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Commit 266d4fd9 authored by zhanggzh's avatar zhanggzh
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add lietorch src code and eigen src code, update readme

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eigen-master/Eigen/src/Core/ArrayWrapper.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_ARRAYWRAPPER_H
#define EIGEN_ARRAYWRAPPER_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \class ArrayWrapper
* \ingroup Core_Module
*
* \brief Expression of a mathematical vector or matrix as an array object
*
* This class is the return type of MatrixBase::array(), and most of the time
* this is the only way it is use.
*
* \sa MatrixBase::array(), class MatrixWrapper
*/
namespace internal {
template <typename ExpressionType>
struct traits<ArrayWrapper<ExpressionType> > : public traits<remove_all_t<typename ExpressionType::Nested> > {
typedef ArrayXpr XprKind;
// Let's remove NestByRefBit
enum {
Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
};
};
} // namespace internal
template <typename ExpressionType>
class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> > {
public:
typedef ArrayBase<ArrayWrapper> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
typedef internal::remove_all_t<ExpressionType> NestedExpression;
typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
ScalarWithConstIfNotLvalue;
typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
using Base::coeffRef;
EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
return m_expression.coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
template <typename Dest>
EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const {
dst = m_expression;
}
EIGEN_DEVICE_FUNC const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
return m_expression;
}
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index) */
EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index,Index)*/
EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
protected:
NestedExpressionType m_expression;
};
/** \class MatrixWrapper
* \ingroup Core_Module
*
* \brief Expression of an array as a mathematical vector or matrix
*
* This class is the return type of ArrayBase::matrix(), and most of the time
* this is the only way it is use.
*
* \sa MatrixBase::matrix(), class ArrayWrapper
*/
namespace internal {
template <typename ExpressionType>
struct traits<MatrixWrapper<ExpressionType> > : public traits<remove_all_t<typename ExpressionType::Nested> > {
typedef MatrixXpr XprKind;
// Let's remove NestByRefBit
enum {
Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
};
};
} // namespace internal
template <typename ExpressionType>
class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> > {
public:
typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
typedef internal::remove_all_t<ExpressionType> NestedExpression;
typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
ScalarWithConstIfNotLvalue;
typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
using Base::coeffRef;
EIGEN_DEVICE_FUNC explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
return m_expression.derived().coeffRef(rowId, colId);
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
EIGEN_DEVICE_FUNC const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
return m_expression;
}
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index) */
EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
/** Forwards the resizing request to the nested expression
* \sa DenseBase::resize(Index,Index)*/
EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
protected:
NestedExpressionType m_expression;
};
} // end namespace Eigen
#endif // EIGEN_ARRAYWRAPPER_H
eigen-master/Eigen/src/Core/Assign.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2007 Michael Olbrich <michael.olbrich@gmx.net>
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_ASSIGN_H
#define EIGEN_ASSIGN_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::lazyAssign(const DenseBase<OtherDerived>& other) {
enum { SameType = internal::is_same<typename Derived::Scalar, typename OtherDerived::Scalar>::value };
EIGEN_STATIC_ASSERT_LVALUE(Derived)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived, OtherDerived)
EIGEN_STATIC_ASSERT(
SameType,
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
eigen_assert(rows() == other.rows() && cols() == other.cols());
internal::call_assignment_no_alias(derived(), other.derived());
return derived();
}
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other) {
internal::call_assignment(derived(), other.derived());
return derived();
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other) {
internal::call_assignment(derived(), other.derived());
return derived();
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other) {
internal::call_assignment(derived(), other.derived());
return derived();
}
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other) {
internal::call_assignment(derived(), other.derived());
return derived();
}
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other) {
internal::call_assignment(derived(), other.derived());
return derived();
}
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
const ReturnByValue<OtherDerived>& other) {
other.derived().evalTo(derived());
return derived();
}
} // end namespace Eigen
#endif // EIGEN_ASSIGN_H
eigen-master/Eigen/src/Core/AssignEvaluator.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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_ASSIGN_EVALUATOR_H
#define EIGEN_ASSIGN_EVALUATOR_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
// This implementation is based on Assign.h
namespace internal {
/***************************************************************************
* Part 1 : the logic deciding a strategy for traversal and unrolling *
***************************************************************************/
// copy_using_evaluator_traits is based on assign_traits
template <typename DstEvaluator, typename SrcEvaluator, typename AssignFunc, int MaxPacketSize = Dynamic>
struct copy_using_evaluator_traits {
using Src = typename SrcEvaluator::XprType;
using Dst = typename DstEvaluator::XprType;
using DstScalar = typename Dst::Scalar;
static constexpr int DstFlags = DstEvaluator::Flags;
static constexpr int SrcFlags = SrcEvaluator::Flags;
public:
static constexpr int DstAlignment = DstEvaluator::Alignment;
static constexpr int SrcAlignment = SrcEvaluator::Alignment;
static constexpr int JointAlignment = plain_enum_min(DstAlignment, SrcAlignment);
static constexpr bool DstHasDirectAccess = bool(DstFlags & DirectAccessBit);
static constexpr bool SrcIsRowMajor = bool(SrcFlags & RowMajorBit);
static constexpr bool DstIsRowMajor = bool(DstFlags & RowMajorBit);
static constexpr bool IsVectorAtCompileTime = Dst::IsVectorAtCompileTime;
static constexpr int RowsAtCompileTime = size_prefer_fixed(Src::RowsAtCompileTime, Dst::RowsAtCompileTime);
static constexpr int ColsAtCompileTime = size_prefer_fixed(Src::ColsAtCompileTime, Dst::ColsAtCompileTime);
static constexpr int SizeAtCompileTime = size_at_compile_time(RowsAtCompileTime, ColsAtCompileTime);
static constexpr int MaxRowsAtCompileTime =
min_size_prefer_fixed(Src::MaxRowsAtCompileTime, Dst::MaxRowsAtCompileTime);
static constexpr int MaxColsAtCompileTime =
min_size_prefer_fixed(Src::MaxColsAtCompileTime, Dst::MaxColsAtCompileTime);
static constexpr int MaxSizeAtCompileTime =
min_size_prefer_fixed(Src::MaxSizeAtCompileTime, Dst::MaxSizeAtCompileTime);
static constexpr int InnerSizeAtCompileTime = IsVectorAtCompileTime ? SizeAtCompileTime
: DstIsRowMajor ? ColsAtCompileTime
: RowsAtCompileTime;
static constexpr int MaxInnerSizeAtCompileTime = IsVectorAtCompileTime ? MaxSizeAtCompileTime
: DstIsRowMajor ? MaxColsAtCompileTime
: MaxRowsAtCompileTime;
static constexpr int RestrictedInnerSize = min_size_prefer_fixed(MaxInnerSizeAtCompileTime, MaxPacketSize);
static constexpr int RestrictedLinearSize = min_size_prefer_fixed(MaxSizeAtCompileTime, MaxPacketSize);
static constexpr int OuterStride = outer_stride_at_compile_time<Dst>::ret;
// TODO distinguish between linear traversal and inner-traversals
using LinearPacketType = typename find_best_packet<DstScalar, RestrictedLinearSize>::type;
using InnerPacketType = typename find_best_packet<DstScalar, RestrictedInnerSize>::type;
static constexpr int LinearPacketSize = unpacket_traits<LinearPacketType>::size;
static constexpr int InnerPacketSize = unpacket_traits<InnerPacketType>::size;
public:
static constexpr int LinearRequiredAlignment = unpacket_traits<LinearPacketType>::alignment;
static constexpr int InnerRequiredAlignment = unpacket_traits<InnerPacketType>::alignment;
private:
static constexpr bool StorageOrdersAgree = DstIsRowMajor == SrcIsRowMajor;
static constexpr bool MightVectorize = StorageOrdersAgree && bool(DstFlags & SrcFlags & ActualPacketAccessBit) &&
bool(functor_traits<AssignFunc>::PacketAccess);
static constexpr bool MayInnerVectorize = MightVectorize && (InnerSizeAtCompileTime != Dynamic) &&
(InnerSizeAtCompileTime % InnerPacketSize == 0) &&
(OuterStride != Dynamic) && (OuterStride % InnerPacketSize == 0) &&
(EIGEN_UNALIGNED_VECTORIZE || JointAlignment >= InnerRequiredAlignment);
static constexpr bool MayLinearize = StorageOrdersAgree && (DstFlags & SrcFlags & LinearAccessBit);
static constexpr bool MayLinearVectorize =
MightVectorize && MayLinearize && DstHasDirectAccess &&
(EIGEN_UNALIGNED_VECTORIZE || (DstAlignment >= LinearRequiredAlignment) || MaxSizeAtCompileTime == Dynamic) &&
(MaxSizeAtCompileTime == Dynamic || MaxSizeAtCompileTime >= LinearPacketSize);
/* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
so it's only good for large enough sizes. */
static constexpr int InnerSizeThreshold = (EIGEN_UNALIGNED_VECTORIZE ? 1 : 3) * InnerPacketSize;
static constexpr bool MaySliceVectorize =
MightVectorize && DstHasDirectAccess &&
(MaxInnerSizeAtCompileTime == Dynamic || MaxInnerSizeAtCompileTime >= InnerSizeThreshold);
/* slice vectorization can be slow, so we only want it if the slices are big, which is
indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
in a fixed-size matrix
However, with EIGEN_UNALIGNED_VECTORIZE and unrolling, slice vectorization is still worth it */
public:
static constexpr int Traversal = SizeAtCompileTime == 0 ? AllAtOnceTraversal
: (MayLinearVectorize && (LinearPacketSize > InnerPacketSize))
? LinearVectorizedTraversal
: MayInnerVectorize ? InnerVectorizedTraversal
: MayLinearVectorize ? LinearVectorizedTraversal
: MaySliceVectorize ? SliceVectorizedTraversal
: MayLinearize ? LinearTraversal
: DefaultTraversal;
static constexpr bool Vectorized = Traversal == InnerVectorizedTraversal || Traversal == LinearVectorizedTraversal ||
Traversal == SliceVectorizedTraversal;
using PacketType = std::conditional_t<Traversal == LinearVectorizedTraversal, LinearPacketType, InnerPacketType>;
private:
static constexpr int ActualPacketSize = Vectorized ? unpacket_traits<PacketType>::size : 1;
static constexpr int UnrollingLimit = EIGEN_UNROLLING_LIMIT * ActualPacketSize;
static constexpr int CoeffReadCost = int(DstEvaluator::CoeffReadCost) + int(SrcEvaluator::CoeffReadCost);
static constexpr bool MayUnrollCompletely =
(SizeAtCompileTime != Dynamic) && (SizeAtCompileTime * CoeffReadCost <= UnrollingLimit);
static constexpr bool MayUnrollInner =
(InnerSizeAtCompileTime != Dynamic) && (InnerSizeAtCompileTime * CoeffReadCost <= UnrollingLimit);
public:
static constexpr int Unrolling =
(Traversal == InnerVectorizedTraversal || Traversal == DefaultTraversal)
? (MayUnrollCompletely ? CompleteUnrolling
: MayUnrollInner ? InnerUnrolling
: NoUnrolling)
: Traversal == LinearVectorizedTraversal
? (MayUnrollCompletely && (EIGEN_UNALIGNED_VECTORIZE || (DstAlignment >= LinearRequiredAlignment))
? CompleteUnrolling
: NoUnrolling)
: Traversal == LinearTraversal ? (MayUnrollCompletely ? CompleteUnrolling : NoUnrolling)
#if EIGEN_UNALIGNED_VECTORIZE
: Traversal == SliceVectorizedTraversal ? (MayUnrollInner ? InnerUnrolling : NoUnrolling)
#endif
: NoUnrolling;
static constexpr bool UsePacketSegment = has_packet_segment<PacketType>::value;
#ifdef EIGEN_DEBUG_ASSIGN
static void debug() {
std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl;
std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl;
std::cerr.setf(std::ios::hex, std::ios::basefield);
std::cerr << "DstFlags"
<< " = " << DstFlags << " (" << demangle_flags(DstFlags) << " )" << std::endl;
std::cerr << "SrcFlags"
<< " = " << SrcFlags << " (" << demangle_flags(SrcFlags) << " )" << std::endl;
std::cerr.unsetf(std::ios::hex);
EIGEN_DEBUG_VAR(DstAlignment)
EIGEN_DEBUG_VAR(SrcAlignment)
EIGEN_DEBUG_VAR(LinearRequiredAlignment)
EIGEN_DEBUG_VAR(InnerRequiredAlignment)
EIGEN_DEBUG_VAR(JointAlignment)
EIGEN_DEBUG_VAR(InnerSizeAtCompileTime)
EIGEN_DEBUG_VAR(MaxInnerSizeAtCompileTime)
EIGEN_DEBUG_VAR(LinearPacketSize)
EIGEN_DEBUG_VAR(InnerPacketSize)
EIGEN_DEBUG_VAR(ActualPacketSize)
EIGEN_DEBUG_VAR(StorageOrdersAgree)
EIGEN_DEBUG_VAR(MightVectorize)
EIGEN_DEBUG_VAR(MayLinearize)
EIGEN_DEBUG_VAR(MayInnerVectorize)
EIGEN_DEBUG_VAR(MayLinearVectorize)
EIGEN_DEBUG_VAR(MaySliceVectorize)
std::cerr << "Traversal"
<< " = " << Traversal << " (" << demangle_traversal(Traversal) << ")" << std::endl;
EIGEN_DEBUG_VAR(SrcEvaluator::CoeffReadCost)
EIGEN_DEBUG_VAR(DstEvaluator::CoeffReadCost)
EIGEN_DEBUG_VAR(Dst::SizeAtCompileTime)
EIGEN_DEBUG_VAR(UnrollingLimit)
EIGEN_DEBUG_VAR(MayUnrollCompletely)
EIGEN_DEBUG_VAR(MayUnrollInner)
std::cerr << "Unrolling"
<< " = " << Unrolling << " (" << demangle_unrolling(Unrolling) << ")" << std::endl;
std::cerr << std::endl;
}
#endif
};
/***************************************************************************
* Part 2 : meta-unrollers
***************************************************************************/
/************************
*** Default traversal ***
************************/
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling {
static constexpr int Outer = Index_ / Kernel::AssignmentTraits::InnerSizeAtCompileTime;
static constexpr int Inner = Index_ % Kernel::AssignmentTraits::InnerSizeAtCompileTime;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
kernel.assignCoeffByOuterInner(Outer, Inner);
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Index_ + 1, Stop>::run(kernel);
}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer) {
kernel.assignCoeffByOuterInner(outer, Index_);
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Index_ + 1, Stop>::run(kernel, outer);
}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Stop, Stop> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {}
};
/***********************
*** Linear traversal ***
***********************/
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
kernel.assignCoeff(Index_);
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index_ + 1, Stop>::run(kernel);
}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Stop, Stop> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
/**************************
*** Inner vectorization ***
**************************/
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_innervec_CompleteUnrolling {
using PacketType = typename Kernel::PacketType;
static constexpr int Outer = Index_ / Kernel::AssignmentTraits::InnerSizeAtCompileTime;
static constexpr int Inner = Index_ % Kernel::AssignmentTraits::InnerSizeAtCompileTime;
static constexpr int NextIndex = Index_ + unpacket_traits<PacketType>::size;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment;
static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) {
kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(Outer, Inner);
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
template <typename Kernel, int Index_, int Stop, int SrcAlignment, int DstAlignment>
struct copy_using_evaluator_innervec_InnerUnrolling {
using PacketType = typename Kernel::PacketType;
static constexpr int NextIndex = Index_ + unpacket_traits<PacketType>::size;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel, Index outer) {
kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, Index_);
copy_using_evaluator_innervec_InnerUnrolling<Kernel, NextIndex, Stop, SrcAlignment, DstAlignment>::run(kernel,
outer);
}
};
template <typename Kernel, int Stop, int SrcAlignment, int DstAlignment>
struct copy_using_evaluator_innervec_InnerUnrolling<Kernel, Stop, Stop, SrcAlignment, DstAlignment> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {}
};
template <typename Kernel, int Start, int Stop, int SrcAlignment, int DstAlignment, bool UsePacketSegment>
struct copy_using_evaluator_innervec_segment {
using PacketType = typename Kernel::PacketType;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel, Index outer) {
kernel.template assignPacketSegmentByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, Start, 0,
Stop - Start);
}
};
template <typename Kernel, int Start, int Stop, int SrcAlignment, int DstAlignment>
struct copy_using_evaluator_innervec_segment<Kernel, Start, Stop, SrcAlignment, DstAlignment,
/*UsePacketSegment*/ false>
: copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, Start, Stop> {};
template <typename Kernel, int Stop, int SrcAlignment, int DstAlignment>
struct copy_using_evaluator_innervec_segment<Kernel, Stop, Stop, SrcAlignment, DstAlignment,
/*UsePacketSegment*/ true> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {}
};
template <typename Kernel, int Stop, int SrcAlignment, int DstAlignment>
struct copy_using_evaluator_innervec_segment<Kernel, Stop, Stop, SrcAlignment, DstAlignment,
/*UsePacketSegment*/ false> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {}
};
/***************************************************************************
* Part 3 : implementation of all cases
***************************************************************************/
// dense_assignment_loop is based on assign_impl
template <typename Kernel, int Traversal = Kernel::AssignmentTraits::Traversal,
int Unrolling = Kernel::AssignmentTraits::Unrolling>
struct dense_assignment_loop_impl;
template <typename Kernel, int Traversal = Kernel::AssignmentTraits::Traversal,
int Unrolling = Kernel::AssignmentTraits::Unrolling>
struct dense_assignment_loop {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
#ifdef __cpp_lib_is_constant_evaluated
if (internal::is_constant_evaluated())
dense_assignment_loop_impl<Kernel, Traversal == AllAtOnceTraversal ? AllAtOnceTraversal : DefaultTraversal,
NoUnrolling>::run(kernel);
else
#endif
dense_assignment_loop_impl<Kernel, Traversal, Unrolling>::run(kernel);
}
};
/************************
***** Special Cases *****
************************/
// Zero-sized assignment is a no-op.
template <typename Kernel, int Unrolling>
struct dense_assignment_loop_impl<Kernel, AllAtOnceTraversal, Unrolling> {
static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime;
EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE constexpr run(Kernel& /*kernel*/) {
EIGEN_STATIC_ASSERT(SizeAtCompileTime == 0, EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT)
}
};
/************************
*** Default traversal ***
************************/
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, DefaultTraversal, NoUnrolling> {
EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE constexpr run(Kernel& kernel) {
for (Index outer = 0; outer < kernel.outerSize(); ++outer) {
for (Index inner = 0; inner < kernel.innerSize(); ++inner) {
kernel.assignCoeffByOuterInner(outer, inner);
}
}
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, DefaultTraversal, CompleteUnrolling> {
static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, 0, SizeAtCompileTime>::run(kernel);
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, DefaultTraversal, InnerUnrolling> {
static constexpr int InnerSizeAtCompileTime = Kernel::AssignmentTraits::InnerSizeAtCompileTime;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
const Index outerSize = kernel.outerSize();
for (Index outer = 0; outer < outerSize; ++outer)
copy_using_evaluator_DefaultTraversal_InnerUnrolling<Kernel, 0, InnerSizeAtCompileTime>::run(kernel, outer);
}
};
/***************************
*** Linear vectorization ***
***************************/
// The goal of unaligned_dense_assignment_loop is simply to factorize the handling
// of the non vectorizable beginning and ending parts
template <typename PacketType, int DstAlignment, int SrcAlignment, bool UsePacketSegment, bool Skip>
struct unaligned_dense_assignment_loop {
// if Skip == true, then do nothing
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& /*kernel*/, Index /*start*/, Index /*end*/) {}
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& /*kernel*/, Index /*outer*/,
Index /*innerStart*/, Index /*innerEnd*/) {}
};
template <typename PacketType, int DstAlignment, int SrcAlignment>
struct unaligned_dense_assignment_loop<PacketType, DstAlignment, SrcAlignment, /*UsePacketSegment*/ true,
/*Skip*/ false> {
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index start, Index end) {
Index count = end - start;
eigen_assert(count <= unpacket_traits<PacketType>::size);
if (count > 0) kernel.template assignPacketSegment<DstAlignment, SrcAlignment, PacketType>(start, 0, count);
}
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer, Index start, Index end) {
Index count = end - start;
eigen_assert(count <= unpacket_traits<PacketType>::size);
if (count > 0)
kernel.template assignPacketSegmentByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, start, 0, count);
}
};
template <typename PacketType, int DstAlignment, int SrcAlignment>
struct unaligned_dense_assignment_loop<PacketType, DstAlignment, SrcAlignment, /*UsePacketSegment*/ false,
/*Skip*/ false> {
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index start, Index end) {
for (Index index = start; index < end; ++index) kernel.assignCoeff(index);
}
template <typename Kernel>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer, Index innerStart,
Index innerEnd) {
for (Index inner = innerStart; inner < innerEnd; ++inner) kernel.assignCoeffByOuterInner(outer, inner);
}
};
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_linearvec_CompleteUnrolling {
using PacketType = typename Kernel::PacketType;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment;
static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment;
static constexpr int NextIndex = Index_ + unpacket_traits<PacketType>::size;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) {
kernel.template assignPacket<DstAlignment, SrcAlignment, PacketType>(Index_);
copy_using_evaluator_linearvec_CompleteUnrolling<Kernel, NextIndex, Stop>::run(kernel);
}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_linearvec_CompleteUnrolling<Kernel, Stop, Stop> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
template <typename Kernel, int Index_, int Stop, bool UsePacketSegment>
struct copy_using_evaluator_linearvec_segment {
using PacketType = typename Kernel::PacketType;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment;
static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) {
kernel.template assignPacketSegment<DstAlignment, SrcAlignment, PacketType>(Index_, 0, Stop - Index_);
}
};
template <typename Kernel, int Index_, int Stop>
struct copy_using_evaluator_linearvec_segment<Kernel, Index_, Stop, /*UsePacketSegment*/ false>
: copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, Index_, Stop> {};
template <typename Kernel, int Stop>
struct copy_using_evaluator_linearvec_segment<Kernel, Stop, Stop, /*UsePacketSegment*/ true> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
template <typename Kernel, int Stop>
struct copy_using_evaluator_linearvec_segment<Kernel, Stop, Stop, /*UsePacketSegment*/ false> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, LinearVectorizedTraversal, NoUnrolling> {
using Scalar = typename Kernel::Scalar;
using PacketType = typename Kernel::PacketType;
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment;
static constexpr int DstAlignment = plain_enum_max(Kernel::AssignmentTraits::DstAlignment, alignof(Scalar));
static constexpr int RequestedAlignment = unpacket_traits<PacketType>::alignment;
static constexpr bool Alignable =
(DstAlignment >= RequestedAlignment) || ((RequestedAlignment - DstAlignment) % sizeof(Scalar) == 0);
static constexpr int Alignment = Alignable ? RequestedAlignment : DstAlignment;
static constexpr bool DstIsAligned = DstAlignment >= Alignment;
static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment;
using head_loop =
unaligned_dense_assignment_loop<PacketType, DstAlignment, SrcAlignment, UsePacketSegment, DstIsAligned>;
using tail_loop = unaligned_dense_assignment_loop<PacketType, Alignment, SrcAlignment, UsePacketSegment, false>;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
const Index size = kernel.size();
const Index alignedStart = DstIsAligned ? 0 : first_aligned<Alignment>(kernel.dstDataPtr(), size);
const Index alignedEnd = alignedStart + numext::round_down(size - alignedStart, PacketSize);
head_loop::run(kernel, 0, alignedStart);
for (Index index = alignedStart; index < alignedEnd; index += PacketSize)
kernel.template assignPacket<Alignment, SrcAlignment, PacketType>(index);
tail_loop::run(kernel, alignedEnd, size);
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, LinearVectorizedTraversal, CompleteUnrolling> {
using PacketType = typename Kernel::PacketType;
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int Size = Kernel::AssignmentTraits::SizeAtCompileTime;
static constexpr int AlignedSize = numext::round_down(Size, PacketSize);
static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
copy_using_evaluator_linearvec_CompleteUnrolling<Kernel, 0, AlignedSize>::run(kernel);
copy_using_evaluator_linearvec_segment<Kernel, AlignedSize, Size, UsePacketSegment>::run(kernel);
}
};
/**************************
*** Inner vectorization ***
**************************/
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, InnerVectorizedTraversal, NoUnrolling> {
using PacketType = typename Kernel::PacketType;
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment;
static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
const Index innerSize = kernel.innerSize();
const Index outerSize = kernel.outerSize();
for (Index outer = 0; outer < outerSize; ++outer)
for (Index inner = 0; inner < innerSize; inner += PacketSize)
kernel.template assignPacketByOuterInner<DstAlignment, SrcAlignment, PacketType>(outer, inner);
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, InnerVectorizedTraversal, CompleteUnrolling> {
static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) {
copy_using_evaluator_innervec_CompleteUnrolling<Kernel, 0, SizeAtCompileTime>::run(kernel);
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, InnerVectorizedTraversal, InnerUnrolling> {
static constexpr int InnerSize = Kernel::AssignmentTraits::InnerSizeAtCompileTime;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment;
static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) {
const Index outerSize = kernel.outerSize();
for (Index outer = 0; outer < outerSize; ++outer)
copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, InnerSize, SrcAlignment, DstAlignment>::run(kernel,
outer);
}
};
/***********************
*** Linear traversal ***
***********************/
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, LinearTraversal, NoUnrolling> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
const Index size = kernel.size();
for (Index i = 0; i < size; ++i) kernel.assignCoeff(i);
}
};
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, LinearTraversal, CompleteUnrolling> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, Kernel::AssignmentTraits::SizeAtCompileTime>::run(
kernel);
}
};
/**************************
*** Slice vectorization ***
***************************/
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, SliceVectorizedTraversal, NoUnrolling> {
using Scalar = typename Kernel::Scalar;
using PacketType = typename Kernel::PacketType;
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment;
static constexpr int DstAlignment = plain_enum_max(Kernel::AssignmentTraits::DstAlignment, alignof(Scalar));
static constexpr int RequestedAlignment = unpacket_traits<PacketType>::alignment;
static constexpr bool Alignable =
(DstAlignment >= RequestedAlignment) || ((RequestedAlignment - DstAlignment) % sizeof(Scalar) == 0);
static constexpr int Alignment = Alignable ? RequestedAlignment : DstAlignment;
static constexpr bool DstIsAligned = DstAlignment >= Alignment;
static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment;
using head_loop = unaligned_dense_assignment_loop<PacketType, DstAlignment, Unaligned, UsePacketSegment, !Alignable>;
using tail_loop = unaligned_dense_assignment_loop<PacketType, Alignment, Unaligned, UsePacketSegment, false>;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
const Scalar* dst_ptr = kernel.dstDataPtr();
const Index innerSize = kernel.innerSize();
const Index outerSize = kernel.outerSize();
const Index alignedStep = Alignable ? (PacketSize - kernel.outerStride() % PacketSize) % PacketSize : 0;
Index alignedStart = ((!Alignable) || DstIsAligned) ? 0 : internal::first_aligned<Alignment>(dst_ptr, innerSize);
for (Index outer = 0; outer < outerSize; ++outer) {
const Index alignedEnd = alignedStart + numext::round_down(innerSize - alignedStart, PacketSize);
head_loop::run(kernel, outer, 0, alignedStart);
// do the vectorizable part of the assignment
for (Index inner = alignedStart; inner < alignedEnd; inner += PacketSize)
kernel.template assignPacketByOuterInner<Alignment, Unaligned, PacketType>(outer, inner);
tail_loop::run(kernel, outer, alignedEnd, innerSize);
alignedStart = numext::mini((alignedStart + alignedStep) % PacketSize, innerSize);
}
}
};
#if EIGEN_UNALIGNED_VECTORIZE
template <typename Kernel>
struct dense_assignment_loop_impl<Kernel, SliceVectorizedTraversal, InnerUnrolling> {
using PacketType = typename Kernel::PacketType;
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int InnerSize = Kernel::AssignmentTraits::InnerSizeAtCompileTime;
static constexpr int VectorizableSize = numext::round_down(InnerSize, PacketSize);
static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment;
using packet_loop = copy_using_evaluator_innervec_InnerUnrolling<Kernel, 0, VectorizableSize, Unaligned, Unaligned>;
using packet_segment_loop = copy_using_evaluator_innervec_segment<Kernel, VectorizableSize, InnerSize, Unaligned,
Unaligned, UsePacketSegment>;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) {
for (Index outer = 0; outer < kernel.outerSize(); ++outer) {
packet_loop::run(kernel, outer);
packet_segment_loop::run(kernel, outer);
}
}
};
#endif
/***************************************************************************
* Part 4 : Generic dense assignment kernel
***************************************************************************/
// This class generalize the assignment of a coefficient (or packet) from one dense evaluator
// to another dense writable evaluator.
// It is parametrized by the two evaluators, and the actual assignment functor.
// This abstraction level permits to keep the evaluation loops as simple and as generic as possible.
// One can customize the assignment using this generic dense_assignment_kernel with different
// functors, or by completely overloading it, by-passing a functor.
template <typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor, int Version = Specialized>
class generic_dense_assignment_kernel {
protected:
typedef typename DstEvaluatorTypeT::XprType DstXprType;
typedef typename SrcEvaluatorTypeT::XprType SrcXprType;
public:
typedef DstEvaluatorTypeT DstEvaluatorType;
typedef SrcEvaluatorTypeT SrcEvaluatorType;
typedef typename DstEvaluatorType::Scalar Scalar;
typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
typedef typename AssignmentTraits::PacketType PacketType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr generic_dense_assignment_kernel(DstEvaluatorType& dst,
const SrcEvaluatorType& src,
const Functor& func,
DstXprType& dstExpr)
: m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr) {
#ifdef EIGEN_DEBUG_ASSIGN
AssignmentTraits::debug();
#endif
}
EIGEN_DEVICE_FUNC constexpr Index size() const noexcept { return m_dstExpr.size(); }
EIGEN_DEVICE_FUNC constexpr Index innerSize() const noexcept { return m_dstExpr.innerSize(); }
EIGEN_DEVICE_FUNC constexpr Index outerSize() const noexcept { return m_dstExpr.outerSize(); }
EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_dstExpr.rows(); }
EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_dstExpr.cols(); }
EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_dstExpr.outerStride(); }
EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() noexcept { return m_dst; }
EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const noexcept { return m_src; }
/// Assign src(row,col) to dst(row,col) through the assignment functor.
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void assignCoeff(Index row, Index col) {
m_functor.assignCoeff(m_dst.coeffRef(row, col), m_src.coeff(row, col));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index index) {
m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void assignCoeffByOuterInner(Index outer, Index inner) {
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignCoeff(row, col);
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index row, Index col) {
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row, col),
m_src.template packet<LoadMode, Packet>(row, col));
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index index) {
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode, Packet>(index));
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketByOuterInner(Index outer, Index inner) {
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignPacket<StoreMode, LoadMode, Packet>(row, col);
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegment(Index row, Index col, Index begin, Index count) {
m_functor.template assignPacketSegment<StoreMode>(
&m_dst.coeffRef(row, col), m_src.template packetSegment<LoadMode, Packet>(row, col, begin, count), begin,
count);
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegment(Index index, Index begin, Index count) {
m_functor.template assignPacketSegment<StoreMode>(
&m_dst.coeffRef(index), m_src.template packetSegment<LoadMode, Packet>(index, begin, count), begin, count);
}
template <int StoreMode, int LoadMode, typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegmentByOuterInner(Index outer, Index inner, Index begin,
Index count) {
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignPacketSegment<StoreMode, LoadMode, Packet>(row, col, begin, count);
}
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr Index rowIndexByOuterInner(Index outer, Index inner) {
typedef typename DstEvaluatorType::ExpressionTraits Traits;
return int(Traits::RowsAtCompileTime) == 1 ? 0
: int(Traits::ColsAtCompileTime) == 1 ? inner
: int(DstEvaluatorType::Flags) & RowMajorBit ? outer
: inner;
}
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr Index colIndexByOuterInner(Index outer, Index inner) {
typedef typename DstEvaluatorType::ExpressionTraits Traits;
return int(Traits::ColsAtCompileTime) == 1 ? 0
: int(Traits::RowsAtCompileTime) == 1 ? inner
: int(DstEvaluatorType::Flags) & RowMajorBit ? inner
: outer;
}
EIGEN_DEVICE_FUNC const Scalar* dstDataPtr() const { return m_dstExpr.data(); }
protected:
DstEvaluatorType& m_dst;
const SrcEvaluatorType& m_src;
const Functor& m_functor;
// TODO find a way to avoid the needs of the original expression
DstXprType& m_dstExpr;
};
// Special kernel used when computing small products whose operands have dynamic dimensions. It ensures that the
// PacketSize used is no larger than 4, thereby increasing the chance that vectorized instructions will be used
// when computing the product.
template <typename DstEvaluatorTypeT, typename SrcEvaluatorTypeT, typename Functor>
class restricted_packet_dense_assignment_kernel
: public generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, BuiltIn> {
protected:
typedef generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, BuiltIn> Base;
public:
typedef typename Base::Scalar Scalar;
typedef typename Base::DstXprType DstXprType;
typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, 4> AssignmentTraits;
typedef typename AssignmentTraits::PacketType PacketType;
EIGEN_DEVICE_FUNC restricted_packet_dense_assignment_kernel(DstEvaluatorTypeT& dst, const SrcEvaluatorTypeT& src,
const Functor& func, DstXprType& dstExpr)
: Base(dst, src, func, dstExpr) {}
};
/***************************************************************************
* Part 5 : Entry point for dense rectangular assignment
***************************************************************************/
template <typename DstXprType, typename SrcXprType, typename Functor>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize_if_allowed(DstXprType& dst, const SrcXprType& src,
const Functor& /*func*/) {
EIGEN_ONLY_USED_FOR_DEBUG(dst);
EIGEN_ONLY_USED_FOR_DEBUG(src);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
}
template <typename DstXprType, typename SrcXprType, typename T1, typename T2>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize_if_allowed(DstXprType& dst, const SrcXprType& src,
const internal::assign_op<T1, T2>& /*func*/) {
Index dstRows = src.rows();
Index dstCols = src.cols();
if (((dst.rows() != dstRows) || (dst.cols() != dstCols))) dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == dstRows && dst.cols() == dstCols);
}
template <typename DstXprType, typename SrcXprType, typename Functor>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src,
const Functor& func) {
typedef evaluator<DstXprType> DstEvaluatorType;
typedef evaluator<SrcXprType> SrcEvaluatorType;
SrcEvaluatorType srcEvaluator(src);
// NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
// we need to resize the destination after the source evaluator has been created.
resize_if_allowed(dst, src, func);
DstEvaluatorType dstEvaluator(dst);
typedef generic_dense_assignment_kernel<DstEvaluatorType, SrcEvaluatorType, Functor> Kernel;
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
dense_assignment_loop<Kernel>::run(kernel);
}
template <typename DstXprType, typename SrcXprType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src) {
call_dense_assignment_loop(dst, src, internal::assign_op<typename DstXprType::Scalar, typename SrcXprType::Scalar>());
}
/***************************************************************************
* Part 6 : Generic assignment
***************************************************************************/
// Based on the respective shapes of the destination and source,
// the class AssignmentKind determine the kind of assignment mechanism.
// AssignmentKind must define a Kind typedef.
template <typename DstShape, typename SrcShape>
struct AssignmentKind;
// Assignment kind defined in this file:
struct Dense2Dense {};
struct EigenBase2EigenBase {};
template <typename, typename>
struct AssignmentKind {
typedef EigenBase2EigenBase Kind;
};
template <>
struct AssignmentKind<DenseShape, DenseShape> {
typedef Dense2Dense Kind;
};
// This is the main assignment class
template <typename DstXprType, typename SrcXprType, typename Functor,
typename Kind = typename AssignmentKind<typename evaluator_traits<DstXprType>::Shape,
typename evaluator_traits<SrcXprType>::Shape>::Kind,
typename EnableIf = void>
struct Assignment;
// The only purpose of this call_assignment() function is to deal with noalias() / "assume-aliasing" and automatic
// transposition. Indeed, I (Gael) think that this concept of "assume-aliasing" was a mistake, and it makes thing quite
// complicated. So this intermediate function removes everything related to "assume-aliasing" such that Assignment does
// not has to bother about these annoying details.
template <typename Dst, typename Src>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(Dst& dst, const Src& src) {
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar, typename Src::Scalar>());
}
template <typename Dst, typename Src>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_assignment(const Dst& dst, const Src& src) {
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar, typename Src::Scalar>());
}
// Deal with "assume-aliasing"
template <typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(
Dst& dst, const Src& src, const Func& func, std::enable_if_t<evaluator_assume_aliasing<Src>::value, void*> = 0) {
typename plain_matrix_type<Src>::type tmp(src);
call_assignment_no_alias(dst, tmp, func);
}
template <typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(
Dst& dst, const Src& src, const Func& func, std::enable_if_t<!evaluator_assume_aliasing<Src>::value, void*> = 0) {
call_assignment_no_alias(dst, src, func);
}
// by-pass "assume-aliasing"
// When there is no aliasing, we require that 'dst' has been properly resized
template <typename Dst, template <typename> class StorageBase, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(NoAlias<Dst, StorageBase>& dst, const Src& src,
const Func& func) {
call_assignment_no_alias(dst.expression(), src, func);
}
template <typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(Dst& dst, const Src& src,
const Func& func) {
enum {
NeedToTranspose = ((int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1) ||
(int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)) &&
int(Dst::SizeAtCompileTime) != 1
};
typedef std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst> ActualDstTypeCleaned;
typedef std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst&> ActualDstType;
ActualDstType actualDst(dst);
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned, Src)
EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename ActualDstTypeCleaned::Scalar, typename Src::Scalar);
Assignment<ActualDstTypeCleaned, Src, Func>::run(actualDst, src, func);
}
template <typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_restricted_packet_assignment_no_alias(Dst& dst, const Src& src,
const Func& func) {
typedef evaluator<Dst> DstEvaluatorType;
typedef evaluator<Src> SrcEvaluatorType;
typedef restricted_packet_dense_assignment_kernel<DstEvaluatorType, SrcEvaluatorType, Func> Kernel;
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename Dst::Scalar, typename Src::Scalar);
SrcEvaluatorType srcEvaluator(src);
resize_if_allowed(dst, src, func);
DstEvaluatorType dstEvaluator(dst);
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
dense_assignment_loop<Kernel>::run(kernel);
}
template <typename Dst, typename Src>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(Dst& dst, const Src& src) {
call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar, typename Src::Scalar>());
}
template <typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src,
const Func& func) {
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst, Src)
EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename Dst::Scalar, typename Src::Scalar);
Assignment<Dst, Src, Func>::run(dst, src, func);
}
template <typename Dst, typename Src>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src) {
call_assignment_no_alias_no_transpose(dst, src, internal::assign_op<typename Dst::Scalar, typename Src::Scalar>());
}
// forward declaration
template <typename Dst, typename Src>
EIGEN_DEVICE_FUNC void check_for_aliasing(const Dst& dst, const Src& src);
// Generic Dense to Dense assignment
// Note that the last template argument "Weak" is needed to make it possible to perform
// both partial specialization+SFINAE without ambiguous specialization
template <typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Weak> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(DstXprType& dst, const SrcXprType& src,
const Functor& func) {
#ifndef EIGEN_NO_DEBUG
if (!internal::is_constant_evaluated()) {
internal::check_for_aliasing(dst, src);
}
#endif
call_dense_assignment_loop(dst, src, func);
}
};
template <typename DstXprType, typename SrcPlainObject, typename Weak>
struct Assignment<DstXprType, CwiseNullaryOp<scalar_constant_op<typename DstXprType::Scalar>, SrcPlainObject>,
assign_op<typename DstXprType::Scalar, typename DstXprType::Scalar>, Dense2Dense, Weak> {
using Scalar = typename DstXprType::Scalar;
using NullaryOp = scalar_constant_op<Scalar>;
using SrcXprType = CwiseNullaryOp<NullaryOp, SrcPlainObject>;
using Functor = assign_op<Scalar, Scalar>;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src,
const Functor& /*func*/) {
eigen_fill_impl<DstXprType>::run(dst, src);
}
};
template <typename DstXprType, typename SrcPlainObject, typename Weak>
struct Assignment<DstXprType, CwiseNullaryOp<scalar_zero_op<typename DstXprType::Scalar>, SrcPlainObject>,
assign_op<typename DstXprType::Scalar, typename DstXprType::Scalar>, Dense2Dense, Weak> {
using Scalar = typename DstXprType::Scalar;
using NullaryOp = scalar_zero_op<Scalar>;
using SrcXprType = CwiseNullaryOp<NullaryOp, SrcPlainObject>;
using Functor = assign_op<Scalar, Scalar>;
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src,
const Functor& /*func*/) {
eigen_zero_impl<DstXprType>::run(dst, src);
}
};
// Generic assignment through evalTo.
// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism.
// Note that the last template argument "Weak" is needed to make it possible to perform
// both partial specialization+SFINAE without ambiguous specialization
template <typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Weak> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(
DstXprType& dst, const SrcXprType& src,
const internal::assign_op<typename DstXprType::Scalar, typename SrcXprType::Scalar>& /*func*/) {
Index dstRows = src.rows();
Index dstCols = src.cols();
if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.evalTo(dst);
}
// NOTE The following two functions are templated to avoid their instantiation if not needed
// This is needed because some expressions supports evalTo only and/or have 'void' as scalar type.
template <typename SrcScalarType>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(
DstXprType& dst, const SrcXprType& src,
const internal::add_assign_op<typename DstXprType::Scalar, SrcScalarType>& /*func*/) {
Index dstRows = src.rows();
Index dstCols = src.cols();
if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.addTo(dst);
}
template <typename SrcScalarType>
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(
DstXprType& dst, const SrcXprType& src,
const internal::sub_assign_op<typename DstXprType::Scalar, SrcScalarType>& /*func*/) {
Index dstRows = src.rows();
Index dstCols = src.cols();
if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols);
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
src.subTo(dst);
}
};
} // namespace internal
} // end namespace Eigen
#endif // EIGEN_ASSIGN_EVALUATOR_H
eigen-master/Eigen/src/Core/Assign_MKL.h 0 → 100644
View file @ 266d4fd9
/*
Copyright (c) 2011, Intel Corporation. All rights reserved.
Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of Intel Corporation nor the names of its contributors may
be used to endorse or promote products derived from this software without
specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
********************************************************************************
* Content : Eigen bindings to Intel(R) MKL
* MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
********************************************************************************
*/
#ifndef EIGEN_ASSIGN_VML_H
#define EIGEN_ASSIGN_VML_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename Dst, typename Src>
class vml_assign_traits {
private:
enum {
DstHasDirectAccess = Dst::Flags & DirectAccessBit,
SrcHasDirectAccess = Src::Flags & DirectAccessBit,
StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
: int(Dst::Flags) & RowMajorBit ? int(Dst::ColsAtCompileTime)
: int(Dst::RowsAtCompileTime),
InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
: int(Dst::Flags) & RowMajorBit ? int(Dst::MaxColsAtCompileTime)
: int(Dst::MaxRowsAtCompileTime),
MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess &&
Src::InnerStrideAtCompileTime == 1 && Dst::InnerStrideAtCompileTime == 1,
MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
LargeEnough = VmlSize == Dynamic || VmlSize >= EIGEN_MKL_VML_THRESHOLD
};
public:
enum { EnableVml = MightEnableVml && LargeEnough, Traversal = MightLinearize ? LinearTraversal : DefaultTraversal };
};
#define EIGEN_PP_EXPAND(ARG) ARG
#if !defined(EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
#define EIGEN_VMLMODE_EXPAND_xLA , VML_HA
#else
#define EIGEN_VMLMODE_EXPAND_xLA , VML_LA
#endif
#define EIGEN_VMLMODE_EXPAND_x_
#define EIGEN_VMLMODE_PREFIX_xLA vm
#define EIGEN_VMLMODE_PREFIX_x_ v
#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x, VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
template <typename DstXprType, typename SrcXprNested> \
struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, \
assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense, \
std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> { \
typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
resize_if_allowed(dst, src, func); \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == (int)LinearTraversal) { \
VMLOP(dst.size(), (const VMLTYPE *)src.nestedExpression().data(), \
(VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
} else { \
const Index outerSize = dst.outerSize(); \
for (Index outer = 0; outer < outerSize; ++outer) { \
const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer, 0)) \
: &(src.nestedExpression().coeffRef(0, outer)); \
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \
VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, \
(VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
} \
} \
} \
};
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), s##VMLOP), float, float, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), d##VMLOP), double, double, VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), c##VMLOP), scomplex, \
MKL_Complex8, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), z##VMLOP), dcomplex, \
MKL_Complex16, VMLMODE)
#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(cbrt, Cbrt, _)
#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \
template <typename DstXprType, typename SrcXprNested, typename Plain> \
struct Assignment<DstXprType, \
CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested, \
const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>, \
assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense, \
std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> { \
typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested, \
const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>> \
SrcXprType; \
static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
resize_if_allowed(dst, src, func); \
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \
VMLTYPE exponent = reinterpret_cast<const VMLTYPE &>(src.rhs().functor().m_other); \
if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == LinearTraversal) { \
VMLOP(dst.size(), (const VMLTYPE *)src.lhs().data(), exponent, \
(VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
} else { \
const Index outerSize = dst.outerSize(); \
for (Index outer = 0; outer < outerSize; ++outer) { \
const EIGENTYPE *src_ptr = \
src.IsRowMajor ? &(src.lhs().coeffRef(outer, 0)) : &(src.lhs().coeffRef(0, outer)); \
EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \
VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, exponent, \
(VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \
} \
} \
} \
};
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_ASSIGN_VML_H
eigen-master/Eigen/src/Core/BandMatrix.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_BANDMATRIX_H
#define EIGEN_BANDMATRIX_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename Derived>
class BandMatrixBase : public EigenBase<Derived> {
public:
enum {
Flags = internal::traits<Derived>::Flags,
CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
Supers = internal::traits<Derived>::Supers,
Subs = internal::traits<Derived>::Subs,
Options = internal::traits<Derived>::Options
};
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime> DenseMatrixType;
typedef typename DenseMatrixType::StorageIndex StorageIndex;
typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
typedef EigenBase<Derived> Base;
protected:
enum {
DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic,
SizeAtCompileTime = min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime)
};
public:
using Base::cols;
using Base::derived;
using Base::rows;
/** \returns the number of super diagonals */
inline Index supers() const { return derived().supers(); }
/** \returns the number of sub diagonals */
inline Index subs() const { return derived().subs(); }
/** \returns an expression of the underlying coefficient matrix */
inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
/** \returns an expression of the underlying coefficient matrix */
inline CoefficientsType& coeffs() { return derived().coeffs(); }
/** \returns a vector expression of the \a i -th column,
* only the meaningful part is returned.
* \warning the internal storage must be column major. */
inline Block<CoefficientsType, Dynamic, 1> col(Index i) {
EIGEN_STATIC_ASSERT((int(Options) & int(RowMajor)) == 0, THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
Index start = 0;
Index len = coeffs().rows();
if (i <= supers()) {
start = supers() - i;
len = (std::min)(rows(), std::max<Index>(0, coeffs().rows() - (supers() - i)));
} else if (i >= rows() - subs())
len = std::max<Index>(0, coeffs().rows() - (i + 1 - rows() + subs()));
return Block<CoefficientsType, Dynamic, 1>(coeffs(), start, i, len, 1);
}
/** \returns a vector expression of the main diagonal */
inline Block<CoefficientsType, 1, SizeAtCompileTime> diagonal() {
return Block<CoefficientsType, 1, SizeAtCompileTime>(coeffs(), supers(), 0, 1, (std::min)(rows(), cols()));
}
/** \returns a vector expression of the main diagonal (const version) */
inline const Block<const CoefficientsType, 1, SizeAtCompileTime> diagonal() const {
return Block<const CoefficientsType, 1, SizeAtCompileTime>(coeffs(), supers(), 0, 1, (std::min)(rows(), cols()));
}
template <int Index>
struct DiagonalIntReturnType {
enum {
ReturnOpposite =
(int(Options) & int(SelfAdjoint)) && (((Index) > 0 && Supers == 0) || ((Index) < 0 && Subs == 0)),
Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
ActualIndex = ReturnOpposite ? -Index : Index,
DiagonalSize =
(RowsAtCompileTime == Dynamic || ColsAtCompileTime == Dynamic)
? Dynamic
: (ActualIndex < 0 ? min_size_prefer_dynamic(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
: min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
};
typedef Block<CoefficientsType, 1, DiagonalSize> BuildType;
typedef std::conditional_t<Conjugate, CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, BuildType>, BuildType>
Type;
};
/** \returns a vector expression of the \a N -th sub or super diagonal */
template <int N>
inline typename DiagonalIntReturnType<N>::Type diagonal() {
return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N));
}
/** \returns a vector expression of the \a N -th sub or super diagonal */
template <int N>
inline const typename DiagonalIntReturnType<N>::Type diagonal() const {
return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N));
}
/** \returns a vector expression of the \a i -th sub or super diagonal */
inline Block<CoefficientsType, 1, Dynamic> diagonal(Index i) {
eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers()));
return Block<CoefficientsType, 1, Dynamic>(coeffs(), supers() - i, std::max<Index>(0, i), 1, diagonalLength(i));
}
/** \returns a vector expression of the \a i -th sub or super diagonal */
inline const Block<const CoefficientsType, 1, Dynamic> diagonal(Index i) const {
eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers()));
return Block<const CoefficientsType, 1, Dynamic>(coeffs(), supers() - i, std::max<Index>(0, i), 1,
diagonalLength(i));
}
template <typename Dest>
inline void evalTo(Dest& dst) const {
dst.resize(rows(), cols());
dst.setZero();
dst.diagonal() = diagonal();
for (Index i = 1; i <= supers(); ++i) dst.diagonal(i) = diagonal(i);
for (Index i = 1; i <= subs(); ++i) dst.diagonal(-i) = diagonal(-i);
}
DenseMatrixType toDenseMatrix() const {
DenseMatrixType res(rows(), cols());
evalTo(res);
return res;
}
protected:
inline Index diagonalLength(Index i) const {
return i < 0 ? (std::min)(cols(), rows() + i) : (std::min)(rows(), cols() - i);
}
};
/**
* \class BandMatrix
* \ingroup Core_Module
*
* \brief Represents a rectangular matrix with a banded storage
*
* \tparam Scalar_ Numeric type, i.e. float, double, int
* \tparam Rows_ Number of rows, or \b Dynamic
* \tparam Cols_ Number of columns, or \b Dynamic
* \tparam Supers_ Number of super diagonal
* \tparam Subs_ Number of sub diagonal
* \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
* The former controls \ref TopicStorageOrders "storage order", and defaults to
* column-major. The latter controls whether the matrix represents a selfadjoint
* matrix in which case either Supers of Subs have to be null.
*
* \sa class TridiagonalMatrix
*/
template <typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
struct traits<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> > {
typedef Scalar_ Scalar;
typedef Dense StorageKind;
typedef Eigen::Index StorageIndex;
enum {
CoeffReadCost = NumTraits<Scalar>::ReadCost,
RowsAtCompileTime = Rows_,
ColsAtCompileTime = Cols_,
MaxRowsAtCompileTime = Rows_,
MaxColsAtCompileTime = Cols_,
Flags = LvalueBit,
Supers = Supers_,
Subs = Subs_,
Options = Options_,
DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic
};
typedef Matrix<Scalar, DataRowsAtCompileTime, ColsAtCompileTime, int(Options) & int(RowMajor) ? RowMajor : ColMajor>
CoefficientsType;
};
template <typename Scalar_, int Rows, int Cols, int Supers, int Subs, int Options>
class BandMatrix : public BandMatrixBase<BandMatrix<Scalar_, Rows, Cols, Supers, Subs, Options> > {
public:
typedef typename internal::traits<BandMatrix>::Scalar Scalar;
typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
explicit inline BandMatrix(Index rows = Rows, Index cols = Cols, Index supers = Supers, Index subs = Subs)
: m_coeffs(1 + supers + subs, cols), m_rows(rows), m_supers(supers), m_subs(subs) {}
/** \returns the number of columns */
constexpr Index rows() const { return m_rows.value(); }
/** \returns the number of rows */
constexpr Index cols() const { return m_coeffs.cols(); }
/** \returns the number of super diagonals */
constexpr Index supers() const { return m_supers.value(); }
/** \returns the number of sub diagonals */
constexpr Index subs() const { return m_subs.value(); }
inline const CoefficientsType& coeffs() const { return m_coeffs; }
inline CoefficientsType& coeffs() { return m_coeffs; }
protected:
CoefficientsType m_coeffs;
internal::variable_if_dynamic<Index, Rows> m_rows;
internal::variable_if_dynamic<Index, Supers> m_supers;
internal::variable_if_dynamic<Index, Subs> m_subs;
};
template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
class BandMatrixWrapper;
template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
struct traits<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
typedef typename CoefficientsType_::Scalar Scalar;
typedef typename CoefficientsType_::StorageKind StorageKind;
typedef typename CoefficientsType_::StorageIndex StorageIndex;
enum {
CoeffReadCost = internal::traits<CoefficientsType_>::CoeffReadCost,
RowsAtCompileTime = Rows_,
ColsAtCompileTime = Cols_,
MaxRowsAtCompileTime = Rows_,
MaxColsAtCompileTime = Cols_,
Flags = LvalueBit,
Supers = Supers_,
Subs = Subs_,
Options = Options_,
DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic
};
typedef CoefficientsType_ CoefficientsType;
};
template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
class BandMatrixWrapper
: public BandMatrixBase<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
public:
typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows = Rows_, Index cols = Cols_,
Index supers = Supers_, Index subs = Subs_)
: m_coeffs(coeffs), m_rows(rows), m_supers(supers), m_subs(subs) {
EIGEN_UNUSED_VARIABLE(cols);
// eigen_assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
}
/** \returns the number of columns */
constexpr Index rows() const { return m_rows.value(); }
/** \returns the number of rows */
constexpr Index cols() const { return m_coeffs.cols(); }
/** \returns the number of super diagonals */
constexpr Index supers() const { return m_supers.value(); }
/** \returns the number of sub diagonals */
constexpr Index subs() const { return m_subs.value(); }
inline const CoefficientsType& coeffs() const { return m_coeffs; }
protected:
const CoefficientsType& m_coeffs;
internal::variable_if_dynamic<Index, Rows_> m_rows;
internal::variable_if_dynamic<Index, Supers_> m_supers;
internal::variable_if_dynamic<Index, Subs_> m_subs;
};
/**
* \class TridiagonalMatrix
* \ingroup Core_Module
*
* \brief Represents a tridiagonal matrix with a compact banded storage
*
* \tparam Scalar Numeric type, i.e. float, double, int
* \tparam Size Number of rows and cols, or \b Dynamic
* \tparam Options Can be 0 or \b SelfAdjoint
*
* \sa class BandMatrix
*/
template <typename Scalar, int Size, int Options>
class TridiagonalMatrix : public BandMatrix<Scalar, Size, Size, Options & SelfAdjoint ? 0 : 1, 1, Options | RowMajor> {
typedef BandMatrix<Scalar, Size, Size, Options & SelfAdjoint ? 0 : 1, 1, Options | RowMajor> Base;
typedef typename Base::StorageIndex StorageIndex;
public:
explicit TridiagonalMatrix(Index size = Size) : Base(size, size, Options & SelfAdjoint ? 0 : 1, 1) {}
inline typename Base::template DiagonalIntReturnType<1>::Type super() { return Base::template diagonal<1>(); }
inline const typename Base::template DiagonalIntReturnType<1>::Type super() const {
return Base::template diagonal<1>();
}
inline typename Base::template DiagonalIntReturnType<-1>::Type sub() { return Base::template diagonal<-1>(); }
inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const {
return Base::template diagonal<-1>();
}
protected:
};
struct BandShape {};
template <typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
struct evaluator_traits<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> >
: public evaluator_traits_base<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> > {
typedef BandShape Shape;
};
template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
struct evaluator_traits<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> >
: public evaluator_traits_base<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
typedef BandShape Shape;
};
template <>
struct AssignmentKind<DenseShape, BandShape> {
typedef EigenBase2EigenBase Kind;
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_BANDMATRIX_H
eigen-master/Eigen/src/Core/Block.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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_BLOCK_H
#define EIGEN_BLOCK_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename XprType_, int BlockRows, int BlockCols, bool InnerPanel_>
struct traits<Block<XprType_, BlockRows, BlockCols, InnerPanel_>> : traits<XprType_> {
typedef typename traits<XprType_>::Scalar Scalar;
typedef typename traits<XprType_>::StorageKind StorageKind;
typedef typename traits<XprType_>::XprKind XprKind;
typedef typename ref_selector<XprType_>::type XprTypeNested;
typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
enum {
MatrixRows = traits<XprType_>::RowsAtCompileTime,
MatrixCols = traits<XprType_>::ColsAtCompileTime,
RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows,
ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols,
MaxRowsAtCompileTime = BlockRows == 0 ? 0
: RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
: int(traits<XprType_>::MaxRowsAtCompileTime),
MaxColsAtCompileTime = BlockCols == 0 ? 0
: ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
: int(traits<XprType_>::MaxColsAtCompileTime),
XprTypeIsRowMajor = (int(traits<XprType_>::Flags) & RowMajorBit) != 0,
IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1
: (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0
: XprTypeIsRowMajor,
HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
InnerStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(inner_stride_at_compile_time<XprType_>::ret)
: int(outer_stride_at_compile_time<XprType_>::ret),
OuterStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(outer_stride_at_compile_time<XprType_>::ret)
: int(inner_stride_at_compile_time<XprType_>::ret),
// FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
FlagsLvalueBit = is_lvalue<XprType_>::value ? LvalueBit : 0,
FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
Flags = (traits<XprType_>::Flags & (DirectAccessBit | (InnerPanel_ ? CompressedAccessBit : 0))) | FlagsLvalueBit |
FlagsRowMajorBit,
// FIXME DirectAccessBit should not be handled by expressions
//
// Alignment is needed by MapBase's assertions
// We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the
// respective evaluator
Alignment = 0,
InnerPanel = InnerPanel_ ? 1 : 0
};
};
template <typename XprType, int BlockRows = Dynamic, int BlockCols = Dynamic, bool InnerPanel = false,
bool HasDirectAccess = internal::has_direct_access<XprType>::ret>
class BlockImpl_dense;
} // end namespace internal
template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind>
class BlockImpl;
/** \class Block
* \ingroup Core_Module
*
* \brief Expression of a fixed-size or dynamic-size block
*
* \tparam XprType the type of the expression in which we are taking a block
* \tparam BlockRows the number of rows of the block we are taking at compile time (optional)
* \tparam BlockCols the number of columns of the block we are taking at compile time (optional)
* \tparam InnerPanel is true, if the block maps to a set of rows of a row major matrix or
* to set of columns of a column major matrix (optional). The parameter allows to determine
* at compile time whether aligned access is possible on the block expression.
*
* This class represents an expression of either a fixed-size or dynamic-size block. It is the return
* type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
* most of the time this is the only way it is used.
*
* However, if you want to directly manipulate block expressions,
* for instance if you want to write a function returning such an expression, you
* will need to use this class.
*
* Here is an example illustrating the dynamic case:
* \include class_Block.cpp
* Output: \verbinclude class_Block.out
*
* \note Even though this expression has dynamic size, in the case where \a XprType
* has fixed size, this expression inherits a fixed maximal size which means that evaluating
* it does not cause a dynamic memory allocation.
*
* Here is an example illustrating the fixed-size case:
* \include class_FixedBlock.cpp
* Output: \verbinclude class_FixedBlock.out
*
* \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
*/
template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
class Block
: public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> {
typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
using BlockHelper = internal::block_xpr_helper<Block>;
public:
// typedef typename Impl::Base Base;
typedef Impl Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
typedef internal::remove_all_t<XprType> NestedExpression;
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index i) : Impl(xpr, i) {
eigen_assert((i >= 0) && (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && i < xpr.rows()) ||
((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) && i < xpr.cols())));
}
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol)
: Impl(xpr, startRow, startCol) {
EIGEN_STATIC_ASSERT(RowsAtCompileTime != Dynamic && ColsAtCompileTime != Dynamic,
THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
eigen_assert(startRow >= 0 && BlockRows >= 0 && startRow + BlockRows <= xpr.rows() && startCol >= 0 &&
BlockCols >= 0 && startCol + BlockCols <= xpr.cols());
}
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol, Index blockRows,
Index blockCols)
: Impl(xpr, startRow, startCol, blockRows, blockCols) {
eigen_assert((RowsAtCompileTime == Dynamic || RowsAtCompileTime == blockRows) &&
(ColsAtCompileTime == Dynamic || ColsAtCompileTime == blockCols));
eigen_assert(startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows && startCol >= 0 &&
blockCols >= 0 && startCol <= xpr.cols() - blockCols);
}
// convert nested blocks (e.g. Block<Block<MatrixType>>) to a simple block expression (Block<MatrixType>)
using ConstUnwindReturnType = Block<const typename BlockHelper::BaseType, BlockRows, BlockCols, InnerPanel>;
using UnwindReturnType = Block<typename BlockHelper::BaseType, BlockRows, BlockCols, InnerPanel>;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ConstUnwindReturnType unwind() const {
return ConstUnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0),
this->rows(), this->cols());
}
template <typename T = Block, typename EnableIf = std::enable_if_t<!std::is_const<T>::value>>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE UnwindReturnType unwind() {
return UnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0),
this->rows(), this->cols());
}
};
// The generic default implementation for dense block simply forward to the internal::BlockImpl_dense
// that must be specialized for direct and non-direct access...
template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
: public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> {
typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
typedef typename XprType::StorageIndex StorageIndex;
public:
typedef Impl Base;
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index i) : Impl(xpr, i) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol)
: Impl(xpr, startRow, startCol) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows,
Index blockCols)
: Impl(xpr, startRow, startCol, blockRows, blockCols) {}
};
namespace internal {
/** \internal Internal implementation of dense Blocks in the general case. */
template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess>
class BlockImpl_dense : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel>>::type {
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
public:
typedef typename internal::dense_xpr_base<BlockType>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
// class InnerIterator; // FIXME apparently never used
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index i)
: m_xpr(xpr),
// It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
// and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
// all other cases are invalid.
// The case a 1x1 matrix seems ambiguous, but the result is the same anyway.
m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0),
m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0),
m_blockRows(BlockRows == 1 ? 1 : xpr.rows()),
m_blockCols(BlockCols == 1 ? 1 : xpr.cols()) {}
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(BlockRows), m_blockCols(BlockCols) {}
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows,
Index blockCols)
: m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols) {}
EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index rowId, Index colId) {
EIGEN_STATIC_ASSERT_LVALUE(XprType)
return m_xpr.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
return m_xpr.derived().coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const {
return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index) {
EIGEN_STATIC_ASSERT_LVALUE(XprType)
return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const {
return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const {
return m_xpr.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
template <int LoadMode>
EIGEN_DEVICE_FUNC inline PacketScalar packet(Index rowId, Index colId) const {
return m_xpr.template packet<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value());
}
template <int LoadMode>
EIGEN_DEVICE_FUNC inline void writePacket(Index rowId, Index colId, const PacketScalar& val) {
m_xpr.template writePacket<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value(), val);
}
template <int LoadMode>
EIGEN_DEVICE_FUNC inline PacketScalar packet(Index index) const {
return m_xpr.template packet<Unaligned>(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
}
template <int LoadMode>
EIGEN_DEVICE_FUNC inline void writePacket(Index index, const PacketScalar& val) {
m_xpr.template writePacket<Unaligned>(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
}
#ifdef EIGEN_PARSED_BY_DOXYGEN
/** \sa MapBase::data() */
EIGEN_DEVICE_FUNC constexpr const Scalar* data() const;
EIGEN_DEVICE_FUNC inline Index innerStride() const;
EIGEN_DEVICE_FUNC inline Index outerStride() const;
#endif
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const {
return m_xpr;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); }
protected:
XprTypeNested m_xpr;
const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows == 1) ? 0 : Dynamic>
m_startRow;
const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols == 1) ? 0 : Dynamic>
m_startCol;
const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
};
/** \internal Internal implementation of dense Blocks in the direct access case.*/
template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
class BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel, true>
: public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel>> {
typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
enum { XprTypeIsRowMajor = (int(traits<XprType>::Flags) & RowMajorBit) != 0 };
/** \internal Returns base+offset (unless base is null, in which case returns null).
* Adding an offset to nullptr is undefined behavior, so we must avoid it.
*/
template <typename Scalar>
EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static Scalar* add_to_nullable_pointer(Scalar* base, Index offset) {
return base != nullptr ? base + offset : nullptr;
}
public:
typedef MapBase<BlockType> Base;
EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
/** Column or Row constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index i)
: Base((BlockRows == 0 || BlockCols == 0)
? nullptr
: add_to_nullable_pointer(
xpr.data(),
i * (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) ||
((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) &&
(XprTypeIsRowMajor))
? xpr.innerStride()
: xpr.outerStride())),
BlockRows == 1 ? 1 : xpr.rows(), BlockCols == 1 ? 1 : xpr.cols()),
m_xpr(xpr),
m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0),
m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0) {
init();
}
/** Fixed-size constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
: Base((BlockRows == 0 || BlockCols == 0)
? nullptr
: add_to_nullable_pointer(xpr.data(),
xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) +
xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol))),
m_xpr(xpr),
m_startRow(startRow),
m_startCol(startCol) {
init();
}
/** Dynamic-size constructor
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows,
Index blockCols)
: Base((blockRows == 0 || blockCols == 0)
? nullptr
: add_to_nullable_pointer(xpr.data(),
xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) +
xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol)),
blockRows, blockCols),
m_xpr(xpr),
m_startRow(startRow),
m_startCol(startCol) {
init();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const noexcept {
return m_xpr;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; }
/** \sa MapBase::innerStride() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index innerStride() const noexcept {
return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.innerStride() : m_xpr.outerStride();
}
/** \sa MapBase::outerStride() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const noexcept {
return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); }
#ifndef __SUNPRO_CC
// FIXME sunstudio is not friendly with the above friend...
// META-FIXME there is no 'friend' keyword around here. Is this obsolete?
protected:
#endif
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal used by allowAligned() */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows,
Index blockCols)
: Base(data, blockRows, blockCols), m_xpr(xpr) {
init();
}
#endif
protected:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void init() {
m_outerStride =
internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride();
}
XprTypeNested m_xpr;
const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows == 1) ? 0 : Dynamic>
m_startRow;
const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols == 1) ? 0 : Dynamic>
m_startCol;
Index m_outerStride;
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_BLOCK_H
eigen-master/Eigen/src/Core/CommaInitializer.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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_COMMAINITIALIZER_H
#define EIGEN_COMMAINITIALIZER_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \class CommaInitializer
* \ingroup Core_Module
*
* \brief Helper class used by the comma initializer operator
*
* This class is internally used to implement the comma initializer feature. It is
* the return type of MatrixBase::operator<<, and most of the time this is the only
* way it is used.
*
* \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
*/
template <typename XprType>
struct CommaInitializer {
typedef typename XprType::Scalar Scalar;
EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const Scalar& s)
: m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) {
eigen_assert(m_xpr.rows() > 0 && m_xpr.cols() > 0 && "Cannot comma-initialize a 0x0 matrix (operator<<)");
m_xpr.coeffRef(0, 0) = s;
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
: m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) {
eigen_assert(m_xpr.rows() >= other.rows() && m_xpr.cols() >= other.cols() &&
"Cannot comma-initialize a 0x0 matrix (operator<<)");
m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(0, 0, other.rows(),
other.cols()) = other;
}
/* Copy/Move constructor which transfers ownership. This is crucial in
* absence of return value optimization to avoid assertions during destruction. */
// FIXME in C++11 mode this could be replaced by a proper RValue constructor
EIGEN_DEVICE_FUNC inline CommaInitializer(const CommaInitializer& o)
: m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
// Mark original object as finished. In absence of R-value references we need to const_cast:
const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
}
/* inserts a scalar value in the target matrix */
EIGEN_DEVICE_FUNC CommaInitializer &operator,(const Scalar& s) {
if (m_col == m_xpr.cols()) {
m_row += m_currentBlockRows;
m_col = 0;
m_currentBlockRows = 1;
eigen_assert(m_row < m_xpr.rows() && "Too many rows passed to comma initializer (operator<<)");
}
eigen_assert(m_col < m_xpr.cols() && "Too many coefficients passed to comma initializer (operator<<)");
eigen_assert(m_currentBlockRows == 1);
m_xpr.coeffRef(m_row, m_col++) = s;
return *this;
}
/* inserts a matrix expression in the target matrix */
template <typename OtherDerived>
EIGEN_DEVICE_FUNC CommaInitializer &operator,(const DenseBase<OtherDerived>& other) {
if (m_col == m_xpr.cols() && (other.cols() != 0 || other.rows() != m_currentBlockRows)) {
m_row += m_currentBlockRows;
m_col = 0;
m_currentBlockRows = other.rows();
eigen_assert(m_row + m_currentBlockRows <= m_xpr.rows() &&
"Too many rows passed to comma initializer (operator<<)");
}
eigen_assert((m_col + other.cols() <= m_xpr.cols()) &&
"Too many coefficients passed to comma initializer (operator<<)");
eigen_assert(m_currentBlockRows == other.rows());
m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(m_row, m_col, other.rows(),
other.cols()) = other;
m_col += other.cols();
return *this;
}
EIGEN_DEVICE_FUNC inline ~CommaInitializer()
#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
noexcept(false) // Eigen::eigen_assert_exception
#endif
{
finished();
}
/** \returns the built matrix once all its coefficients have been set.
* Calling finished is 100% optional. Its purpose is to write expressions
* like this:
* \code
* quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
* \endcode
*/
EIGEN_DEVICE_FUNC inline XprType& finished() {
eigen_assert(((m_row + m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0) && m_col == m_xpr.cols() &&
"Too few coefficients passed to comma initializer (operator<<)");
return m_xpr;
}
XprType& m_xpr; // target expression
Index m_row; // current row id
Index m_col; // current col id
Index m_currentBlockRows; // current block height
};
/** \anchor MatrixBaseCommaInitRef
* Convenient operator to set the coefficients of a matrix.
*
* The coefficients must be provided in a row major order and exactly match
* the size of the matrix. Otherwise an assertion is raised.
*
* Example: \include MatrixBase_set.cpp
* Output: \verbinclude MatrixBase_set.out
*
* \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary
* order.
*
* \sa CommaInitializer::finished(), class CommaInitializer
*/
template <typename Derived>
EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(const Scalar& s) {
return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
}
/** \sa operator<<(const Scalar&) */
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(
const DenseBase<OtherDerived>& other) {
return CommaInitializer<Derived>(*static_cast<Derived*>(this), other);
}
} // end namespace Eigen
#endif // EIGEN_COMMAINITIALIZER_H
eigen-master/Eigen/src/Core/ConditionEstimator.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.com)
//
// 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_CONDITIONESTIMATOR_H
#define EIGEN_CONDITIONESTIMATOR_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename Vector, typename RealVector, bool IsComplex>
struct rcond_compute_sign {
static inline Vector run(const Vector& v) {
const RealVector v_abs = v.cwiseAbs();
return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
.select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
}
};
// Partial specialization to avoid elementwise division for real vectors.
template <typename Vector>
struct rcond_compute_sign<Vector, Vector, false> {
static inline Vector run(const Vector& v) {
return (v.array() < static_cast<typename Vector::RealScalar>(0))
.select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
}
};
/**
* \returns an estimate of ||inv(matrix)||_1 given a decomposition of
* \a matrix that implements .solve() and .adjoint().solve() methods.
*
* This function implements Algorithms 4.1 and 5.1 from
* http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf
* which also forms the basis for the condition number estimators in
* LAPACK. Since at most 10 calls to the solve method of dec are
* performed, the total cost is O(dims^2), as opposed to O(dims^3)
* needed to compute the inverse matrix explicitly.
*
* The most common usage is in estimating the condition number
* ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be
* computed directly in O(n^2) operations.
*
* Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and
* LLT.
*
* \sa FullPivLU, PartialPivLU, LDLT, LLT.
*/
template <typename Decomposition>
typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec) {
typedef typename Decomposition::MatrixType MatrixType;
typedef typename Decomposition::Scalar Scalar;
typedef typename Decomposition::RealScalar RealScalar;
typedef typename internal::plain_col_type<MatrixType>::type Vector;
typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
eigen_assert(dec.rows() == dec.cols());
const Index n = dec.rows();
if (n == 0) return 0;
// Disable Index to float conversion warning
#ifdef __INTEL_COMPILER
#pragma warning push
#pragma warning(disable : 2259)
#endif
Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
#ifdef __INTEL_COMPILER
#pragma warning pop
#endif
// lower_bound is a lower bound on
// ||inv(matrix)||_1 = sup_v ||inv(matrix) v||_1 / ||v||_1
// and is the objective maximized by the ("super-") gradient ascent
// algorithm below.
RealScalar lower_bound = v.template lpNorm<1>();
if (n == 1) return lower_bound;
// Gradient ascent algorithm follows: We know that the optimum is achieved at
// one of the simplices v = e_i, so in each iteration we follow a
// super-gradient to move towards the optimal one.
RealScalar old_lower_bound = lower_bound;
Vector sign_vector(n);
Vector old_sign_vector;
Index v_max_abs_index = -1;
Index old_v_max_abs_index = v_max_abs_index;
for (int k = 0; k < 4; ++k) {
sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
// Break if the solution stagnated.
break;
}
// v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )|
v = dec.adjoint().solve(sign_vector);
v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
if (v_max_abs_index == old_v_max_abs_index) {
// Break if the solution stagnated.
break;
}
// Move to the new simplex e_j, where j = v_max_abs_index.
v = dec.solve(Vector::Unit(n, v_max_abs_index)); // v = inv(matrix) * e_j.
lower_bound = v.template lpNorm<1>();
if (lower_bound <= old_lower_bound) {
// Break if the gradient step did not increase the lower_bound.
break;
}
if (!is_complex) {
old_sign_vector = sign_vector;
}
old_v_max_abs_index = v_max_abs_index;
old_lower_bound = lower_bound;
}
// The following calculates an independent estimate of ||matrix||_1 by
// multiplying matrix by a vector with entries of slowly increasing
// magnitude and alternating sign:
// v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1.
// This improvement to Hager's algorithm above is due to Higham. It was
// added to make the algorithm more robust in certain corner cases where
// large elements in the matrix might otherwise escape detection due to
// exact cancellation (especially when op and op_adjoint correspond to a
// sequence of backsubstitutions and permutations), which could cause
// Hager's algorithm to vastly underestimate ||matrix||_1.
Scalar alternating_sign(RealScalar(1));
for (Index i = 0; i < n; ++i) {
// The static_cast is needed when Scalar is a complex and RealScalar implements expression templates
v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
alternating_sign = -alternating_sign;
}
v = dec.solve(v);
const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n));
return numext::maxi(lower_bound, alternate_lower_bound);
}
/** \brief Reciprocal condition number estimator.
*
* Computing a decomposition of a dense matrix takes O(n^3) operations, while
* this method estimates the condition number quickly and reliably in O(n^2)
* operations.
*
* \returns an estimate of the reciprocal condition number
* (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
* its decomposition. Supports the following decompositions: FullPivLU,
* PartialPivLU, LDLT, and LLT.
*
* \sa FullPivLU, PartialPivLU, LDLT, LLT.
*/
template <typename Decomposition>
typename Decomposition::RealScalar rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm,
const Decomposition& dec) {
typedef typename Decomposition::RealScalar RealScalar;
eigen_assert(dec.rows() == dec.cols());
if (dec.rows() == 0) return NumTraits<RealScalar>::infinity();
if (numext::is_exactly_zero(matrix_norm)) return RealScalar(0);
if (dec.rows() == 1) return RealScalar(1);
const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0)
: (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
}
} // namespace internal
} // namespace Eigen
#endif
eigen-master/Eigen/src/Core/CoreEvaluators.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
//
// 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_COREEVALUATORS_H
#define EIGEN_COREEVALUATORS_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
// This class returns the evaluator kind from the expression storage kind.
// Default assumes index based accessors
template <typename StorageKind>
struct storage_kind_to_evaluator_kind {
typedef IndexBased Kind;
};
// This class returns the evaluator shape from the expression storage kind.
// It can be Dense, Sparse, Triangular, Diagonal, SelfAdjoint, Band, etc.
template <typename StorageKind>
struct storage_kind_to_shape;
template <>
struct storage_kind_to_shape<Dense> {
typedef DenseShape Shape;
};
template <>
struct storage_kind_to_shape<SolverStorage> {
typedef SolverShape Shape;
};
template <>
struct storage_kind_to_shape<PermutationStorage> {
typedef PermutationShape Shape;
};
template <>
struct storage_kind_to_shape<TranspositionsStorage> {
typedef TranspositionsShape Shape;
};
// Evaluators have to be specialized with respect to various criteria such as:
// - storage/structure/shape
// - scalar type
// - etc.
// Therefore, we need specialization of evaluator providing additional template arguments for each kind of evaluators.
// We currently distinguish the following kind of evaluators:
// - unary_evaluator for expressions taking only one arguments (CwiseUnaryOp, CwiseUnaryView, Transpose,
// MatrixWrapper, ArrayWrapper, Reverse, Replicate)
// - binary_evaluator for expression taking two arguments (CwiseBinaryOp)
// - ternary_evaluator for expression taking three arguments (CwiseTernaryOp)
// - product_evaluator for linear algebra products (Product); special case of binary_evaluator because it requires
// additional tags for dispatching.
// - mapbase_evaluator for Map, Block, Ref
// - block_evaluator for Block (special dispatching to a mapbase_evaluator or unary_evaluator)
template <typename T, typename Arg1Kind = typename evaluator_traits<typename T::Arg1>::Kind,
typename Arg2Kind = typename evaluator_traits<typename T::Arg2>::Kind,
typename Arg3Kind = typename evaluator_traits<typename T::Arg3>::Kind,
typename Arg1Scalar = typename traits<typename T::Arg1>::Scalar,
typename Arg2Scalar = typename traits<typename T::Arg2>::Scalar,
typename Arg3Scalar = typename traits<typename T::Arg3>::Scalar>
struct ternary_evaluator;
template <typename T, typename LhsKind = typename evaluator_traits<typename T::Lhs>::Kind,
typename RhsKind = typename evaluator_traits<typename T::Rhs>::Kind,
typename LhsScalar = typename traits<typename T::Lhs>::Scalar,
typename RhsScalar = typename traits<typename T::Rhs>::Scalar>
struct binary_evaluator;
template <typename T, typename Kind = typename evaluator_traits<typename T::NestedExpression>::Kind,
typename Scalar = typename T::Scalar>
struct unary_evaluator;
// evaluator_traits<T> contains traits for evaluator<T>
template <typename T>
struct evaluator_traits_base {
// by default, get evaluator kind and shape from storage
typedef typename storage_kind_to_evaluator_kind<typename traits<T>::StorageKind>::Kind Kind;
typedef typename storage_kind_to_shape<typename traits<T>::StorageKind>::Shape Shape;
};
// Default evaluator traits
template <typename T>
struct evaluator_traits : public evaluator_traits_base<T> {};
template <typename T, typename Shape = typename evaluator_traits<T>::Shape>
struct evaluator_assume_aliasing {
static const bool value = false;
};
// By default, we assume a unary expression:
template <typename T>
struct evaluator : public unary_evaluator<T> {
typedef unary_evaluator<T> Base;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const T& xpr) : Base(xpr) {}
};
// TODO: Think about const-correctness
template <typename T>
struct evaluator<const T> : evaluator<T> {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const T& xpr) : evaluator<T>(xpr) {}
};
// ---------- base class for all evaluators ----------
template <typename ExpressionType>
struct evaluator_base {
// TODO that's not very nice to have to propagate all these traits. They are currently only needed to handle
// outer,inner indices.
typedef traits<ExpressionType> ExpressionTraits;
enum { Alignment = 0 };
// noncopyable:
// Don't make this class inherit noncopyable as this kills EBO (Empty Base Optimization)
// and make complex evaluator much larger than then should do.
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator_base() = default;
private:
EIGEN_DEVICE_FUNC evaluator_base(const evaluator_base&);
EIGEN_DEVICE_FUNC const evaluator_base& operator=(const evaluator_base&);
};
// -------------------- Matrix and Array --------------------
//
// evaluator<PlainObjectBase> is a common base class for the
// Matrix and Array evaluators.
// Here we directly specialize evaluator. This is not really a unary expression, and it is, by definition, dense,
// so no need for more sophisticated dispatching.
// this helper permits to completely eliminate m_outerStride if it is known at compiletime.
template <typename Scalar, int OuterStride>
class plainobjectbase_evaluator_data {
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plainobjectbase_evaluator_data(const Scalar* ptr, Index outerStride)
: data(ptr) {
#ifndef EIGEN_INTERNAL_DEBUGGING
EIGEN_UNUSED_VARIABLE(outerStride);
#endif
eigen_internal_assert(outerStride == OuterStride);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const noexcept { return OuterStride; }
const Scalar* data;
};
template <typename Scalar>
class plainobjectbase_evaluator_data<Scalar, Dynamic> {
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plainobjectbase_evaluator_data(const Scalar* ptr, Index outerStride)
: data(ptr), m_outerStride(outerStride) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const { return m_outerStride; }
const Scalar* data;
protected:
Index m_outerStride;
};
template <typename Derived>
struct evaluator<PlainObjectBase<Derived>> : evaluator_base<Derived> {
typedef PlainObjectBase<Derived> PlainObjectType;
typedef typename PlainObjectType::Scalar Scalar;
typedef typename PlainObjectType::CoeffReturnType CoeffReturnType;
enum {
IsRowMajor = PlainObjectType::IsRowMajor,
IsVectorAtCompileTime = PlainObjectType::IsVectorAtCompileTime,
RowsAtCompileTime = PlainObjectType::RowsAtCompileTime,
ColsAtCompileTime = PlainObjectType::ColsAtCompileTime,
CoeffReadCost = NumTraits<Scalar>::ReadCost,
Flags = traits<Derived>::EvaluatorFlags,
Alignment = traits<Derived>::Alignment
};
enum {
// We do not need to know the outer stride for vectors
OuterStrideAtCompileTime = IsVectorAtCompileTime ? 0
: int(IsRowMajor) ? ColsAtCompileTime
: RowsAtCompileTime
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() : m_d(0, OuterStrideAtCompileTime) {
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const PlainObjectType& m)
: m_d(m.data(), IsVectorAtCompileTime ? 0 : m.outerStride()) {
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index row, Index col) const {
return coeff(getIndex(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index index) const { return m_d.data[index]; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index row, Index col) {
return coeffRef(getIndex(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) {
return const_cast<Scalar*>(m_d.data)[index];
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return packet<LoadMode, PacketType>(getIndex(row, col));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return ploadt<PacketType, LoadMode>(m_d.data + index);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
writePacket<StoreMode, PacketType>(getIndex(row, col), x);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
pstoret<Scalar, PacketType, StoreMode>(const_cast<Scalar*>(m_d.data) + index, x);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return packetSegment<LoadMode, PacketType>(getIndex(row, col), begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return ploadtSegment<PacketType, LoadMode>(m_d.data + index, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
writePacketSegment<StoreMode, PacketType>(getIndex(row, col), x, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
pstoretSegment<Scalar, PacketType, StoreMode>(const_cast<Scalar*>(m_d.data) + index, x, begin, count);
}
protected:
plainobjectbase_evaluator_data<Scalar, OuterStrideAtCompileTime> m_d;
private:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index constexpr getIndex(Index row, Index col) const {
return IsRowMajor ? row * m_d.outerStride() + col : row + col * m_d.outerStride();
}
};
template <typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
struct evaluator<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols>>
: evaluator<PlainObjectBase<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols>>> {
typedef Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const XprType& m)
: evaluator<PlainObjectBase<XprType>>(m) {}
};
template <typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
struct evaluator<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols>>
: evaluator<PlainObjectBase<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols>>> {
typedef Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const XprType& m)
: evaluator<PlainObjectBase<XprType>>(m) {}
};
// -------------------- Transpose --------------------
template <typename ArgType>
struct unary_evaluator<Transpose<ArgType>, IndexBased> : evaluator_base<Transpose<ArgType>> {
typedef Transpose<ArgType> XprType;
enum {
CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
Flags = evaluator<ArgType>::Flags ^ RowMajorBit,
Alignment = evaluator<ArgType>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& t) : m_argImpl(t.nestedExpression()) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_argImpl.coeff(col, row);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_argImpl.coeff(index); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { return m_argImpl.coeffRef(col, row); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename XprType::Scalar& coeffRef(Index index) {
return m_argImpl.coeffRef(index);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_argImpl.template packet<LoadMode, PacketType>(col, row);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return m_argImpl.template packet<LoadMode, PacketType>(index);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
m_argImpl.template writePacket<StoreMode, PacketType>(col, row, x);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
m_argImpl.template writePacket<StoreMode, PacketType>(index, x);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_argImpl.template packetSegment<LoadMode, PacketType>(col, row, begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return m_argImpl.template packetSegment<LoadMode, PacketType>(index, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
m_argImpl.template writePacketSegment<StoreMode, PacketType>(col, row, x, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
m_argImpl.template writePacketSegment<StoreMode, PacketType>(index, x, begin, count);
}
protected:
evaluator<ArgType> m_argImpl;
};
// -------------------- CwiseNullaryOp --------------------
// Like Matrix and Array, this is not really a unary expression, so we directly specialize evaluator.
// Likewise, there is not need to more sophisticated dispatching here.
template <typename Scalar, typename NullaryOp, bool has_nullary = has_nullary_operator<NullaryOp>::value,
bool has_unary = has_unary_operator<NullaryOp>::value,
bool has_binary = has_binary_operator<NullaryOp>::value>
struct nullary_wrapper {
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const {
return op(i, j);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const {
return op(i);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const {
return op.template packetOp<T>(i, j);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const {
return op.template packetOp<T>(i);
}
};
template <typename Scalar, typename NullaryOp>
struct nullary_wrapper<Scalar, NullaryOp, true, false, false> {
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType = 0, IndexType = 0) const {
return op();
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType = 0, IndexType = 0) const {
return op.template packetOp<T>();
}
};
template <typename Scalar, typename NullaryOp>
struct nullary_wrapper<Scalar, NullaryOp, false, false, true> {
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j = 0) const {
return op(i, j);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j = 0) const {
return op.template packetOp<T>(i, j);
}
};
// We need the following specialization for vector-only functors assigned to a runtime vector,
// for instance, using linspace and assigning a RowVectorXd to a MatrixXd or even a row of a MatrixXd.
// In this case, i==0 and j is used for the actual iteration.
template <typename Scalar, typename NullaryOp>
struct nullary_wrapper<Scalar, NullaryOp, false, true, false> {
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const {
eigen_assert(i == 0 || j == 0);
return op(i + j);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const {
eigen_assert(i == 0 || j == 0);
return op.template packetOp<T>(i + j);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const {
return op(i);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const {
return op.template packetOp<T>(i);
}
};
template <typename Scalar, typename NullaryOp>
struct nullary_wrapper<Scalar, NullaryOp, false, false, false> {};
#if 0 && EIGEN_COMP_MSVC > 0
// Disable this ugly workaround. This is now handled in traits<Ref>::match,
// but this piece of code might still become handly if some other weird compilation
// errors pop up again.
// MSVC exhibits a weird compilation error when
// compiling:
// Eigen::MatrixXf A = MatrixXf::Random(3,3);
// Ref<const MatrixXf> R = 2.f*A;
// and that has_*ary_operator<scalar_constant_op<float>> have not been instantiated yet.
// The "problem" is that evaluator<2.f*A> is instantiated by traits<Ref>::match<2.f*A>
// and at that time has_*ary_operator<T> returns true regardless of T.
// Then nullary_wrapper is badly instantiated as nullary_wrapper<.,.,true,true,true>.
// The trick is thus to defer the proper instantiation of nullary_wrapper when coeff(),
// and packet() are really instantiated as implemented below:
// This is a simple wrapper around Index to enforce the re-instantiation of
// has_*ary_operator when needed.
template<typename T> struct nullary_wrapper_workaround_msvc {
nullary_wrapper_workaround_msvc(const T&);
operator T()const;
};
template<typename Scalar,typename NullaryOp>
struct nullary_wrapper<Scalar,NullaryOp,true,true,true>
{
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const {
return nullary_wrapper<Scalar,NullaryOp,
has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().operator()(op,i,j);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const {
return nullary_wrapper<Scalar,NullaryOp,
has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().operator()(op,i);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const {
return nullary_wrapper<Scalar,NullaryOp,
has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().template packetOp<T>(op,i,j);
}
template <typename T, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const {
return nullary_wrapper<Scalar,NullaryOp,
has_nullary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_unary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value,
has_binary_operator<NullaryOp,nullary_wrapper_workaround_msvc<IndexType> >::value>().template packetOp<T>(op,i);
}
};
#endif // MSVC workaround
template <typename NullaryOp, typename PlainObjectType>
struct evaluator<CwiseNullaryOp<NullaryOp, PlainObjectType>>
: evaluator_base<CwiseNullaryOp<NullaryOp, PlainObjectType>> {
typedef CwiseNullaryOp<NullaryOp, PlainObjectType> XprType;
typedef remove_all_t<PlainObjectType> PlainObjectTypeCleaned;
enum {
CoeffReadCost = functor_traits<NullaryOp>::Cost,
Flags = (evaluator<PlainObjectTypeCleaned>::Flags &
(HereditaryBits | (functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0) |
(functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0))) |
(functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
Alignment = AlignedMax
};
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& n) : m_functor(n.functor()), m_wrapper() {
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(IndexType row, IndexType col) const {
return m_wrapper(m_functor, row, col);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(IndexType index) const {
return m_wrapper(m_functor, index);
}
template <int LoadMode, typename PacketType, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(IndexType row, IndexType col) const {
return m_wrapper.template packetOp<PacketType>(m_functor, row, col);
}
template <int LoadMode, typename PacketType, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(IndexType index) const {
return m_wrapper.template packetOp<PacketType>(m_functor, index);
}
template <int LoadMode, typename PacketType, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(IndexType row, IndexType col, Index /*begin*/,
Index /*count*/) const {
return packet<LoadMode, PacketType, IndexType>(row, col);
}
template <int LoadMode, typename PacketType, typename IndexType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(IndexType index, Index /*begin*/,
Index /*count*/) const {
return packet<LoadMode, PacketType, IndexType>(index);
}
protected:
const NullaryOp m_functor;
const nullary_wrapper<CoeffReturnType, NullaryOp> m_wrapper;
};
// -------------------- CwiseUnaryOp --------------------
template <typename UnaryOp, typename ArgType>
struct unary_evaluator<CwiseUnaryOp<UnaryOp, ArgType>, IndexBased> : evaluator_base<CwiseUnaryOp<UnaryOp, ArgType>> {
typedef CwiseUnaryOp<UnaryOp, ArgType> XprType;
enum {
CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
Flags = evaluator<ArgType>::Flags &
(HereditaryBits | LinearAccessBit | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
Alignment = evaluator<ArgType>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& op) : m_d(op) {
EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<UnaryOp>::Cost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_d.func()(m_d.argImpl.coeff(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_d.func()(m_d.argImpl.coeff(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_d.func().packetOp(m_d.argImpl.template packet<LoadMode, PacketType>(row, col));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return m_d.func().packetOp(m_d.argImpl.template packet<LoadMode, PacketType>(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_d.func().packetOp(m_d.argImpl.template packetSegment<LoadMode, PacketType>(row, col, begin, count));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return m_d.func().packetOp(m_d.argImpl.template packetSegment<LoadMode, PacketType>(index, begin, count));
}
protected:
// this helper permits to completely eliminate the functor if it is empty
struct Data {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr)
: op(xpr.functor()), argImpl(xpr.nestedExpression()) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& func() const { return op; }
UnaryOp op;
evaluator<ArgType> argImpl;
};
Data m_d;
};
// ----------------------- Casting ---------------------
template <typename SrcType, typename DstType, typename ArgType>
struct unary_evaluator<CwiseUnaryOp<core_cast_op<SrcType, DstType>, ArgType>, IndexBased> {
using CastOp = core_cast_op<SrcType, DstType>;
using XprType = CwiseUnaryOp<CastOp, ArgType>;
// Use the largest packet type by default
using SrcPacketType = typename packet_traits<SrcType>::type;
static constexpr int SrcPacketSize = unpacket_traits<SrcPacketType>::size;
static constexpr int SrcPacketBytes = SrcPacketSize * sizeof(SrcType);
enum {
CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<CastOp>::Cost),
PacketAccess = functor_traits<CastOp>::PacketAccess,
ActualPacketAccessBit = PacketAccess ? PacketAccessBit : 0,
Flags = evaluator<ArgType>::Flags & (HereditaryBits | LinearAccessBit | ActualPacketAccessBit),
IsRowMajor = (evaluator<ArgType>::Flags & RowMajorBit),
Alignment = evaluator<ArgType>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& xpr)
: m_argImpl(xpr.nestedExpression()), m_rows(xpr.rows()), m_cols(xpr.cols()) {
EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<CastOp>::Cost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
template <typename DstPacketType>
using AltSrcScalarOp = std::enable_if_t<(unpacket_traits<DstPacketType>::size < SrcPacketSize &&
!find_packet_by_size<SrcType, unpacket_traits<DstPacketType>::size>::value),
bool>;
template <typename DstPacketType>
using SrcPacketArgs1 =
std::enable_if_t<(find_packet_by_size<SrcType, unpacket_traits<DstPacketType>::size>::value), bool>;
template <typename DstPacketType>
using SrcPacketArgs2 = std::enable_if_t<(unpacket_traits<DstPacketType>::size) == (2 * SrcPacketSize), bool>;
template <typename DstPacketType>
using SrcPacketArgs4 = std::enable_if_t<(unpacket_traits<DstPacketType>::size) == (4 * SrcPacketSize), bool>;
template <typename DstPacketType>
using SrcPacketArgs8 = std::enable_if_t<(unpacket_traits<DstPacketType>::size) == (8 * SrcPacketSize), bool>;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool check_array_bounds(Index row, Index col, Index begin, Index count) const {
return IsRowMajor ? (col + count + begin <= cols()) : (row + count + begin <= rows());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool check_array_bounds(Index index, Index begin, Index count) const {
return index + count + begin <= size();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE SrcType srcCoeff(Index row, Index col, Index offset) const {
Index actualRow = IsRowMajor ? row : row + offset;
Index actualCol = IsRowMajor ? col + offset : col;
return m_argImpl.coeff(actualRow, actualCol);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE SrcType srcCoeff(Index index, Index offset) const {
Index actualIndex = index + offset;
return m_argImpl.coeff(actualIndex);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstType coeff(Index row, Index col) const {
return cast<SrcType, DstType>(srcCoeff(row, col, 0));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstType coeff(Index index) const {
return cast<SrcType, DstType>(srcCoeff(index, 0));
}
template <int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacket(Index row, Index col, Index offset) const {
constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index packetOffset = offset * PacketSize;
Index actualRow = IsRowMajor ? row : row + packetOffset;
Index actualCol = IsRowMajor ? col + packetOffset : col;
eigen_assert(check_array_bounds(actualRow, actualCol, 0, PacketSize) && "Array index out of bounds");
return m_argImpl.template packet<LoadMode, PacketType>(actualRow, actualCol);
}
template <int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacket(Index index, Index offset) const {
constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index packetOffset = offset * PacketSize;
Index actualIndex = index + packetOffset;
eigen_assert(check_array_bounds(actualIndex, 0, PacketSize) && "Array index out of bounds");
return m_argImpl.template packet<LoadMode, PacketType>(actualIndex);
}
template <int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacketSegment(Index row, Index col, Index begin, Index count,
Index offset) const {
constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index packetOffset = offset * PacketSize;
Index actualRow = IsRowMajor ? row : row + packetOffset;
Index actualCol = IsRowMajor ? col + packetOffset : col;
eigen_assert(check_array_bounds(actualRow, actualCol, 0, count) && "Array index out of bounds");
return m_argImpl.template packetSegment<LoadMode, PacketType>(actualRow, actualCol, begin, count);
}
template <int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacketSegment(Index index, Index begin, Index count,
Index offset) const {
constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index packetOffset = offset * PacketSize;
Index actualIndex = index + packetOffset + begin;
eigen_assert(check_array_bounds(actualIndex, 0, count) && "Array index out of bounds");
return m_argImpl.template packetSegment<LoadMode, PacketType>(actualIndex, begin, count);
}
template <int NumPackets, int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketBlock<PacketType, NumPackets> srcPacketSegmentHelper(Index row, Index col,
Index begin,
Index count) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<PacketType, NumPackets> packets;
for (Index i = 0; i < NumPackets; i++) packets.packet[i] = pzero(PacketType());
Index offset = begin / SrcPacketSize;
Index actualBegin = begin % SrcPacketSize;
for (; offset < NumPackets; offset++) {
Index actualCount = numext::mini(SrcPacketSize - actualBegin, count);
packets.packet[offset] = srcPacketSegment<SrcLoadMode>(row, col, actualBegin, actualCount, offset);
if (count == actualCount) break;
actualBegin = 0;
count -= actualCount;
}
return packets;
}
template <int NumPackets, int LoadMode, typename PacketType = SrcPacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketBlock<PacketType, NumPackets> srcPacketSegmentHelper(Index index,
Index begin,
Index count) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<PacketType, NumPackets> packets;
for (Index i = 0; i < NumPackets; i++) packets.packet[i] = pzero(PacketType());
Index offset = begin / SrcPacketSize;
Index actualBegin = begin % SrcPacketSize;
for (; offset < NumPackets; offset++) {
Index actualCount = numext::mini(SrcPacketSize - actualBegin, count);
packets.packet[offset] = srcPacketSegment<SrcLoadMode>(index, actualBegin, actualCount, offset);
if (count == actualCount) break;
actualBegin = 0;
count -= actualCount;
}
return packets;
}
// There is no source packet type with equal or fewer elements than DstPacketType.
// This is problematic as the evaluation loop may attempt to access data outside the bounds of the array.
// For example, consider the cast utilizing pcast<Packet4f,Packet2d> with an array of size 4: {0.0f,1.0f,2.0f,3.0f}.
// The first iteration of the evaluation loop will load 16 bytes: {0.0f,1.0f,2.0f,3.0f} and cast to {0.0,1.0}, which
// is acceptable. The second iteration will load 16 bytes: {2.0f,3.0f,?,?}, which is outside the bounds of the array.
template <int LoadMode, typename DstPacketType, AltSrcScalarOp<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacketSegment<SrcLoadMode>(row, col, 0, DstPacketSize, 0));
}
// Use the source packet type with the same size as DstPacketType, if it exists
template <int LoadMode, typename DstPacketType, SrcPacketArgs1<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
using SizedSrcPacketType = typename find_packet_by_size<SrcType, DstPacketSize>::type;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SizedSrcPacketType, DstPacketType>(srcPacket<SrcLoadMode, SizedSrcPacketType>(row, col, 0));
}
// unpacket_traits<DstPacketType>::size == 2 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs2<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacket<SrcLoadMode>(row, col, 0),
srcPacket<SrcLoadMode>(row, col, 1));
}
// unpacket_traits<DstPacketType>::size == 4 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs4<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacket<SrcLoadMode>(row, col, 0), srcPacket<SrcLoadMode>(row, col, 1),
srcPacket<SrcLoadMode>(row, col, 2),
srcPacket<SrcLoadMode>(row, col, 3));
}
// unpacket_traits<DstPacketType>::size == 8 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs8<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(
srcPacket<SrcLoadMode>(row, col, 0), srcPacket<SrcLoadMode>(row, col, 1), srcPacket<SrcLoadMode>(row, col, 2),
srcPacket<SrcLoadMode>(row, col, 3), srcPacket<SrcLoadMode>(row, col, 4), srcPacket<SrcLoadMode>(row, col, 5),
srcPacket<SrcLoadMode>(row, col, 6), srcPacket<SrcLoadMode>(row, col, 7));
}
// packetSegment variants
template <int LoadMode, typename DstPacketType, AltSrcScalarOp<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin,
Index count) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacketSegment<SrcLoadMode>(row, col, begin, count, 0));
}
// Use the source packet type with the same size as DstPacketType, if it exists
template <int LoadMode, typename DstPacketType, SrcPacketArgs1<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin,
Index count) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
using SizedSrcPacketType = typename find_packet_by_size<SrcType, DstPacketSize>::type;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SizedSrcPacketType, DstPacketType>(
srcPacketSegment<SrcLoadMode, SizedSrcPacketType>(row, col, begin, count, 0));
}
// unpacket_traits<DstPacketType>::size == 2 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs2<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin,
Index count) const {
constexpr int NumPackets = 2;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(row, col, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1]);
}
// unpacket_traits<DstPacketType>::size == 4 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs4<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin,
Index count) const {
constexpr int NumPackets = 4;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(row, col, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1], packets.packet[2],
packets.packet[3]);
}
// unpacket_traits<DstPacketType>::size == 8 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs8<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin,
Index count) const {
constexpr int NumPackets = 8;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(row, col, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1], packets.packet[2],
packets.packet[3], packets.packet[4], packets.packet[5],
packets.packet[6], packets.packet[7]);
}
// Analogous routines for linear access.
template <int LoadMode, typename DstPacketType, AltSrcScalarOp<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacketSegment<SrcLoadMode>(index, 0, DstPacketSize, 0));
}
template <int LoadMode, typename DstPacketType, SrcPacketArgs1<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
using SizedSrcPacketType = typename find_packet_by_size<SrcType, DstPacketSize>::type;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SizedSrcPacketType, DstPacketType>(srcPacket<SrcLoadMode, SizedSrcPacketType>(index, 0));
}
template <int LoadMode, typename DstPacketType, SrcPacketArgs2<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacket<SrcLoadMode>(index, 0), srcPacket<SrcLoadMode>(index, 1));
}
template <int LoadMode, typename DstPacketType, SrcPacketArgs4<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacket<SrcLoadMode>(index, 0), srcPacket<SrcLoadMode>(index, 1),
srcPacket<SrcLoadMode>(index, 2), srcPacket<SrcLoadMode>(index, 3));
}
template <int LoadMode, typename DstPacketType, SrcPacketArgs8<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const {
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacket<SrcLoadMode>(index, 0), srcPacket<SrcLoadMode>(index, 1),
srcPacket<SrcLoadMode>(index, 2), srcPacket<SrcLoadMode>(index, 3),
srcPacket<SrcLoadMode>(index, 4), srcPacket<SrcLoadMode>(index, 5),
srcPacket<SrcLoadMode>(index, 6), srcPacket<SrcLoadMode>(index, 7));
}
// packetSegment variants
template <int LoadMode, typename DstPacketType, AltSrcScalarOp<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SrcPacketType, DstPacketType>(srcPacketSegment<SrcLoadMode>(index, begin, count, 0));
}
// Use the source packet type with the same size as DstPacketType, if it exists
template <int LoadMode, typename DstPacketType, SrcPacketArgs1<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const {
constexpr int DstPacketSize = unpacket_traits<DstPacketType>::size;
using SizedSrcPacketType = typename find_packet_by_size<SrcType, DstPacketSize>::type;
constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType);
constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode);
return pcast<SizedSrcPacketType, DstPacketType>(
srcPacketSegment<SrcLoadMode, SizedSrcPacketType>(index, begin, count, 0));
}
// unpacket_traits<DstPacketType>::size == 2 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs2<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const {
constexpr int NumPackets = 2;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(index, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1]);
}
// unpacket_traits<DstPacketType>::size == 4 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs4<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const {
constexpr int NumPackets = 4;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(index, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1], packets.packet[2],
packets.packet[3]);
}
// unpacket_traits<DstPacketType>::size == 8 * SrcPacketSize
template <int LoadMode, typename DstPacketType, SrcPacketArgs8<DstPacketType> = true>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const {
constexpr int NumPackets = 8;
constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode);
PacketBlock<SrcPacketType, NumPackets> packets =
srcPacketSegmentHelper<NumPackets, SrcLoadMode>(index, begin, count);
return pcast<SrcPacketType, DstPacketType>(packets.packet[0], packets.packet[1], packets.packet[2],
packets.packet[3], packets.packet[4], packets.packet[5],
packets.packet[6], packets.packet[7]);
}
constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { return m_rows; }
constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { return m_cols; }
constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_rows * m_cols; }
protected:
const evaluator<ArgType> m_argImpl;
const variable_if_dynamic<Index, XprType::RowsAtCompileTime> m_rows;
const variable_if_dynamic<Index, XprType::ColsAtCompileTime> m_cols;
};
// -------------------- CwiseTernaryOp --------------------
// this is a ternary expression
template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
struct evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>
: public ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> {
typedef CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> XprType;
typedef ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {}
};
template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
struct ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>, IndexBased, IndexBased>
: evaluator_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> {
typedef CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> XprType;
enum {
CoeffReadCost = int(evaluator<Arg1>::CoeffReadCost) + int(evaluator<Arg2>::CoeffReadCost) +
int(evaluator<Arg3>::CoeffReadCost) + int(functor_traits<TernaryOp>::Cost),
Arg1Flags = evaluator<Arg1>::Flags,
Arg2Flags = evaluator<Arg2>::Flags,
Arg3Flags = evaluator<Arg3>::Flags,
SameType = is_same<typename Arg1::Scalar, typename Arg2::Scalar>::value &&
is_same<typename Arg1::Scalar, typename Arg3::Scalar>::value,
StorageOrdersAgree = (int(Arg1Flags) & RowMajorBit) == (int(Arg2Flags) & RowMajorBit) &&
(int(Arg1Flags) & RowMajorBit) == (int(Arg3Flags) & RowMajorBit),
Flags0 = (int(Arg1Flags) | int(Arg2Flags) | int(Arg3Flags)) &
(HereditaryBits |
(int(Arg1Flags) & int(Arg2Flags) & int(Arg3Flags) &
((StorageOrdersAgree ? LinearAccessBit : 0) |
(functor_traits<TernaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)))),
Flags = (Flags0 & ~RowMajorBit) | (Arg1Flags & RowMajorBit),
Alignment = plain_enum_min(plain_enum_min(evaluator<Arg1>::Alignment, evaluator<Arg2>::Alignment),
evaluator<Arg3>::Alignment)
};
EIGEN_DEVICE_FUNC explicit ternary_evaluator(const XprType& xpr) : m_d(xpr) {
EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<TernaryOp>::Cost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_d.func()(m_d.arg1Impl.coeff(row, col), m_d.arg2Impl.coeff(row, col), m_d.arg3Impl.coeff(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_d.func()(m_d.arg1Impl.coeff(index), m_d.arg2Impl.coeff(index), m_d.arg3Impl.coeff(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_d.func().packetOp(m_d.arg1Impl.template packet<LoadMode, PacketType>(row, col),
m_d.arg2Impl.template packet<LoadMode, PacketType>(row, col),
m_d.arg3Impl.template packet<LoadMode, PacketType>(row, col));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return m_d.func().packetOp(m_d.arg1Impl.template packet<LoadMode, PacketType>(index),
m_d.arg2Impl.template packet<LoadMode, PacketType>(index),
m_d.arg3Impl.template packet<LoadMode, PacketType>(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_d.func().packetOp(m_d.arg1Impl.template packetSegment<LoadMode, PacketType>(row, col, begin, count),
m_d.arg2Impl.template packetSegment<LoadMode, PacketType>(row, col, begin, count),
m_d.arg3Impl.template packetSegment<LoadMode, PacketType>(row, col, begin, count));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return m_d.func().packetOp(m_d.arg1Impl.template packetSegment<LoadMode, PacketType>(index, begin, count),
m_d.arg2Impl.template packetSegment<LoadMode, PacketType>(index, begin, count),
m_d.arg3Impl.template packetSegment<LoadMode, PacketType>(index, begin, count));
}
protected:
// this helper permits to completely eliminate the functor if it is empty
struct Data {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr)
: op(xpr.functor()), arg1Impl(xpr.arg1()), arg2Impl(xpr.arg2()), arg3Impl(xpr.arg3()) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TernaryOp& func() const { return op; }
TernaryOp op;
evaluator<Arg1> arg1Impl;
evaluator<Arg2> arg2Impl;
evaluator<Arg3> arg3Impl;
};
Data m_d;
};
// specialization for expressions like (a < b).select(c, d) to enable full vectorization
template <typename Arg1, typename Arg2, typename Scalar, typename CmpLhsType, typename CmpRhsType, ComparisonName cmp>
struct evaluator<CwiseTernaryOp<scalar_boolean_select_op<Scalar, Scalar, bool>, Arg1, Arg2,
CwiseBinaryOp<scalar_cmp_op<Scalar, Scalar, cmp, false>, CmpLhsType, CmpRhsType>>>
: public ternary_evaluator<
CwiseTernaryOp<scalar_boolean_select_op<Scalar, Scalar, Scalar>, Arg1, Arg2,
CwiseBinaryOp<scalar_cmp_op<Scalar, Scalar, cmp, true>, CmpLhsType, CmpRhsType>>> {
using DummyTernaryOp = scalar_boolean_select_op<Scalar, Scalar, bool>;
using DummyArg3 = CwiseBinaryOp<scalar_cmp_op<Scalar, Scalar, cmp, false>, CmpLhsType, CmpRhsType>;
using DummyXprType = CwiseTernaryOp<DummyTernaryOp, Arg1, Arg2, DummyArg3>;
using TernaryOp = scalar_boolean_select_op<Scalar, Scalar, Scalar>;
using Arg3 = CwiseBinaryOp<scalar_cmp_op<Scalar, Scalar, cmp, true>, CmpLhsType, CmpRhsType>;
using XprType = CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>;
using Base = ternary_evaluator<XprType>;
EIGEN_DEVICE_FUNC explicit evaluator(const DummyXprType& xpr)
: Base(XprType(xpr.arg1(), xpr.arg2(), Arg3(xpr.arg3().lhs(), xpr.arg3().rhs()))) {}
};
// -------------------- CwiseBinaryOp --------------------
// this is a binary expression
template <typename BinaryOp, typename Lhs, typename Rhs>
struct evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> : public binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> {
typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
typedef binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> Base;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
};
template <typename BinaryOp, typename Lhs, typename Rhs>
struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IndexBased, IndexBased>
: evaluator_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> {
typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> XprType;
enum {
CoeffReadCost =
int(evaluator<Lhs>::CoeffReadCost) + int(evaluator<Rhs>::CoeffReadCost) + int(functor_traits<BinaryOp>::Cost),
LhsFlags = evaluator<Lhs>::Flags,
RhsFlags = evaluator<Rhs>::Flags,
SameType = is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value,
StorageOrdersAgree = (int(LhsFlags) & RowMajorBit) == (int(RhsFlags) & RowMajorBit),
Flags0 = (int(LhsFlags) | int(RhsFlags)) &
(HereditaryBits |
(int(LhsFlags) & int(RhsFlags) &
((StorageOrdersAgree ? LinearAccessBit : 0) |
(functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)))),
Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
Alignment = plain_enum_min(evaluator<Lhs>::Alignment, evaluator<Rhs>::Alignment)
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit binary_evaluator(const XprType& xpr) : m_d(xpr) {
EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<BinaryOp>::Cost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_d.func()(m_d.lhsImpl.coeff(row, col), m_d.rhsImpl.coeff(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_d.func()(m_d.lhsImpl.coeff(index), m_d.rhsImpl.coeff(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_d.func().packetOp(m_d.lhsImpl.template packet<LoadMode, PacketType>(row, col),
m_d.rhsImpl.template packet<LoadMode, PacketType>(row, col));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return m_d.func().packetOp(m_d.lhsImpl.template packet<LoadMode, PacketType>(index),
m_d.rhsImpl.template packet<LoadMode, PacketType>(index));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_d.func().packetOp(m_d.lhsImpl.template packetSegment<LoadMode, PacketType>(row, col, begin, count),
m_d.rhsImpl.template packetSegment<LoadMode, PacketType>(row, col, begin, count));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return m_d.func().packetOp(m_d.lhsImpl.template packetSegment<LoadMode, PacketType>(index, begin, count),
m_d.rhsImpl.template packetSegment<LoadMode, PacketType>(index, begin, count));
}
protected:
// this helper permits to completely eliminate the functor if it is empty
struct Data {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr)
: op(xpr.functor()), lhsImpl(xpr.lhs()), rhsImpl(xpr.rhs()) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& func() const { return op; }
BinaryOp op;
evaluator<Lhs> lhsImpl;
evaluator<Rhs> rhsImpl;
};
Data m_d;
};
// -------------------- CwiseUnaryView --------------------
template <typename UnaryOp, typename ArgType, typename StrideType>
struct unary_evaluator<CwiseUnaryView<UnaryOp, ArgType, StrideType>, IndexBased>
: evaluator_base<CwiseUnaryView<UnaryOp, ArgType, StrideType>> {
typedef CwiseUnaryView<UnaryOp, ArgType, StrideType> XprType;
enum {
CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
Flags = (evaluator<ArgType>::Flags & (HereditaryBits | LinearAccessBit | DirectAccessBit)),
Alignment = 0 // FIXME it is not very clear why alignment is necessarily lost...
};
EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& op) : m_d(op) {
EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits<UnaryOp>::Cost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_d.func()(m_d.argImpl.coeff(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_d.func()(m_d.argImpl.coeff(index));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
return m_d.func()(m_d.argImpl.coeffRef(row, col));
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return m_d.func()(m_d.argImpl.coeffRef(index));
}
protected:
// this helper permits to completely eliminate the functor if it is empty
struct Data {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr)
: op(xpr.functor()), argImpl(xpr.nestedExpression()) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& func() const { return op; }
UnaryOp op;
evaluator<ArgType> argImpl;
};
Data m_d;
};
// -------------------- Map --------------------
// FIXME perhaps the PlainObjectType could be provided by Derived::PlainObject ?
// but that might complicate template specialization
template <typename Derived, typename PlainObjectType>
struct mapbase_evaluator;
template <typename Derived, typename PlainObjectType>
struct mapbase_evaluator : evaluator_base<Derived> {
typedef Derived XprType;
typedef typename XprType::PointerType PointerType;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum {
IsRowMajor = XprType::RowsAtCompileTime,
ColsAtCompileTime = XprType::ColsAtCompileTime,
CoeffReadCost = NumTraits<Scalar>::ReadCost
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit mapbase_evaluator(const XprType& map)
: m_data(const_cast<PointerType>(map.data())),
m_innerStride(map.innerStride()),
m_outerStride(map.outerStride()) {
EIGEN_STATIC_ASSERT(check_implication((evaluator<Derived>::Flags & PacketAccessBit) != 0,
inner_stride_at_compile_time<Derived>::ret == 1),
PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_data[col * colStride() + row * rowStride()];
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_data[index * m_innerStride.value()];
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
return m_data[col * colStride() + row * rowStride()];
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_data[index * m_innerStride.value()]; }
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
PointerType ptr = m_data + row * rowStride() + col * colStride();
return ploadt<PacketType, LoadMode>(ptr);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return ploadt<PacketType, LoadMode>(m_data + index * m_innerStride.value());
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
PointerType ptr = m_data + row * rowStride() + col * colStride();
pstoret<Scalar, PacketType, StoreMode>(ptr, x);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
pstoret<Scalar, PacketType, StoreMode>(m_data + index * m_innerStride.value(), x);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
PointerType ptr = m_data + row * rowStride() + col * colStride();
return ploadtSegment<PacketType, LoadMode>(ptr, begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return ploadtSegment<PacketType, LoadMode>(m_data + index * m_innerStride.value(), begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
PointerType ptr = m_data + row * rowStride() + col * colStride();
pstoretSegment<Scalar, PacketType, StoreMode>(ptr, x, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
pstoretSegment<Scalar, PacketType, StoreMode>(m_data + index * m_innerStride.value(), x, begin, count);
}
protected:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowStride() const noexcept {
return XprType::IsRowMajor ? m_outerStride.value() : m_innerStride.value();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colStride() const noexcept {
return XprType::IsRowMajor ? m_innerStride.value() : m_outerStride.value();
}
PointerType m_data;
const variable_if_dynamic<Index, XprType::InnerStrideAtCompileTime> m_innerStride;
const variable_if_dynamic<Index, XprType::OuterStrideAtCompileTime> m_outerStride;
};
template <typename PlainObjectType, int MapOptions, typename StrideType>
struct evaluator<Map<PlainObjectType, MapOptions, StrideType>>
: public mapbase_evaluator<Map<PlainObjectType, MapOptions, StrideType>, PlainObjectType> {
typedef Map<PlainObjectType, MapOptions, StrideType> XprType;
typedef typename XprType::Scalar Scalar;
// TODO: should check for smaller packet types once we can handle multi-sized packet types
typedef typename packet_traits<Scalar>::type PacketScalar;
enum {
InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
? int(PlainObjectType::InnerStrideAtCompileTime)
: int(StrideType::InnerStrideAtCompileTime),
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
? int(PlainObjectType::OuterStrideAtCompileTime)
: int(StrideType::OuterStrideAtCompileTime),
HasNoInnerStride = InnerStrideAtCompileTime == 1,
HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
HasNoStride = HasNoInnerStride && HasNoOuterStride,
IsDynamicSize = PlainObjectType::SizeAtCompileTime == Dynamic,
PacketAccessMask = bool(HasNoInnerStride) ? ~int(0) : ~int(PacketAccessBit),
LinearAccessMask =
bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime) ? ~int(0) : ~int(LinearAccessBit),
Flags = int(evaluator<PlainObjectType>::Flags) & (LinearAccessMask & PacketAccessMask),
Alignment = int(MapOptions) & int(AlignedMask)
};
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& map) : mapbase_evaluator<XprType, PlainObjectType>(map) {}
};
// -------------------- Ref --------------------
template <typename PlainObjectType, int RefOptions, typename StrideType>
struct evaluator<Ref<PlainObjectType, RefOptions, StrideType>>
: public mapbase_evaluator<Ref<PlainObjectType, RefOptions, StrideType>, PlainObjectType> {
typedef Ref<PlainObjectType, RefOptions, StrideType> XprType;
enum {
Flags = evaluator<Map<PlainObjectType, RefOptions, StrideType>>::Flags,
Alignment = evaluator<Map<PlainObjectType, RefOptions, StrideType>>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& ref)
: mapbase_evaluator<XprType, PlainObjectType>(ref) {}
};
// -------------------- Block --------------------
template <typename ArgType, int BlockRows, int BlockCols, bool InnerPanel,
bool HasDirectAccess = has_direct_access<ArgType>::ret>
struct block_evaluator;
template <typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>>
: block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> {
typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
typedef typename XprType::Scalar Scalar;
// TODO: should check for smaller packet types once we can handle multi-sized packet types
typedef typename packet_traits<Scalar>::type PacketScalar;
enum {
CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
RowsAtCompileTime = traits<XprType>::RowsAtCompileTime,
ColsAtCompileTime = traits<XprType>::ColsAtCompileTime,
MaxRowsAtCompileTime = traits<XprType>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = traits<XprType>::MaxColsAtCompileTime,
ArgTypeIsRowMajor = (int(evaluator<ArgType>::Flags) & RowMajorBit) != 0,
IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1
: (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0
: ArgTypeIsRowMajor,
HasSameStorageOrderAsArgType = (IsRowMajor == ArgTypeIsRowMajor),
InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
InnerStrideAtCompileTime = HasSameStorageOrderAsArgType ? int(inner_stride_at_compile_time<ArgType>::ret)
: int(outer_stride_at_compile_time<ArgType>::ret),
OuterStrideAtCompileTime = HasSameStorageOrderAsArgType ? int(outer_stride_at_compile_time<ArgType>::ret)
: int(inner_stride_at_compile_time<ArgType>::ret),
MaskPacketAccessBit = (InnerStrideAtCompileTime == 1 || HasSameStorageOrderAsArgType) ? PacketAccessBit : 0,
FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 ||
(InnerPanel && (evaluator<ArgType>::Flags & LinearAccessBit)))
? LinearAccessBit
: 0,
FlagsRowMajorBit = XprType::Flags & RowMajorBit,
Flags0 = evaluator<ArgType>::Flags & ((HereditaryBits & ~RowMajorBit) | DirectAccessBit | MaskPacketAccessBit),
Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit,
PacketAlignment = unpacket_traits<PacketScalar>::alignment,
Alignment0 = (InnerPanel && (OuterStrideAtCompileTime != Dynamic) && (OuterStrideAtCompileTime != 0) &&
(((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0))
? int(PacketAlignment)
: 0,
Alignment = plain_enum_min(evaluator<ArgType>::Alignment, Alignment0)
};
typedef block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> block_evaluator_type;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& block) : block_evaluator_type(block) {
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
};
// no direct-access => dispatch to a unary evaluator
template <typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
struct block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel, /*HasDirectAccess*/ false>
: unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>> {
typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit block_evaluator(const XprType& block)
: unary_evaluator<XprType>(block) {}
};
template <typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBased>
: evaluator_base<Block<ArgType, BlockRows, BlockCols, InnerPanel>> {
typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& block)
: m_argImpl(block.nestedExpression()),
m_startRow(block.startRow()),
m_startCol(block.startCol()),
m_linear_offset(ForwardLinearAccess
? (ArgType::IsRowMajor
? block.startRow() * block.nestedExpression().cols() + block.startCol()
: block.startCol() * block.nestedExpression().rows() + block.startRow())
: 0) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum {
RowsAtCompileTime = XprType::RowsAtCompileTime,
ForwardLinearAccess = (InnerPanel || int(XprType::IsRowMajor) == int(ArgType::IsRowMajor)) &&
bool(evaluator<ArgType>::Flags & LinearAccessBit)
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_argImpl.coeff(m_startRow.value() + row, m_startCol.value() + col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return linear_coeff_impl(index, bool_constant<ForwardLinearAccess>());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
return m_argImpl.coeffRef(m_startRow.value() + row, m_startCol.value() + col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return linear_coeffRef_impl(index, bool_constant<ForwardLinearAccess>());
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_argImpl.template packet<LoadMode, PacketType>(m_startRow.value() + row, m_startCol.value() + col);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
if (ForwardLinearAccess)
return m_argImpl.template packet<LoadMode, PacketType>(m_linear_offset.value() + index);
else
return packet<LoadMode, PacketType>(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
return m_argImpl.template writePacket<StoreMode, PacketType>(m_startRow.value() + row, m_startCol.value() + col, x);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
if (ForwardLinearAccess)
return m_argImpl.template writePacket<StoreMode, PacketType>(m_linear_offset.value() + index, x);
else
return writePacket<StoreMode, PacketType>(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0,
x);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_argImpl.template packetSegment<LoadMode, PacketType>(m_startRow.value() + row, m_startCol.value() + col,
begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
if (ForwardLinearAccess)
return m_argImpl.template packetSegment<LoadMode, PacketType>(m_linear_offset.value() + index, begin, count);
else
return packetSegment<LoadMode, PacketType>(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0,
begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
return m_argImpl.template writePacketSegment<StoreMode, PacketType>(m_startRow.value() + row,
m_startCol.value() + col, x, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
if (ForwardLinearAccess)
return m_argImpl.template writePacketSegment<StoreMode, PacketType>(m_linear_offset.value() + index, x, begin,
count);
else
return writePacketSegment<StoreMode, PacketType>(RowsAtCompileTime == 1 ? 0 : index,
RowsAtCompileTime == 1 ? index : 0, x, begin, count);
}
protected:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType
linear_coeff_impl(Index index, internal::true_type /* ForwardLinearAccess */) const {
return m_argImpl.coeff(m_linear_offset.value() + index);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType
linear_coeff_impl(Index index, internal::false_type /* not ForwardLinearAccess */) const {
return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& linear_coeffRef_impl(Index index,
internal::true_type /* ForwardLinearAccess */) {
return m_argImpl.coeffRef(m_linear_offset.value() + index);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& linear_coeffRef_impl(
Index index, internal::false_type /* not ForwardLinearAccess */) {
return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0);
}
evaluator<ArgType> m_argImpl;
const variable_if_dynamic<Index, (ArgType::RowsAtCompileTime == 1 && BlockRows == 1) ? 0 : Dynamic> m_startRow;
const variable_if_dynamic<Index, (ArgType::ColsAtCompileTime == 1 && BlockCols == 1) ? 0 : Dynamic> m_startCol;
const variable_if_dynamic<Index, ForwardLinearAccess ? Dynamic : 0> m_linear_offset;
};
// TODO: This evaluator does not actually use the child evaluator;
// all action is via the data() as returned by the Block expression.
template <typename ArgType, int BlockRows, int BlockCols, bool InnerPanel>
struct block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel, /* HasDirectAccess */ true>
: mapbase_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>,
typename Block<ArgType, BlockRows, BlockCols, InnerPanel>::PlainObject> {
typedef Block<ArgType, BlockRows, BlockCols, InnerPanel> XprType;
typedef typename XprType::Scalar Scalar;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit block_evaluator(const XprType& block)
: mapbase_evaluator<XprType, typename XprType::PlainObject>(block) {
eigen_internal_assert((internal::is_constant_evaluated() ||
(std::uintptr_t(block.data()) % plain_enum_max(1, evaluator<XprType>::Alignment)) == 0) &&
"data is not aligned");
}
};
// -------------------- Select --------------------
// NOTE shall we introduce a ternary_evaluator?
// TODO enable vectorization for Select
template <typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
struct evaluator<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType>>
: evaluator_base<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType>> {
typedef Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> XprType;
enum {
CoeffReadCost = evaluator<ConditionMatrixType>::CoeffReadCost +
plain_enum_max(evaluator<ThenMatrixType>::CoeffReadCost, evaluator<ElseMatrixType>::CoeffReadCost),
Flags = (unsigned int)evaluator<ThenMatrixType>::Flags & evaluator<ElseMatrixType>::Flags & HereditaryBits,
Alignment = plain_enum_min(evaluator<ThenMatrixType>::Alignment, evaluator<ElseMatrixType>::Alignment)
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& select)
: m_conditionImpl(select.conditionMatrix()), m_thenImpl(select.thenMatrix()), m_elseImpl(select.elseMatrix()) {
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
if (m_conditionImpl.coeff(row, col))
return m_thenImpl.coeff(row, col);
else
return m_elseImpl.coeff(row, col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
if (m_conditionImpl.coeff(index))
return m_thenImpl.coeff(index);
else
return m_elseImpl.coeff(index);
}
protected:
evaluator<ConditionMatrixType> m_conditionImpl;
evaluator<ThenMatrixType> m_thenImpl;
evaluator<ElseMatrixType> m_elseImpl;
};
// -------------------- Replicate --------------------
template <typename ArgType, int RowFactor, int ColFactor>
struct unary_evaluator<Replicate<ArgType, RowFactor, ColFactor>>
: evaluator_base<Replicate<ArgType, RowFactor, ColFactor>> {
typedef Replicate<ArgType, RowFactor, ColFactor> XprType;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum { Factor = (RowFactor == Dynamic || ColFactor == Dynamic) ? Dynamic : RowFactor * ColFactor };
typedef typename nested_eval<ArgType, Factor>::type ArgTypeNested;
typedef remove_all_t<ArgTypeNested> ArgTypeNestedCleaned;
enum {
CoeffReadCost = evaluator<ArgTypeNestedCleaned>::CoeffReadCost,
LinearAccessMask = XprType::IsVectorAtCompileTime ? LinearAccessBit : 0,
Flags = (evaluator<ArgTypeNestedCleaned>::Flags & (HereditaryBits | LinearAccessMask) & ~RowMajorBit) |
(traits<XprType>::Flags & RowMajorBit),
Alignment = evaluator<ArgTypeNestedCleaned>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& replicate)
: m_arg(replicate.nestedExpression()),
m_argImpl(m_arg),
m_rows(replicate.nestedExpression().rows()),
m_cols(replicate.nestedExpression().cols()) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
// try to avoid using modulo; this is a pure optimization strategy
const Index actual_row = traits<XprType>::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value();
const Index actual_col = traits<XprType>::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value();
return m_argImpl.coeff(actual_row, actual_col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
// try to avoid using modulo; this is a pure optimization strategy
const Index actual_index = traits<XprType>::RowsAtCompileTime == 1
? (ColFactor == 1 ? index : index % m_cols.value())
: (RowFactor == 1 ? index : index % m_rows.value());
return m_argImpl.coeff(actual_index);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
const Index actual_row = traits<XprType>::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value();
const Index actual_col = traits<XprType>::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value();
return m_argImpl.template packet<LoadMode, PacketType>(actual_row, actual_col);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
const Index actual_index = traits<XprType>::RowsAtCompileTime == 1
? (ColFactor == 1 ? index : index % m_cols.value())
: (RowFactor == 1 ? index : index % m_rows.value());
return m_argImpl.template packet<LoadMode, PacketType>(actual_index);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
const Index actual_row = traits<XprType>::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value();
const Index actual_col = traits<XprType>::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value();
return m_argImpl.template packetSegment<LoadMode, PacketType>(actual_row, actual_col, begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
const Index actual_index = traits<XprType>::RowsAtCompileTime == 1
? (ColFactor == 1 ? index : index % m_cols.value())
: (RowFactor == 1 ? index : index % m_rows.value());
return m_argImpl.template packetSegment<LoadMode, PacketType>(actual_index, begin, count);
}
protected:
const ArgTypeNested m_arg;
evaluator<ArgTypeNestedCleaned> m_argImpl;
const variable_if_dynamic<Index, ArgType::RowsAtCompileTime> m_rows;
const variable_if_dynamic<Index, ArgType::ColsAtCompileTime> m_cols;
};
// -------------------- MatrixWrapper and ArrayWrapper --------------------
//
// evaluator_wrapper_base<T> is a common base class for the
// MatrixWrapper and ArrayWrapper evaluators.
template <typename XprType>
struct evaluator_wrapper_base : evaluator_base<XprType> {
typedef remove_all_t<typename XprType::NestedExpressionType> ArgType;
enum {
CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
Flags = evaluator<ArgType>::Flags,
Alignment = evaluator<ArgType>::Alignment
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator_wrapper_base(const ArgType& arg) : m_argImpl(arg) {}
typedef typename ArgType::Scalar Scalar;
typedef typename ArgType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_argImpl.coeff(row, col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_argImpl.coeff(index); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { return m_argImpl.coeffRef(row, col); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_argImpl.coeffRef(index); }
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
return m_argImpl.template packet<LoadMode, PacketType>(row, col);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
return m_argImpl.template packet<LoadMode, PacketType>(index);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
m_argImpl.template writePacket<StoreMode>(row, col, x);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
m_argImpl.template writePacket<StoreMode>(index, x);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
return m_argImpl.template packetSegment<LoadMode, PacketType>(row, col, begin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
return m_argImpl.template packetSegment<LoadMode, PacketType>(index, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
m_argImpl.template writePacketSegment<StoreMode>(row, col, x, begin, count);
}
template <int StoreMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
m_argImpl.template writePacketSegment<StoreMode>(index, x, begin, count);
}
protected:
evaluator<ArgType> m_argImpl;
};
template <typename TArgType>
struct unary_evaluator<MatrixWrapper<TArgType>> : evaluator_wrapper_base<MatrixWrapper<TArgType>> {
typedef MatrixWrapper<TArgType> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& wrapper)
: evaluator_wrapper_base<MatrixWrapper<TArgType>>(wrapper.nestedExpression()) {}
};
template <typename TArgType>
struct unary_evaluator<ArrayWrapper<TArgType>> : evaluator_wrapper_base<ArrayWrapper<TArgType>> {
typedef ArrayWrapper<TArgType> XprType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& wrapper)
: evaluator_wrapper_base<ArrayWrapper<TArgType>>(wrapper.nestedExpression()) {}
};
// -------------------- Reverse --------------------
// defined in Reverse.h:
template <typename PacketType, bool ReversePacket>
struct reverse_packet_cond;
template <typename ArgType, int Direction>
struct unary_evaluator<Reverse<ArgType, Direction>> : evaluator_base<Reverse<ArgType, Direction>> {
typedef Reverse<ArgType, Direction> XprType;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
enum {
IsRowMajor = XprType::IsRowMajor,
IsColMajor = !IsRowMajor,
ReverseRow = (Direction == Vertical) || (Direction == BothDirections),
ReverseCol = (Direction == Horizontal) || (Direction == BothDirections),
ReversePacket = (Direction == BothDirections) || ((Direction == Vertical) && IsColMajor) ||
((Direction == Horizontal) && IsRowMajor),
CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
// let's enable LinearAccess only with vectorization because of the product overhead
// FIXME enable DirectAccess with negative strides?
Flags0 = evaluator<ArgType>::Flags,
LinearAccess =
((Direction == BothDirections) && (int(Flags0) & PacketAccessBit)) ||
((ReverseRow && XprType::ColsAtCompileTime == 1) || (ReverseCol && XprType::RowsAtCompileTime == 1))
? LinearAccessBit
: 0,
Flags = int(Flags0) & (HereditaryBits | PacketAccessBit | LinearAccess),
Alignment = 0 // FIXME in some rare cases, Alignment could be preserved, like a Vector4f.
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& reverse)
: m_argImpl(reverse.nestedExpression()),
m_rows(ReverseRow ? reverse.nestedExpression().rows() : 1),
m_cols(ReverseCol ? reverse.nestedExpression().cols() : 1) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_argImpl.coeff(ReverseRow ? m_rows.value() - row - 1 : row, ReverseCol ? m_cols.value() - col - 1 : col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_argImpl.coeff(m_rows.value() * m_cols.value() - index - 1);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
return m_argImpl.coeffRef(ReverseRow ? m_rows.value() - row - 1 : row, ReverseCol ? m_cols.value() - col - 1 : col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return m_argImpl.coeffRef(m_rows.value() * m_cols.value() - index - 1);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1;
static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1;
using reverse_packet = reverse_packet_cond<PacketType, ReversePacket>;
Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row;
Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col;
return reverse_packet::run(m_argImpl.template packet<LoadMode, PacketType>(actualRow, actualCol));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize;
return preverse(m_argImpl.template packet<LoadMode, PacketType>(actualIndex));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1;
static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1;
using reverse_packet = reverse_packet_cond<PacketType, ReversePacket>;
Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row;
Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col;
m_argImpl.template writePacket<LoadMode>(actualRow, actualCol, reverse_packet::run(x));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize;
m_argImpl.template writePacket<LoadMode>(actualIndex, preverse(x));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1;
static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1;
using reverse_packet = reverse_packet_cond<PacketType, ReversePacket>;
Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row;
Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col;
Index actualBegin = ReversePacket ? (PacketSize - count - begin) : begin;
return reverse_packet::run(
m_argImpl.template packetSegment<LoadMode, PacketType>(actualRow, actualCol, actualBegin, count));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize;
Index actualBegin = PacketSize - count - begin;
return preverse(m_argImpl.template packetSegment<LoadMode, PacketType>(actualIndex, actualBegin, count));
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin,
Index count) {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1;
static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1;
using reverse_packet = reverse_packet_cond<PacketType, ReversePacket>;
Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row;
Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col;
Index actualBegin = ReversePacket ? (PacketSize - count - begin) : begin;
m_argImpl.template writePacketSegment<LoadMode>(actualRow, actualCol, reverse_packet::run(x), actualBegin, count);
}
template <int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin,
Index count) {
static constexpr int PacketSize = unpacket_traits<PacketType>::size;
Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize;
Index actualBegin = PacketSize - count - begin;
m_argImpl.template writePacketSegment<LoadMode>(actualIndex, preverse(x), actualBegin, count);
}
protected:
evaluator<ArgType> m_argImpl;
// If we do not reverse rows, then we do not need to know the number of rows; same for columns
// Nonetheless, in this case it is important to set to 1 such that the coeff(index) method works fine for vectors.
const variable_if_dynamic<Index, ReverseRow ? ArgType::RowsAtCompileTime : 1> m_rows;
const variable_if_dynamic<Index, ReverseCol ? ArgType::ColsAtCompileTime : 1> m_cols;
};
// -------------------- Diagonal --------------------
template <typename ArgType, int DiagIndex>
struct evaluator<Diagonal<ArgType, DiagIndex>> : evaluator_base<Diagonal<ArgType, DiagIndex>> {
typedef Diagonal<ArgType, DiagIndex> XprType;
enum {
CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
Flags =
(unsigned int)(evaluator<ArgType>::Flags & (HereditaryBits | DirectAccessBit) & ~RowMajorBit) | LinearAccessBit,
Alignment = 0
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& diagonal)
: m_argImpl(diagonal.nestedExpression()), m_index(diagonal.index()) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index) const {
return m_argImpl.coeff(row + rowOffset(), row + colOffset());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
return m_argImpl.coeff(index + rowOffset(), index + colOffset());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index) {
return m_argImpl.coeffRef(row + rowOffset(), row + colOffset());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return m_argImpl.coeffRef(index + rowOffset(), index + colOffset());
}
protected:
evaluator<ArgType> m_argImpl;
const variable_if_dynamicindex<Index, XprType::DiagIndex> m_index;
private:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowOffset() const {
return m_index.value() > 0 ? 0 : -m_index.value();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colOffset() const {
return m_index.value() > 0 ? m_index.value() : 0;
}
};
//----------------------------------------------------------------------
// deprecated code
//----------------------------------------------------------------------
// -------------------- EvalToTemp --------------------
// expression class for evaluating nested expression to a temporary
template <typename ArgType>
class EvalToTemp;
template <typename ArgType>
struct traits<EvalToTemp<ArgType>> : public traits<ArgType> {};
template <typename ArgType>
class EvalToTemp : public dense_xpr_base<EvalToTemp<ArgType>>::type {
public:
typedef typename dense_xpr_base<EvalToTemp>::type Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(EvalToTemp)
explicit EvalToTemp(const ArgType& arg) : m_arg(arg) {}
const ArgType& arg() const { return m_arg; }
constexpr Index rows() const noexcept { return m_arg.rows(); }
constexpr Index cols() const noexcept { return m_arg.cols(); }
private:
const ArgType& m_arg;
};
template <typename ArgType>
struct evaluator<EvalToTemp<ArgType>> : public evaluator<typename ArgType::PlainObject> {
typedef EvalToTemp<ArgType> XprType;
typedef typename ArgType::PlainObject PlainObject;
typedef evaluator<PlainObject> Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : m_result(xpr.arg()) {
internal::construct_at<Base>(this, m_result);
}
// This constructor is used when nesting an EvalTo evaluator in another evaluator
EIGEN_DEVICE_FUNC evaluator(const ArgType& arg) : m_result(arg) { internal::construct_at<Base>(this, m_result); }
protected:
PlainObject m_result;
};
} // namespace internal
} // end namespace Eigen
#endif // EIGEN_COREEVALUATORS_H
eigen-master/Eigen/src/Core/CoreIterators.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_COREITERATORS_H
#define EIGEN_COREITERATORS_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
*/
namespace internal {
template <typename XprType, typename EvaluatorKind>
class inner_iterator_selector;
}
/** \class InnerIterator
* \brief An InnerIterator allows to loop over the element of any matrix expression.
*
* \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is
* constructed.
*
* TODO: add a usage example
*/
template <typename XprType>
class InnerIterator {
protected:
typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
typedef internal::evaluator<XprType> EvaluatorType;
typedef typename internal::traits<XprType>::Scalar Scalar;
public:
/** Construct an iterator over the \a outerId -th row or column of \a xpr */
InnerIterator(const XprType &xpr, const Index &outerId) : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize()) {}
/// \returns the value of the current coefficient.
EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
/** Increment the iterator \c *this to the next non-zero coefficient.
* Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
*/
EIGEN_STRONG_INLINE InnerIterator &operator++() {
m_iter.operator++();
return *this;
}
EIGEN_STRONG_INLINE InnerIterator &operator+=(Index i) {
m_iter.operator+=(i);
return *this;
}
EIGEN_STRONG_INLINE InnerIterator operator+(Index i) {
InnerIterator result(*this);
result += i;
return result;
}
/// \returns the column or row index of the current coefficient.
EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
/// \returns the row index of the current coefficient.
EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
/// \returns the column index of the current coefficient.
EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
/// \returns \c true if the iterator \c *this still references a valid coefficient.
EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
protected:
EvaluatorType m_eval;
IteratorType m_iter;
private:
// If you get here, then you're not using the right InnerIterator type, e.g.:
// SparseMatrix<double,RowMajor> A;
// SparseMatrix<double>::InnerIterator it(A,0);
template <typename T>
InnerIterator(const EigenBase<T> &, Index outer);
};
namespace internal {
// Generic inner iterator implementation for dense objects
template <typename XprType>
class inner_iterator_selector<XprType, IndexBased> {
protected:
typedef evaluator<XprType> EvaluatorType;
typedef typename traits<XprType>::Scalar Scalar;
enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit };
public:
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
: m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize) {}
EIGEN_STRONG_INLINE Scalar value() const {
return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner) : m_eval.coeff(m_inner, m_outer);
}
EIGEN_STRONG_INLINE inner_iterator_selector &operator++() {
m_inner++;
return *this;
}
EIGEN_STRONG_INLINE Index index() const { return m_inner; }
inline Index row() const { return IsRowMajor ? m_outer : index(); }
inline Index col() const { return IsRowMajor ? index() : m_outer; }
EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; }
protected:
const EvaluatorType &m_eval;
Index m_inner;
const Index m_outer;
const Index m_end;
};
// For iterator-based evaluator, inner-iterator is already implemented as
// evaluator<>::InnerIterator
template <typename XprType>
class inner_iterator_selector<XprType, IteratorBased> : public evaluator<XprType>::InnerIterator {
protected:
typedef typename evaluator<XprType>::InnerIterator Base;
typedef evaluator<XprType> EvaluatorType;
public:
EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId,
const Index & /*innerSize*/)
: Base(eval, outerId) {}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_COREITERATORS_H
eigen-master/Eigen/src/Core/CwiseBinaryOp.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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_CWISE_BINARY_OP_H
#define EIGEN_CWISE_BINARY_OP_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename BinaryOp, typename Lhs, typename Rhs>
struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> {
// we must not inherit from traits<Lhs> since it has
// the potential to cause problems with MSVC
typedef remove_all_t<Lhs> Ancestor;
typedef typename traits<Ancestor>::XprKind XprKind;
enum {
RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
};
// even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor),
// we still want to handle the case when the result type is different.
typedef typename result_of<BinaryOp(const typename Lhs::Scalar&, const typename Rhs::Scalar&)>::type Scalar;
typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
BinaryOp>::ret StorageKind;
typedef typename promote_index_type<typename traits<Lhs>::StorageIndex, typename traits<Rhs>::StorageIndex>::type
StorageIndex;
typedef typename Lhs::Nested LhsNested;
typedef typename Rhs::Nested RhsNested;
typedef std::remove_reference_t<LhsNested> LhsNested_;
typedef std::remove_reference_t<RhsNested> RhsNested_;
enum {
Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
LhsNested_::Flags & RowMajorBit, RhsNested_::Flags & RowMajorBit>::value
};
};
} // end namespace internal
template <typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
class CwiseBinaryOpImpl;
/** \class CwiseBinaryOp
* \ingroup Core_Module
*
* \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
*
* \tparam BinaryOp template functor implementing the operator
* \tparam LhsType the type of the left-hand side
* \tparam RhsType the type of the right-hand side
*
* This class represents an expression where a coefficient-wise binary operator is applied to two expressions.
* It is the return type of binary operators, by which we mean only those binary operators where
* both the left-hand side and the right-hand side are Eigen expressions.
* For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
*
* Most of the time, this is the only way that it is used, so you typically don't have to name
* CwiseBinaryOp types explicitly.
*
* \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class
* CwiseNullaryOp
*/
template <typename BinaryOp, typename LhsType, typename RhsType>
class CwiseBinaryOp : public CwiseBinaryOpImpl<BinaryOp, LhsType, RhsType,
typename internal::cwise_promote_storage_type<
typename internal::traits<LhsType>::StorageKind,
typename internal::traits<RhsType>::StorageKind, BinaryOp>::ret>,
internal::no_assignment_operator {
public:
typedef internal::remove_all_t<BinaryOp> Functor;
typedef internal::remove_all_t<LhsType> Lhs;
typedef internal::remove_all_t<RhsType> Rhs;
typedef typename CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
typename internal::traits<Rhs>::StorageKind, BinaryOp>::ret>::Base
Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp, typename Lhs::Scalar, typename Rhs::Scalar)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
typedef typename internal::ref_selector<LhsType>::type LhsNested;
typedef typename internal::ref_selector<RhsType>::type RhsNested;
typedef std::remove_reference_t<LhsNested> LhsNested_;
typedef std::remove_reference_t<RhsNested> RhsNested_;
#if EIGEN_COMP_MSVC
// Required for Visual Studio or the Copy constructor will probably not get inlined!
EIGEN_STRONG_INLINE CwiseBinaryOp(const CwiseBinaryOp<BinaryOp, LhsType, RhsType>&) = default;
#endif
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs,
const BinaryOp& func = BinaryOp())
: m_lhs(aLhs), m_rhs(aRhs), m_functor(func) {
eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept {
// return the fixed size type if available to enable compile time optimizations
return internal::traits<internal::remove_all_t<LhsNested>>::RowsAtCompileTime == Dynamic ? m_rhs.rows()
: m_lhs.rows();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept {
// return the fixed size type if available to enable compile time optimizations
return internal::traits<internal::remove_all_t<LhsNested>>::ColsAtCompileTime == Dynamic ? m_rhs.cols()
: m_lhs.cols();
}
/** \returns the left hand side nested expression */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const LhsNested_& lhs() const { return m_lhs; }
/** \returns the right hand side nested expression */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const RhsNested_& rhs() const { return m_rhs; }
/** \returns the functor representing the binary operation */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; }
protected:
LhsNested m_lhs;
RhsNested m_rhs;
const BinaryOp m_functor;
};
// Generic API dispatcher
template <typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
class CwiseBinaryOpImpl : public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type {
public:
typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type Base;
};
/** replaces \c *this by \c *this - \a other.
*
* \returns a reference to \c *this
*/
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived>& other) {
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
return derived();
}
/** replaces \c *this by \c *this + \a other.
*
* \returns a reference to \c *this
*/
template <typename Derived>
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other) {
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
return derived();
}
} // end namespace Eigen
#endif // EIGEN_CWISE_BINARY_OP_H
eigen-master/Eigen/src/Core/CwiseNullaryOp.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_CWISE_NULLARY_OP_H
#define EIGEN_CWISE_NULLARY_OP_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename NullaryOp, typename PlainObjectType>
struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType> {
enum { Flags = traits<PlainObjectType>::Flags & RowMajorBit };
};
} // namespace internal
/** \class CwiseNullaryOp
* \ingroup Core_Module
*
* \brief Generic expression of a matrix where all coefficients are defined by a functor
*
* \tparam NullaryOp template functor implementing the operator
* \tparam PlainObjectType the underlying plain matrix/array type
*
* This class represents an expression of a generic nullary operator.
* It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() methods,
* and most of the time this is the only way it is used.
*
* However, if you want to write a function returning such an expression, you
* will need to use this class.
*
* The functor NullaryOp must expose one of the following method:
<table class="manual">
<tr ><td>\c operator()() </td><td>if the procedural generation does not depend on the coefficient entries
(e.g., random numbers)</td></tr> <tr class="alt"><td>\c operator()(Index i)</td><td>if the procedural generation makes
sense for vectors only and that it depends on the coefficient index \c i (e.g., linspace) </td></tr> <tr ><td>\c
operator()(Index i,Index j)</td><td>if the procedural generation depends on the matrix coordinates \c i, \c j (e.g.,
to generate a checkerboard with 0 and 1)</td></tr>
</table>
* It is also possible to expose the last two operators if the generation makes sense for matrices but can be optimized
for vectors.
*
* See DenseBase::NullaryExpr(Index,const CustomNullaryOp&) for an example binding
* C++11 random number generators.
*
* A nullary expression can also be used to implement custom sophisticated matrix manipulations
* that cannot be covered by the existing set of natively supported matrix manipulations.
* See this \ref TopicCustomizing_NullaryExpr "page" for some examples and additional explanations
* on the behavior of CwiseNullaryOp.
*
* \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr
*/
template <typename NullaryOp, typename PlainObjectType>
class CwiseNullaryOp : public internal::dense_xpr_base<CwiseNullaryOp<NullaryOp, PlainObjectType> >::type,
internal::no_assignment_operator {
public:
typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
EIGEN_DEVICE_FUNC CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
: m_rows(rows), m_cols(cols), m_functor(func) {
eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && cols >= 0 &&
(ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
}
EIGEN_DEVICE_FUNC CwiseNullaryOp(Index size, const NullaryOp& func = NullaryOp())
: CwiseNullaryOp(RowsAtCompileTime == 1 ? 1 : size, RowsAtCompileTime == 1 ? size : 1, func) {
EIGEN_STATIC_ASSERT(CwiseNullaryOp::IsVectorAtCompileTime, YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows.value(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols.value(); }
/** \returns the functor representing the nullary operation */
EIGEN_DEVICE_FUNC const NullaryOp& functor() const { return m_functor; }
protected:
const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
const NullaryOp m_functor;
};
/** \returns an expression of a matrix defined by a custom functor \a func
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
* instead.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
#ifndef EIGEN_PARSED_BY_DOXYGEN
const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
#else
const CwiseNullaryOp<CustomNullaryOp, PlainObject>
#endif
DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func) {
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(rows, cols, func);
}
/** \returns an expression of a matrix defined by a custom functor \a func
*
* The parameter \a size is the size of the returned vector.
* Must be compatible with this MatrixBase type.
*
* \only_for_vectors
*
* This variant is meant to be used for dynamic-size vector types. For fixed-size types,
* it is redundant to pass \a size as argument, so Zero() should be used
* instead.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* Here is an example with C++11 random generators: \include random_cpp11.cpp
* Output: \verbinclude random_cpp11.out
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
#ifndef EIGEN_PARSED_BY_DOXYGEN
const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
#else
const CwiseNullaryOp<CustomNullaryOp, PlainObject>
#endif
DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
if (RowsAtCompileTime == 1)
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(1, size, func);
else
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(size, 1, func);
}
/** \returns an expression of a matrix defined by a custom functor \a func
*
* This variant is only for fixed-size DenseBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
#ifndef EIGEN_PARSED_BY_DOXYGEN
const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
#else
const CwiseNullaryOp<CustomNullaryOp, PlainObject>
#endif
DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func) {
return CwiseNullaryOp<CustomNullaryOp, PlainObject>(RowsAtCompileTime, ColsAtCompileTime, func);
}
/** \returns an expression of a constant matrix of value \a value
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this DenseBase type.
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
* instead.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value) {
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_constant_op<Scalar>(value));
}
/** \returns an expression of a constant matrix of value \a value
*
* The parameter \a size is the size of the returned vector.
* Must be compatible with this DenseBase type.
*
* \only_for_vectors
*
* This variant is meant to be used for dynamic-size vector types. For fixed-size types,
* it is redundant to pass \a size as argument, so Zero() should be used
* instead.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(Index size, const Scalar& value) {
return DenseBase<Derived>::NullaryExpr(size, internal::scalar_constant_op<Scalar>(value));
}
/** \returns an expression of a constant matrix of value \a value
*
* This variant is only for fixed-size DenseBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
* The template parameter \a CustomNullaryOp is the type of the functor.
*
* \sa class CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(const Scalar& value) {
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return DenseBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime,
internal::scalar_constant_op<Scalar>(value));
}
/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(Index,const Scalar&,const Scalar&)
*
* \only_for_vectors
*
* Example: \include DenseBase_LinSpaced_seq_deprecated.cpp
* Output: \verbinclude DenseBase_LinSpaced_seq_deprecated.out
*
* \sa LinSpaced(Index,const Scalar&, const Scalar&), setLinSpaced(Index,const Scalar&,const Scalar&)
*/
template <typename Derived>
EIGEN_DEPRECATED EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<
Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar>(low, high, size));
}
/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(const Scalar&,const Scalar&)
*
* \sa LinSpaced(const Scalar&, const Scalar&)
*/
template <typename Derived>
EIGEN_DEPRECATED EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<
Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime,
internal::linspaced_op<Scalar>(low, high, Derived::SizeAtCompileTime));
}
/**
* \brief Sets a linearly spaced vector.
*
* The function generates 'size' equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
*
* \only_for_vectors
*
* Example: \include DenseBase_LinSpaced.cpp
* Output: \verbinclude DenseBase_LinSpaced.out
*
* For integer scalar types, an even spacing is possible if and only if the length of the range,
* i.e., \c high-low is a scalar multiple of \c size-1, or if \c size is a scalar multiple of the
* number of values \c high-low+1 (meaning each value can be repeated the same number of time).
* If one of these two considions is not satisfied, then \c high is lowered to the largest value
* satisfying one of this constraint.
* Here are some examples:
*
* Example: \include DenseBase_LinSpacedInt.cpp
* Output: \verbinclude DenseBase_LinSpacedInt.out
*
* \sa setLinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar>(low, high, size));
}
/**
* \copydoc DenseBase::LinSpaced(Index, const DenseBase::Scalar&, const DenseBase::Scalar&)
* Special version for fixed size types which does not require the size parameter.
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime,
internal::linspaced_op<Scalar>(low, high, Derived::SizeAtCompileTime));
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessEqualSpacedReturnType
DenseBase<Derived>::EqualSpaced(Index size, const Scalar& low, const Scalar& step) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(size, internal::equalspaced_op<Scalar>(low, step));
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessEqualSpacedReturnType
DenseBase<Derived>::EqualSpaced(const Scalar& low, const Scalar& step) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::equalspaced_op<Scalar>(low, step));
}
/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
template <typename Derived>
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApproxToConstant(const Scalar& val, const RealScalar& prec) const {
typename internal::nested_eval<Derived, 1>::type self(derived());
for (Index j = 0; j < cols(); ++j)
for (Index i = 0; i < rows(); ++i)
if (!internal::isApprox(self.coeff(i, j), val, prec)) return false;
return true;
}
/** This is just an alias for isApproxToConstant().
*
* \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
template <typename Derived>
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isConstant(const Scalar& val, const RealScalar& prec) const {
return isApproxToConstant(val, prec);
}
/** Alias for setConstant(): sets all coefficients in this expression to \a val.
*
* \sa setConstant(), Constant(), class CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val) {
setConstant(val);
}
/** Sets all coefficients in this expression to value \a val.
*
* \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(),
* Constant(), class CwiseNullaryOp, setZero(), setOnes()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val) {
internal::eigen_fill_impl<Derived>::run(derived(), val);
return derived();
}
/** Resizes to the given \a size, and sets all coefficients in this expression to the given value \a val.
*
* \only_for_vectors
*
* Example: \include Matrix_setConstant_int.cpp
* Output: \verbinclude Matrix_setConstant_int.out
*
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp,
* MatrixBase::Constant(const Scalar&)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val) {
resize(size);
return setConstant(val);
}
/** Resizes to the given size, and sets all coefficients in this expression to the given value \a val.
*
* \param rows the new number of rows
* \param cols the new number of columns
* \param val the value to which all coefficients are set
*
* Example: \include Matrix_setConstant_int_int.cpp
* Output: \verbinclude Matrix_setConstant_int_int.out
*
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp,
* MatrixBase::Constant(const Scalar&)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setConstant(Index rows, Index cols,
const Scalar& val) {
resize(rows, cols);
return setConstant(val);
}
/** Resizes to the given size, changing only the number of columns, and sets all
* coefficients in this expression to the given value \a val. For the parameter
* of type NoChange_t, just pass the special value \c NoChange.
*
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp,
* MatrixBase::Constant(const Scalar&)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setConstant(NoChange_t, Index cols,
const Scalar& val) {
return setConstant(rows(), cols, val);
}
/** Resizes to the given size, changing only the number of rows, and sets all
* coefficients in this expression to the given value \a val. For the parameter
* of type NoChange_t, just pass the special value \c NoChange.
*
* \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp,
* MatrixBase::Constant(const Scalar&)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setConstant(Index rows, NoChange_t,
const Scalar& val) {
return setConstant(rows, cols(), val);
}
/**
* \brief Sets a linearly spaced vector.
*
* The function generates 'size' equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
*
* \only_for_vectors
*
* Example: \include DenseBase_setLinSpaced.cpp
* Output: \verbinclude DenseBase_setLinSpaced.out
*
* For integer scalar types, do not miss the explanations on the definition
* of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
*
* \sa LinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low,
const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar>(low, high, newSize));
}
/**
* \brief Sets a linearly spaced vector.
*
* The function fills \c *this with equally spaced values in the closed interval [low,high].
* When size is set to 1, a vector of length 1 containing 'high' is returned.
*
* \only_for_vectors
*
* For integer scalar types, do not miss the explanations on the definition
* of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink.
*
* \sa LinSpaced(Index,const Scalar&,const Scalar&), setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return setLinSpaced(size(), low, high);
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setEqualSpaced(Index newSize, const Scalar& low,
const Scalar& step) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return derived() = Derived::NullaryExpr(newSize, internal::equalspaced_op<Scalar>(low, step));
}
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setEqualSpaced(const Scalar& low,
const Scalar& step) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return setEqualSpaced(size(), low, step);
}
// zero:
/** \returns an expression of a zero matrix.
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
* instead.
*
* Example: \include MatrixBase_zero_int_int.cpp
* Output: \verbinclude MatrixBase_zero_int_int.out
*
* \sa Zero(), Zero(Index)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ZeroReturnType DenseBase<Derived>::Zero(
Index rows, Index cols) {
return ZeroReturnType(rows, cols);
}
/** \returns an expression of a zero vector.
*
* The parameter \a size is the size of the returned vector.
* Must be compatible with this MatrixBase type.
*
* \only_for_vectors
*
* This variant is meant to be used for dynamic-size vector types. For fixed-size types,
* it is redundant to pass \a size as argument, so Zero() should be used
* instead.
*
* Example: \include MatrixBase_zero_int.cpp
* Output: \verbinclude MatrixBase_zero_int.out
*
* \sa Zero(), Zero(Index,Index)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ZeroReturnType DenseBase<Derived>::Zero(
Index size) {
return ZeroReturnType(size);
}
/** \returns an expression of a fixed-size zero matrix or vector.
*
* This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
* Example: \include MatrixBase_zero.cpp
* Output: \verbinclude MatrixBase_zero.out
*
* \sa Zero(Index), Zero(Index,Index)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ZeroReturnType DenseBase<Derived>::Zero() {
return ZeroReturnType(RowsAtCompileTime, ColsAtCompileTime);
}
/** \returns true if *this is approximately equal to the zero matrix,
* within the precision given by \a prec.
*
* Example: \include MatrixBase_isZero.cpp
* Output: \verbinclude MatrixBase_isZero.out
*
* \sa class CwiseNullaryOp, Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isZero(const RealScalar& prec) const {
typename internal::nested_eval<Derived, 1>::type self(derived());
for (Index j = 0; j < cols(); ++j)
for (Index i = 0; i < rows(); ++i)
if (!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<Scalar>(1), prec)) return false;
return true;
}
/** Sets all coefficients in this expression to zero.
*
* Example: \include MatrixBase_setZero.cpp
* Output: \verbinclude MatrixBase_setZero.out
*
* \sa class CwiseNullaryOp, Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero() {
internal::eigen_zero_impl<Derived>::run(derived());
return derived();
}
/** Resizes to the given \a size, and sets all coefficients in this expression to zero.
*
* \only_for_vectors
*
* Example: \include Matrix_setZero_int.cpp
* Output: \verbinclude Matrix_setZero_int.out
*
* \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setZero(Index newSize) {
resize(newSize);
return setZero();
}
/** Resizes to the given size, and sets all coefficients in this expression to zero.
*
* \param rows the new number of rows
* \param cols the new number of columns
*
* Example: \include Matrix_setZero_int_int.cpp
* Output: \verbinclude Matrix_setZero_int_int.out
*
* \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setZero(Index rows, Index cols) {
resize(rows, cols);
return setZero();
}
/** Resizes to the given size, changing only the number of columns, and sets all
* coefficients in this expression to zero. For the parameter of type NoChange_t,
* just pass the special value \c NoChange.
*
* \sa DenseBase::setZero(), setZero(Index), setZero(Index, Index), setZero(Index, NoChange_t), class CwiseNullaryOp,
* DenseBase::Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setZero(NoChange_t, Index cols) {
return setZero(rows(), cols);
}
/** Resizes to the given size, changing only the number of rows, and sets all
* coefficients in this expression to zero. For the parameter of type NoChange_t,
* just pass the special value \c NoChange.
*
* \sa DenseBase::setZero(), setZero(Index), setZero(Index, Index), setZero(NoChange_t, Index), class CwiseNullaryOp,
* DenseBase::Zero()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setZero(Index rows, NoChange_t) {
return setZero(rows, cols());
}
// ones:
/** \returns an expression of a matrix where all coefficients equal one.
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used
* instead.
*
* Example: \include MatrixBase_ones_int_int.cpp
* Output: \verbinclude MatrixBase_ones_int_int.out
*
* \sa Ones(), Ones(Index), isOnes(), class Ones
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType DenseBase<Derived>::Ones(
Index rows, Index cols) {
return Constant(rows, cols, Scalar(1));
}
/** \returns an expression of a vector where all coefficients equal one.
*
* The parameter \a newSize is the size of the returned vector.
* Must be compatible with this MatrixBase type.
*
* \only_for_vectors
*
* This variant is meant to be used for dynamic-size vector types. For fixed-size types,
* it is redundant to pass \a size as argument, so Ones() should be used
* instead.
*
* Example: \include MatrixBase_ones_int.cpp
* Output: \verbinclude MatrixBase_ones_int.out
*
* \sa Ones(), Ones(Index,Index), isOnes(), class Ones
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType DenseBase<Derived>::Ones(
Index newSize) {
return Constant(newSize, Scalar(1));
}
/** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
*
* This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
* Example: \include MatrixBase_ones.cpp
* Output: \verbinclude MatrixBase_ones.out
*
* \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType DenseBase<Derived>::Ones() {
return Constant(Scalar(1));
}
/** \returns true if *this is approximately equal to the matrix where all coefficients
* are equal to 1, within the precision given by \a prec.
*
* Example: \include MatrixBase_isOnes.cpp
* Output: \verbinclude MatrixBase_isOnes.out
*
* \sa class CwiseNullaryOp, Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isOnes(const RealScalar& prec) const {
return isApproxToConstant(Scalar(1), prec);
}
/** Sets all coefficients in this expression to one.
*
* Example: \include MatrixBase_setOnes.cpp
* Output: \verbinclude MatrixBase_setOnes.out
*
* \sa class CwiseNullaryOp, Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes() {
return setConstant(Scalar(1));
}
/** Resizes to the given \a newSize, and sets all coefficients in this expression to one.
*
* \only_for_vectors
*
* Example: \include Matrix_setOnes_int.cpp
* Output: \verbinclude Matrix_setOnes_int.out
*
* \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setOnes(Index newSize) {
resize(newSize);
return setConstant(Scalar(1));
}
/** Resizes to the given size, and sets all coefficients in this expression to one.
*
* \param rows the new number of rows
* \param cols the new number of columns
*
* Example: \include Matrix_setOnes_int_int.cpp
* Output: \verbinclude Matrix_setOnes_int_int.out
*
* \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setOnes(Index rows, Index cols) {
resize(rows, cols);
return setConstant(Scalar(1));
}
/** Resizes to the given size, changing only the number of rows, and sets all
* coefficients in this expression to one. For the parameter of type NoChange_t,
* just pass the special value \c NoChange.
*
* \sa MatrixBase::setOnes(), setOnes(Index), setOnes(Index, Index), setOnes(NoChange_t, Index), class CwiseNullaryOp,
* MatrixBase::Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setOnes(Index rows, NoChange_t) {
return setOnes(rows, cols());
}
/** Resizes to the given size, changing only the number of columns, and sets all
* coefficients in this expression to one. For the parameter of type NoChange_t,
* just pass the special value \c NoChange.
*
* \sa MatrixBase::setOnes(), setOnes(Index), setOnes(Index, Index), setOnes(Index, NoChange_t) class CwiseNullaryOp,
* MatrixBase::Ones()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase<Derived>::setOnes(NoChange_t, Index cols) {
return setOnes(rows(), cols);
}
// Identity:
/** \returns an expression of the identity matrix (not necessarily square).
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used
* instead.
*
* Example: \include MatrixBase_identity_int_int.cpp
* Output: \verbinclude MatrixBase_identity_int_int.out
*
* \sa Identity(), setIdentity(), isIdentity()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
MatrixBase<Derived>::Identity(Index rows, Index cols) {
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
}
/** \returns an expression of the identity matrix (not necessarily square).
*
* This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variant taking size arguments.
*
* Example: \include MatrixBase_identity.cpp
* Output: \verbinclude MatrixBase_identity.out
*
* \sa Identity(Index,Index), setIdentity(), isIdentity()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
MatrixBase<Derived>::Identity() {
EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
return MatrixBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_identity_op<Scalar>());
}
/** \returns true if *this is approximately equal to the identity matrix
* (not necessarily square),
* within the precision given by \a prec.
*
* Example: \include MatrixBase_isIdentity.cpp
* Output: \verbinclude MatrixBase_isIdentity.out
*
* \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity()
*/
template <typename Derived>
bool MatrixBase<Derived>::isIdentity(const RealScalar& prec) const {
typename internal::nested_eval<Derived, 1>::type self(derived());
for (Index j = 0; j < cols(); ++j) {
for (Index i = 0; i < rows(); ++i) {
if (i == j) {
if (!internal::isApprox(self.coeff(i, j), static_cast<Scalar>(1), prec)) return false;
} else {
if (!internal::isMuchSmallerThan(self.coeff(i, j), static_cast<RealScalar>(1), prec)) return false;
}
}
}
return true;
}
namespace internal {
template <typename Derived, bool Big = (Derived::SizeAtCompileTime >= 16)>
struct setIdentity_impl {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Derived& run(Derived& m) {
return m = Derived::Identity(m.rows(), m.cols());
}
};
template <typename Derived>
struct setIdentity_impl<Derived, true> {
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Derived& run(Derived& m) {
m.setZero();
const Index size = numext::mini(m.rows(), m.cols());
for (Index i = 0; i < size; ++i) m.coeffRef(i, i) = typename Derived::Scalar(1);
return m;
}
};
} // end namespace internal
/** Writes the identity expression (not necessarily square) into *this.
*
* Example: \include MatrixBase_setIdentity.cpp
* Output: \verbinclude MatrixBase_setIdentity.out
*
* \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity() {
return internal::setIdentity_impl<Derived>::run(derived());
}
/** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
*
* \param rows the new number of rows
* \param cols the new number of columns
*
* Example: \include Matrix_setIdentity_int_int.cpp
* Output: \verbinclude Matrix_setIdentity_int_int.out
*
* \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols) {
derived().resize(rows, cols);
return setIdentity();
}
/** \returns an expression of the i-th unit (basis) vector.
*
* \only_for_vectors
*
* \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(
Index newSize, Index i) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return BasisReturnType(SquareMatrixType::Identity(newSize, newSize), i);
}
/** \returns an expression of the i-th unit (basis) vector.
*
* \only_for_vectors
*
* This variant is for fixed-size vector only.
*
* \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(
Index i) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
return BasisReturnType(SquareMatrixType::Identity(), i);
}
/** \returns an expression of the X axis unit vector (1{,0}^*)
*
* \only_for_vectors
*
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(),
* MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX() {
return Derived::Unit(0);
}
/** \returns an expression of the Y axis unit vector (0,1{,0}^*)
*
* \only_for_vectors
*
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(),
* MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY() {
return Derived::Unit(1);
}
/** \returns an expression of the Z axis unit vector (0,0,1{,0}^*)
*
* \only_for_vectors
*
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(),
* MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ() {
return Derived::Unit(2);
}
/** \returns an expression of the W axis unit vector (0,0,0,1)
*
* \only_for_vectors
*
* \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(),
* MatrixBase::UnitW()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW() {
return Derived::Unit(3);
}
/** \brief Set the coefficients of \c *this to the i-th unit (basis) vector
*
* \param i index of the unique coefficient to be set to 1
*
* \only_for_vectors
*
* \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Unit(Index,Index)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setUnit(Index i) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
eigen_assert(i < size());
derived().setZero();
derived().coeffRef(i) = Scalar(1);
return derived();
}
/** \brief Resizes to the given \a newSize, and writes the i-th unit (basis) vector into *this.
*
* \param newSize the new size of the vector
* \param i index of the unique coefficient to be set to 1
*
* \only_for_vectors
*
* \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Unit(Index,Index)
*/
template <typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setUnit(Index newSize, Index i) {
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived);
eigen_assert(i < newSize);
derived().resize(newSize);
return setUnit(i);
}
} // end namespace Eigen
#endif // EIGEN_CWISE_NULLARY_OP_H
eigen-master/Eigen/src/Core/CwiseTernaryOp.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
//
// 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_CWISE_TERNARY_OP_H
#define EIGEN_CWISE_TERNARY_OP_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> {
// we must not inherit from traits<Arg1> since it has
// the potential to cause problems with MSVC
typedef remove_all_t<Arg1> Ancestor;
typedef typename traits<Ancestor>::XprKind XprKind;
enum {
RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
};
// even though we require Arg1, Arg2, and Arg3 to have the same scalar type
// (see CwiseTernaryOp constructor),
// we still want to handle the case when the result type is different.
typedef typename result_of<TernaryOp(const typename Arg1::Scalar&, const typename Arg2::Scalar&,
const typename Arg3::Scalar&)>::type Scalar;
typedef typename internal::traits<Arg1>::StorageKind StorageKind;
typedef typename internal::traits<Arg1>::StorageIndex StorageIndex;
typedef typename Arg1::Nested Arg1Nested;
typedef typename Arg2::Nested Arg2Nested;
typedef typename Arg3::Nested Arg3Nested;
typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
enum { Flags = Arg1Nested_::Flags & RowMajorBit };
};
} // end namespace internal
template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
class CwiseTernaryOpImpl;
/** \class CwiseTernaryOp
* \ingroup Core_Module
*
* \brief Generic expression where a coefficient-wise ternary operator is
* applied to two expressions
*
* \tparam TernaryOp template functor implementing the operator
* \tparam Arg1Type the type of the first argument
* \tparam Arg2Type the type of the second argument
* \tparam Arg3Type the type of the third argument
*
* This class represents an expression where a coefficient-wise ternary
* operator is applied to three expressions.
* It is the return type of ternary operators, by which we mean only those
* ternary operators where
* all three arguments are Eigen expressions.
* For example, the return type of betainc(matrix1, matrix2, matrix3) is a
* CwiseTernaryOp.
*
* Most of the time, this is the only way that it is used, so you typically
* don't have to name
* CwiseTernaryOp types explicitly.
*
* \sa MatrixBase::ternaryExpr(const MatrixBase<Argument2> &, const
* MatrixBase<Argument3> &, const CustomTernaryOp &) const, class CwiseBinaryOp,
* class CwiseUnaryOp, class CwiseNullaryOp
*/
template <typename TernaryOp, typename Arg1Type, typename Arg2Type, typename Arg3Type>
class CwiseTernaryOp : public CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
typename internal::traits<Arg1Type>::StorageKind>,
internal::no_assignment_operator {
public:
typedef internal::remove_all_t<Arg1Type> Arg1;
typedef internal::remove_all_t<Arg2Type> Arg2;
typedef internal::remove_all_t<Arg3Type> Arg3;
// require the sizes to match
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
// The index types should match
EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
typename internal::traits<Arg2Type>::StorageKind>::value),
STORAGE_KIND_MUST_MATCH)
EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
typename internal::traits<Arg3Type>::StorageKind>::value),
STORAGE_KIND_MUST_MATCH)
typedef typename CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
typename internal::traits<Arg1Type>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp)
typedef typename internal::ref_selector<Arg1Type>::type Arg1Nested;
typedef typename internal::ref_selector<Arg2Type>::type Arg2Nested;
typedef typename internal::ref_selector<Arg3Type>::type Arg3Nested;
typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2, const Arg3& a3,
const TernaryOp& func = TernaryOp())
: m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) {
eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() && a1.rows() == a3.rows() && a1.cols() == a3.cols());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const {
// return the fixed size type if available to enable compile time
// optimizations
if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
internal::traits<internal::remove_all_t<Arg2Nested>>::RowsAtCompileTime == Dynamic)
return m_arg3.rows();
else if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
internal::traits<internal::remove_all_t<Arg3Nested>>::RowsAtCompileTime == Dynamic)
return m_arg2.rows();
else
return m_arg1.rows();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const {
// return the fixed size type if available to enable compile time
// optimizations
if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
internal::traits<internal::remove_all_t<Arg2Nested>>::ColsAtCompileTime == Dynamic)
return m_arg3.cols();
else if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
internal::traits<internal::remove_all_t<Arg3Nested>>::ColsAtCompileTime == Dynamic)
return m_arg2.cols();
else
return m_arg1.cols();
}
/** \returns the first argument nested expression */
EIGEN_DEVICE_FUNC const Arg1Nested_& arg1() const { return m_arg1; }
/** \returns the first argument nested expression */
EIGEN_DEVICE_FUNC const Arg2Nested_& arg2() const { return m_arg2; }
/** \returns the third argument nested expression */
EIGEN_DEVICE_FUNC const Arg3Nested_& arg3() const { return m_arg3; }
/** \returns the functor representing the ternary operation */
EIGEN_DEVICE_FUNC const TernaryOp& functor() const { return m_functor; }
protected:
Arg1Nested m_arg1;
Arg2Nested m_arg2;
Arg3Nested m_arg3;
const TernaryOp m_functor;
};
// Generic API dispatcher
template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
class CwiseTernaryOpImpl : public internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type {
public:
typedef typename internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type Base;
};
} // end namespace Eigen
#endif // EIGEN_CWISE_TERNARY_OP_H
eigen-master/Eigen/src/Core/CwiseUnaryOp.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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_CWISE_UNARY_OP_H
#define EIGEN_CWISE_UNARY_OP_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename UnaryOp, typename XprType>
struct traits<CwiseUnaryOp<UnaryOp, XprType> > : traits<XprType> {
typedef typename result_of<UnaryOp(const typename XprType::Scalar&)>::type Scalar;
typedef typename XprType::Nested XprTypeNested;
typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
enum { Flags = XprTypeNested_::Flags & RowMajorBit };
};
} // namespace internal
template <typename UnaryOp, typename XprType, typename StorageKind>
class CwiseUnaryOpImpl;
/** \class CwiseUnaryOp
* \ingroup Core_Module
*
* \brief Generic expression where a coefficient-wise unary operator is applied to an expression
*
* \tparam UnaryOp template functor implementing the operator
* \tparam XprType the type of the expression to which we are applying the unary operator
*
* This class represents an expression where a unary operator is applied to an expression.
* It is the return type of all operations taking exactly 1 input expression, regardless of the
* presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
* is considered unary, because only the right-hand side is an expression, and its
* return type is a specialization of CwiseUnaryOp.
*
* Most of the time, this is the only way that it is used, so you typically don't have to name
* CwiseUnaryOp types explicitly.
*
* \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
*/
template <typename UnaryOp, typename XprType>
class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>,
internal::no_assignment_operator {
public:
typedef typename CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
typedef typename internal::ref_selector<XprType>::type XprTypeNested;
typedef internal::remove_all_t<XprType> NestedExpression;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
: m_xpr(xpr), m_functor(func) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_xpr.cols(); }
/** \returns the functor representing the unary operation */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& functor() const { return m_functor; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const {
return m_xpr;
}
/** \returns the nested expression */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE internal::remove_all_t<XprTypeNested>& nestedExpression() { return m_xpr; }
protected:
XprTypeNested m_xpr;
const UnaryOp m_functor;
};
// Generic API dispatcher
template <typename UnaryOp, typename XprType, typename StorageKind>
class CwiseUnaryOpImpl : public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type {
public:
typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
};
} // end namespace Eigen
#endif // EIGEN_CWISE_UNARY_OP_H
eigen-master/Eigen/src/Core/CwiseUnaryView.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_CWISE_UNARY_VIEW_H
#define EIGEN_CWISE_UNARY_VIEW_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename ViewOp, typename MatrixType, typename StrideType>
struct traits<CwiseUnaryView<ViewOp, MatrixType, StrideType> > : traits<MatrixType> {
typedef typename result_of<ViewOp(typename traits<MatrixType>::Scalar&)>::type1 ScalarRef;
static_assert(std::is_reference<ScalarRef>::value, "Views must return a reference type.");
typedef remove_all_t<ScalarRef> Scalar;
typedef typename MatrixType::Nested MatrixTypeNested;
typedef remove_all_t<MatrixTypeNested> MatrixTypeNested_;
enum {
FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
Flags =
traits<MatrixTypeNested_>::Flags &
(RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions
MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret,
// need to cast the sizeof's from size_t to int explicitly, otherwise:
// "error: no integral type can represent all of the enumerator values
InnerStrideAtCompileTime =
StrideType::InnerStrideAtCompileTime == 0
? (MatrixTypeInnerStride == Dynamic
? int(Dynamic)
: int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
: int(StrideType::InnerStrideAtCompileTime),
OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
? (outer_stride_at_compile_time<MatrixType>::ret == Dynamic
? int(Dynamic)
: outer_stride_at_compile_time<MatrixType>::ret *
int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
: int(StrideType::OuterStrideAtCompileTime)
};
};
// Generic API dispatcher
template <typename ViewOp, typename XprType, typename StrideType, typename StorageKind,
bool Mutable = !std::is_const<XprType>::value>
class CwiseUnaryViewImpl : public generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type {
public:
typedef typename generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type Base;
};
template <typename ViewOp, typename MatrixType, typename StrideType>
class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false>
: public dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type {
public:
typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
typedef typename dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeffRef(0)); }
EIGEN_DEVICE_FUNC constexpr Index innerStride() const {
return StrideType::InnerStrideAtCompileTime != 0 ? int(StrideType::InnerStrideAtCompileTime)
: derived().nestedExpression().innerStride() *
sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
}
EIGEN_DEVICE_FUNC constexpr Index outerStride() const {
return StrideType::OuterStrideAtCompileTime != 0 ? int(StrideType::OuterStrideAtCompileTime)
: derived().nestedExpression().outerStride() *
sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
}
protected:
EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
// Allow const access to coeffRef for the case of direct access being enabled.
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const {
return internal::evaluator<Derived>(derived()).coeffRef(index);
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const {
return internal::evaluator<Derived>(derived()).coeffRef(row, col);
}
};
template <typename ViewOp, typename MatrixType, typename StrideType>
class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, true>
: public CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> {
public:
typedef CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> Base;
typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
using Base::data;
EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
return internal::evaluator<Derived>(derived()).coeffRef(row, col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return internal::evaluator<Derived>(derived()).coeffRef(index);
}
protected:
EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
};
} // namespace internal
/** \class CwiseUnaryView
* \ingroup Core_Module
*
* \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
*
* \tparam ViewOp template functor implementing the view
* \tparam MatrixType the type of the matrix we are applying the unary operator
*
* This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
* It is the return type of real() and imag(), and most of the time this is the only way it is used.
*
* \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
*/
template <typename ViewOp, typename MatrixType, typename StrideType>
class CwiseUnaryView : public internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
typename internal::traits<MatrixType>::StorageKind> {
public:
typedef typename internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
typename internal::traits<MatrixType>::StorageKind>::Base Base;
EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
typedef internal::remove_all_t<MatrixType> NestedExpression;
explicit EIGEN_DEVICE_FUNC inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
: m_matrix(mat), m_functor(func) {}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_matrix.rows(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_matrix.cols(); }
/** \returns the functor representing unary operation */
EIGEN_DEVICE_FUNC const ViewOp& functor() const { return m_functor; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC const internal::remove_all_t<MatrixTypeNested>& nestedExpression() const { return m_matrix; }
/** \returns the nested expression */
EIGEN_DEVICE_FUNC std::remove_reference_t<MatrixTypeNested>& nestedExpression() { return m_matrix; }
protected:
MatrixTypeNested m_matrix;
ViewOp m_functor;
};
} // namespace Eigen
#endif // EIGEN_CWISE_UNARY_VIEW_H
eigen-master/Eigen/src/Core/DenseBase.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_DENSEBASE_H
#define EIGEN_DENSEBASE_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
// The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned, THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE)
/** \class DenseBase
* \ingroup Core_Module
*
* \brief Base class for all dense matrices, vectors, and arrays
*
* This class is the base that is inherited by all dense objects (matrix, vector, arrays,
* and related expression types). The common Eigen API for dense objects is contained in this class.
*
* \tparam Derived is the derived type, e.g., a matrix type or an expression.
*
* This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
*
* \sa \blank \ref TopicClassHierarchy
*/
template <typename Derived>
class DenseBase
#ifndef EIGEN_PARSED_BY_DOXYGEN
: public DenseCoeffsBase<Derived, internal::accessors_level<Derived>::value>
#else
: public DenseCoeffsBase<Derived, DirectWriteAccessors>
#endif // not EIGEN_PARSED_BY_DOXYGEN
{
public:
/** Inner iterator type to iterate over the coefficients of a row or column.
* \sa class InnerIterator
*/
typedef Eigen::InnerIterator<Derived> InnerIterator;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
/**
* \brief The type used to store indices
* \details This typedef is relevant for types that store multiple indices such as
* PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
* \sa \blank \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
*/
typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
typedef typename internal::traits<Derived>::Scalar Scalar;
/** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
*
* It is an alias for the Scalar type */
typedef Scalar value_type;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef DenseCoeffsBase<Derived, internal::accessors_level<Derived>::value> Base;
using Base::coeff;
using Base::coeffByOuterInner;
using Base::colIndexByOuterInner;
using Base::cols;
using Base::const_cast_derived;
using Base::derived;
using Base::rowIndexByOuterInner;
using Base::rows;
using Base::size;
using Base::operator();
using Base::operator[];
using Base::colStride;
using Base::innerStride;
using Base::outerStride;
using Base::rowStride;
using Base::stride;
using Base::w;
using Base::x;
using Base::y;
using Base::z;
typedef typename Base::CoeffReturnType CoeffReturnType;
enum {
RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
/**< The number of rows at compile-time. This is just a copy of the value provided
* by the \a Derived type. If a value is not known at compile-time,
* it is set to the \a Dynamic constant.
* \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */
ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
/**< The number of columns at compile-time. This is just a copy of the value provided
* by the \a Derived type. If a value is not known at compile-time,
* it is set to the \a Dynamic constant.
* \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
SizeAtCompileTime = (internal::size_of_xpr_at_compile_time<Derived>::ret),
/**< This is equal to the number of coefficients, i.e. the number of
* rows times the number of columns, or to \a Dynamic if this is not
* known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
/**< This value is equal to the maximum possible number of rows that this expression
* might have. If this expression might have an arbitrarily high number of rows,
* this value is set to \a Dynamic.
*
* This value is useful to know when evaluating an expression, in order to determine
* whether it is possible to avoid doing a dynamic memory allocation.
*
* \sa RowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime
*/
MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
/**< This value is equal to the maximum possible number of columns that this expression
* might have. If this expression might have an arbitrarily high number of columns,
* this value is set to \a Dynamic.
*
* This value is useful to know when evaluating an expression, in order to determine
* whether it is possible to avoid doing a dynamic memory allocation.
*
* \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime
*/
MaxSizeAtCompileTime = internal::size_at_compile_time(internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime),
/**< This value is equal to the maximum possible number of coefficients that this expression
* might have. If this expression might have an arbitrarily high number of coefficients,
* this value is set to \a Dynamic.
*
* This value is useful to know when evaluating an expression, in order to determine
* whether it is possible to avoid doing a dynamic memory allocation.
*
* \sa SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime
*/
IsVectorAtCompileTime =
internal::traits<Derived>::RowsAtCompileTime == 1 || internal::traits<Derived>::ColsAtCompileTime == 1,
/**< This is set to true if either the number of rows or the number of
* columns is known at compile-time to be equal to 1. Indeed, in that case,
* we are dealing with a column-vector (if there is only one column) or with
* a row-vector (if there is only one row). */
NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0
: bool(IsVectorAtCompileTime) ? 1
: 2,
/**< This value is equal to Tensor::NumDimensions, i.e. 0 for scalars, 1 for vectors,
* and 2 for matrices.
*/
Flags = internal::traits<Derived>::Flags,
/**< This stores expression \ref flags flags which may or may not be inherited by new expressions
* constructed from this one. See the \ref flags "list of flags".
*/
IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
: int(IsRowMajor) ? int(ColsAtCompileTime)
: int(RowsAtCompileTime),
InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
};
typedef typename internal::find_best_packet<Scalar, SizeAtCompileTime>::type PacketScalar;
enum { IsPlainObjectBase = 0 };
/** The plain matrix type corresponding to this expression.
* \sa PlainObject */
typedef Matrix<typename internal::traits<Derived>::Scalar, internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags & RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime, internal::traits<Derived>::MaxColsAtCompileTime>
PlainMatrix;
/** The plain array type corresponding to this expression.
* \sa PlainObject */
typedef Array<typename internal::traits<Derived>::Scalar, internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime,
AutoAlign | (internal::traits<Derived>::Flags & RowMajorBit ? RowMajor : ColMajor),
internal::traits<Derived>::MaxRowsAtCompileTime, internal::traits<Derived>::MaxColsAtCompileTime>
PlainArray;
/** \brief The plain matrix or array type corresponding to this expression.
*
* This is not necessarily exactly the return type of eval(). In the case of plain matrices,
* the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed
* that the return type of eval() is either PlainObject or const PlainObject&.
*/
typedef std::conditional_t<internal::is_same<typename internal::traits<Derived>::XprKind, MatrixXpr>::value,
PlainMatrix, PlainArray>
PlainObject;
/** \returns the outer size.
*
* \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
* with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a
* column-major matrix, and the number of rows for a row-major matrix. */
EIGEN_DEVICE_FUNC constexpr Index outerSize() const {
return IsVectorAtCompileTime ? 1 : int(IsRowMajor) ? this->rows() : this->cols();
}
/** \returns the inner size.
*
* \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
* with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a
* column-major matrix, and the number of columns for a row-major matrix. */
EIGEN_DEVICE_FUNC constexpr Index innerSize() const {
return IsVectorAtCompileTime ? this->size() : int(IsRowMajor) ? this->cols() : this->rows();
}
/** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and
* does nothing else.
*/
EIGEN_DEVICE_FUNC void resize(Index newSize) {
EIGEN_ONLY_USED_FOR_DEBUG(newSize);
eigen_assert(newSize == this->size() && "DenseBase::resize() does not actually allow to resize.");
}
/** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
* Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and
* does nothing else.
*/
EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) {
EIGEN_ONLY_USED_FOR_DEBUG(rows);
EIGEN_ONLY_USED_FOR_DEBUG(cols);
eigen_assert(rows == this->rows() && cols == this->cols() &&
"DenseBase::resize() does not actually allow to resize.");
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
/** \internal Represents a matrix with all coefficients equal to one another*/
typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> ConstantReturnType;
/** \internal Represents a matrix with all coefficients equal to zero*/
typedef CwiseNullaryOp<internal::scalar_zero_op<Scalar>, PlainObject> ZeroReturnType;
/** \internal \deprecated Represents a vector with linearly spaced coefficients that allows sequential access only. */
EIGEN_DEPRECATED typedef CwiseNullaryOp<internal::linspaced_op<Scalar>, PlainObject> SequentialLinSpacedReturnType;
/** \internal Represents a vector with linearly spaced coefficients that allows random access. */
typedef CwiseNullaryOp<internal::linspaced_op<Scalar>, PlainObject> RandomAccessLinSpacedReturnType;
/** \internal Represents a vector with equally spaced coefficients that allows random access. */
typedef CwiseNullaryOp<internal::equalspaced_op<Scalar>, PlainObject> RandomAccessEqualSpacedReturnType;
/** \internal the return type of MatrixBase::eigenvalues() */
typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real,
internal::traits<Derived>::ColsAtCompileTime, 1>
EigenvaluesReturnType;
#endif // not EIGEN_PARSED_BY_DOXYGEN
/** Copies \a other into *this. \returns a reference to *this. */
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase<OtherDerived>& other);
/** Special case of the template operator=, in order to prevent the compiler
* from generating a default operator= (issue hit with g++ 4.1)
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase& other);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC Derived& operator=(const EigenBase<OtherDerived>& other);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC Derived& operator+=(const EigenBase<OtherDerived>& other);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC Derived& operator-=(const EigenBase<OtherDerived>& other);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC Derived& operator=(const ReturnByValue<OtherDerived>& func);
/** \internal
* Copies \a other into *this without evaluating other. \returns a reference to *this. */
template <typename OtherDerived>
/** \deprecated */
EIGEN_DEPRECATED EIGEN_DEVICE_FUNC Derived& lazyAssign(const DenseBase<OtherDerived>& other);
EIGEN_DEVICE_FUNC CommaInitializer<Derived> operator<<(const Scalar& s);
template <unsigned int Added, unsigned int Removed>
/** \deprecated it now returns \c *this */
EIGEN_DEPRECATED const Derived& flagged() const {
return derived();
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC CommaInitializer<Derived> operator<<(const DenseBase<OtherDerived>& other);
typedef Transpose<Derived> TransposeReturnType;
EIGEN_DEVICE_FUNC TransposeReturnType transpose();
typedef Transpose<const Derived> ConstTransposeReturnType;
EIGEN_DEVICE_FUNC const ConstTransposeReturnType transpose() const;
EIGEN_DEVICE_FUNC void transposeInPlace();
EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index rows, Index cols, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index size, const Scalar& value);
EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(const Scalar& value);
EIGEN_DEPRECATED EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, Index size,
const Scalar& low,
const Scalar& high);
EIGEN_DEPRECATED EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t,
const Scalar& low,
const Scalar& high);
EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Index size, const Scalar& low,
const Scalar& high);
EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(Index size, const Scalar& low,
const Scalar& step);
EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(const Scalar& low, const Scalar& step);
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(Index rows, Index cols,
const CustomNullaryOp& func);
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(Index size,
const CustomNullaryOp& func);
template <typename CustomNullaryOp>
EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(const CustomNullaryOp& func);
EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index size);
EIGEN_DEVICE_FUNC static const ZeroReturnType Zero();
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size);
EIGEN_DEVICE_FUNC static const ConstantReturnType Ones();
EIGEN_DEVICE_FUNC void fill(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high);
EIGEN_DEVICE_FUNC Derived& setEqualSpaced(Index size, const Scalar& low, const Scalar& step);
EIGEN_DEVICE_FUNC Derived& setEqualSpaced(const Scalar& low, const Scalar& step);
EIGEN_DEVICE_FUNC Derived& setZero();
EIGEN_DEVICE_FUNC Derived& setOnes();
EIGEN_DEVICE_FUNC Derived& setRandom();
template <typename OtherDerived>
EIGEN_DEVICE_FUNC bool isApprox(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const RealScalar& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
template <typename OtherDerived>
EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value,
const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
EIGEN_DEVICE_FUNC inline bool hasNaN() const;
EIGEN_DEVICE_FUNC inline bool allFinite() const;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const Scalar& other);
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const Scalar& other);
typedef internal::add_const_on_value_type_t<typename internal::eval<Derived>::type> EvalReturnType;
/** \returns the matrix or vector obtained by evaluating this expression.
*
* Notice that in the case of a plain matrix or vector (not an expression) this function just returns
* a const reference, in order to avoid a useless copy.
*
* \warning Be careful with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page
* \endlink.
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EvalReturnType eval() const {
// Even though MSVC does not honor strong inlining when the return type
// is a dynamic matrix, we desperately need strong inlining for fixed
// size types on MSVC.
return typename internal::eval<Derived>::type(derived());
}
/** swaps *this with the expression \a other.
*
*/
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(const DenseBase<OtherDerived>& other) {
EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase, THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
eigen_assert(rows() == other.rows() && cols() == other.cols());
call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
}
/** swaps *this with the matrix or array \a other.
*
*/
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(PlainObjectBase<OtherDerived>& other) {
eigen_assert(rows() == other.rows() && cols() == other.cols());
call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
}
EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
template <bool Enable>
EIGEN_DEVICE_FUNC inline const std::conditional_t<Enable, ForceAlignedAccess<Derived>, Derived&>
forceAlignedAccessIf() const;
template <bool Enable>
EIGEN_DEVICE_FUNC inline std::conditional_t<Enable, ForceAlignedAccess<Derived>, Derived&> forceAlignedAccessIf();
EIGEN_DEVICE_FUNC Scalar sum() const;
EIGEN_DEVICE_FUNC Scalar mean() const;
EIGEN_DEVICE_FUNC Scalar trace() const;
EIGEN_DEVICE_FUNC Scalar prod() const;
template <int NaNPropagation>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff() const;
template <int NaNPropagation>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() const;
// By default, the fastest version with undefined NaN propagation semantics is
// used.
// TODO(rmlarsen): Replace with default template argument when we move to
// c++11 or beyond.
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff() const {
return minCoeff<PropagateFast>();
}
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff() const {
return maxCoeff<PropagateFast>();
}
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
// TODO(rmlarsen): Replace these methods with a default template argument.
template <typename IndexType>
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const {
return minCoeff<PropagateFast>(row, col);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const {
return maxCoeff<PropagateFast>(row, col);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const {
return minCoeff<PropagateFast>(index);
}
template <typename IndexType>
EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const {
return maxCoeff<PropagateFast>(index);
}
template <typename BinaryOp>
EIGEN_DEVICE_FUNC Scalar redux(const BinaryOp& func) const;
template <typename Visitor>
EIGEN_DEVICE_FUNC void visit(Visitor& func) const;
/** \returns a WithFormat proxy object allowing to print a matrix the with given
* format \a fmt.
*
* See class IOFormat for some examples.
*
* \sa class IOFormat, class WithFormat
*/
inline const WithFormat<Derived> format(const IOFormat& fmt) const { return WithFormat<Derived>(derived(), fmt); }
/** \returns the unique coefficient of a 1x1 expression */
EIGEN_DEVICE_FUNC CoeffReturnType value() const {
EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) eigen_assert(this->rows() == 1 && this->cols() == 1);
return derived().coeff(0, 0);
}
EIGEN_DEVICE_FUNC bool all() const;
EIGEN_DEVICE_FUNC bool any() const;
EIGEN_DEVICE_FUNC Index count() const;
typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
typedef const VectorwiseOp<const Derived, Horizontal> ConstRowwiseReturnType;
typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
/** \returns a VectorwiseOp wrapper of *this for broadcasting and partial reductions
*
* Example: \include MatrixBase_rowwise.cpp
* Output: \verbinclude MatrixBase_rowwise.out
*
* \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
// Code moved here due to a CUDA compiler bug
EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const { return ConstRowwiseReturnType(derived()); }
EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
/** \returns a VectorwiseOp wrapper of *this broadcasting and partial reductions
*
* Example: \include MatrixBase_colwise.cpp
* Output: \verbinclude MatrixBase_colwise.out
*
* \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const { return ConstColwiseReturnType(derived()); }
EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>, PlainObject> RandomReturnType;
static const RandomReturnType Random(Index rows, Index cols);
static const RandomReturnType Random(Index size);
static const RandomReturnType Random();
template <typename ThenDerived, typename ElseDerived>
inline EIGEN_DEVICE_FUNC
CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ThenDerived>::Scalar,
typename DenseBase<ElseDerived>::Scalar, Scalar>,
ThenDerived, ElseDerived, Derived>
select(const DenseBase<ThenDerived>& thenMatrix, const DenseBase<ElseDerived>& elseMatrix) const;
template <typename ThenDerived>
inline EIGEN_DEVICE_FUNC
CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ThenDerived>::Scalar,
typename DenseBase<ThenDerived>::Scalar, Scalar>,
ThenDerived, typename DenseBase<ThenDerived>::ConstantReturnType, Derived>
select(const DenseBase<ThenDerived>& thenMatrix, const typename DenseBase<ThenDerived>::Scalar& elseScalar) const;
template <typename ElseDerived>
inline EIGEN_DEVICE_FUNC
CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ElseDerived>::Scalar,
typename DenseBase<ElseDerived>::Scalar, Scalar>,
typename DenseBase<ElseDerived>::ConstantReturnType, ElseDerived, Derived>
select(const typename DenseBase<ElseDerived>::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
template <int p>
RealScalar lpNorm() const;
template <int RowFactor, int ColFactor>
EIGEN_DEVICE_FUNC const Replicate<Derived, RowFactor, ColFactor> replicate() const;
/**
* \return an expression of the replication of \c *this
*
* Example: \include MatrixBase_replicate_int_int.cpp
* Output: \verbinclude MatrixBase_replicate_int_int.out
*
* \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
*/
// Code moved here due to a CUDA compiler bug
EIGEN_DEVICE_FUNC const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const {
return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
}
typedef Reverse<Derived, BothDirections> ReverseReturnType;
typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
EIGEN_DEVICE_FUNC ReverseReturnType reverse();
/** This is the const version of reverse(). */
// Code moved here due to a CUDA compiler bug
EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const { return ConstReverseReturnType(derived()); }
EIGEN_DEVICE_FUNC void reverseInPlace();
#ifdef EIGEN_PARSED_BY_DOXYGEN
/** STL-like <a href="https://en.cppreference.com/w/cpp/named_req/RandomAccessIterator">RandomAccessIterator</a>
* iterator type as returned by the begin() and end() methods.
*/
typedef random_access_iterator_type iterator;
/** This is the const version of iterator (aka read-only) */
typedef random_access_iterator_type const_iterator;
#else
typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit,
internal::pointer_based_stl_iterator<Derived>,
internal::generic_randaccess_stl_iterator<Derived> >
iterator_type;
typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit,
internal::pointer_based_stl_iterator<const Derived>,
internal::generic_randaccess_stl_iterator<const Derived> >
const_iterator_type;
// Stl-style iterators are supported only for vectors.
typedef std::conditional_t<IsVectorAtCompileTime, iterator_type, void> iterator;
typedef std::conditional_t<IsVectorAtCompileTime, const_iterator_type, void> const_iterator;
#endif
inline iterator begin();
inline const_iterator begin() const;
inline const_iterator cbegin() const;
inline iterator end();
inline const_iterator end() const;
inline const_iterator cend() const;
#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
#define EIGEN_DOC_UNARY_ADDONS(X, Y)
#include "../plugins/CommonCwiseUnaryOps.inc"
#include "../plugins/BlockMethods.inc"
#include "../plugins/IndexedViewMethods.inc"
#include "../plugins/ReshapedMethods.inc"
#ifdef EIGEN_DENSEBASE_PLUGIN
#include EIGEN_DENSEBASE_PLUGIN
#endif
#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
#undef EIGEN_DOC_UNARY_ADDONS
// disable the use of evalTo for dense objects with a nice compilation error
template <typename Dest>
EIGEN_DEVICE_FUNC inline void evalTo(Dest&) const {
EIGEN_STATIC_ASSERT((internal::is_same<Dest, void>::value),
THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
}
protected:
EIGEN_DEFAULT_COPY_CONSTRUCTOR(DenseBase)
/** Default constructor. Do nothing. */
#ifdef EIGEN_INTERNAL_DEBUGGING
EIGEN_DEVICE_FUNC constexpr DenseBase() {
/* Just checks for self-consistency of the flags.
* Only do it when debugging Eigen, as this borders on paranoia and could slow compilation down
*/
EIGEN_STATIC_ASSERT(
(internal::check_implication(MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1, int(IsRowMajor)) &&
internal::check_implication(MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1, int(!IsRowMajor))),
INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
}
#else
EIGEN_DEVICE_FUNC constexpr DenseBase() = default;
#endif
private:
EIGEN_DEVICE_FUNC explicit DenseBase(int);
EIGEN_DEVICE_FUNC DenseBase(int, int);
template <typename OtherDerived>
EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&);
};
/** Free-function swap.
*/
template <typename DerivedA, typename DerivedB>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
// Use forwarding references to capture all combinations of cv-qualified l+r-value cases.
std::enable_if_t<std::is_base_of<DenseBase<std::decay_t<DerivedA>>, std::decay_t<DerivedA>>::value &&
std::is_base_of<DenseBase<std::decay_t<DerivedB>>, std::decay_t<DerivedB>>::value,
void>
swap(DerivedA&& a, DerivedB&& b) {
a.swap(b);
}
} // end namespace Eigen
#endif // EIGEN_DENSEBASE_H
eigen-master/Eigen/src/Core/DenseCoeffsBase.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// 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_DENSECOEFFSBASE_H
#define EIGEN_DENSECOEFFSBASE_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename T>
struct add_const_on_value_type_if_arithmetic {
typedef std::conditional_t<is_arithmetic<T>::value, T, add_const_on_value_type_t<T>> type;
};
} // namespace internal
/** \brief Base class providing read-only coefficient access to matrices and arrays.
* \ingroup Core_Module
* \tparam Derived Type of the derived class
*
* \note #ReadOnlyAccessors Constant indicating read-only access
*
* This class defines the \c operator() \c const function and friends, which can be used to read specific
* entries of a matrix or array.
*
* \sa DenseCoeffsBase<Derived, WriteAccessors>, DenseCoeffsBase<Derived, DirectAccessors>,
* \ref TopicClassHierarchy
*/
template <typename Derived>
class DenseCoeffsBase<Derived, ReadOnlyAccessors> : public EigenBase<Derived> {
public:
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
// Explanation for this CoeffReturnType typedef.
// - This is the return type of the coeff() method.
// - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references
// to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value).
// - The is_arithmetic check is required since "const int", "const double", etc. will cause warnings on some systems
// while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is
// not possible, since the underlying expressions might not offer a valid address the reference could be referring to.
typedef std::conditional_t<bool(internal::traits<Derived>::Flags& LvalueBit), const Scalar&,
std::conditional_t<internal::is_arithmetic<Scalar>::value, Scalar, const Scalar>>
CoeffReturnType;
typedef typename internal::add_const_on_value_type_if_arithmetic<typename internal::packet_traits<Scalar>::type>::type
PacketReturnType;
typedef EigenBase<Derived> Base;
using Base::cols;
using Base::derived;
using Base::rows;
using Base::size;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const {
return int(Derived::RowsAtCompileTime) == 1 ? 0
: int(Derived::ColsAtCompileTime) == 1 ? inner
: int(Derived::Flags) & RowMajorBit ? outer
: inner;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const {
return int(Derived::ColsAtCompileTime) == 1 ? 0
: int(Derived::RowsAtCompileTime) == 1 ? inner
: int(Derived::Flags) & RowMajorBit ? inner
: outer;
}
/** Short version: don't use this function, use
* \link operator()(Index,Index) const \endlink instead.
*
* Long version: this function is similar to
* \link operator()(Index,Index) const \endlink, but without the assertion.
* Use this for limiting the performance cost of debugging code when doing
* repeated coefficient access. Only use this when it is guaranteed that the
* parameters \a row and \a col are in range.
*
* If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
* function equivalent to \link operator()(Index,Index) const \endlink.
*
* \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index row, Index col) const {
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).coeff(row, col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeffByOuterInner(Index outer, Index inner) const {
return coeff(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner));
}
/** \returns the coefficient at given the given row and column.
*
* \sa operator()(Index,Index), operator[](Index)
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator()(Index row, Index col) const {
eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return coeff(row, col);
}
/** Short version: don't use this function, use
* \link operator[](Index) const \endlink instead.
*
* Long version: this function is similar to
* \link operator[](Index) const \endlink, but without the assertion.
* Use this for limiting the performance cost of debugging code when doing
* repeated coefficient access. Only use this when it is guaranteed that the
* parameter \a index is in range.
*
* If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
* function equivalent to \link operator[](Index) const \endlink.
*
* \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index index) const {
EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).coeff(index);
}
/** \returns the coefficient at given index.
*
* This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
*
* \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
* z() const, w() const
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator[](Index index) const {
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
eigen_assert(index >= 0 && index < size());
return coeff(index);
}
/** \returns the coefficient at given index.
*
* This is synonymous to operator[](Index) const.
*
* This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
*
* \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
* z() const, w() const
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator()(Index index) const {
eigen_assert(index >= 0 && index < size());
return coeff(index);
}
/** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType x() const { return (*this)[0]; }
/** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType y() const {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 2, OUT_OF_RANGE_ACCESS);
return (*this)[1];
}
/** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType z() const {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 3, OUT_OF_RANGE_ACCESS);
return (*this)[2];
}
/** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType w() const {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 4, OUT_OF_RANGE_ACCESS);
return (*this)[3];
}
/** \internal
* \returns the packet of coefficients starting at the given row and column. It is your responsibility
* to ensure that a packet really starts there. This method is only available on expressions having the
* PacketAccessBit.
*
* The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
* starting at an address which is a multiple of the packet size.
*/
template <int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const {
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).template packet<LoadMode, DefaultPacketType>(row, col);
}
/** \internal */
template <int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packetByOuterInner(Index outer, Index inner) const {
return packet<LoadMode>(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner));
}
/** \internal
* \returns the packet of coefficients starting at the given index. It is your responsibility
* to ensure that a packet really starts there. This method is only available on expressions having the
* PacketAccessBit and the LinearAccessBit.
*
* The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
* the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
* starting at an address which is a multiple of the packet size.
*/
template <int LoadMode>
EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const {
EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
typedef typename internal::packet_traits<Scalar>::type DefaultPacketType;
eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).template packet<LoadMode, DefaultPacketType>(index);
}
protected:
// explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase.
// But some methods are only available in the DirectAccess case.
// So we add dummy methods here with these names, so that "using... " doesn't fail.
// It's not private so that the child class DenseBase can access them, and it's not public
// either since it's an implementation detail, so has to be protected.
void coeffRef();
void coeffRefByOuterInner();
void writePacket();
void writePacketByOuterInner();
void copyCoeff();
void copyCoeffByOuterInner();
void copyPacket();
void copyPacketByOuterInner();
void stride();
void innerStride();
void outerStride();
void rowStride();
void colStride();
};
/** \brief Base class providing read/write coefficient access to matrices and arrays.
* \ingroup Core_Module
* \tparam Derived Type of the derived class
*
* \note #WriteAccessors Constant indicating read/write access
*
* This class defines the non-const \c operator() function and friends, which can be used to write specific
* entries of a matrix or array. This class inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which
* defines the const variant for reading specific entries.
*
* \sa DenseCoeffsBase<Derived, DirectAccessors>, \ref TopicClassHierarchy
*/
template <typename Derived>
class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors> {
public:
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::packet_traits<Scalar>::type PacketScalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
using Base::coeff;
using Base::colIndexByOuterInner;
using Base::cols;
using Base::derived;
using Base::rowIndexByOuterInner;
using Base::rows;
using Base::size;
using Base::operator[];
using Base::operator();
using Base::w;
using Base::x;
using Base::y;
using Base::z;
/** Short version: don't use this function, use
* \link operator()(Index,Index) \endlink instead.
*
* Long version: this function is similar to
* \link operator()(Index,Index) \endlink, but without the assertion.
* Use this for limiting the performance cost of debugging code when doing
* repeated coefficient access. Only use this when it is guaranteed that the
* parameters \a row and \a col are in range.
*
* If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
* function equivalent to \link operator()(Index,Index) \endlink.
*
* \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index row, Index col) {
eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return internal::evaluator<Derived>(derived()).coeffRef(row, col);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRefByOuterInner(Index outer, Index inner) {
return coeffRef(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner));
}
/** \returns a reference to the coefficient at given the given row and column.
*
* \sa operator[](Index)
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator()(Index row, Index col) {
eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols());
return coeffRef(row, col);
}
/** Short version: don't use this function, use
* \link operator[](Index) \endlink instead.
*
* Long version: this function is similar to
* \link operator[](Index) \endlink, but without the assertion.
* Use this for limiting the performance cost of debugging code when doing
* repeated coefficient access. Only use this when it is guaranteed that the
* parameters \a row and \a col are in range.
*
* If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
* function equivalent to \link operator[](Index) \endlink.
*
* \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) {
EIGEN_STATIC_ASSERT(internal::evaluator<Derived>::Flags & LinearAccessBit,
THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS)
eigen_internal_assert(index >= 0 && index < size());
return internal::evaluator<Derived>(derived()).coeffRef(index);
}
/** \returns a reference to the coefficient at given index.
*
* This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
*
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator[](Index index) {
EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
eigen_assert(index >= 0 && index < size());
return coeffRef(index);
}
/** \returns a reference to the coefficient at given index.
*
* This is synonymous to operator[](Index).
*
* This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
*
* \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
*/
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator()(Index index) {
eigen_assert(index >= 0 && index < size());
return coeffRef(index);
}
/** equivalent to operator[](0). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& x() { return (*this)[0]; }
/** equivalent to operator[](1). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& y() {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 2, OUT_OF_RANGE_ACCESS);
return (*this)[1];
}
/** equivalent to operator[](2). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& z() {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 3, OUT_OF_RANGE_ACCESS);
return (*this)[2];
}
/** equivalent to operator[](3). */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& w() {
EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 4, OUT_OF_RANGE_ACCESS);
return (*this)[3];
}
};
/** \brief Base class providing direct read-only coefficient access to matrices and arrays.
* \ingroup Core_Module
* \tparam Derived Type of the derived class
*
* \note #DirectAccessors Constant indicating direct access
*
* This class defines functions to work with strides which can be used to access entries directly. This class
* inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which defines functions to access entries read-only using
* \c operator() .
*
* \sa \blank \ref TopicClassHierarchy
*/
template <typename Derived>
class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors> {
public:
typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
using Base::cols;
using Base::derived;
using Base::rows;
using Base::size;
/** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
*
* \sa outerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index innerStride() const { return derived().innerStride(); }
/** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
* in a column-major matrix).
*
* \sa innerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index outerStride() const { return derived().outerStride(); }
// FIXME shall we remove it ?
constexpr Index stride() const { return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); }
/** \returns the pointer increment between two consecutive rows.
*
* \sa innerStride(), outerStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index rowStride() const { return Derived::IsRowMajor ? outerStride() : innerStride(); }
/** \returns the pointer increment between two consecutive columns.
*
* \sa innerStride(), outerStride(), rowStride()
*/
EIGEN_DEVICE_FUNC constexpr Index colStride() const { return Derived::IsRowMajor ? innerStride() : outerStride(); }
};
/** \brief Base class providing direct read/write coefficient access to matrices and arrays.
* \ingroup Core_Module
* \tparam Derived Type of the derived class
*
* \note #DirectWriteAccessors Constant indicating direct access
*
* This class defines functions to work with strides which can be used to access entries directly. This class
* inherits DenseCoeffsBase<Derived, WriteAccessors> which defines functions to access entries read/write using
* \c operator().
*
* \sa \blank \ref TopicClassHierarchy
*/
template <typename Derived>
class DenseCoeffsBase<Derived, DirectWriteAccessors> : public DenseCoeffsBase<Derived, WriteAccessors> {
public:
typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
using Base::cols;
using Base::derived;
using Base::rows;
using Base::size;
/** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
*
* \sa outerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return derived().innerStride(); }
/** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
* in a column-major matrix).
*
* \sa innerStride(), rowStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return derived().outerStride(); }
// FIXME shall we remove it ?
constexpr Index stride() const noexcept { return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); }
/** \returns the pointer increment between two consecutive rows.
*
* \sa innerStride(), outerStride(), colStride()
*/
EIGEN_DEVICE_FUNC constexpr Index rowStride() const noexcept {
return Derived::IsRowMajor ? outerStride() : innerStride();
}
/** \returns the pointer increment between two consecutive columns.
*
* \sa innerStride(), outerStride(), rowStride()
*/
EIGEN_DEVICE_FUNC constexpr Index colStride() const noexcept {
return Derived::IsRowMajor ? innerStride() : outerStride();
}
};
namespace internal {
template <int Alignment, typename Derived, bool JustReturnZero>
struct first_aligned_impl {
static constexpr Index run(const Derived&) noexcept { return 0; }
};
template <int Alignment, typename Derived>
struct first_aligned_impl<Alignment, Derived, false> {
static inline Index run(const Derived& m) { return internal::first_aligned<Alignment>(m.data(), m.size()); }
};
/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect
* to \a Alignment for vectorization.
*
* \tparam Alignment requested alignment in Bytes.
*
* There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
* documentation.
*/
template <int Alignment, typename Derived>
static inline Index first_aligned(const DenseBase<Derived>& m) {
enum { ReturnZero = (int(evaluator<Derived>::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) };
return first_aligned_impl<Alignment, Derived, ReturnZero>::run(m.derived());
}
template <typename Derived>
static inline Index first_default_aligned(const DenseBase<Derived>& m) {
typedef typename Derived::Scalar Scalar;
typedef typename packet_traits<Scalar>::type DefaultPacketType;
return internal::first_aligned<int(unpacket_traits<DefaultPacketType>::alignment), Derived>(m);
}
template <typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
struct inner_stride_at_compile_time {
enum { ret = traits<Derived>::InnerStrideAtCompileTime };
};
template <typename Derived>
struct inner_stride_at_compile_time<Derived, false> {
enum { ret = 0 };
};
template <typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
struct outer_stride_at_compile_time {
enum { ret = traits<Derived>::OuterStrideAtCompileTime };
};
template <typename Derived>
struct outer_stride_at_compile_time<Derived, false> {
enum { ret = 0 };
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_DENSECOEFFSBASE_H
eigen-master/Eigen/src/Core/DenseStorage.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2010-2013 Hauke Heibel <hauke.heibel@gmail.com>
//
// 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_MATRIXSTORAGE_H
#define EIGEN_MATRIXSTORAGE_H
#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) \
X; \
EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
#else
#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
#endif
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment)
#else
#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment) \
eigen_assert((is_constant_evaluated() || (std::uintptr_t(array) % Alignment == 0)) && \
"this assertion is explained here: " \
"http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
" **** READ THIS WEB PAGE !!! ****");
#endif
#if EIGEN_STACK_ALLOCATION_LIMIT
#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X) \
EIGEN_STATIC_ASSERT(X <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG)
#else
#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X)
#endif
/** \internal
* Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
* to 16 bytes boundary if the total size is a multiple of 16 bytes.
*/
template <typename T, int Size, int MatrixOrArrayOptions,
int Alignment = (MatrixOrArrayOptions & DontAlign) ? 0 : compute_default_alignment<T, Size>::value>
struct plain_array {
EIGEN_ALIGN_TO_BOUNDARY(Alignment) T array[Size];
#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() = default;
#else
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() {
EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment)
EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T))
}
#endif
};
template <typename T, int Size, int MatrixOrArrayOptions>
struct plain_array<T, Size, MatrixOrArrayOptions, 0> {
T array[Size];
#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() = default;
#else
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() { EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T)) }
#endif
};
template <typename T, int MatrixOrArrayOptions, int Alignment>
struct plain_array<T, 0, MatrixOrArrayOptions, Alignment> {
T array[1];
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() = default;
};
template <typename T, int Size, int Options, int Alignment>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap_plain_array(plain_array<T, Size, Options, Alignment>& a,
plain_array<T, Size, Options, Alignment>& b,
Index a_size, Index b_size) {
Index common_size = numext::mini(a_size, b_size);
std::swap_ranges(a.array, a.array + common_size, b.array);
if (a_size > b_size)
smart_copy(a.array + common_size, a.array + a_size, b.array + common_size);
else if (b_size > a_size)
smart_copy(b.array + common_size, b.array + b_size, a.array + common_size);
}
template <typename T, int Size, int Rows, int Cols, int Options>
class DenseStorage_impl {
plain_array<T, Size, Options> m_data;
public:
#ifndef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
#else
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
smart_copy(other.m_data.array, other.m_data.array + Size, m_data.array);
}
#endif
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
numext::swap(m_data, other.m_data);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/,
Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; }
};
template <typename T, int Size, int Cols, int Options>
class DenseStorage_impl<T, Size, Dynamic, Cols, Options> {
plain_array<T, Size, Options> m_data;
Index m_rows = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_rows(other.m_rows) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/)
: m_rows(rows) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
EIGEN_UNUSED_VARIABLE(size)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
m_rows = other.m_rows;
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
swap_plain_array(m_data, other.m_data, size(), other.size());
numext::swap(m_rows, other.m_rows);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) {
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) {
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; }
};
template <typename T, int Size, int Rows, int Options>
class DenseStorage_impl<T, Size, Rows, Dynamic, Options> {
plain_array<T, Size, Options> m_data;
Index m_cols = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_cols(other.m_cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols)
: m_cols(cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
EIGEN_UNUSED_VARIABLE(size)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
m_cols = other.m_cols;
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
swap_plain_array(m_data, other.m_data, size(), other.size());
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) {
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) {
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; }
};
template <typename T, int Size, int Options>
class DenseStorage_impl<T, Size, Dynamic, Dynamic, Options> {
plain_array<T, Size, Options> m_data;
Index m_rows = 0;
Index m_cols = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_rows(other.m_rows), m_cols(other.m_cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols)
: m_rows(rows), m_cols(cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
EIGEN_UNUSED_VARIABLE(size)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
m_rows = other.m_rows;
m_cols = other.m_cols;
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
swap_plain_array(m_data, other.m_data, size(), other.size());
numext::swap(m_rows, other.m_rows);
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) {
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) {
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; }
};
// null matrix variants
template <typename T, int Rows, int Cols, int Options>
class DenseStorage_impl<T, 0, Rows, Cols, Options> {
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl&) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/,
Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; }
};
template <typename T, int Cols, int Options>
class DenseStorage_impl<T, 0, Dynamic, Cols, Options> {
Index m_rows = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index /*cols*/)
: m_rows(rows) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_rows, other.m_rows);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) {
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) {
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; }
};
template <typename T, int Rows, int Options>
class DenseStorage_impl<T, 0, Rows, Dynamic, Options> {
Index m_cols = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index cols)
: m_cols(cols) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) {
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) {
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; }
};
template <typename T, int Options>
class DenseStorage_impl<T, 0, Dynamic, Dynamic, Options> {
Index m_rows = 0;
Index m_cols = 0;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index cols)
: m_rows(rows), m_cols(cols) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_rows, other.m_rows);
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) {
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) {
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; }
};
// fixed-size matrix with dynamic memory allocation not currently supported
template <typename T, int Rows, int Cols, int Options>
class DenseStorage_impl<T, Dynamic, Rows, Cols, Options> {};
// dynamic-sized variants
template <typename T, int Cols, int Options>
class DenseStorage_impl<T, Dynamic, Dynamic, Cols, Options> {
static constexpr bool Align = (Options & DontAlign) == 0;
T* m_data = nullptr;
Index m_rows = 0;
public:
static constexpr int Size = Dynamic;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_rows(other.m_rows) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data, other.m_data + other.size(), m_data);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/)
: m_data(conditional_aligned_new_auto<T, Align>(size)), m_rows(rows) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
: m_data(other.m_data), m_rows(other.m_rows) {
other.m_data = nullptr;
other.m_rows = 0;
}
EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
resize(other.size(), other.rows(), other.cols());
smart_copy(other.m_data, other.m_data + other.size(), m_data);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
this->swap(other);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_data, other.m_data);
numext::swap(m_rows, other.m_rows);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index /*cols*/) {
m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index /*cols*/) {
Index oldSize = this->size();
if (oldSize != size) {
conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
m_data = conditional_aligned_new_auto<T, Align>(size);
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_rows = rows;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; }
};
template <typename T, int Rows, int Options>
class DenseStorage_impl<T, Dynamic, Rows, Dynamic, Options> {
static constexpr bool Align = (Options & DontAlign) == 0;
T* m_data = nullptr;
Index m_cols = 0;
public:
static constexpr int Size = Dynamic;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_cols(other.m_cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data, other.m_data + other.size(), m_data);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols)
: m_data(conditional_aligned_new_auto<T, Align>(size)), m_cols(cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
: m_data(other.m_data), m_cols(other.m_cols) {
other.m_data = nullptr;
other.m_cols = 0;
}
EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
resize(other.size(), other.rows(), other.cols());
smart_copy(other.m_data, other.m_data + other.size(), m_data);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
this->swap(other);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_data, other.m_data);
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index /*rows*/, Index cols) {
m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index /*rows*/, Index cols) {
Index oldSize = this->size();
if (oldSize != size) {
conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
m_data = conditional_aligned_new_auto<T, Align>(size);
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; }
};
template <typename T, int Options>
class DenseStorage_impl<T, Dynamic, Dynamic, Dynamic, Options> {
static constexpr bool Align = (Options & DontAlign) == 0;
T* m_data = nullptr;
Index m_rows = 0;
Index m_cols = 0;
public:
static constexpr int Size = Dynamic;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
: m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_rows(other.m_rows), m_cols(other.m_cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
smart_copy(other.m_data, other.m_data + other.size(), m_data);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols)
: m_data(conditional_aligned_new_auto<T, Align>(size)), m_rows(rows), m_cols(cols) {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
: m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {
other.m_data = nullptr;
other.m_rows = 0;
other.m_cols = 0;
}
EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
resize(other.size(), other.rows(), other.cols());
smart_copy(other.m_data, other.m_data + other.size(), m_data);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
this->swap(other);
return *this;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
numext::swap(m_data, other.m_data);
numext::swap(m_rows, other.m_rows);
numext::swap(m_cols, other.m_cols);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index cols) {
m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index cols) {
Index oldSize = this->size();
if (oldSize != size) {
conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
m_data = conditional_aligned_new_auto<T, Align>(size);
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
}
m_rows = rows;
m_cols = cols;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; }
};
template <typename T, int Size, int Rows, int Cols>
struct use_default_move {
static constexpr bool DynamicObject = Size == Dynamic;
static constexpr bool TrivialObject =
(!NumTraits<T>::RequireInitialization) && (Rows >= 0) && (Cols >= 0) && (Size == Rows * Cols);
static constexpr bool value = DynamicObject || TrivialObject;
};
} // end namespace internal
/** \internal
*
* \class DenseStorage_impl
* \ingroup Core_Module
*
* \brief Stores the data of a matrix
*
* This class stores the data of fixed-size, dynamic-size or mixed matrices
* in a way as compact as possible.
*
* \sa Matrix
*/
template <typename T, int Size, int Rows, int Cols, int Options,
bool Trivial = internal::use_default_move<T, Size, Rows, Cols>::value>
class DenseStorage : public internal::DenseStorage_impl<T, Size, Rows, Cols, Options> {
using Base = internal::DenseStorage_impl<T, Size, Rows, Cols, Options>;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols)
: Base(size, rows, cols) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(const DenseStorage&) = default;
// if DenseStorage meets the requirements of use_default_move, then use the move construction and move assignment
// operation defined in DenseStorage_impl, or the compiler-generated version if none is defined
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(DenseStorage&&) = default;
};
template <typename T, int Size, int Rows, int Cols, int Options>
class DenseStorage<T, Size, Rows, Cols, Options, false>
: public internal::DenseStorage_impl<T, Size, Rows, Cols, Options> {
using Base = internal::DenseStorage_impl<T, Size, Rows, Cols, Options>;
public:
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage() = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols)
: Base(size, rows, cols) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(const DenseStorage&) = default;
// if DenseStorage does not meet the requirements of use_default_move, then defer to the copy construction and copy
// assignment behavior
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&& other)
: DenseStorage(static_cast<const DenseStorage&>(other)) {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(DenseStorage&& other) {
*this = other;
return *this;
}
};
} // end namespace Eigen
#endif // EIGEN_MATRIX_H
eigen-master/Eigen/src/Core/DeviceWrapper.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2023 Charlie Schlosser <cs.schlosser@gmail.com>
//
// 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_DEVICEWRAPPER_H
#define EIGEN_DEVICEWRAPPER_H
namespace Eigen {
template <typename Derived, typename Device>
struct DeviceWrapper {
using Base = EigenBase<internal::remove_all_t<Derived>>;
using Scalar = typename Derived::Scalar;
EIGEN_DEVICE_FUNC DeviceWrapper(Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {}
EIGEN_DEVICE_FUNC DeviceWrapper(const Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived>& other) {
using AssignOp = internal::assign_op<Scalar, typename OtherDerived::Scalar>;
internal::call_assignment(*this, other.derived(), AssignOp());
return m_xpr;
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const EigenBase<OtherDerived>& other) {
using AddAssignOp = internal::add_assign_op<Scalar, typename OtherDerived::Scalar>;
internal::call_assignment(*this, other.derived(), AddAssignOp());
return m_xpr;
}
template <typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const EigenBase<OtherDerived>& other) {
using SubAssignOp = internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>;
internal::call_assignment(*this, other.derived(), SubAssignOp());
return m_xpr;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& derived() { return m_xpr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Device& device() { return m_device; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NoAlias<DeviceWrapper, EigenBase> noalias() {
return NoAlias<DeviceWrapper, EigenBase>(*this);
}
Derived& m_xpr;
Device& m_device;
};
namespace internal {
// this is where we differentiate between lazy assignment and specialized kernels (e.g. matrix products)
template <typename DstXprType, typename SrcXprType, typename Functor, typename Device,
typename Kind = typename AssignmentKind<typename evaluator_traits<DstXprType>::Shape,
typename evaluator_traits<SrcXprType>::Shape>::Kind,
typename EnableIf = void>
struct AssignmentWithDevice;
// unless otherwise specified, use the default product implementation
template <typename DstXprType, typename Lhs, typename Rhs, int Options, typename Functor, typename Device,
typename Weak>
struct AssignmentWithDevice<DstXprType, Product<Lhs, Rhs, Options>, Functor, Device, Dense2Dense, Weak> {
using SrcXprType = Product<Lhs, Rhs, Options>;
using Base = Assignment<DstXprType, SrcXprType, Functor>;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func,
Device&) {
Base::run(dst, src, func);
}
};
// specialization for coeffcient-wise assignment
template <typename DstXprType, typename SrcXprType, typename Functor, typename Device, typename Weak>
struct AssignmentWithDevice<DstXprType, SrcXprType, Functor, Device, Dense2Dense, Weak> {
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func,
Device& device) {
#ifndef EIGEN_NO_DEBUG
internal::check_for_aliasing(dst, src);
#endif
call_dense_assignment_loop(dst, src, func, device);
}
};
// this allows us to use the default evaluation scheme if it is not specialized for the device
template <typename Kernel, typename Device, int Traversal = Kernel::AssignmentTraits::Traversal,
int Unrolling = Kernel::AssignmentTraits::Unrolling>
struct dense_assignment_loop_with_device {
using Base = dense_assignment_loop<Kernel, Traversal, Unrolling>;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Device&) { Base::run(kernel); }
};
// entry point for a generic expression with device
template <typename Dst, typename Src, typename Func, typename Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(DeviceWrapper<Dst, Device> dst,
const Src& src, const Func& func) {
enum {
NeedToTranspose = ((int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1) ||
(int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)) &&
int(Dst::SizeAtCompileTime) != 1
};
using ActualDstTypeCleaned = std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst>;
using ActualDstType = std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst&>;
ActualDstType actualDst(dst.derived());
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned, Src)
EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename ActualDstTypeCleaned::Scalar, typename Src::Scalar);
// this provides a mechanism for specializing simple assignments, matrix products, etc
AssignmentWithDevice<ActualDstTypeCleaned, Src, Func, Device>::run(actualDst, src, func, dst.device());
}
// copy and pasted from AssignEvaluator except forward device to kernel
template <typename DstXprType, typename SrcXprType, typename Functor, typename Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src,
const Functor& func, Device& device) {
using DstEvaluatorType = evaluator<DstXprType>;
using SrcEvaluatorType = evaluator<SrcXprType>;
SrcEvaluatorType srcEvaluator(src);
// NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
// we need to resize the destination after the source evaluator has been created.
resize_if_allowed(dst, src, func);
DstEvaluatorType dstEvaluator(dst);
using Kernel = generic_dense_assignment_kernel<DstEvaluatorType, SrcEvaluatorType, Functor>;
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
dense_assignment_loop_with_device<Kernel, Device>::run(kernel, device);
}
} // namespace internal
template <typename Derived>
template <typename Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<Derived, Device> EigenBase<Derived>::device(Device& device) {
return DeviceWrapper<Derived, Device>(derived(), device);
}
template <typename Derived>
template <typename Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<const Derived, Device> EigenBase<Derived>::device(
Device& device) const {
return DeviceWrapper<const Derived, Device>(derived(), device);
}
} // namespace Eigen
#endif
eigen-master/Eigen/src/Core/Diagonal.h 0 → 100644
View file @ 266d4fd9
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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_DIAGONAL_H
#define EIGEN_DIAGONAL_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \class Diagonal
* \ingroup Core_Module
*
* \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
*
* \tparam MatrixType the type of the object in which we are taking a sub/main/super diagonal
* \tparam DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
* A positive value means a superdiagonal, a negative value means a subdiagonal.
* You can also use DynamicIndex so the index can be set at runtime.
*
* The matrix is not required to be square.
*
* This class represents an expression of the main diagonal, or any sub/super diagonal
* of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
* time this is the only way it is used.
*
* \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
*/
namespace internal {
template <typename MatrixType, int DiagIndex>
struct traits<Diagonal<MatrixType, DiagIndex> > : traits<MatrixType> {
typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNested_;
typedef typename MatrixType::StorageKind StorageKind;
enum {
RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic)
? Dynamic
: (plain_enum_min(MatrixType::RowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
MatrixType::ColsAtCompileTime - plain_enum_max(DiagIndex, 0))),
ColsAtCompileTime = 1,
MaxRowsAtCompileTime =
int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
: DiagIndex == DynamicIndex
? min_size_prefer_fixed(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime)
: (plain_enum_min(MatrixType::MaxRowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
MatrixType::MaxColsAtCompileTime - plain_enum_max(DiagIndex, 0))),
MaxColsAtCompileTime = 1,
MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
Flags = (unsigned int)MatrixTypeNested_::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) &
~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride + 1,
OuterStrideAtCompileTime = 0
};
};
} // namespace internal
template <typename MatrixType, int DiagIndex_>
class Diagonal : public internal::dense_xpr_base<Diagonal<MatrixType, DiagIndex_> >::type {
public:
enum { DiagIndex = DiagIndex_ };
typedef typename internal::dense_xpr_base<Diagonal>::type Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
EIGEN_DEVICE_FUNC explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex)
: m_matrix(matrix), m_index(a_index) {
eigen_assert(a_index <= m_matrix.cols() && -a_index <= m_matrix.rows());
}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
EIGEN_DEVICE_FUNC inline Index rows() const {
return m_index.value() < 0 ? numext::mini<Index>(m_matrix.cols(), m_matrix.rows() + m_index.value())
: numext::mini<Index>(m_matrix.rows(), m_matrix.cols() - m_index.value());
}
EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return 1; }
EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_matrix.outerStride() + 1; }
EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return 0; }
typedef std::conditional_t<internal::is_lvalue<MatrixType>::value, Scalar, const Scalar> ScalarWithConstIfNotLvalue;
EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index) {
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.coeffRef(row + rowOffset(), row + colOffset());
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index) const {
return m_matrix.coeffRef(row + rowOffset(), row + colOffset());
}
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index row, Index) const {
return m_matrix.coeff(row + rowOffset(), row + colOffset());
}
EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index idx) {
EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset());
}
EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index idx) const {
return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset());
}
EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index idx) const {
return m_matrix.coeff(idx + rowOffset(), idx + colOffset());
}
EIGEN_DEVICE_FUNC inline const internal::remove_all_t<typename MatrixType::Nested>& nestedExpression() const {
return m_matrix;
}
EIGEN_DEVICE_FUNC inline Index index() const { return m_index.value(); }
protected:
typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
private:
// some compilers may fail to optimize std::max etc in case of compile-time constants...
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index absDiagIndex() const noexcept {
return m_index.value() > 0 ? m_index.value() : -m_index.value();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowOffset() const noexcept {
return m_index.value() > 0 ? 0 : -m_index.value();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colOffset() const noexcept {
return m_index.value() > 0 ? m_index.value() : 0;
}
// trigger a compile-time error if someone try to call packet
template <int LoadMode>
typename MatrixType::PacketReturnType packet(Index) const;
template <int LoadMode>
typename MatrixType::PacketReturnType packet(Index, Index) const;
};
/** \returns an expression of the main diagonal of the matrix \c *this
*
* \c *this is not required to be square.
*
* Example: \include MatrixBase_diagonal.cpp
* Output: \verbinclude MatrixBase_diagonal.out
*
* \sa class Diagonal */
template <typename Derived>
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::DiagonalReturnType MatrixBase<Derived>::diagonal() {
return DiagonalReturnType(derived());
}
/** This is the const version of diagonal(). */
template <typename Derived>
EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::ConstDiagonalReturnType MatrixBase<Derived>::diagonal()
const {
return ConstDiagonalReturnType(derived());
}
/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
*
* \c *this is not required to be square.
*
* The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
* and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
*
* Example: \include MatrixBase_diagonal_int.cpp
* Output: \verbinclude MatrixBase_diagonal_int.out
*
* \sa MatrixBase::diagonal(), class Diagonal */
template <typename Derived>
EIGEN_DEVICE_FUNC inline Diagonal<Derived, DynamicIndex> MatrixBase<Derived>::diagonal(Index index) {
return Diagonal<Derived, DynamicIndex>(derived(), index);
}
/** This is the const version of diagonal(Index). */
template <typename Derived>
EIGEN_DEVICE_FUNC inline const Diagonal<const Derived, DynamicIndex> MatrixBase<Derived>::diagonal(Index index) const {
return Diagonal<const Derived, DynamicIndex>(derived(), index);
}
/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
*
* \c *this is not required to be square.
*
* The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
* and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
*
* Example: \include MatrixBase_diagonal_template_int.cpp
* Output: \verbinclude MatrixBase_diagonal_template_int.out
*
* \sa MatrixBase::diagonal(), class Diagonal */
template <typename Derived>
template <int Index_>
EIGEN_DEVICE_FUNC inline Diagonal<Derived, Index_> MatrixBase<Derived>::diagonal() {
return Diagonal<Derived, Index_>(derived());
}
/** This is the const version of diagonal<int>(). */
template <typename Derived>
template <int Index_>
EIGEN_DEVICE_FUNC inline const Diagonal<const Derived, Index_> MatrixBase<Derived>::diagonal() const {
return Diagonal<const Derived, Index_>(derived());
}
} // end namespace Eigen
#endif // EIGEN_DIAGONAL_H
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