Disabled external gits

2022-04-07 18:46:57 +02:00
parent 88cb3426ad
commit 15e7120d6d
5316 changed files with 4563444 additions and 6 deletions
--- a/cs440-acg/ext/eigen/test/eigensolver_generalized_real.cpp
+++ b/cs440-acg/ext/eigen/test/eigensolver_generalized_real.cpp
@@ -0,0 +1,103 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// 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/.
+
+#define EIGEN_RUNTIME_NO_MALLOC
+#include "main.h"
+#include <limits>
+#include <Eigen/Eigenvalues>
+#include <Eigen/LU>
+
+template<typename MatrixType> void generalized_eigensolver_real(const MatrixType& m)
+{
+  /* this test covers the following files:
+     GeneralizedEigenSolver.h
+  */
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef std::complex<Scalar> ComplexScalar;
+  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+
+  MatrixType a = MatrixType::Random(rows,cols);
+  MatrixType b = MatrixType::Random(rows,cols);
+  MatrixType a1 = MatrixType::Random(rows,cols);
+  MatrixType b1 = MatrixType::Random(rows,cols);
+  MatrixType spdA =  a.adjoint() * a + a1.adjoint() * a1;
+  MatrixType spdB =  b.adjoint() * b + b1.adjoint() * b1;
+
+  // lets compare to GeneralizedSelfAdjointEigenSolver
+  {
+    GeneralizedSelfAdjointEigenSolver<MatrixType> symmEig(spdA, spdB);
+    GeneralizedEigenSolver<MatrixType> eig(spdA, spdB);
+
+    VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0);
+
+    VectorType realEigenvalues = eig.eigenvalues().real();
+    std::sort(realEigenvalues.data(), realEigenvalues.data()+realEigenvalues.size());
+    VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues());
+
+    // check eigenvectors
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal();
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType V = eig.eigenvectors();
+    VERIFY_IS_APPROX(spdA*V, spdB*V*D);
+  }
+
+  // non symmetric case:
+  {
+    GeneralizedEigenSolver<MatrixType> eig(rows);
+    // TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition
+    //Eigen::internal::set_is_malloc_allowed(false);
+    eig.compute(a,b);
+    //Eigen::internal::set_is_malloc_allowed(true);
+    for(Index k=0; k<cols; ++k)
+    {
+      Matrix<ComplexScalar,Dynamic,Dynamic> tmp = (eig.betas()(k)*a).template cast<ComplexScalar>() - eig.alphas()(k)*b;
+      if(tmp.size()>1 && tmp.norm()>(std::numeric_limits<Scalar>::min)())
+        tmp /= tmp.norm();
+      VERIFY_IS_MUCH_SMALLER_THAN( std::abs(tmp.determinant()), Scalar(1) );
+    }
+    // check eigenvectors
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal();
+    typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType V = eig.eigenvectors();
+    VERIFY_IS_APPROX(a*V, b*V*D);
+  }
+
+  // regression test for bug 1098
+  {
+    GeneralizedSelfAdjointEigenSolver<MatrixType> eig1(a.adjoint() * a,b.adjoint() * b);
+    eig1.compute(a.adjoint() * a,b.adjoint() * b);
+    GeneralizedEigenSolver<MatrixType> eig2(a.adjoint() * a,b.adjoint() * b);
+    eig2.compute(a.adjoint() * a,b.adjoint() * b);
+  }
+
+  // check without eigenvectors
+  {
+    GeneralizedEigenSolver<MatrixType> eig1(spdA, spdB, true);
+    GeneralizedEigenSolver<MatrixType> eig2(spdA, spdB, false);
+    VERIFY_IS_APPROX(eig1.eigenvalues(), eig2.eigenvalues());
+  }
+}
+
+void test_eigensolver_generalized_real()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    int s = 0;
+    CALL_SUBTEST_1( generalized_eigensolver_real(Matrix4f()) );
+    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+    CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(s,s)) );
+
+    // some trivial but implementation-wise special cases
+    CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(1,1)) );
+    CALL_SUBTEST_2( generalized_eigensolver_real(MatrixXd(2,2)) );
+    CALL_SUBTEST_3( generalized_eigensolver_real(Matrix<double,1,1>()) );
+    CALL_SUBTEST_4( generalized_eigensolver_real(Matrix2d()) );
+    TEST_SET_BUT_UNUSED_VARIABLE(s)
+  }
+}