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* coefficient wise operators are more generic, with controllable result type.
- compatible with current STL's functors as well as with the extention proposal (TR1) * thanks to the above, Cast and ScalarMultiple have been removed * benchmark_suite is more flexible (compiler and matrix size)
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@@ -3,9 +3,9 @@ USING_PART_OF_NAMESPACE_EIGEN
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using namespace std;
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// define a custom template binary functor
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struct CwiseMinOp {
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struct CwiseMinOp EIGEN_EMPTY_STRUCT {
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template<typename Scalar>
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static Scalar op(const Scalar& a, const Scalar& b) { return std::min(a,b); }
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Scalar operator()(const Scalar& a, const Scalar& b) const { return std::min(a,b); }
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};
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// define a custom binary operator between two matrices
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@@ -14,14 +14,13 @@ const Eigen::CwiseBinaryOp<CwiseMinOp, Derived1, Derived2>
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cwiseMin(const MatrixBase<Scalar, Derived1> &mat1, const MatrixBase<Scalar, Derived2> &mat2)
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{
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return Eigen::CwiseBinaryOp<CwiseMinOp, Derived1, Derived2>(mat1.asArg(), mat2.asArg());
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// Note that the above is equivalent to:
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// return mat1.template cwise<CwiseMinOp>(mat2);
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}
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int main(int, char**)
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{
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Matrix4d m1 = Matrix4d::random(), m2 = Matrix4d::random();
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cout << cwiseMin(m1,m2) << endl; // use our new global operator
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cout << m1.cwise<CwiseMinOp>(m2) << endl; // directly use the generic expression member
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cout << cwiseMin(m1,m2) << endl; // use our new global operator
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cout << m1.cwise<CwiseMinOp>(m2) << endl; // directly use the generic expression member
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cout << m1.cwise(m2, CwiseMinOp()) << endl; // directly use the generic expression member (variant)
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return 0;
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}
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