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Implement evaluator for Replicate.
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@ -615,6 +615,56 @@ protected:
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};
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// -------------------- Replicate --------------------
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template<typename XprType, int RowFactor, int ColFactor>
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struct evaluator_impl<Replicate<XprType, RowFactor, ColFactor> >
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{
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typedef Replicate<XprType, RowFactor, ColFactor> ReplicateType;
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evaluator_impl(const ReplicateType& replicate)
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: m_argImpl(replicate.nestedExpression()),
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m_rows(replicate.nestedExpression().rows()),
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m_cols(replicate.nestedExpression().cols())
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{ }
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typedef typename ReplicateType::Index Index;
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typedef typename ReplicateType::CoeffReturnType CoeffReturnType;
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typedef typename ReplicateType::PacketReturnType PacketReturnType;
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CoeffReturnType coeff(Index row, Index col) const
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{
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// try to avoid using modulo; this is a pure optimization strategy
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const Index actual_row = internal::traits<XprType>::RowsAtCompileTime==1 ? 0
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: RowFactor==1 ? row
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: row % m_rows;
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const Index actual_col = internal::traits<XprType>::ColsAtCompileTime==1 ? 0
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: ColFactor==1 ? col
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: col % m_cols;
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return m_argImpl.coeff(actual_row, actual_col);
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}
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template<int LoadMode>
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PacketReturnType packet(Index row, Index col) const
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{
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const Index actual_row = internal::traits<XprType>::RowsAtCompileTime==1 ? 0
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: RowFactor==1 ? row
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: row % m_rows;
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const Index actual_col = internal::traits<XprType>::ColsAtCompileTime==1 ? 0
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: ColFactor==1 ? col
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: col % m_cols;
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return m_argImpl.template packet<LoadMode>(actual_row, actual_col);
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}
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protected:
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typename evaluator<XprType>::type m_argImpl;
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Index m_rows;
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Index m_cols;
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};
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} // namespace internal
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#endif // EIGEN_COREEVALUATORS_H
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@ -122,6 +122,10 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
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return m_matrix.template packet<LoadMode>(actual_row, actual_col);
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}
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const typename internal::remove_all<typename MatrixType::Nested>::type& nestedExpression() const
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{
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return m_matrix;
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}
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protected:
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const typename MatrixType::Nested m_matrix;
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@ -167,4 +167,13 @@ void test_evaluators()
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// test Select
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VERIFY_IS_APPROX_EVALUATOR(aX, (aXsrc > 0).select(aXsrc, -aXsrc));
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// test Replicate
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mXsrc = MatrixXf::Random(6, 6);
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VectorXf vX = VectorXf::Random(6);
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mX.resize(6, 6);
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VERIFY_IS_APPROX_EVALUATOR(mX, mXsrc.colwise() + vX);
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matXcd.resize(12, 12);
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VERIFY_IS_APPROX_EVALUATOR(matXcd, matXcd_ref.replicate(2,2));
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VERIFY_IS_APPROX_EVALUATOR(matXcd, (matXcd_ref.replicate<2,2>()));
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}
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