SparseDot.h
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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9 
10 #ifndef EIGEN_SPARSE_DOT_H
11 #define EIGEN_SPARSE_DOT_H
12 
13 namespace Eigen {
14 
15 template<typename Derived>
16 template<typename OtherDerived>
17 typename internal::traits<Derived>::Scalar
19 {
22  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
24  YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
25 
26  eigen_assert(size() == other.size());
27  eigen_assert(other.size()>0 && "you are using a non initialized vector");
28 
29  internal::evaluator<Derived> thisEval(derived());
30  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
31  Scalar res(0);
32  while (i)
33  {
34  res += numext::conj(i.value()) * other.coeff(i.index());
35  ++i;
36  }
37  return res;
38 }
39 
40 template<typename Derived>
41 template<typename OtherDerived>
44 {
47  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
49  YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
50 
51  eigen_assert(size() == other.size());
52 
53  internal::evaluator<Derived> thisEval(derived());
54  typename internal::evaluator<Derived>::InnerIterator i(thisEval, 0);
55 
56  internal::evaluator<OtherDerived> otherEval(other.derived());
57  typename internal::evaluator<OtherDerived>::InnerIterator j(otherEval, 0);
58 
59  Scalar res(0);
60  while (i && j)
61  {
62  if (i.index()==j.index())
63  {
64  res += numext::conj(i.value()) * j.value();
65  ++i; ++j;
66  }
67  else if (i.index()<j.index())
68  ++i;
69  else
70  ++j;
71  }
72  return res;
73 }
74 
75 template<typename Derived>
78 {
79  return numext::real((*this).cwiseAbs2().sum());
80 }
81 
82 template<typename Derived>
85 {
86  using std::sqrt;
87  return sqrt(squaredNorm());
88 }
89 
90 template<typename Derived>
93 {
94  return internal::blueNorm_impl(*this);
95 }
96 } // end namespace Eigen
97 
98 #endif // EIGEN_SPARSE_DOT_H
RealScalar squaredNorm() const
Definition: SparseDot.h:77
const AutoDiffScalar< DerType > & conj(const AutoDiffScalar< DerType > &x)
RealScalar norm() const
Definition: SparseDot.h:84
EIGEN_DEVICE_FUNC RealReturnType real() const
RealScalar blueNorm() const
Definition: SparseDot.h:92
#define EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(TYPE0, TYPE1)
Definition: StaticAssert.h:162
EIGEN_DEVICE_FUNC const SqrtReturnType sqrt() const
Definition: LDLT.h:16
static constexpr size_t size(Tuple< Args... > &)
Provides access to the number of elements in a tuple as a compile-time constant expression.
Holds information about the various numeric (i.e. scalar) types allowed by Eigen. ...
Definition: NumTraits.h:150
#define EIGEN_STATIC_ASSERT(CONDITION, MSG)
Definition: StaticAssert.h:122
Scalar dot(const MatrixBase< OtherDerived > &other) const
NumTraits< typename traits< Derived >::Scalar >::Real blueNorm_impl(const EigenBase< Derived > &_vec)
Definition: StableNorm.h:55
Base class of any sparse matrices or sparse expressions.
internal::traits< Derived >::Scalar Scalar
#define eigen_assert(x)
Definition: Macros.h:577
const Derived & derived() const
#define EIGEN_STATIC_ASSERT_VECTOR_ONLY(TYPE)
Definition: StaticAssert.h:137
Base class for all dense matrices, vectors, and expressions.
Definition: MatrixBase.h:48


hebiros
Author(s): Xavier Artache , Matthew Tesch
autogenerated on Thu Sep 3 2020 04:08:53