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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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99
test/qr_fullpivoting.cpp
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@@ -12,21 +12,20 @@
#include <Eigen/QR>
#include "solverbase.h"
template<typename MatrixType> void qr()
{
template <typename MatrixType>
void qr() {
static const int Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime;
Index max_size = EIGEN_TEST_MAX_SIZE;
Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10);
Index rows = Rows == Dynamic ? internal::random<Index>(min_size,max_size) : Rows,
cols = Cols == Dynamic ? internal::random<Index>(min_size,max_size) : Cols,
cols2 = Cols == Dynamic ? internal::random<Index>(min_size,max_size) : Cols,
rank = internal::random<Index>(1, (std::min)(rows, cols)-1);
Index min_size = numext::maxi(1, EIGEN_TEST_MAX_SIZE / 10);
Index rows = Rows == Dynamic ? internal::random<Index>(min_size, max_size) : Rows,
cols = Cols == Dynamic ? internal::random<Index>(min_size, max_size) : Cols,
cols2 = Cols == Dynamic ? internal::random<Index>(min_size, max_size) : Cols,
rank = internal::random<Index>(1, (std::min)(rows, cols) - 1);
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType;
MatrixType m1;
createRandomPIMatrixOfRank(rank,rows,cols,m1);
createRandomPIMatrixOfRank(rank, rows, cols, m1);
FullPivHouseholderQR<MatrixType> qr(m1);
VERIFY_IS_EQUAL(rank, qr.rank());
VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel());
@@ -35,55 +34,56 @@ template<typename MatrixType> void qr()
VERIFY(!qr.isSurjective());
MatrixType r = qr.matrixQR();
MatrixQType q = qr.matrixQ();
VERIFY_IS_UNITARY(q);
// FIXME need better way to construct trapezoid
for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) if(i>j) r(i,j) = Scalar(0);
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
if (i > j) r(i, j) = Scalar(0);
MatrixType c = qr.matrixQ() * r * qr.colsPermutation().inverse();
VERIFY_IS_APPROX(m1, c);
// stress the ReturnByValue mechanism
MatrixType tmp;
VERIFY_IS_APPROX(tmp.noalias() = qr.matrixQ() * r, (qr.matrixQ() * r).eval());
check_solverbase<MatrixType, MatrixType>(m1, qr, rows, cols, cols2);
{
MatrixType m2, m3;
Index size = rows;
do {
m1 = MatrixType::Random(size,size);
m1 = MatrixType::Random(size, size);
qr.compute(m1);
} while(!qr.isInvertible());
} while (!qr.isInvertible());
MatrixType m1_inv = qr.inverse();
m3 = m1 * MatrixType::Random(size,cols2);
m3 = m1 * MatrixType::Random(size, cols2);
m2 = qr.solve(m3);
VERIFY_IS_APPROX(m2, m1_inv*m3);
VERIFY_IS_APPROX(m2, m1_inv * m3);
}
}
template<typename MatrixType> void qr_invertible()
{
using std::log;
template <typename MatrixType>
void qr_invertible() {
using std::abs;
using std::log;
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
typedef typename MatrixType::Scalar Scalar;
Index max_size = numext::mini(50,EIGEN_TEST_MAX_SIZE);
Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10);
Index size = internal::random<Index>(min_size,max_size);
Index max_size = numext::mini(50, EIGEN_TEST_MAX_SIZE);
Index min_size = numext::maxi(1, EIGEN_TEST_MAX_SIZE / 10);
Index size = internal::random<Index>(min_size, max_size);
MatrixType m1(size, size), m2(size, size), m3(size, size);
m1 = MatrixType::Random(size,size);
m1 = MatrixType::Random(size, size);
if (internal::is_same<RealScalar,float>::value)
{
if (internal::is_same<RealScalar, float>::value) {
// let's build a matrix more stable to inverse
MatrixType a = MatrixType::Random(size,size*2);
MatrixType a = MatrixType::Random(size, size * 2);
m1 += a * a.adjoint();
}
@@ -96,10 +96,10 @@ template<typename MatrixType> void qr_invertible()
// now construct a matrix with prescribed determinant
m1.setZero();
for(int i = 0; i < size; i++) m1(i,i) = internal::random<Scalar>();
for (int i = 0; i < size; i++) m1(i, i) = internal::random<Scalar>();
Scalar det = m1.diagonal().prod();
RealScalar absdet = abs(det);
m3 = qr.matrixQ(); // get a unitary
m3 = qr.matrixQ(); // get a unitary
m1 = m3 * m1 * m3.adjoint();
qr.compute(m1);
VERIFY_IS_APPROX(det, qr.determinant());
@@ -107,8 +107,8 @@ template<typename MatrixType> void qr_invertible()
VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant());
}
template<typename MatrixType> void qr_verify_assert()
{
template <typename MatrixType>
void qr_verify_assert() {
MatrixType tmp;
FullPivHouseholderQR<MatrixType> qr;
@@ -127,22 +127,21 @@ template<typename MatrixType> void qr_verify_assert()
VERIFY_RAISES_ASSERT(qr.logAbsDeterminant())
}
EIGEN_DECLARE_TEST(qr_fullpivoting)
{
for(int i = 0; i < 1; i++) {
CALL_SUBTEST_5( qr<Matrix3f>() );
CALL_SUBTEST_6( qr<Matrix3d>() );
CALL_SUBTEST_8( qr<Matrix2f>() );
CALL_SUBTEST_1( qr<MatrixXf>() );
CALL_SUBTEST_2( qr<MatrixXd>() );
CALL_SUBTEST_3( qr<MatrixXcd>() );
EIGEN_DECLARE_TEST(qr_fullpivoting) {
for (int i = 0; i < 1; i++) {
CALL_SUBTEST_5(qr<Matrix3f>());
CALL_SUBTEST_6(qr<Matrix3d>());
CALL_SUBTEST_8(qr<Matrix2f>());
CALL_SUBTEST_1(qr<MatrixXf>());
CALL_SUBTEST_2(qr<MatrixXd>());
CALL_SUBTEST_3(qr<MatrixXcd>());
}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( qr_invertible<MatrixXf>() );
CALL_SUBTEST_2( qr_invertible<MatrixXd>() );
CALL_SUBTEST_4( qr_invertible<MatrixXcf>() );
CALL_SUBTEST_3( qr_invertible<MatrixXcd>() );
for (int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1(qr_invertible<MatrixXf>());
CALL_SUBTEST_2(qr_invertible<MatrixXd>());
CALL_SUBTEST_4(qr_invertible<MatrixXcf>());
CALL_SUBTEST_3(qr_invertible<MatrixXcd>());
}
CALL_SUBTEST_5(qr_verify_assert<Matrix3f>());
@@ -154,8 +153,8 @@ EIGEN_DECLARE_TEST(qr_fullpivoting)
// Test problem size constructors
CALL_SUBTEST_7(FullPivHouseholderQR<MatrixXf>(10, 20));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,10,20> >(10,20)));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,10,20> >(Matrix<float,10,20>::Random())));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,20,10> >(20,10)));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,20,10> >(Matrix<float,20,10>::Random())));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float, 10, 20> >(10, 20)));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float, 10, 20> >(Matrix<float, 10, 20>::Random())));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float, 20, 10> >(20, 10)));
CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float, 20, 10> >(Matrix<float, 20, 10>::Random())));
}