split and extend eigen-solver tests

test/CMakeLists.txt

@@ -113,7 +113,8 @@ ei_add_test(lu ${EI_OFLAG})
 ei_add_test(determinant)
 ei_add_test(inverse)
 ei_add_test(qr)
-ei_add_test(eigensolver " " "${GSL_LIBRARIES}")
+ei_add_test(eigensolver_selfadjoint " " "${GSL_LIBRARIES}")
+ei_add_test(eigensolver_generic " " "${GSL_LIBRARIES}")
 ei_add_test(svd)
 ei_add_test(geo_orthomethods)
 ei_add_test(geo_homogeneous)

test/eigensolver_generic.cpp

@@ -0,0 +1,77 @@
+// 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 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 "main.h"
+#include <Eigen/QR>
+
+#ifdef HAS_GSL
+#include "gsl_helper.h"
+#endif
+
+template<typename MatrixType> void eigensolver(const MatrixType& m)
+{
+  /* this test covers the following files:
+     EigenSolver.h
+  */
+  int rows = m.rows();
+  int cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
+  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
+
+  // RealScalar largerEps = 10*test_precision<RealScalar>();
+
+  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_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_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
+  VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
+                   ei1.eigenvectors() * ei1.eigenvalues().asDiagonal().eval());
+
+}
+
+void test_eigensolver_generic()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST( eigensolver(Matrix4f()) );
+    CALL_SUBTEST( eigensolver(MatrixXd(17,17)) );
+
+    // some trivial but implementation-wise tricky cases
+    CALL_SUBTEST( eigensolver(MatrixXd(1,1)) );
+    CALL_SUBTEST( eigensolver(MatrixXd(2,2)) );
+    CALL_SUBTEST( eigensolver(Matrix<double,1,1>()) );
+    CALL_SUBTEST( eigensolver(Matrix<double,2,2>()) );
+  }
+}
+

test/eigensolver_selfadjoint.cpp

@@ -113,39 +113,7 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
   VERIFY_IS_APPROX(sqrtSymmA, symmA*eiSymm.operatorInverseSqrt());
 }
 
-template<typename MatrixType> void eigensolver(const MatrixType& m)
+void test_eigensolver_selfadjoint()
-{
-  /* this test covers the following files:
-     EigenSolver.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
-  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
-
-  // RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  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_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_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
-  VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
-                   ei1.eigenvectors() * ei1.eigenvalues().asDiagonal().eval());
-
-}
-
-void test_eigensolver()
 {
   for(int i = 0; i < g_repeat; i++) {
     // very important to test a 3x3 matrix since we provide a special path for it
@@ -155,8 +123,11 @@ void test_eigensolver()
     CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(5,5)) );
     CALL_SUBTEST( selfadjointeigensolver(MatrixXd(19,19)) );
 
-    CALL_SUBTEST( eigensolver(Matrix4f()) );
+    // some trivial but implementation-wise tricky cases
-    CALL_SUBTEST( eigensolver(MatrixXd(17,17)) );
+    CALL_SUBTEST( selfadjointeigensolver(MatrixXd(1,1)) );
+    CALL_SUBTEST( selfadjointeigensolver(MatrixXd(2,2)) );
+    CALL_SUBTEST( selfadjointeigensolver(Matrix<double,1,1>()) );
+    CALL_SUBTEST( selfadjointeigensolver(Matrix<double,2,2>()) );
   }
 }