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import evaluator works
This commit is contained in:
parent
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@ -350,6 +350,11 @@ using std::size_t;
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#include "src/Core/ArrayBase.h"
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#include "src/Core/ArrayWrapper.h"
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#ifdef EIGEN_ENABLE_EVALUATORS
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#include "src/Core/CoreEvaluators.h"
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#include "src/Core/AssignEvaluator.h"
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#endif
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} // namespace Eigen
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#include "src/Core/GlobalFunctions.h"
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180
Eigen/src/Core/AssignEvaluator.h
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180
Eigen/src/Core/AssignEvaluator.h
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@ -0,0 +1,180 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
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// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_ASSIGN_EVALUATOR_H
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#define EIGEN_ASSIGN_EVALUATOR_H
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// This implementation is based on Assign.h
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// copy_using_evaluator_traits is based on assign_traits
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namespace internal {
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template <typename Derived, typename OtherDerived>
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struct copy_using_evaluator_traits
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{
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public:
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enum {
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DstIsAligned = Derived::Flags & AlignedBit,
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DstHasDirectAccess = Derived::Flags & DirectAccessBit,
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SrcIsAligned = OtherDerived::Flags & AlignedBit,
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JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
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};
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private:
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enum {
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InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
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: int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
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: int(Derived::RowsAtCompileTime),
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InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
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: int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
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: int(Derived::MaxRowsAtCompileTime),
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MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
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PacketSize = packet_traits<typename Derived::Scalar>::size
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};
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enum {
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StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
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MightVectorize = StorageOrdersAgree
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&& (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
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MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
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&& int(DstIsAligned) && int(SrcIsAligned),
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MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
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MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
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&& (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
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/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
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so it's only good for large enough sizes. */
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MaySliceVectorize = MightVectorize && DstHasDirectAccess
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&& (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
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/* slice vectorization can be slow, so we only want it if the slices are big, which is
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indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
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in a fixed-size matrix */
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};
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public:
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enum {
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Traversal = int(MayInnerVectorize) ? int(DefaultTraversal) // int(InnerVectorizedTraversal)
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: int(MayLinearVectorize) ? int(DefaultTraversal) // int(LinearVectorizedTraversal)
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: int(MaySliceVectorize) ? int(DefaultTraversal) // int(SliceVectorizedTraversal)
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: int(MayLinearize) ? int(DefaultTraversal) // int(LinearTraversal)
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: int(DefaultTraversal),
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Vectorized = int(Traversal) == InnerVectorizedTraversal
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|| int(Traversal) == LinearVectorizedTraversal
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|| int(Traversal) == SliceVectorizedTraversal
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};
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private:
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enum {
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UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
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MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
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&& int(OtherDerived::CoeffReadCost) != Dynamic
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&& int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
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MayUnrollInner = int(InnerSize) != Dynamic
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&& int(OtherDerived::CoeffReadCost) != Dynamic
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&& int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
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};
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public:
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enum {
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Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
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? (
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int(MayUnrollCompletely) ? int(NoUnrolling) // int(CompleteUnrolling)
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: int(MayUnrollInner) ? int(NoUnrolling) // int(InnerUnrolling)
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: int(NoUnrolling)
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)
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: int(Traversal) == int(LinearVectorizedTraversal)
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? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(NoUnrolling) // int(CompleteUnrolling)
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: int(NoUnrolling) )
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: int(Traversal) == int(LinearTraversal)
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? ( bool(MayUnrollCompletely) ? int(NoUnrolling) // int(CompleteUnrolling)
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: int(NoUnrolling) )
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: int(NoUnrolling)
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};
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#ifdef EIGEN_DEBUG_ASSIGN
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static void debug()
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{
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EIGEN_DEBUG_VAR(DstIsAligned)
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EIGEN_DEBUG_VAR(SrcIsAligned)
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EIGEN_DEBUG_VAR(JointAlignment)
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EIGEN_DEBUG_VAR(InnerSize)
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EIGEN_DEBUG_VAR(InnerMaxSize)
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EIGEN_DEBUG_VAR(PacketSize)
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EIGEN_DEBUG_VAR(StorageOrdersAgree)
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EIGEN_DEBUG_VAR(MightVectorize)
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EIGEN_DEBUG_VAR(MayLinearize)
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EIGEN_DEBUG_VAR(MayInnerVectorize)
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EIGEN_DEBUG_VAR(MayLinearVectorize)
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EIGEN_DEBUG_VAR(MaySliceVectorize)
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EIGEN_DEBUG_VAR(Traversal)
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EIGEN_DEBUG_VAR(UnrollingLimit)
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EIGEN_DEBUG_VAR(MayUnrollCompletely)
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EIGEN_DEBUG_VAR(MayUnrollInner)
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EIGEN_DEBUG_VAR(Unrolling)
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}
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#endif
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};
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// copy_using_evaluator_impl is based on assign_impl
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template<typename LhsXprType, typename RhsXprType,
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int Traversal = copy_using_evaluator_traits<LhsXprType, RhsXprType>::Traversal,
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int Unrolling = copy_using_evaluator_traits<LhsXprType, RhsXprType>::Unrolling>
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struct copy_using_evaluator_impl;
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template<typename LhsXprType, typename RhsXprType>
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struct copy_using_evaluator_impl<LhsXprType, RhsXprType, DefaultTraversal, NoUnrolling>
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{
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static void run(const LhsXprType& lhs, const RhsXprType& rhs)
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{
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typedef typename evaluator<LhsXprType>::type LhsEvaluatorType;
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typedef typename evaluator<RhsXprType>::type RhsEvaluatorType;
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typedef typename LhsXprType::Index Index;
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LhsEvaluatorType lhsEvaluator(lhs.const_cast_derived());
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RhsEvaluatorType rhsEvaluator(rhs);
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for(Index outer = 0; outer < lhs.outerSize(); ++outer) {
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for(Index inner = 0; inner < lhs.innerSize(); ++inner) {
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Index row = lhs.rowIndexByOuterInner(outer, inner);
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Index col = lhs.colIndexByOuterInner(outer, inner);
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lhsEvaluator.coeffRef(row, col) = rhsEvaluator.coeff(row, col);
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}
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}
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}
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};
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// Based on DenseBase::LazyAssign()
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template<typename LhsXprType, typename RhsXprType>
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void copy_using_evaluator(const LhsXprType& lhs, const RhsXprType& rhs)
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{
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copy_using_evaluator_impl<LhsXprType, RhsXprType>::run(lhs, rhs);
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}
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} // namespace internal
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#endif // EIGEN_ASSIGN_EVALUATOR_H
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212
Eigen/src/Core/CoreEvaluators.h
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212
Eigen/src/Core/CoreEvaluators.h
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@ -0,0 +1,212 @@
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
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// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#ifndef EIGEN_COREEVALUATORS_H
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#define EIGEN_COREEVALUATORS_H
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namespace internal {
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template<typename T>
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struct evaluator_impl {};
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template<typename T>
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struct evaluator
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{
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typedef evaluator_impl<T> type;
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};
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template<typename T>
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struct evaluator<const T>
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{
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typedef evaluator_impl<T> type;
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};
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template<typename ExpressionType>
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struct evaluator_impl<Transpose<ExpressionType> >
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{
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typedef Transpose<ExpressionType> TransposeType;
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evaluator_impl(const TransposeType& t) : m_argImpl(t.nestedExpression()) {}
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typedef typename TransposeType::Index Index;
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typename TransposeType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_argImpl.coeff(j, i);
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}
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typename TransposeType::Scalar& coeffRef(Index i, Index j)
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{
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return m_argImpl.coeffRef(j, i);
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}
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protected:
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typename evaluator<ExpressionType>::type m_argImpl;
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};
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template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
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struct evaluator_impl<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
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{
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typedef Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> MatrixType;
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evaluator_impl(const MatrixType& m) : m_matrix(m) {}
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typedef typename MatrixType::Index Index;
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typename MatrixType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_matrix.coeff(i, j);
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}
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typename MatrixType::Scalar& coeffRef(Index i, Index j)
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{
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return m_matrix.const_cast_derived().coeffRef(i, j);
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}
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protected:
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const MatrixType &m_matrix;
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};
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template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
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struct evaluator_impl<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
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{
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typedef Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> ArrayType;
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evaluator_impl(const ArrayType& a) : m_array(a) {}
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typedef typename ArrayType::Index Index;
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Index colIndexByOuterInner(Index outer, Index inner) const
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{
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return m_array.colIndexByOuterInner(outer, inner);
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}
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typename ArrayType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_array.coeff(i, j);
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}
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typename ArrayType::Scalar& coeffRef(Index i, Index j)
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{
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return m_array.const_cast_derived().coeffRef(i, j);
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}
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protected:
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const ArrayType &m_array;
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};
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template<typename NullaryOp, typename PlainObjectType>
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struct evaluator_impl<CwiseNullaryOp<NullaryOp,PlainObjectType> >
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{
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typedef CwiseNullaryOp<NullaryOp,PlainObjectType> NullaryOpType;
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evaluator_impl(const NullaryOpType& n) : m_nullaryOp(n) {}
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typedef typename NullaryOpType::Index Index;
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typename NullaryOpType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_nullaryOp.coeff(i, j);
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}
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protected:
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const NullaryOpType& m_nullaryOp;
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};
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template<typename UnaryOp, typename ArgType>
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struct evaluator_impl<CwiseUnaryOp<UnaryOp, ArgType> >
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{
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typedef CwiseUnaryOp<UnaryOp, ArgType> UnaryOpType;
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evaluator_impl(const UnaryOpType& op) : m_unaryOp(op), m_argImpl(op.nestedExpression()) {}
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typedef typename UnaryOpType::Index Index;
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typename UnaryOpType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_unaryOp.functor()(m_argImpl.coeff(i, j));
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}
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protected:
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const UnaryOpType& m_unaryOp;
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typename evaluator<ArgType>::type m_argImpl;
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};
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template<typename BinaryOp, typename Lhs, typename Rhs>
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struct evaluator_impl<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
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{
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typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> BinaryOpType;
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evaluator_impl(const BinaryOpType& xpr) : m_binaryOp(xpr), m_lhsImpl(xpr.lhs()), m_rhsImpl(xpr.rhs()) {}
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typedef typename BinaryOpType::Index Index;
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typename BinaryOpType::CoeffReturnType coeff(Index i, Index j) const
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{
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return m_binaryOp.functor()(m_lhsImpl.coeff(i, j),m_rhsImpl.coeff(i, j));
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}
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protected:
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const BinaryOpType& m_binaryOp;
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typename evaluator<Lhs>::type m_lhsImpl;
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typename evaluator<Rhs>::type m_rhsImpl;
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};
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// products
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template<typename Lhs, typename Rhs, int ProductType>
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struct evaluator_impl<GeneralProduct<Lhs,Rhs,ProductType> > : public evaluator<typename GeneralProduct<Lhs,Rhs,ProductType>::PlainObject>::type
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{
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typedef GeneralProduct<Lhs,Rhs,ProductType> XprType;
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typedef typename XprType::PlainObject PlainObject;
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typedef typename evaluator<PlainObject>::type evaluator_base;
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// enum {
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// EvaluateLhs = ;
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// EvaluateRhs = ;
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// };
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evaluator_impl(const XprType& product) : evaluator_base(m_result), m_lhsImpl(product.lhs()), m_rhsImpl(product.rhs())
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{
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m_result.resize(product.rows(), product.cols());
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product.evalTo(m_result);
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}
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protected:
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PlainObject m_result;
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typename evaluator<Lhs>::type m_lhsImpl;
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typename evaluator<Rhs>::type m_rhsImpl;
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};
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} // namespace internal
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#endif // EIGEN_COREEVALUATORS_H
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@ -120,9 +120,11 @@ ei_add_test(nullary)
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ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}")
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ei_add_test(zerosized)
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ei_add_test(dontalign)
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ei_add_test(evaluators)
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ei_add_test(prec_inverse_4x4)
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string(TOLOWER "${CMAKE_CXX_COMPILER}" cmake_cxx_compiler_tolower)
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if(cmake_cxx_compiler_tolower MATCHES "qcc")
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set(CXX_IS_QCC "ON")
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|
103
test/evaluators.cpp
Normal file
103
test/evaluators.cpp
Normal file
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#define EIGEN_ENABLE_EVALUATORS
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#include "main.h"
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using internal::copy_using_evaluator;
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using namespace std;
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void test_evaluators()
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{
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// Testing Matrix evaluator and Transpose
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Vector2d v(1,2);
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const Vector2d v_const(v);
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Vector2d v2;
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RowVector2d w;
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copy_using_evaluator(v2, v);
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assert(v2.isApprox((Vector2d() << 1,2).finished()));
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copy_using_evaluator(v2, v_const);
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assert(v2.isApprox((Vector2d() << 1,2).finished()));
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// Testing Transpose
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copy_using_evaluator(w, v.transpose()); // Transpose as rvalue
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||||
assert(w.isApprox((RowVector2d() << 1,2).finished()));
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||||
|
||||
copy_using_evaluator(w, v_const.transpose());
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||||
assert(w.isApprox((RowVector2d() << 1,2).finished()));
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||||
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||||
copy_using_evaluator(w.transpose(), v); // Transpose as lvalue
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assert(w.isApprox((RowVector2d() << 1,2).finished()));
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||||
|
||||
copy_using_evaluator(w.transpose(), v_const);
|
||||
assert(w.isApprox((RowVector2d() << 1,2).finished()));
|
||||
|
||||
// Testing Array evaluator
|
||||
ArrayXXf a(2,3);
|
||||
ArrayXXf b(3,2);
|
||||
a << 1,2,3, 4,5,6;
|
||||
const ArrayXXf a_const(a);
|
||||
|
||||
ArrayXXf b_expected(3,2);
|
||||
b_expected << 1,4, 2,5, 3,6;
|
||||
copy_using_evaluator(b, a.transpose());
|
||||
assert(b.isApprox(b_expected));
|
||||
|
||||
copy_using_evaluator(b, a_const.transpose());
|
||||
assert(b.isApprox(b_expected));
|
||||
|
||||
// Testing CwiseNullaryOp evaluator
|
||||
copy_using_evaluator(w, RowVector2d::Random());
|
||||
assert((w.array() >= -1).all() && (w.array() <= 1).all()); // not easy to test ...
|
||||
|
||||
copy_using_evaluator(w, RowVector2d::Zero());
|
||||
assert(w.isApprox((RowVector2d() << 0,0).finished()));
|
||||
|
||||
copy_using_evaluator(w, RowVector2d::Constant(3));
|
||||
assert(w.isApprox((RowVector2d() << 3,3).finished()));
|
||||
|
||||
// mix CwiseNullaryOp and transpose
|
||||
copy_using_evaluator(w, Vector2d::Zero().transpose());
|
||||
assert(w.isApprox((RowVector2d() << 0,0).finished()));
|
||||
|
||||
{
|
||||
MatrixXf a(2,2), b(2,2), c(2,2), d(2,2);
|
||||
a << 1, 2, 3, 4; b << 5, 6, 7, 8; c << 9, 10, 11, 12;
|
||||
copy_using_evaluator(d, (a + b));
|
||||
cout << d << endl;
|
||||
|
||||
copy_using_evaluator(d, (a + b).transpose());
|
||||
cout << d << endl;
|
||||
|
||||
// copy_using_evaluator(d, (a * b).transpose());
|
||||
// cout << d << endl;
|
||||
|
||||
// copy_using_evaluator(d, a.transpose() + (a.transpose() * (b+b)));
|
||||
// cout << d << endl;
|
||||
}
|
||||
|
||||
// this does not work because Random is eval-before-nested:
|
||||
// copy_using_evaluator(w, Vector2d::Random().transpose());
|
||||
|
||||
// test CwiseUnaryOp
|
||||
copy_using_evaluator(v2, 3 * v);
|
||||
assert(v2.isApprox((Vector2d() << 3,6).finished()));
|
||||
|
||||
copy_using_evaluator(w, (3 * v).transpose());
|
||||
assert(w.isApprox((RowVector2d() << 3,6).finished()));
|
||||
|
||||
copy_using_evaluator(b, (a + 3).transpose());
|
||||
b_expected << 4,7, 5,8, 6,9;
|
||||
assert(b.isApprox(b_expected));
|
||||
|
||||
copy_using_evaluator(b, (2 * a_const + 3).transpose());
|
||||
b_expected << 5,11, 7,13, 9,15;
|
||||
assert(b.isApprox(b_expected));
|
||||
|
||||
// test CwiseBinaryOp
|
||||
copy_using_evaluator(v2, v + Vector2d::Ones());
|
||||
assert(v2.isApprox((Vector2d() << 2,3).finished()));
|
||||
|
||||
copy_using_evaluator(w, (v + Vector2d::Ones()).transpose().cwiseProduct(RowVector2d::Constant(3)));
|
||||
assert(w.isApprox((RowVector2d() << 6,9).finished()));
|
||||
}
|
Loading…
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Reference in New Issue
Block a user