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c4c70669d1
That means a lot of features which were available for sparse matrices via the dense (and super slow) implemention are no longer available. All features which make sense for sparse matrices (aka can be implemented efficiently) will be implemented soon, but don't expect to see an API as rich as for the dense path. Other changes: * no block(), row(), col() anymore. * instead use .innerVector() to get a col or row vector of a matrix. * .segment(), start(), end() will be back soon, not sure for block() * faster cwise product
98 lines
3.3 KiB
C++
98 lines
3.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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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_SPARSE_DOT_H
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#define EIGEN_SPARSE_DOT_H
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template<typename Derived>
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template<typename OtherDerived>
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typename ei_traits<Derived>::Scalar
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SparseMatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
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{
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
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EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
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EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
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YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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ei_assert(size() == other.size());
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ei_assert(other.size()>0 && "you are using a non initialized vector");
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typename Derived::InnerIterator i(derived(),0);
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Scalar res = 0;
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while (i)
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{
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res += i.value() * ei_conj(other.coeff(i.index()));
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++i;
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}
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return res;
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}
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template<typename Derived>
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template<typename OtherDerived>
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typename ei_traits<Derived>::Scalar
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SparseMatrixBase<Derived>::dot(const SparseMatrixBase<OtherDerived>& other) const
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{
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
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EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
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EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
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EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
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YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
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ei_assert(size() == other.size());
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typename Derived::InnerIterator i(derived(),0);
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typename OtherDerived::InnerIterator j(other.derived(),0);
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Scalar res = 0;
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while (i && j)
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{
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if (i.index()==j.index())
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{
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res += i.value() * ei_conj(j.value());
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++i; ++j;
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}
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else if (i.index()<j.index())
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++i;
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else
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++j;
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}
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return res;
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}
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template<typename Derived>
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inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real
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SparseMatrixBase<Derived>::squaredNorm() const
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{
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return ei_real((*this).cwise().abs2().sum());
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}
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template<typename Derived>
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inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real
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SparseMatrixBase<Derived>::norm() const
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{
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return ei_sqrt(squaredNorm());
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}
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#endif // EIGEN_SPARSE_DOT_H
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