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diff --git a/eigen/test/eigen2/eigen2_sparse_product.cpp b/eigen/test/eigen2/eigen2_sparse_product.cpp
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+++ b/eigen/test/eigen2/eigen2_sparse_product.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "sparse.h"
+
+template<typename SparseMatrixType> void sparse_product(const SparseMatrixType& ref)
+{
+  const int rows = ref.rows();
+  const int cols = ref.cols();
+  typedef typename SparseMatrixType::Scalar Scalar;
+  enum { Flags = SparseMatrixType::Flags };
+
+  double density = std::max(8./(rows*cols), 0.01);
+  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+  typedef Matrix<Scalar,Dynamic,1> DenseVector;
+
+  // test matrix-matrix product
+  {
+    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows);
+    DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType m2(rows, rows);
+    SparseMatrixType m3(rows, rows);
+    SparseMatrixType m4(rows, rows);
+    initSparse<Scalar>(density, refMat2, m2);
+    initSparse<Scalar>(density, refMat3, m3);
+    initSparse<Scalar>(density, refMat4, m4);
+    VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(m4=m2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
+    VERIFY_IS_APPROX(m4=m2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
+    VERIFY_IS_APPROX(m4=m2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
+
+    // sparse * dense
+    VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=m2*refMat3.transpose(), refMat4=refMat2*refMat3.transpose());
+    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3, refMat4=refMat2.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
+
+    // dense * sparse
+    VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
+    VERIFY_IS_APPROX(dm4=refMat2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
+    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
+    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
+
+    VERIFY_IS_APPROX(m3=m3*m3, refMat3=refMat3*refMat3);
+  }
+
+  // test matrix - diagonal product
+  if(false) // it compiles, but the precision is terrible. probably doesn't matter in this branch....
+  {
+    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
+    DiagonalMatrix<DenseVector> d1(DenseVector::Random(rows));
+    SparseMatrixType m2(rows, rows);
+    SparseMatrixType m3(rows, rows);
+    initSparse<Scalar>(density, refM2, m2);
+    initSparse<Scalar>(density, refM3, m3);
+    VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
+    VERIFY_IS_APPROX(m3=m2.transpose()*d1, refM3=refM2.transpose()*d1);
+    VERIFY_IS_APPROX(m3=d1*m2, refM3=d1*refM2);
+    VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1 * refM2.transpose());
+  }
+
+  // test self adjoint products
+  {
+    DenseMatrix b = DenseMatrix::Random(rows, rows);
+    DenseMatrix x = DenseMatrix::Random(rows, rows);
+    DenseMatrix refX = DenseMatrix::Random(rows, rows);
+    DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
+    DenseMatrix refS = DenseMatrix::Zero(rows, rows);
+    SparseMatrixType mUp(rows, rows);
+    SparseMatrixType mLo(rows, rows);
+    SparseMatrixType mS(rows, rows);
+    do {
+      initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
+    } while (refUp.isZero());
+    refLo = refUp.transpose().conjugate();
+    mLo = mUp.transpose().conjugate();
+    refS = refUp + refLo;
+    refS.diagonal() *= 0.5;
+    mS = mUp + mLo;
+    for (int k=0; k<mS.outerSize(); ++k)
+      for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
+        if (it.index() == k)
+          it.valueRef() *= 0.5;
+
+    VERIFY_IS_APPROX(refS.adjoint(), refS);
+    VERIFY_IS_APPROX(mS.transpose().conjugate(), mS);
+    VERIFY_IS_APPROX(mS, refS);
+    VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
+    VERIFY_IS_APPROX(x=mUp.template marked<UpperTriangular|SelfAdjoint>()*b, refX=refS*b);
+    VERIFY_IS_APPROX(x=mLo.template marked<LowerTriangular|SelfAdjoint>()*b, refX=refS*b);
+    VERIFY_IS_APPROX(x=mS.template marked<SelfAdjoint>()*b, refX=refS*b);
+  }
+
+}
+
+void test_eigen2_sparse_product()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(8, 8)) );
+    CALL_SUBTEST_2( sparse_product(SparseMatrix<std::complex<double> >(16, 16)) );
+    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(33, 33)) );
+
+    CALL_SUBTEST_3( sparse_product(DynamicSparseMatrix<double>(8, 8)) );
+  }
+}