Remove more R__HAS_VECCORE guards

wiene · Jul 4, 2017 · 325133e · 325133e
1 parent cbc38d6
commit 325133e
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Showing 2 changed files with 7 additions and 18 deletions.
diff --git a/math/mathcore/inc/Fit/Fitter.h b/math/mathcore/inc/Fit/Fitter.h
@@ -83,6 +83,8 @@ class Fitter {
    using IModelFunctionTempl =                             ROOT::Math::IParamMultiFunctionTempl<T>;
 #ifdef R__HAS_VECCORE
    typedef ROOT::Math::IParametricFunctionMultiDimTempl<ROOT::Double_v>  IModelFunction_v;
+#else
+   typedef ROOT::Math::IParamMultiFunction                 IModelFunction_v;
 #endif
    typedef ROOT::Math::IParamMultiGradFunction             IGradModelFunction;
    typedef ROOT::Math::IParamFunction                      IModel1DFunction;
@@ -171,7 +173,7 @@ class Fitter {
       SetData(data);
       return DoBinnedLikelihoodFit(extended, executionPolicy);
    }
-   
+
    bool LikelihoodFit(const std::shared_ptr<BinData> &data, bool extended = true,
                       ROOT::Fit::ExecutionPolicy executionPolicy = ROOT::Fit::kSerial) {
       SetData(data);
@@ -490,11 +492,9 @@ class Fitter {
    int fDataSize;  // size of data sets (need for Fumili or LM fitters)
 
    FitConfig fConfig;       // fitter configuration (options and parameter settings)
-#ifdef R__HAS_VECCORE
+
    std::shared_ptr<IModelFunction_v> fFunc_v;  //! copy of the fitted  function containing on output the fit result
-#else
-    std::shared_ptr<IModelFunction> fFunc_v;   //dummy for when VecCore not available. Keeps the code cleaner.
-#endif
+
    std::shared_ptr<IModelFunction> fFunc;  //! copy of the fitted  function containing on output the fit result
 
    std::shared_ptr<ROOT::Fit::FitResult>  fResult;  //! pointer to the object containing the result of the fit

diff --git a/math/mathcore/src/Fitter.cxx b/math/mathcore/src/Fitter.cxx
@@ -339,12 +339,10 @@ bool Fitter::DoLeastSquareFit(ROOT::Fit::ExecutionPolicy executionPolicy) {
       if (!fFunc_v ) {
          MATH_ERROR_MSG("Fitter::DoLeastSquareFit","model function is not set");
          return false;
-#ifdef R__HAS_VECCORE
       } else{
          Chi2FCN<BaseFunc, IModelFunction_v> chi2(data, fFunc_v, executionPolicy);
          fFitType = chi2.Type();
          return DoMinimization (chi2);
-#endif
      }
    } else {
 
@@ -410,7 +408,6 @@ bool Fitter::DoBinnedLikelihoodFit(bool extended, ROOT::Fit::ExecutionPolicy exe
 
    if (!fUseGradient) {
       // do minimization without using the gradient
-#ifdef R__HAS_VECCORE
       if (fFunc_v) {
          // create a chi2 function to be used for the equivalent chi-square
          Chi2FCN<BaseFunc, IModelFunction_v> chi2(data, fFunc_v);
@@ -433,10 +430,7 @@ bool Fitter::DoBinnedLikelihoodFit(bool extended, ROOT::Fit::ExecutionPolicy exe
             logl.UseSumOfWeightSquare();
             if (!ApplyWeightCorrection(logl)) return false;
          }
-#endif
-#ifdef R__HAS_VECCORE
       }
-#endif
    } else {
       // create a chi2 function to be used for the equivalent chi-square
       Chi2FCN<BaseFunc> chi2(data, fFunc);
@@ -501,7 +495,6 @@ bool Fitter::DoUnbinnedLikelihoodFit(bool extended, ROOT::Fit::ExecutionPolicy e
 
    if (!fUseGradient) {
       // do minimization without using the gradient
-#ifdef R__HAS_VECCORE
      if (fFunc_v ){
        LogLikelihoodFCN<BaseFunc, IModelFunction_v> logl(data, fFunc_v, useWeight, extended, executionPolicy);
        fFitType = logl.Type();
@@ -511,10 +504,8 @@ bool Fitter::DoUnbinnedLikelihoodFit(bool extended, ROOT::Fit::ExecutionPolicy e
           if (!ApplyWeightCorrection(logl) ) return false;
         }
         return true;
-     }
-     else{         
-#endif
-       LogLikelihoodFCN<BaseFunc> logl(data, fFunc, useWeight, extended, executionPolicy);
+     } else {
+        LogLikelihoodFCN<BaseFunc> logl(data, fFunc, useWeight, extended, executionPolicy);
 
         fFitType = logl.Type();
         if (!DoMinimization (logl) ) return false;
@@ -523,9 +514,7 @@ bool Fitter::DoUnbinnedLikelihoodFit(bool extended, ROOT::Fit::ExecutionPolicy e
           if (!ApplyWeightCorrection(logl) ) return false;
         }
         return true;
-#ifdef R__HAS_VECCORE
      }
-#endif
    } else {
       // use gradient : check if fFunc provides gradient
       if (fConfig.MinimizerOptions().PrintLevel() > 0)