devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix bug #314:

Browse Source 
- remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std)
- remove the overloads for array expression that were in the std namespace
This commit is contained in:
Gael Guennebaud
2012-11-06 15:25:50 +01:00
parent 959ef37006
commit a76fbbf397
88 changed files with 496 additions and 468 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
test/array_for_matrix.cpp
View File

@@ -73,6 +73,7 @@ template<typename MatrixType> void array_for_matrix(const MatrixType& m)
template<typename MatrixType> void comparisons(const MatrixType& m)
{
using std::abs;
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -110,7 +111,7 @@ template<typename MatrixType> void comparisons(const MatrixType& m)
Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
for (int j=0; j<cols; ++j)
for (int i=0; i<rows; ++i)
m3(i,j) = internal::abs(m1(i,j))<mid ? 0 : m1(i,j);
m3(i,j) = abs(m1(i,j))<mid ? 0 : m1(i,j);
VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
.select(MatrixType::Zero(rows,cols),m1), m3);
// shorter versions:
@@ -133,11 +134,12 @@ template<typename MatrixType> void comparisons(const MatrixType& m)
template<typename VectorType> void lpNorm(const VectorType& v)
{
using std::sqrt;
VectorType u = VectorType::Random(v.size());
VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum());
VERIFY_IS_APPROX(u.template lpNorm<2>(), internal::sqrt(u.array().abs().square().sum()));
VERIFY_IS_APPROX(u.template lpNorm<2>(), sqrt(u.array().abs().square().sum()));
VERIFY_IS_APPROX(internal::pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum());
}