From 729960e4656ab9f61e523a3908edf5474b04638d Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Fri, 18 Jun 2010 11:36:30 +0200
Subject: add missing files

---
 unsupported/test/sparse_ldlt.cpp | 68 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 68 insertions(+)
 create mode 100644 unsupported/test/sparse_ldlt.cpp

(limited to 'unsupported/test/sparse_ldlt.cpp')

diff --git a/unsupported/test/sparse_ldlt.cpp b/unsupported/test/sparse_ldlt.cpp
new file mode 100644
index 000000000..8671807c9
--- /dev/null
+++ b/unsupported/test/sparse_ldlt.cpp
@@ -0,0 +1,68 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
+//
+// Eigen is free software; you can redistribute it and/or
+// modify it under the terms of the GNU Lesser General Public
+// License as published by the Free Software Foundation; either
+// version 3 of the License, or (at your option) any later version.
+//
+// Alternatively, you can redistribute it and/or
+// modify it under the terms of the GNU General Public License as
+// published by the Free Software Foundation; either version 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
+// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+
+#include "sparse.h"
+
+#ifdef EIGEN_TAUCS_SUPPORT
+#include <Eigen/TaucsSupport>
+#endif
+
+template<typename Scalar> void sparse_ldlt(int rows, int cols)
+{
+  double density = std::max(8./(rows*cols), 0.01);
+  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
+  typedef Matrix<Scalar,Dynamic,1> DenseVector;
+
+  SparseMatrix<Scalar> m2(rows, cols);
+  DenseMatrix refMat2(rows, cols);
+
+  DenseVector b = DenseVector::Random(cols);
+  DenseVector refX(cols), x(cols);
+
+  initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
+  for(int i=0; i<rows; ++i)
+    m2.coeffRef(i,i) = refMat2(i,i) = ei_abs(ei_real(refMat2(i,i)));
+
+  refX = refMat2.template selfadjointView<Upper>().ldlt().solve(b);
+  typedef SparseMatrix<Scalar,Upper|SelfAdjoint> SparseSelfAdjointMatrix;
+  x = b;
+  SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
+  if (ldlt.succeeded())
+    ldlt.solveInPlace(x);
+  else
+    std::cerr << "warning LDLT failed\n";
+
+  VERIFY_IS_APPROX(refMat2.template selfadjointView<Upper>() * x, b);
+  VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
+}
+
+void test_sparse_ldlt()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1(sparse_ldlt<double>(8, 8) );
+    int s = ei_random<int>(1,300);
+    CALL_SUBTEST_2(sparse_ldlt<std::complex<double> >(s,s) );
+    CALL_SUBTEST_1(sparse_ldlt<double>(s,s) );
+  }
+}
-- 
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