Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/test/eigensolver_generic.cpp b/test/eigensolver_generic.cpp
new file mode 100644
index 0000000..005af81
--- /dev/null
+++ b/test/eigensolver_generic.cpp
@@ -0,0 +1,125 @@
+// 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)
+}