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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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12
test/lu.cpp
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@@ -51,7 +51,8 @@ template<typename MatrixType> void lu_non_invertible()
/* this test covers the following files:
LU.h
*/
int rows = ei_random<int>(10,200), cols = ei_random<int>(10,200), cols2 = ei_random<int>(10,200);
// NOTE lu.dimensionOfKernel() fails most of the time for rows or cols smaller that 11
int rows = ei_random<int>(11,200), cols = ei_random<int>(11,200), cols2 = ei_random<int>(11,200);
int rank = ei_random<int>(1, std::min(rows, cols)-1);
MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
@@ -91,6 +92,13 @@ template<typename MatrixType> void lu_invertible()
MatrixType m1(size, size), m2(size, size), m3(size, size);
m1 = test_random_matrix<MatrixType>(size,size);
if (ei_is_same_type<RealScalar,float>::ret)
{
// let's build a matrix more stable to inverse
MatrixType a = test_random_matrix<MatrixType>(size,size*2);
m1 += a * a.adjoint();
}
LU<MatrixType> lu(m1);
VERIFY(0 == lu.dimensionOfKernel());
VERIFY(size == lu.rank());
@@ -99,7 +107,7 @@ template<typename MatrixType> void lu_invertible()
VERIFY(lu.isInvertible());
m3 = test_random_matrix<MatrixType>(size,size);
lu.solve(m3, &m2);
VERIFY(m3.isApprox(m1*m2, test_precision<RealScalar>()*RealScalar(100))); // FIXME
VERIFY_IS_APPROX(m3, m1*m2);
VERIFY_IS_APPROX(m2, lu.inverse()*m3);
m3 = test_random_matrix<MatrixType>(size,size);
VERIFY(lu.solve(m3, &m2));