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* bugfix in SolveTriangular found by Timothy Hunter (did not compiled for very small fixed size matrices)

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* bugfix in Dot unroller
* added special random generator for the unit tests and reduced the tolerance threshold by an order of magnitude
  this fixes issues with sum.cpp but other tests still failed sometimes, this have to be carefully checked...
This commit is contained in:
Gael Guennebaud
2008-08-22 17:48:36 +00:00
parent a95c1e190b
commit f0394edfa7
14 changed files with 103 additions and 65 deletions
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17
test/lu.cpp
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@@ -55,7 +55,7 @@ template<typename MatrixType> void lu_non_invertible()
int rank = ei_random<int>(1, std::min(rows, cols)-1);
MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
m1.setRandom();
m1 = test_random_matrix<MatrixType>(rows,cols);
if(rows <= cols)
for(int i = rank; i < rows; i++) m1.row(i).setZero();
else
@@ -71,12 +71,12 @@ template<typename MatrixType> void lu_non_invertible()
VERIFY((m1 * lu.kernel()).isMuchSmallerThan(m1));
lu.computeKernel(&k);
VERIFY((m1 * k).isMuchSmallerThan(m1));
m2.setRandom();
m2 = test_random_matrix<MatrixType>(cols,cols2);
m3 = m1*m2;
m2.setRandom();
m2 = test_random_matrix<MatrixType>(cols,cols2);
lu.solve(m3, &m2);
VERIFY_IS_APPROX(m3, m1*m2);
m3.setRandom();
m3 = test_random_matrix<MatrixType>(rows,cols2);
VERIFY(!lu.solve(m3, &m2));
}
@@ -85,10 +85,11 @@ template<typename MatrixType> void lu_invertible()
/* this test covers the following files:
LU.h
*/
typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
int size = ei_random<int>(10,200);
MatrixType m1(size, size), m2(size, size), m3(size, size);
m1.setRandom();
m1 = test_random_matrix<MatrixType>(size,size);
LU<MatrixType> lu(m1);
VERIFY(0 == lu.dimensionOfKernel());
@@ -96,11 +97,11 @@ template<typename MatrixType> void lu_invertible()
VERIFY(lu.isInjective());
VERIFY(lu.isSurjective());
VERIFY(lu.isInvertible());
m3.setRandom();
m3 = test_random_matrix<MatrixType>(size,size);
lu.solve(m3, &m2);
VERIFY_IS_APPROX(m3, m1*m2);
VERIFY(m3.isApprox(m1*m2, test_precision<RealScalar>()*RealScalar(100))); // FIXME
VERIFY_IS_APPROX(m2, lu.inverse()*m3);
m3.setRandom();
m3 = test_random_matrix<MatrixType>(size,size);
VERIFY(lu.solve(m3, &m2));
}