2012-09-09 23:34:45 +08:00
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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) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
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#define EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
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namespace internal {
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template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
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struct packed_triangular_matrix_vector_product;
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template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
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struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor>
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{
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Relax mixing-type constraints for binary coefficient-wise operators:
- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP>
- Remove the "functor_is_product_like" helper (was pretty ugly)
- Currently, OP is not used, but it is available to the user for fine grained tuning
- Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-=
- TODO: generalize all other binray operators (comparisons,pow,etc.)
- TODO: handle "scalar op array" operators (currently only * is handled)
- TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
2016-06-06 21:11:41 +08:00
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typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
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2012-09-09 23:34:45 +08:00
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enum {
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IsLower = (Mode & Lower) ==Lower,
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HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
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HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
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};
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static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha)
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{
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internal::conj_if<ConjRhs> cj;
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typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
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typedef typename conj_expr_if<ConjLhs,LhsMap>::type ConjLhsType;
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typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap;
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for (Index i=0; i<size; ++i)
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{
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Index s = IsLower&&(HasUnitDiag||HasZeroDiag) ? 1 : 0;
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Index r = IsLower ? size-i: i+1;
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if (EIGEN_IMPLIES(HasUnitDiag||HasZeroDiag, (--r)>0))
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ResMap(res+(IsLower ? s+i : 0),r) += alpha * cj(rhs[i]) * ConjLhsType(LhsMap(lhs+s,r));
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if (HasUnitDiag)
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res[i] += alpha * cj(rhs[i]);
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lhs += IsLower ? size-i: i+1;
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}
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};
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};
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template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
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struct packed_triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor>
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{
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Relax mixing-type constraints for binary coefficient-wise operators:
- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP>
- Remove the "functor_is_product_like" helper (was pretty ugly)
- Currently, OP is not used, but it is available to the user for fine grained tuning
- Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-=
- TODO: generalize all other binray operators (comparisons,pow,etc.)
- TODO: handle "scalar op array" operators (currently only * is handled)
- TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
2016-06-06 21:11:41 +08:00
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typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
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2012-09-09 23:34:45 +08:00
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enum {
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IsLower = (Mode & Lower) ==Lower,
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HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
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HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
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};
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static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha)
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{
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internal::conj_if<ConjRhs> cj;
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typedef Map<const Matrix<LhsScalar,Dynamic,1> > LhsMap;
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typedef typename conj_expr_if<ConjLhs,LhsMap>::type ConjLhsType;
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typedef Map<const Matrix<RhsScalar,Dynamic,1> > RhsMap;
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typedef typename conj_expr_if<ConjRhs,RhsMap>::type ConjRhsType;
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for (Index i=0; i<size; ++i)
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{
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Index s = !IsLower&&(HasUnitDiag||HasZeroDiag) ? 1 : 0;
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Index r = IsLower ? i+1 : size-i;
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if (EIGEN_IMPLIES(HasUnitDiag||HasZeroDiag, (--r)>0))
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res[i] += alpha * (ConjLhsType(LhsMap(lhs+s,r)).cwiseProduct(ConjRhsType(RhsMap(rhs+(IsLower ? 0 : s+i),r)))).sum();
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if (HasUnitDiag)
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res[i] += alpha * cj(rhs[i]);
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lhs += IsLower ? i+1 : size-i;
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}
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};
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};
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} // end namespace internal
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#endif // EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H
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