1 files changed, 125 insertions, 0 deletions
diff --git a/eigen/test/eigensolver_generic.cpp b/eigen/test/eigensolver_generic.cpp
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+++ b/eigen/test/eigensolver_generic.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// 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 "main.h"
+#include <limits>
+#include <Eigen/Eigenvalues>
+
+template<typename MatrixType> void eigensolver(const MatrixType& m)
+{
+  typedef typename MatrixType::Index Index;
+  /* this test covers the following files:
+     EigenSolver.h
+  */
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
+  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
+
+  MatrixType a = MatrixType::Random(rows,cols);
+  MatrixType a1 = MatrixType::Random(rows,cols);
+  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
+
+  EigenSolver<MatrixType> ei0(symmA);
+  VERIFY_IS_EQUAL(ei0.info(), Success);
+  VERIFY_IS_APPROX(symmA * ei0.pseudoEigenvectors(), ei0.pseudoEigenvectors() * ei0.pseudoEigenvalueMatrix());
+  VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
+    (ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
+
+  EigenSolver<MatrixType> ei1(a);
+  VERIFY_IS_EQUAL(ei1.info(), Success);
+  VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
+  VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
+                   ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
+  VERIFY_IS_APPROX(ei1.eigenvectors().colwise().norm(), RealVectorType::Ones(rows).transpose());
+  VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues());
+
+  EigenSolver<MatrixType> ei2;
+  ei2.setMaxIterations(RealSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
+  VERIFY_IS_EQUAL(ei2.info(), Success);
+  VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
+  VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
+  if (rows > 2) {
+    ei2.setMaxIterations(1).compute(a);
+    VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
+    VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
+  }
+
+  EigenSolver<MatrixType> eiNoEivecs(a, false);
+  VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
+  VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
+  VERIFY_IS_APPROX(ei1.pseudoEigenvalueMatrix(), eiNoEivecs.pseudoEigenvalueMatrix());
+
+  MatrixType id = MatrixType::Identity(rows, cols);
+  VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
+
+  if (rows > 2)
+  {
+    // Test matrix with NaN
+    a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
+    EigenSolver<MatrixType> eiNaN(a);
+    VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
+  }
+}
+
+template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
+{
+  EigenSolver<MatrixType> eig;
+  VERIFY_RAISES_ASSERT(eig.eigenvectors());
+  VERIFY_RAISES_ASSERT(eig.pseudoEigenvectors());
+  VERIFY_RAISES_ASSERT(eig.pseudoEigenvalueMatrix());
+  VERIFY_RAISES_ASSERT(eig.eigenvalues());
+
+  MatrixType a = MatrixType::Random(m.rows(),m.cols());
+  eig.compute(a, false);
+  VERIFY_RAISES_ASSERT(eig.eigenvectors());
+  VERIFY_RAISES_ASSERT(eig.pseudoEigenvectors());
+}
+
+void test_eigensolver_generic()
+{
+  int s = 0;
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( eigensolver(Matrix4f()) );
+    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+    CALL_SUBTEST_2( eigensolver(MatrixXd(s,s)) );
+
+    // some trivial but implementation-wise tricky cases
+    CALL_SUBTEST_2( eigensolver(MatrixXd(1,1)) );
+    CALL_SUBTEST_2( eigensolver(MatrixXd(2,2)) );
+    CALL_SUBTEST_3( eigensolver(Matrix<double,1,1>()) );
+    CALL_SUBTEST_4( eigensolver(Matrix2d()) );
+  }
+
+  CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4f()) );
+  s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+  CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXd(s,s)) );
+  CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<double,1,1>()) );
+  CALL_SUBTEST_4( eigensolver_verify_assert(Matrix2d()) );
+
+  // Test problem size constructors
+  CALL_SUBTEST_5(EigenSolver<MatrixXf> tmp(s));
+
+  // regression test for bug 410
+  CALL_SUBTEST_2(
+  {
+     MatrixXd A(1,1);
+     A(0,0) = std::sqrt(-1.);
+     Eigen::EigenSolver<MatrixXd> solver(A);
+     MatrixXd V(1, 1);
+     V(0,0) = solver.eigenvectors()(0,0).real();
+  }
+  );
+  
+  TEST_SET_BUT_UNUSED_VARIABLE(s)
+}