasic501 : public RooUnitTest {
       RooPlot *frame1 = x.frame(Bins(30), Title("Physics sample"));
 
       // Plot all data tagged as physics sample
-      combData.plotOn(frame1, Cut("sample==sample::physics"));
+      std::unique_ptr<RooAbsData> slicedData1{combData.reduce(Cut("sample==sample::physics"))};
+      slicedData1->SetName("combData_Cut[sample==sample::physics]"); // to be consistent with reference file
+      slicedData1->plotOn(frame1);
 
       // Plot "physics" slice of simultaneous pdf.
-      // NBL You _must_ project the sample index category with data using ProjWData
-      // as a RooSimultaneous makes no prediction on the shape in the index category
-      // and can thus not be integrated
-      simPdf.plotOn(frame1, Slice(sample, "physics"), ProjWData(sample, combData));
-      simPdf.plotOn(frame1, Slice(sample, "physics"), Components("px"), ProjWData(sample, combData),
-                    LineStyle(kDashed));
-
-      // The same plot for the control sample slice
+      simPdf.getPdf("physics")->plotOn(frame1);
+      simPdf.getPdf("physics")->plotOn(frame1, Components("px"), LineStyle(kDashed));
+
+      // The same plot for the control sample slice.
       RooPlot *frame2 = x.frame(Bins(30), Title("Control sample"));
-      combData.plotOn(frame2, Cut("sample==sample::control"));
-      simPdf.plotOn(frame2, Slice(sample, "control"), ProjWData(sample, combData));
-      simPdf.plotOn(frame2, Slice(sample, "control"), Components("px_ctl"), ProjWData(sample, combData),
-                    LineStyle(kDashed));
+      std::unique_ptr<RooAbsData> slicedData2{combData.reduce(Cut("sample==sample::control"))};
+      slicedData2->SetName("combData_Cut[sample==sample::control]"); // to be consistent with reference file
+      slicedData2->plotOn(frame2);
+      simPdf.getPdf("control")->plotOn(frame2);
+      simPdf.getPdf("control")->plotOn(frame2, Components("px_ctl"), LineStyle(kDashed));
 
       regPlot(frame1, "rf501_plot1");
       regPlot(frame2, "rf501_plot2");

tutorials/roofit/roofit/rf501_simultaneouspdf.C

@@ -102,29 +102,28 @@ void rf501_simultaneouspdf()
    RooPlot *frame1 = x.frame(Title("Physics sample"));
 
    // Plot all data tagged as physics sample
-   combData.plotOn(frame1, Cut("sample==sample::physics"));
+   std::unique_ptr<RooAbsData> slicedData1{combData.reduce(Cut("sample==sample::physics"))};
+   slicedData1->plotOn(frame1);
 
    // Plot "physics" slice of simultaneous pdf.
+   simPdf.getPdf("physics")->plotOn(frame1);
+   simPdf.getPdf("physics")->plotOn(frame1, Components("px"), LineStyle(kDashed));
+
+   // The same plot for the control sample slice. We do this with a different
+   // approach, using the data slice for the projection. This approach is more
+   // general, because you can plot sums of slices by using logical or in the
+   // Cut() command.
    // NBL You _must_ project the sample index category with data using ProjWData
    // as a RooSimultaneous makes no prediction on the shape in the index category
    // and can thus not be integrated.
    // In other words: Since the PDF doesn't know the number of events in the different
    // category states, it doesn't know how much of each component it has to project out.
    // This information is read from the data.
-   simPdf.plotOn(frame1, Slice(sample, "physics"), ProjWData(sample, combData));
-   simPdf.plotOn(frame1, Slice(sample, "physics"), Components("px"), ProjWData(sample, combData), LineStyle(kDashed));
-
-   // The same plot for the control sample slice. We do this with a different
-   // approach this time, for illustration purposes. Here, we are slicing the
-   // dataset and then use the data slice for the projection, because then the
-   // RooFit::Slice() becomes unnecessary. This approach is more general,
-   // because you can plot sums of slices by using logical or in the Cut()
-   // command.
    RooPlot *frame2 = x.frame(Bins(30), Title("Control sample"));
-   std::unique_ptr<RooAbsData> slicedData{combData.reduce(Cut("sample==sample::control"))};
-   slicedData->plotOn(frame2);
-   simPdf.plotOn(frame2, ProjWData(sample, *slicedData));
-   simPdf.plotOn(frame2, Components("px_ctl"), ProjWData(sample, *slicedData), LineStyle(kDashed));
+   std::unique_ptr<RooAbsData> slicedData2{combData.reduce(Cut("sample==sample::control"))};
+   slicedData2->plotOn(frame2);
+   simPdf.plotOn(frame2, ProjWData(sample, *slicedData2));
+   simPdf.plotOn(frame2, Components("px_ctl"), ProjWData(sample, *slicedData2), LineStyle(kDashed));
 
    // The same plot for all the phase space. Here, we can just use the original
    // combined dataset.

tutorials/roofit/roofit/rf501_simultaneouspdf.py

@@ -11,7 +11,7 @@
 ## \date February 2018
 ## \authors Clemens Lange, Wouter Verkerke (C++ version)
 
 import ROOT
 
 
 # Create model for physics sample
@@ -96,28 +96,28 @@
 frame1 = x.frame(Title="Physics sample")
 
 # Plot all data tagged as physics sample
-combData.plotOn(frame1, Cut="sample==sample::physics")
+slicedData1 = combData.reduce(Cut="sample==sample::physics")
+slicedData1.plotOn(frame1)
 
 # Plot "physics" slice of simultaneous pdf.
-# NB: You *must* project the sample index category with data using ProjWData as
-# a RooSimultaneous makes no prediction on the shape in the index category and
-# can thus not be integrated. In other words: Since the PDF doesn't know the
-# number of events in the different category states, it doesn't know how much
-# of each component it has to project out. This info is read from the data.
-simPdf.plotOn(frame1, Slice=(sample, "physics"), ProjWData=(sample, combData))
-simPdf.plotOn(frame1, Slice=(sample, "physics"), Components="px", ProjWData=(sample, combData), LineStyle="--")
+simPdf.getPdf("physics").plotOn(frame1)
+simPdf.getPdf("physics").plotOn(frame1, Components="px", LineStyle="--")
 
 # The same plot for the control sample slice. We do this with a different
-# approach this time, for illustration purposes. Here, we are slicing the
-# dataset and then use the data slice for the projection, because then the
-# RooFit::Slice() becomes unnecessary. This approach is more general,
-# because you can plot sums of slices by using logical or in the Cut()
-# command.
+# approach, using the data slice for the projection. This approach is more
+# general, because you can plot sums of slices by using logical or in the
+# Cut() command.
+# NBL You _must_ project the sample index category with data using ProjWData
+# as a RooSimultaneous makes no prediction on the shape in the index category
+# and can thus not be integrated.
+# In other words: Since the PDF doesn't know the number of events in the different
+# category states, it doesn't know how much of each component it has to project out.
+# This information is read from the data.
 frame2 = x.frame(Title="Control sample")
-slicedData = combData.reduce(Cut="sample==sample::control")
-slicedData.plotOn(frame2)
-simPdf.plotOn(frame2, ProjWData=(sample, slicedData))
-simPdf.plotOn(frame2, Components="px_ctl", ProjWData=(sample, slicedData), LineStyle="--")
+slicedData2 = combData.reduce(Cut="sample==sample::control")
+slicedData2.plotOn(frame2)
+simPdf.plotOn(frame2, ProjWData=(sample, slicedData2))
+simPdf.plotOn(frame2, Components="px_ctl", ProjWData=(sample, slicedData2), LineStyle="--")
 
 # The same plot for all the phase space. Here, we can just use the original
 # combined dataset.