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/eigen2/eigen2_cholesky.cpp b/test/eigen2/eigen2_cholesky.cpp
new file mode 100644
index 0000000..9c4b6f5
--- /dev/null
+++ b/test/eigen2/eigen2_cholesky.cpp
@@ -0,0 +1,113 @@
+// 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>
+//
+// 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_NO_ASSERTION_CHECKING
+#include "main.h"
+#include <Eigen/Cholesky>
+#include <Eigen/LU>
+
+#ifdef HAS_GSL
+#include "gsl_helper.h"
+#endif
+
+template<typename MatrixType> void cholesky(const MatrixType& m)
+{
+ /* this test covers the following files:
+ LLT.h LDLT.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, MatrixType::RowsAtCompileTime> SquareMatrixType;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+
+ MatrixType a0 = MatrixType::Random(rows,cols);
+ VectorType vecB = VectorType::Random(rows), vecX(rows);
+ MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols);
+ SquareMatrixType symm = a0 * a0.adjoint();
+ // let's make sure the matrix is not singular or near singular
+ MatrixType a1 = MatrixType::Random(rows,cols);
+ symm += a1 * a1.adjoint();
+
+ #ifdef HAS_GSL
+ if (ei_is_same_type<RealScalar,double>::ret)
+ {
+ typedef GslTraits<Scalar> Gsl;
+ typename Gsl::Matrix gMatA=0, gSymm=0;
+ typename Gsl::Vector gVecB=0, gVecX=0;
+ convert<MatrixType>(symm, gSymm);
+ convert<MatrixType>(symm, gMatA);
+ convert<VectorType>(vecB, gVecB);
+ convert<VectorType>(vecB, gVecX);
+ Gsl::cholesky(gMatA);
+ Gsl::cholesky_solve(gMatA, gVecB, gVecX);
+ VectorType vecX(rows), _vecX, _vecB;
+ convert(gVecX, _vecX);
+ symm.llt().solve(vecB, &vecX);
+ Gsl::prod(gSymm, gVecX, gVecB);
+ convert(gVecB, _vecB);
+ // test gsl itself !
+ VERIFY_IS_APPROX(vecB, _vecB);
+ VERIFY_IS_APPROX(vecX, _vecX);
+
+ Gsl::free(gMatA);
+ Gsl::free(gSymm);
+ Gsl::free(gVecB);
+ Gsl::free(gVecX);
+ }
+ #endif
+
+ {
+ LDLT<SquareMatrixType> ldlt(symm);
+ VERIFY(ldlt.isPositiveDefinite());
+ // in eigen3, LDLT is pivoting
+ //VERIFY_IS_APPROX(symm, ldlt.matrixL() * ldlt.vectorD().asDiagonal() * ldlt.matrixL().adjoint());
+ ldlt.solve(vecB, &vecX);
+ VERIFY_IS_APPROX(symm * vecX, vecB);
+ ldlt.solve(matB, &matX);
+ VERIFY_IS_APPROX(symm * matX, matB);
+ }
+
+ {
+ LLT<SquareMatrixType> chol(symm);
+ VERIFY(chol.isPositiveDefinite());
+ VERIFY_IS_APPROX(symm, chol.matrixL() * chol.matrixL().adjoint());
+ chol.solve(vecB, &vecX);
+ VERIFY_IS_APPROX(symm * vecX, vecB);
+ chol.solve(matB, &matX);
+ VERIFY_IS_APPROX(symm * matX, matB);
+ }
+
+#if 0 // cholesky is not rank-revealing anyway
+ // test isPositiveDefinite on non definite matrix
+ if (rows>4)
+ {
+ SquareMatrixType symm = a0.block(0,0,rows,cols-4) * a0.block(0,0,rows,cols-4).adjoint();
+ LLT<SquareMatrixType> chol(symm);
+ VERIFY(!chol.isPositiveDefinite());
+ LDLT<SquareMatrixType> cholnosqrt(symm);
+ VERIFY(!cholnosqrt.isPositiveDefinite());
+ }
+#endif
+}
+
+void test_eigen2_cholesky()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( cholesky(Matrix<double,1,1>()) );
+ CALL_SUBTEST_2( cholesky(Matrix2d()) );
+ CALL_SUBTEST_3( cholesky(Matrix3f()) );
+ CALL_SUBTEST_4( cholesky(Matrix4d()) );
+ CALL_SUBTEST_5( cholesky(MatrixXcd(7,7)) );
+ CALL_SUBTEST_6( cholesky(MatrixXf(17,17)) );
+ CALL_SUBTEST_7( cholesky(MatrixXd(33,33)) );
+ }
+}