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PR 567: makes all dense solvers inherit SoverBase (LU,Cholesky,QR,SVD).

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This changeset also includes:
 * add HouseholderSequence::conjugateIf
 * define int as the StorageIndex type for all dense solvers
 * dedicated unit tests, including assertion checking
 * _check_solve_assertion(): this method can be implemented in derived solver classes to implement custom checks
 * CompleteOrthogonalDecompositions: add applyZOnTheLeftInPlace, fix scalar type in applyZAdjointOnTheLeftInPlace(), add missing assertions
 * Cholesky: add missing assertions
 * FullPivHouseholderQR: Corrected Scalar type in _solve_impl()
 * BDCSVD: Unambiguous return type for ternary operator
 * SVDBase: Corrected Scalar type in _solve_impl()
This commit is contained in:
Patrick Peltzer
2019-01-17 01:17:39 +01:00
parent 7f32109c11
commit 15e53d5d93
23 changed files with 576 additions and 239 deletions
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64
test/qr_colpivoting.cpp
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@@ -11,9 +11,12 @@
#include "main.h"
#include <Eigen/QR>
#include <Eigen/SVD>
#include "solverbase.h"
template <typename MatrixType>
void cod() {
STATIC_CHECK(( internal::is_same<typename CompleteOrthogonalDecomposition<MatrixType>::StorageIndex,int>::value ));
Index rows = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
Index cols = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
Index cols2 = internal::random<Index>(2, EIGEN_TEST_MAX_SIZE);
@@ -46,12 +49,12 @@ void cod() {
MatrixType c = q * t * z * cod.colsPermutation().inverse();
VERIFY_IS_APPROX(matrix, c);
check_solverbase<MatrixType, MatrixType>(matrix, cod, rows, cols, cols2);
// Verify that we get the same minimum-norm solution as the SVD.
MatrixType exact_solution = MatrixType::Random(cols, cols2);
MatrixType rhs = matrix * exact_solution;
MatrixType cod_solution = cod.solve(rhs);
VERIFY_IS_APPROX(rhs, matrix * cod_solution);
// Verify that we get the same minimum-norm solution as the SVD.
JacobiSVD<MatrixType> svd(matrix, ComputeThinU | ComputeThinV);
MatrixType svd_solution = svd.solve(rhs);
VERIFY_IS_APPROX(cod_solution, svd_solution);
@@ -77,13 +80,13 @@ void cod_fixedsize() {
VERIFY(cod.isSurjective() == (rank == Cols));
VERIFY(cod.isInvertible() == (cod.isInjective() && cod.isSurjective()));
check_solverbase<Matrix<Scalar, Cols, Cols2>, Matrix<Scalar, Rows, Cols2> >(matrix, cod, Rows, Cols, Cols2);
// Verify that we get the same minimum-norm solution as the SVD.
Matrix<Scalar, Cols, Cols2> exact_solution;
exact_solution.setRandom(Cols, Cols2);
Matrix<Scalar, Rows, Cols2> rhs = matrix * exact_solution;
Matrix<Scalar, Cols, Cols2> cod_solution = cod.solve(rhs);
VERIFY_IS_APPROX(rhs, matrix * cod_solution);
// Verify that we get the same minimum-norm solution as the SVD.
JacobiSVD<MatrixType> svd(matrix, ComputeFullU | ComputeFullV);
Matrix<Scalar, Cols, Cols2> svd_solution = svd.solve(rhs);
VERIFY_IS_APPROX(cod_solution, svd_solution);
@@ -93,6 +96,8 @@ template<typename MatrixType> void qr()
{
using std::sqrt;
STATIC_CHECK(( internal::is_same<typename ColPivHouseholderQR<MatrixType>::StorageIndex,int>::value ));
Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols2 = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE);
Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1);
@@ -133,13 +138,10 @@ template<typename MatrixType> void qr()
VERIFY_IS_APPROX_OR_LESS_THAN(y, x);
}
MatrixType m2 = MatrixType::Random(cols,cols2);
MatrixType m3 = m1*m2;
m2 = MatrixType::Random(cols,cols2);
m2 = qr.solve(m3);
VERIFY_IS_APPROX(m3, m1*m2);
check_solverbase<MatrixType, MatrixType>(m1, qr, rows, cols, cols2);
{
MatrixType m2, m3;
Index size = rows;
do {
m1 = MatrixType::Random(size,size);
@@ -173,11 +175,8 @@ template<typename MatrixType, int Cols2> void qr_fixedsize()
Matrix<Scalar,Rows,Cols> c = qr.householderQ() * r * qr.colsPermutation().inverse();
VERIFY_IS_APPROX(m1, c);
Matrix<Scalar,Cols,Cols2> m2 = Matrix<Scalar,Cols,Cols2>::Random(Cols,Cols2);
Matrix<Scalar,Rows,Cols2> m3 = m1*m2;
m2 = Matrix<Scalar,Cols,Cols2>::Random(Cols,Cols2);
m2 = qr.solve(m3);
VERIFY_IS_APPROX(m3, m1*m2);
check_solverbase<Matrix<Scalar,Cols,Cols2>, Matrix<Scalar,Rows,Cols2> >(m1, qr, Rows, Cols, Cols2);
// Verify that the absolute value of the diagonal elements in R are
// non-increasing until they reache the singularity threshold.
RealScalar threshold =
@@ -264,9 +263,8 @@ template<typename MatrixType> void qr_invertible()
}
ColPivHouseholderQR<MatrixType> qr(m1);
m3 = MatrixType::Random(size,size);
m2 = qr.solve(m3);
//VERIFY_IS_APPROX(m3, m1*m2);
check_solverbase<MatrixType, MatrixType>(m1, qr, size, size, size);
// now construct a matrix with prescribed determinant
m1.setZero();
@@ -286,6 +284,8 @@ template<typename MatrixType> void qr_verify_assert()
ColPivHouseholderQR<MatrixType> qr;
VERIFY_RAISES_ASSERT(qr.matrixQR())
VERIFY_RAISES_ASSERT(qr.solve(tmp))
VERIFY_RAISES_ASSERT(qr.transpose().solve(tmp))
VERIFY_RAISES_ASSERT(qr.adjoint().solve(tmp))
VERIFY_RAISES_ASSERT(qr.householderQ())
VERIFY_RAISES_ASSERT(qr.dimensionOfKernel())
VERIFY_RAISES_ASSERT(qr.isInjective())
@@ -296,6 +296,25 @@ template<typename MatrixType> void qr_verify_assert()
VERIFY_RAISES_ASSERT(qr.logAbsDeterminant())
}
template<typename MatrixType> void cod_verify_assert()
{
MatrixType tmp;
CompleteOrthogonalDecomposition<MatrixType> cod;
VERIFY_RAISES_ASSERT(cod.matrixQTZ())
VERIFY_RAISES_ASSERT(cod.solve(tmp))
VERIFY_RAISES_ASSERT(cod.transpose().solve(tmp))
VERIFY_RAISES_ASSERT(cod.adjoint().solve(tmp))
VERIFY_RAISES_ASSERT(cod.householderQ())
VERIFY_RAISES_ASSERT(cod.dimensionOfKernel())
VERIFY_RAISES_ASSERT(cod.isInjective())
VERIFY_RAISES_ASSERT(cod.isSurjective())
VERIFY_RAISES_ASSERT(cod.isInvertible())
VERIFY_RAISES_ASSERT(cod.pseudoInverse())
VERIFY_RAISES_ASSERT(cod.absDeterminant())
VERIFY_RAISES_ASSERT(cod.logAbsDeterminant())
}
EIGEN_DECLARE_TEST(qr_colpivoting)
{
for(int i = 0; i < g_repeat; i++) {
@@ -330,6 +349,13 @@ EIGEN_DECLARE_TEST(qr_colpivoting)
CALL_SUBTEST_6(qr_verify_assert<MatrixXcf>());
CALL_SUBTEST_3(qr_verify_assert<MatrixXcd>());
CALL_SUBTEST_7(cod_verify_assert<Matrix3f>());
CALL_SUBTEST_8(cod_verify_assert<Matrix3d>());
CALL_SUBTEST_1(cod_verify_assert<MatrixXf>());
CALL_SUBTEST_2(cod_verify_assert<MatrixXd>());
CALL_SUBTEST_6(cod_verify_assert<MatrixXcf>());
CALL_SUBTEST_3(cod_verify_assert<MatrixXcd>());
// Test problem size constructors
CALL_SUBTEST_9(ColPivHouseholderQR<MatrixXf>(10, 20));