// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2012 Chen-Pang He // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #ifndef EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H #define EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H namespace internal { template struct packed_triangular_matrix_vector_product; template struct packed_triangular_matrix_vector_product { typedef typename ScalarBinaryOpTraits::ReturnType ResScalar; enum { IsLower = (Mode & Lower) ==Lower, HasUnitDiag = (Mode & UnitDiag)==UnitDiag, HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag }; static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha) { internal::conj_if cj; typedef Map > LhsMap; typedef typename conj_expr_if::type ConjLhsType; typedef Map > ResMap; for (Index i = 0; i < size; ++i) { Index s = IsLower && (HasUnitDiag || HasZeroDiag) ? 1 : 0; Index r = IsLower ? size - i : i + 1; if (!(HasUnitDiag || HasZeroDiag) || (--r > 0)) { ResMap(res + (IsLower ? s + i : 0), r) += alpha * cj(rhs[i]) * ConjLhsType(LhsMap(lhs + s, r)); } if (HasUnitDiag) { res[i] += alpha * cj(rhs[i]); } lhs += IsLower ? size - i : i + 1; } }; }; template struct packed_triangular_matrix_vector_product { typedef typename ScalarBinaryOpTraits::ReturnType ResScalar; enum { IsLower = (Mode & Lower) ==Lower, HasUnitDiag = (Mode & UnitDiag)==UnitDiag, HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag }; static void run(Index size, const LhsScalar* lhs, const RhsScalar* rhs, ResScalar* res, ResScalar alpha) { internal::conj_if cj; typedef Map > LhsMap; typedef typename conj_expr_if::type ConjLhsType; typedef Map > RhsMap; typedef typename conj_expr_if::type ConjRhsType; for (Index i = 0; i < size; ++i) { Index s = !IsLower && (HasUnitDiag || HasZeroDiag) ? 1 : 0; Index r = IsLower ? i + 1 : size - i; if (!(HasUnitDiag || HasZeroDiag) || (--r > 0)) { res[i] += alpha * (ConjLhsType(LhsMap(lhs + s, r)).cwiseProduct(ConjRhsType(RhsMap(rhs + (IsLower ? 0 : s + i), r)))).sum(); } if (HasUnitDiag) { res[i] += alpha * cj(rhs[i]); } lhs += IsLower ? i + 1 : size - i; } }; }; } // end namespace internal #endif // EIGEN_PACKED_TRIANGULAR_MATRIX_VECTOR_H