Save one extra temporary when assigning a sparse product to a row-major sparse matrix

3 files changed, 16 insertions, 1 deletions

diff --git a/Eigen/src/SparseCore/SparseMatrix.h b/Eigen/src/SparseCore/SparseMatrix.h
index e0910a2cb..2218b220b 100644
--- a/Eigen/src/SparseCore/SparseMatrix.h
+++ b/Eigen/src/SparseCore/SparseMatrix.h
@@ -782,6 +782,9 @@ class SparseMatrix
     template<typename OtherDerived>
     inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
     { return Base::operator=(other.derived()); }
+
+    template<typename Lhs, typename Rhs>
+    inline SparseMatrix& operator=(const Product<Lhs,Rhs,AliasFreeProduct>& other);
 #endif // EIGEN_PARSED_BY_DOXYGEN
 
     template<typename OtherDerived>
diff --git a/Eigen/src/SparseCore/SparseProduct.h b/Eigen/src/SparseCore/SparseProduct.h
index c495a7398..af8a7744d 100644
--- a/Eigen/src/SparseCore/SparseProduct.h
+++ b/Eigen/src/SparseCore/SparseProduct.h
@@ -164,6 +164,18 @@ protected:
 
 } // end namespace internal
 
+// sparse matrix = sparse-product (can be sparse*sparse, sparse*perm, etc.)
+template<typename Scalar, int _Options, typename _StorageIndex>
+template<typename Lhs, typename Rhs>
+SparseMatrix<Scalar,_Options,_StorageIndex>& SparseMatrix<Scalar,_Options,_StorageIndex>::operator=(const Product<Lhs,Rhs,AliasFreeProduct>& src)
+{
+  // std::cout << "in Assignment : " << DstOptions << "\n";
+  SparseMatrix dst(src.rows(),src.cols());
+  internal::generic_product_impl<Lhs, Rhs>::evalTo(dst,src.lhs(),src.rhs());
+  this->swap(dst);
+  return *this;
+}
+
 } // end namespace Eigen
 
 #endif // EIGEN_SPARSEPRODUCT_H
diff --git a/test/sparse_product.cpp b/test/sparse_product.cpp
index db1b0e833..c8caebef7 100644
--- a/test/sparse_product.cpp
+++ b/test/sparse_product.cpp
@@ -103,7 +103,7 @@ template<typename SparseMatrixType> void sparse_product()
     // make sure the right product implementation is called:
     if((!SparseMatrixType::IsRowMajor) && m2.rows()<=m3.cols())
     {
-      VERIFY_EVALUATION_COUNT(m4 = m2*m3, 3); // 1 temp for the result + 2 for transposing and get a sorted result.
+      VERIFY_EVALUATION_COUNT(m4 = m2*m3, 2); // 2 for transposing and get a sorted result.
       VERIFY_EVALUATION_COUNT(m4 = (m2*m3).pruned(0), 1);
       VERIFY_EVALUATION_COUNT(m4 = (m2*m3).eval().pruned(0), 4);
     }