diff --git a/test/vectorwiseop.cpp b/test/vectorwiseop.cpp
index a6745cb85..37dbcf970 100644
--- a/test/vectorwiseop.cpp
+++ b/test/vectorwiseop.cpp
@@ -199,22 +199,21 @@ template<typename MatrixType> void vectorwiseop_matrix(const MatrixType& m)
 
   // ------ partial reductions ------
 
-  // test norm
-  #define TEST_PARTIAL_REDUX_BASIC(FUNC,ROW,COL,PREPROCESS) {                         \
+  #define TEST_PARTIAL_REDUX_BASIC(FUNC,ROW,COL,PREPROCESS) {                          \
     ROW = m1 PREPROCESS .colwise().FUNC ;                                              \
     for(Index k=0; k<cols; ++k) VERIFY_IS_APPROX(ROW(k), m1.col(k) PREPROCESS .FUNC ); \
     COL = m1 PREPROCESS .rowwise().FUNC ;                                              \
     for(Index k=0; k<rows; ++k) VERIFY_IS_APPROX(COL(k), m1.row(k) PREPROCESS .FUNC ); \
   }
 
-  TEST_PARTIAL_REDUX_BASIC(sum(),rowvec,colvec,);
-  TEST_PARTIAL_REDUX_BASIC(prod(),rowvec,colvec,);
-  TEST_PARTIAL_REDUX_BASIC(mean(),rowvec,colvec,);
-  TEST_PARTIAL_REDUX_BASIC(minCoeff(),rrres,rcres,.real());
-  TEST_PARTIAL_REDUX_BASIC(maxCoeff(),rrres,rcres,.real());
-  TEST_PARTIAL_REDUX_BASIC(norm(),rrres,rcres,);
-  TEST_PARTIAL_REDUX_BASIC(squaredNorm(),rrres,rcres,);
-  TEST_PARTIAL_REDUX_BASIC(redux(internal::scalar_sum_op<Scalar,Scalar>()),rowvec,colvec,);
+  TEST_PARTIAL_REDUX_BASIC(sum(),        rowvec,colvec,EIGEN_EMPTY);
+  TEST_PARTIAL_REDUX_BASIC(prod(),       rowvec,colvec,EIGEN_EMPTY);
+  TEST_PARTIAL_REDUX_BASIC(mean(),       rowvec,colvec,EIGEN_EMPTY);
+  TEST_PARTIAL_REDUX_BASIC(minCoeff(),   rrres, rcres, .real());
+  TEST_PARTIAL_REDUX_BASIC(maxCoeff(),   rrres, rcres, .real());
+  TEST_PARTIAL_REDUX_BASIC(norm(),       rrres, rcres, EIGEN_EMPTY);
+  TEST_PARTIAL_REDUX_BASIC(squaredNorm(),rrres, rcres, EIGEN_EMPTY);
+  TEST_PARTIAL_REDUX_BASIC(redux(internal::scalar_sum_op<Scalar,Scalar>()),rowvec,colvec,EIGEN_EMPTY);
 
   VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum(), m1.colwise().template lpNorm<1>());
   VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().sum(), m1.rowwise().template lpNorm<1>());