eigen/doc/examples/class_CwiseBinaryOp.cpp
Benoit Jacob d1a29d6319 -new: recursive costs system, useful to determine automatically
when to evaluate arguments and when to meta-unroll.
-use it in Product to determine when to eval args. not yet used
 to determine when to unroll. for now, not used anywhere else but
 that'll follow.
-fix badness of my last commit
2008-04-03 11:10:17 +00:00

30 lines
1.3 KiB
C++

// FIXME - this example is not too good as that functionality is provided in the Eigen API
// additionally it's quite heavy. the CwiseUnaryOp example is better.
#include <Eigen/Core>
USING_PART_OF_NAMESPACE_EIGEN
using namespace std;
// define a custom template binary functor
template<typename Scalar> struct CwiseMinOp EIGEN_EMPTY_STRUCT {
Scalar operator()(const Scalar& a, const Scalar& b) const { return std::min(a,b); }
enum { Cost = Eigen::ConditionalJumpCost + Eigen::NumTraits<Scalar>::AddCost };
};
// define a custom binary operator between two matrices
template<typename Derived1, typename Derived2>
const Eigen::CwiseBinaryOp<CwiseMinOp<typename Derived1::Scalar>, Derived1, Derived2>
cwiseMin(const MatrixBase<Derived1> &mat1, const MatrixBase<Derived2> &mat2)
{
return Eigen::CwiseBinaryOp<CwiseMinOp<typename Derived1::Scalar>, Derived1, Derived2>(mat1, mat2);
}
int main(int, char**)
{
Matrix4d m1 = Matrix4d::random(), m2 = Matrix4d::random();
cout << cwiseMin(m1,m2) << endl; // use our new global operator
cout << m1.cwise<CwiseMinOp<double> >(m2) << endl; // directly use the generic expression member
cout << m1.cwise(m2, CwiseMinOp<double>()) << endl; // directly use the generic expression member (variant)
return 0;
}