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* bug fixes in: Dot, generalized eigen problem, singular matrix detetection in Cholesky

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* fix all numerical instabilies in the unit tests, now all tests can be run 2000 times
  with almost zero failures.
This commit is contained in:
Gael Guennebaud
2008-08-23 15:14:20 +00:00
parent 312013a089
commit 2120fed849
20 changed files with 632 additions and 103 deletions
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50
test/adjoint.cpp
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@@ -31,25 +31,29 @@ template<typename MatrixType> void adjoint(const MatrixType& m)
*/
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
int rows = m.rows();
int cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols),
RealScalar largerEps = test_precision<RealScalar>();
if (ei_is_same_type<RealScalar,float>::ret)
largerEps = 1e-3f;
MatrixType m1 = test_random_matrix<MatrixType>(rows, cols),
m2 = test_random_matrix<MatrixType>(rows, cols),
m3(rows, cols),
mzero = MatrixType::Zero(rows, cols),
identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Identity(rows, rows),
square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
::Random(rows, rows);
VectorType v1 = VectorType::Random(rows),
v2 = VectorType::Random(rows),
v3 = VectorType::Random(rows),
identity = SquareMatrixType::Identity(rows, rows),
square = test_random_matrix<SquareMatrixType>(rows, rows);
VectorType v1 = test_random_matrix<VectorType>(rows),
v2 = test_random_matrix<VectorType>(rows),
v3 = test_random_matrix<VectorType>(rows),
vzero = VectorType::Zero(rows);
Scalar s1 = ei_random<Scalar>(),
s2 = ei_random<Scalar>();
Scalar s1 = test_random<Scalar>(),
s2 = test_random<Scalar>();
// check basic compatibility of adjoint, transpose, conjugate
VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
@@ -61,19 +65,18 @@ template<typename MatrixType> void adjoint(const MatrixType& m)
// check basic properties of dot, norm, norm2
typedef typename NumTraits<Scalar>::Real RealScalar;
VERIFY_IS_APPROX((s1 * v1 + s2 * v2).dot(v3), s1 * v1.dot(v3) + s2 * v2.dot(v3));
VERIFY_IS_APPROX(v3.dot(s1 * v1 + s2 * v2), ei_conj(s1)*v3.dot(v1)+ei_conj(s2)*v3.dot(v2));
VERIFY_IS_APPROX(ei_conj(v1.dot(v2)), v2.dot(v1));
VERIFY_IS_APPROX(ei_abs(v1.dot(v1)), v1.norm2());
VERIFY(ei_isApprox((s1 * v1 + s2 * v2).dot(v3), s1 * v1.dot(v3) + s2 * v2.dot(v3), largerEps));
VERIFY(ei_isApprox(v3.dot(s1 * v1 + s2 * v2), ei_conj(s1)*v3.dot(v1)+ei_conj(s2)*v3.dot(v2), largerEps));
VERIFY_IS_APPROX(ei_conj(v1.dot(v2)), v2.dot(v1));
VERIFY_IS_APPROX(ei_abs(v1.dot(v1)), v1.norm2());
if(NumTraits<Scalar>::HasFloatingPoint)
VERIFY_IS_APPROX(v1.norm2(), v1.norm() * v1.norm());
VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.dot(v1)), static_cast<RealScalar>(1));
VERIFY_IS_APPROX(v1.norm2(), v1.norm() * v1.norm());
VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.dot(v1)), static_cast<RealScalar>(1));
if(NumTraits<Scalar>::HasFloatingPoint)
VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1));
// check compatibility of dot and adjoint
// FIXME this line failed with MSVC and complex<double> in the ei_aligned_free()
VERIFY_IS_APPROX(v1.dot(square * v2), (square.adjoint() * v1).dot(v2));
VERIFY(ei_isApprox(v1.dot(square * v2), (square.adjoint() * v1).dot(v2), largerEps));
// like in testBasicStuff, test operator() to check const-qualification
int r = ei_random<int>(0, rows-1),
@@ -93,10 +96,11 @@ void test_adjoint()
{
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST( adjoint(Matrix<float, 1, 1>()) );
CALL_SUBTEST( adjoint(Matrix4d()) );
CALL_SUBTEST( adjoint(MatrixXcf(3, 3)) );
CALL_SUBTEST( adjoint(Matrix3d()) );
CALL_SUBTEST( adjoint(Matrix4f()) );
CALL_SUBTEST( adjoint(MatrixXcf(4, 4)) );
CALL_SUBTEST( adjoint(MatrixXi(8, 12)) );
CALL_SUBTEST( adjoint(MatrixXcd(20, 20)) );
CALL_SUBTEST( adjoint(MatrixXf(21, 21)) );
}
// test a large matrix only once
CALL_SUBTEST( adjoint(Matrix<float, 100, 100>()) );