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Clang-format tests, examples, libraries, benchmarks, etc.

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This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions
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103
test/eigensolver_complex.cpp
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@@ -13,35 +13,30 @@
#include <Eigen/Eigenvalues>
#include <Eigen/LU>
template<typename MatrixType> bool find_pivot(typename MatrixType::Scalar tol, MatrixType &diffs, Index col=0)
{
template <typename MatrixType>
bool find_pivot(typename MatrixType::Scalar tol, MatrixType& diffs, Index col = 0) {
bool match = diffs.diagonal().sum() <= tol;
if(match || col==diffs.cols())
{
if (match || col == diffs.cols()) {
return match;
}
else
{
} else {
Index n = diffs.cols();
std::vector<std::pair<Index,Index> > transpositions;
for(Index i=col; i<n; ++i)
{
std::vector<std::pair<Index, Index> > transpositions;
for (Index i = col; i < n; ++i) {
Index best_index(0);
if(diffs.col(col).segment(col,n-i).minCoeff(&best_index) > tol)
break;
if (diffs.col(col).segment(col, n - i).minCoeff(&best_index) > tol) break;
best_index += col;
diffs.row(col).swap(diffs.row(best_index));
if(find_pivot(tol,diffs,col+1)) return true;
if (find_pivot(tol, diffs, col + 1)) return true;
diffs.row(col).swap(diffs.row(best_index));
// move current pivot to the end
diffs.row(n-(i-col)-1).swap(diffs.row(best_index));
transpositions.push_back(std::pair<Index,Index>(n-(i-col)-1,best_index));
diffs.row(n - (i - col) - 1).swap(diffs.row(best_index));
transpositions.push_back(std::pair<Index, Index>(n - (i - col) - 1, best_index));
}
// restore
for(Index k=transpositions.size()-1; k>=0; --k)
for (Index k = transpositions.size() - 1; k >= 0; --k)
diffs.row(transpositions[k].first).swap(diffs.row(transpositions[k].second));
}
return false;
@@ -51,26 +46,26 @@ template<typename MatrixType> bool find_pivot(typename MatrixType::Scalar tol, M
* Initially, this method checked that the k-th power sums are equal for all k = 1, ..., vec1.rows(),
* however this strategy is numerically inacurate because of numerical cancellation issues.
*/
template<typename VectorType>
void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2)
{
template <typename VectorType>
void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2) {
typedef typename VectorType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
VERIFY(vec1.cols() == 1);
VERIFY(vec2.cols() == 1);
VERIFY(vec1.rows() == vec2.rows());
Index n = vec1.rows();
RealScalar tol = test_precision<RealScalar>()*test_precision<RealScalar>()*numext::maxi(vec1.squaredNorm(),vec2.squaredNorm());
Matrix<RealScalar,Dynamic,Dynamic> diffs = (vec1.rowwise().replicate(n) - vec2.rowwise().replicate(n).transpose()).cwiseAbs2();
VERIFY( find_pivot(tol, diffs) );
RealScalar tol = test_precision<RealScalar>() * test_precision<RealScalar>() *
numext::maxi(vec1.squaredNorm(), vec2.squaredNorm());
Matrix<RealScalar, Dynamic, Dynamic> diffs =
(vec1.rowwise().replicate(n) - vec2.rowwise().replicate(n).transpose()).cwiseAbs2();
VERIFY(find_pivot(tol, diffs));
}
template<typename MatrixType> void eigensolver(const MatrixType& m)
{
template <typename MatrixType>
void eigensolver(const MatrixType& m) {
/* this test covers the following files:
ComplexEigenSolver.h, and indirectly ComplexSchur.h
*/
@@ -80,8 +75,8 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
MatrixType a = MatrixType::Random(rows,cols);
MatrixType symmA = a.adjoint() * a;
MatrixType a = MatrixType::Random(rows, cols);
MatrixType symmA = a.adjoint() * a;
ComplexEigenSolver<MatrixType> ei0(symmA);
VERIFY_IS_EQUAL(ei0.info(), Success);
@@ -110,17 +105,16 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
// Regression test for issue #66
MatrixType z = MatrixType::Zero(rows,cols);
MatrixType z = MatrixType::Zero(rows, cols);
ComplexEigenSolver<MatrixType> eiz(z);
VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
MatrixType id = MatrixType::Identity(rows, cols);
VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
if (rows > 1 && rows < 20)
{
if (rows > 1 && rows < 20) {
// Test matrix with NaN
a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
a(0, 0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
ComplexEigenSolver<MatrixType> eiNaN(a);
VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
}
@@ -136,41 +130,40 @@ template<typename MatrixType> void eigensolver(const MatrixType& m)
a.setZero();
ComplexEigenSolver<MatrixType> ei3(a);
VERIFY_IS_EQUAL(ei3.info(), Success);
VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1));
VERIFY((ei3.eigenvectors().transpose()*ei3.eigenvectors().transpose()).eval().isIdentity());
VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(), RealScalar(1));
VERIFY((ei3.eigenvectors().transpose() * ei3.eigenvectors().transpose()).eval().isIdentity());
}
}
template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
{
template <typename MatrixType>
void eigensolver_verify_assert(const MatrixType& m) {
ComplexEigenSolver<MatrixType> eig;
VERIFY_RAISES_ASSERT(eig.eigenvectors());
VERIFY_RAISES_ASSERT(eig.eigenvalues());
MatrixType a = MatrixType::Random(m.rows(),m.cols());
MatrixType a = MatrixType::Random(m.rows(), m.cols());
eig.compute(a, false);
VERIFY_RAISES_ASSERT(eig.eigenvectors());
}
EIGEN_DECLARE_TEST(eigensolver_complex)
{
EIGEN_DECLARE_TEST(eigensolver_complex) {
int s = 0;
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( eigensolver(Matrix4cf()) );
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) );
CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) );
CALL_SUBTEST_4( eigensolver(Matrix3f()) );
for (int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(eigensolver(Matrix4cf()));
s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 4);
CALL_SUBTEST_2(eigensolver(MatrixXcd(s, s)));
CALL_SUBTEST_3(eigensolver(Matrix<std::complex<float>, 1, 1>()));
CALL_SUBTEST_4(eigensolver(Matrix3f()));
TEST_SET_BUT_UNUSED_VARIABLE(s)
}
CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) );
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) );
CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()) );
CALL_SUBTEST_4( eigensolver_verify_assert(Matrix3f()) );
CALL_SUBTEST_1(eigensolver_verify_assert(Matrix4cf()));
s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 4);
CALL_SUBTEST_2(eigensolver_verify_assert(MatrixXcd(s, s)));
CALL_SUBTEST_3(eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()));
CALL_SUBTEST_4(eigensolver_verify_assert(Matrix3f()));
// Test problem size constructors
CALL_SUBTEST_5(ComplexEigenSolver<MatrixXf> tmp(s));
TEST_SET_BUT_UNUSED_VARIABLE(s)
}