blas/PackedTriangularMatrixVector.h

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
//
// 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 <typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,
          int StorageOrder>
struct packed_triangular_matrix_vector_product;

template <typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
struct packed_triangular_matrix_vector_product<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, ColMajor> {
  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::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<ConjRhs> cj;
    typedef Map<const Matrix<LhsScalar, Dynamic, 1> > LhsMap;
    typedef typename conj_expr_if<ConjLhs, LhsMap>::type ConjLhsType;
    typedef Map<Matrix<ResScalar, Dynamic, 1> > 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 <typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
struct packed_triangular_matrix_vector_product<Index, Mode, LhsScalar, ConjLhs, RhsScalar, ConjRhs, RowMajor> {
  typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::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<ConjRhs> cj;
    typedef Map<const Matrix<LhsScalar, Dynamic, 1> > LhsMap;
    typedef typename conj_expr_if<ConjLhs, LhsMap>::type ConjLhsType;
    typedef Map<const Matrix<RhsScalar, Dynamic, 1> > RhsMap;
    typedef typename conj_expr_if<ConjRhs, RhsMap>::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