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if EIGEN_NICE_RANDOM is defined, the random functions will return numbers with

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few bits left of the comma and for floating-point types will never return zero.
This replaces the custom functions in test/main.h, so one does not anymore need
to think about that when writing tests.
This commit is contained in:
Benoit Jacob
2008-09-01 17:31:21 +00:00
parent 49ff9b204c
commit 46fe7a3d9e
15 changed files with 78 additions and 83 deletions
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16
test/lu.cpp
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@@ -56,7 +56,7 @@ 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 = test_random_matrix<MatrixType>(rows,cols);
m1 = MatrixType::Random(rows,cols);
if(rows <= cols)
for(int i = rank; i < rows; i++) m1.row(i).setZero();
else
@@ -72,12 +72,12 @@ template<typename MatrixType> void lu_non_invertible()
VERIFY((m1 * lu.kernel()).isMuchSmallerThan(m1));
lu.computeKernel(&k);
VERIFY((m1 * k).isMuchSmallerThan(m1));
m2 = test_random_matrix<MatrixType>(cols,cols2);
m2 = MatrixType::Random(cols,cols2);
m3 = m1*m2;
m2 = test_random_matrix<MatrixType>(cols,cols2);
m2 = MatrixType::Random(cols,cols2);
lu.solve(m3, &m2);
VERIFY_IS_APPROX(m3, m1*m2);
m3 = test_random_matrix<MatrixType>(rows,cols2);
m3 = MatrixType::Random(rows,cols2);
VERIFY(!lu.solve(m3, &m2));
}
@@ -90,12 +90,12 @@ template<typename MatrixType> void lu_invertible()
int size = ei_random<int>(10,200);
MatrixType m1(size, size), m2(size, size), m3(size, size);
m1 = test_random_matrix<MatrixType>(size,size);
m1 = MatrixType::Random(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);
MatrixType a = MatrixType::Random(size,size*2);
m1 += a * a.adjoint();
}
@@ -105,11 +105,11 @@ template<typename MatrixType> void lu_invertible()
VERIFY(lu.isInjective());
VERIFY(lu.isSurjective());
VERIFY(lu.isInvertible());
m3 = test_random_matrix<MatrixType>(size,size);
m3 = MatrixType::Random(size,size);
lu.solve(m3, &m2);
VERIFY_IS_APPROX(m3, m1*m2);
VERIFY_IS_APPROX(m2, lu.inverse()*m3);
m3 = test_random_matrix<MatrixType>(size,size);
m3 = MatrixType::Random(size,size);
VERIFY(lu.solve(m3, &m2));
}