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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// 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_VISITOR_H
#define EIGEN_VISITOR_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template <typename Visitor, typename Derived, int UnrollCount,
bool Vectorize = (Derived::PacketAccess && functor_traits<Visitor>::PacketAccess), bool LinearAccess = false,
bool ShortCircuitEvaluation = false>
struct visitor_impl;
template <typename Visitor, bool ShortCircuitEvaluation = false>
struct short_circuit_eval_impl {
// if short circuit evaluation is not used, do nothing
static EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool run(const Visitor&) { return false; }
};
template <typename Visitor>
struct short_circuit_eval_impl<Visitor, true> {
// if short circuit evaluation is used, check the visitor
static EIGEN_CONSTEXPR EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool run(const Visitor& visitor) {
return visitor.done();
}
};
// unrolled inner-outer traversal
template <typename Visitor, typename Derived, int UnrollCount, bool Vectorize, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, UnrollCount, Vectorize, false, ShortCircuitEvaluation> {
// don't use short circuit evaulation for unrolled version
using Scalar = typename Derived::Scalar;
using Packet = typename packet_traits<Scalar>::type;
static constexpr bool RowMajor = Derived::IsRowMajor;
static constexpr int RowsAtCompileTime = Derived::RowsAtCompileTime;
static constexpr int ColsAtCompileTime = Derived::ColsAtCompileTime;
static constexpr int PacketSize = packet_traits<Scalar>::size;
static constexpr bool CanVectorize(int K) {
constexpr int InnerSizeAtCompileTime = RowMajor ? ColsAtCompileTime : RowsAtCompileTime;
if (InnerSizeAtCompileTime < PacketSize) return false;
return Vectorize && (InnerSizeAtCompileTime - (K % InnerSizeAtCompileTime) >= PacketSize);
}
template <int K = 0, bool Empty = (K == UnrollCount), std::enable_if_t<Empty, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived&, Visitor&) {}
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && Initialize && !DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
visitor.init(mat.coeff(0, 0), 0, 0);
run<1>(mat, visitor);
}
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && !Initialize && !DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
static constexpr int R = RowMajor ? (K / ColsAtCompileTime) : (K % RowsAtCompileTime);
static constexpr int C = RowMajor ? (K % ColsAtCompileTime) : (K / RowsAtCompileTime);
visitor(mat.coeff(R, C), R, C);
run<K + 1>(mat, visitor);
}
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && Initialize && DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
Packet P = mat.template packet<Packet>(0, 0);
visitor.initpacket(P, 0, 0);
run<PacketSize>(mat, visitor);
}
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && !Initialize && DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
static constexpr int R = RowMajor ? (K / ColsAtCompileTime) : (K % RowsAtCompileTime);
static constexpr int C = RowMajor ? (K % ColsAtCompileTime) : (K / RowsAtCompileTime);
Packet P = mat.template packet<Packet>(R, C);
visitor.packet(P, R, C);
run<K + PacketSize>(mat, visitor);
}
};
// unrolled linear traversal
template <typename Visitor, typename Derived, int UnrollCount, bool Vectorize, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, UnrollCount, Vectorize, true, ShortCircuitEvaluation> {
// don't use short circuit evaulation for unrolled version
using Scalar = typename Derived::Scalar;
using Packet = typename packet_traits<Scalar>::type;
static constexpr int PacketSize = packet_traits<Scalar>::size;
static constexpr bool CanVectorize(int K) { return Vectorize && ((UnrollCount - K) >= PacketSize); }
// empty
template <int K = 0, bool Empty = (K == UnrollCount), std::enable_if_t<Empty, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived&, Visitor&) {}
// scalar initialization
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && Initialize && !DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
visitor.init(mat.coeff(0), 0);
run<1>(mat, visitor);
}
// scalar iteration
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && !Initialize && !DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
visitor(mat.coeff(K), K);
run<K + 1>(mat, visitor);
}
// vector initialization
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && Initialize && DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
Packet P = mat.template packet<Packet>(0);
visitor.initpacket(P, 0);
run<PacketSize>(mat, visitor);
}
// vector iteration
template <int K = 0, bool Empty = (K == UnrollCount), bool Initialize = (K == 0), bool DoVectorOp = CanVectorize(K),
std::enable_if_t<!Empty && !Initialize && DoVectorOp, bool> = true>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
Packet P = mat.template packet<Packet>(K);
visitor.packet(P, K);
run<K + PacketSize>(mat, visitor);
}
};
// dynamic scalar outer-inner traversal
template <typename Visitor, typename Derived, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/false, /*LinearAccess=*/false, ShortCircuitEvaluation> {
using short_circuit = short_circuit_eval_impl<Visitor, ShortCircuitEvaluation>;
static constexpr bool RowMajor = Derived::IsRowMajor;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
const Index innerSize = RowMajor ? mat.cols() : mat.rows();
const Index outerSize = RowMajor ? mat.rows() : mat.cols();
if (innerSize == 0 || outerSize == 0) return;
{
visitor.init(mat.coeff(0, 0), 0, 0);
if (short_circuit::run(visitor)) return;
for (Index i = 1; i < innerSize; ++i) {
Index r = RowMajor ? 0 : i;
Index c = RowMajor ? i : 0;
visitor(mat.coeff(r, c), r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
for (Index j = 1; j < outerSize; j++) {
for (Index i = 0; i < innerSize; ++i) {
Index r = RowMajor ? j : i;
Index c = RowMajor ? i : j;
visitor(mat.coeff(r, c), r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
}
};
// dynamic vectorized outer-inner traversal
template <typename Visitor, typename Derived, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/true, /*LinearAccess=*/false, ShortCircuitEvaluation> {
using Scalar = typename Derived::Scalar;
using Packet = typename packet_traits<Scalar>::type;
static constexpr int PacketSize = packet_traits<Scalar>::size;
using short_circuit = short_circuit_eval_impl<Visitor, ShortCircuitEvaluation>;
static constexpr bool RowMajor = Derived::IsRowMajor;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
const Index innerSize = RowMajor ? mat.cols() : mat.rows();
const Index outerSize = RowMajor ? mat.rows() : mat.cols();
if (innerSize == 0 || outerSize == 0) return;
{
Index i = 0;
if (innerSize < PacketSize) {
visitor.init(mat.coeff(0, 0), 0, 0);
i = 1;
} else {
Packet p = mat.template packet<Packet>(0, 0);
visitor.initpacket(p, 0, 0);
i = PacketSize;
}
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
for (; i + PacketSize - 1 < innerSize; i += PacketSize) {
Index r = RowMajor ? 0 : i;
Index c = RowMajor ? i : 0;
Packet p = mat.template packet<Packet>(r, c);
visitor.packet(p, r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
for (; i < innerSize; ++i) {
Index r = RowMajor ? 0 : i;
Index c = RowMajor ? i : 0;
visitor(mat.coeff(r, c), r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
for (Index j = 1; j < outerSize; j++) {
Index i = 0;
for (; i + PacketSize - 1 < innerSize; i += PacketSize) {
Index r = RowMajor ? j : i;
Index c = RowMajor ? i : j;
Packet p = mat.template packet<Packet>(r, c);
visitor.packet(p, r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
for (; i < innerSize; ++i) {
Index r = RowMajor ? j : i;
Index c = RowMajor ? i : j;
visitor(mat.coeff(r, c), r, c);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
}
};
// dynamic scalar linear traversal
template <typename Visitor, typename Derived, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/false, /*LinearAccess=*/true, ShortCircuitEvaluation> {
using short_circuit = short_circuit_eval_impl<Visitor, ShortCircuitEvaluation>;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
const Index size = mat.size();
if (size == 0) return;
visitor.init(mat.coeff(0), 0);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
for (Index k = 1; k < size; k++) {
visitor(mat.coeff(k), k);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
};
// dynamic vectorized linear traversal
template <typename Visitor, typename Derived, bool ShortCircuitEvaluation>
struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/true, /*LinearAccess=*/true, ShortCircuitEvaluation> {
using Scalar = typename Derived::Scalar;
using Packet = typename packet_traits<Scalar>::type;
static constexpr int PacketSize = packet_traits<Scalar>::size;
using short_circuit = short_circuit_eval_impl<Visitor, ShortCircuitEvaluation>;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& mat, Visitor& visitor) {
const Index size = mat.size();
if (size == 0) return;
Index k = 0;
if (size < PacketSize) {
visitor.init(mat.coeff(0), 0);
k = 1;
} else {
Packet p = mat.template packet<Packet>(k);
visitor.initpacket(p, k);
k = PacketSize;
}
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
for (; k + PacketSize - 1 < size; k += PacketSize) {
Packet p = mat.template packet<Packet>(k);
visitor.packet(p, k);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
for (; k < size; k++) {
visitor(mat.coeff(k), k);
if EIGEN_PREDICT_FALSE (short_circuit::run(visitor)) return;
}
}
};
// evaluator adaptor
template <typename XprType>
class visitor_evaluator {
public:
typedef evaluator<XprType> Evaluator;
typedef typename XprType::Scalar Scalar;
using Packet = typename packet_traits<Scalar>::type;
typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType;
static constexpr bool PacketAccess = static_cast<bool>(Evaluator::Flags & PacketAccessBit);
static constexpr bool LinearAccess = static_cast<bool>(Evaluator::Flags & LinearAccessBit);
static constexpr bool IsRowMajor = static_cast<bool>(XprType::IsRowMajor);
static constexpr int RowsAtCompileTime = XprType::RowsAtCompileTime;
static constexpr int ColsAtCompileTime = XprType::ColsAtCompileTime;
static constexpr int XprAlignment = Evaluator::Alignment;
static constexpr int CoeffReadCost = Evaluator::CoeffReadCost;
EIGEN_DEVICE_FUNC explicit visitor_evaluator(const XprType& xpr) : m_evaluator(xpr), m_xpr(xpr) {}
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_xpr.cols(); }
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index size() const EIGEN_NOEXCEPT { return m_xpr.size(); }
// outer-inner access
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const {
return m_evaluator.coeff(row, col);
}
template <typename Packet, int Alignment = Unaligned>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(Index row, Index col) const {
return m_evaluator.template packet<Alignment, Packet>(row, col);
}
// linear access
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_evaluator.coeff(index); }
template <typename Packet, int Alignment = XprAlignment>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(Index index) const {
return m_evaluator.template packet<Alignment, Packet>(index);
}
protected:
Evaluator m_evaluator;
const XprType& m_xpr;
};
template <typename Derived, typename Visitor, bool ShortCircuitEvaulation>
struct visit_impl {
using Evaluator = visitor_evaluator<Derived>;
using Scalar = typename DenseBase<Derived>::Scalar;
static constexpr bool IsRowMajor = DenseBase<Derived>::IsRowMajor;
static constexpr int SizeAtCompileTime = DenseBase<Derived>::SizeAtCompileTime;
static constexpr int RowsAtCompileTime = DenseBase<Derived>::RowsAtCompileTime;
static constexpr int ColsAtCompileTime = DenseBase<Derived>::ColsAtCompileTime;
static constexpr int InnerSizeAtCompileTime = IsRowMajor ? ColsAtCompileTime : RowsAtCompileTime;
static constexpr int OuterSizeAtCompileTime = IsRowMajor ? RowsAtCompileTime : ColsAtCompileTime;
static constexpr bool LinearAccess =
Evaluator::LinearAccess && static_cast<bool>(functor_traits<Visitor>::LinearAccess);
static constexpr bool Vectorize = Evaluator::PacketAccess && static_cast<bool>(functor_traits<Visitor>::PacketAccess);
static constexpr int PacketSize = packet_traits<Scalar>::size;
static constexpr int VectorOps =
Vectorize ? (LinearAccess ? (SizeAtCompileTime / PacketSize)
: (OuterSizeAtCompileTime * (InnerSizeAtCompileTime / PacketSize)))
: 0;
static constexpr int ScalarOps = SizeAtCompileTime - (VectorOps * PacketSize);
// treat vector op and scalar op as same cost for unroll logic
static constexpr int TotalOps = VectorOps + ScalarOps;
static constexpr int UnrollCost = int(Evaluator::CoeffReadCost) + int(functor_traits<Visitor>::Cost);
static constexpr bool Unroll = (SizeAtCompileTime != Dynamic) && ((TotalOps * UnrollCost) <= EIGEN_UNROLLING_LIMIT);
static constexpr int UnrollCount = Unroll ? int(SizeAtCompileTime) : Dynamic;
using impl = visitor_impl<Visitor, Evaluator, UnrollCount, Vectorize, LinearAccess, ShortCircuitEvaulation>;
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const DenseBase<Derived>& mat, Visitor& visitor) {
Evaluator evaluator(mat.derived());
impl::run(evaluator, visitor);
}
};
} // end namespace internal
/** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
*
* The template parameter \a Visitor is the type of the visitor and provides the following interface:
* \code
* struct MyVisitor {
* // called for the first coefficient
* void init(const Scalar& value, Index i, Index j);
* // called for all other coefficients
* void operator() (const Scalar& value, Index i, Index j);
* };
* \endcode
*
* \note compared to one or two \em for \em loops, visitors offer automatic
* unrolling for small fixed size matrix.
*
* \note if the matrix is empty, then the visitor is left unchanged.
*
* \sa minCoeff(Index*,Index*), maxCoeff(Index*,Index*), DenseBase::redux()
*/
template <typename Derived>
template <typename Visitor>
EIGEN_DEVICE_FUNC void DenseBase<Derived>::visit(Visitor& visitor) const {
using impl = internal::visit_impl<Derived, Visitor, /*ShortCircuitEvaulation*/ false>;
impl::run(derived(), visitor);
}
namespace internal {
/** \internal
* \brief Base class to implement min and max visitors
*/
template <typename Derived>
struct coeff_visitor {
// default initialization to avoid countless invalid maybe-uninitialized warnings by gcc
EIGEN_DEVICE_FUNC coeff_visitor() : row(-1), col(-1), res(0) {}
typedef typename Derived::Scalar Scalar;
Index row, col;
Scalar res;
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index i, Index j) {
res = value;
row = i;
col = j;
}
};
template <typename Scalar, int NaNPropagation, bool is_min = true>
struct minmax_compare {
typedef typename packet_traits<Scalar>::type Packet;
static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a < b; }
static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_min<NaNPropagation>(p); }
};
template <typename Scalar, int NaNPropagation>
struct minmax_compare<Scalar, NaNPropagation, false> {
typedef typename packet_traits<Scalar>::type Packet;
static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a > b; }
static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_max<NaNPropagation>(p); }
};
// Default implementation used by non-floating types, where we do not
// need special logic for NaN handling.
template <typename Derived, bool is_min, int NaNPropagation,
bool isInt = NumTraits<typename Derived::Scalar>::IsInteger>
struct minmax_coeff_visitor : coeff_visitor<Derived> {
using Scalar = typename Derived::Scalar;
using Packet = typename packet_traits<Scalar>::type;
using Comparator = minmax_compare<Scalar, NaNPropagation, is_min>;
static constexpr Index PacketSize = packet_traits<Scalar>::size;
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index i, Index j) {
if (Comparator::compare(value, this->res)) {
this->res = value;
this->row = i;
this->col = j;
}
}
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index i, Index j) {
Scalar value = Comparator::predux(p);
if (Comparator::compare(value, this->res)) {
const Packet range = preverse(plset<Packet>(Scalar(1)));
Packet mask = pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
}
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index i, Index j) {
Scalar value = Comparator::predux(p);
const Packet range = preverse(plset<Packet>(Scalar(1)));
Packet mask = pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
};
// Suppress NaN. The only case in which we return NaN is if the matrix is all NaN,
// in which case, row=0, col=0 is returned for the location.
template <typename Derived, bool is_min>
struct minmax_coeff_visitor<Derived, is_min, PropagateNumbers, false> : coeff_visitor<Derived> {
typedef typename Derived::Scalar Scalar;
using Packet = typename packet_traits<Scalar>::type;
using Comparator = minmax_compare<Scalar, PropagateNumbers, is_min>;
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index i, Index j) {
if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
this->res = value;
this->row = i;
this->col = j;
}
}
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index i, Index j) {
const Index PacketSize = packet_traits<Scalar>::size;
Scalar value = Comparator::predux(p);
if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
const Packet range = preverse(plset<Packet>(Scalar(1)));
/* mask will be zero for NaNs, so they will be ignored. */
Packet mask = pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
}
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index i, Index j) {
const Index PacketSize = packet_traits<Scalar>::size;
Scalar value = Comparator::predux(p);
if ((numext::isnan)(value)) {
this->res = value;
this->row = 0;
this->col = 0;
return;
}
const Packet range = preverse(plset<Packet>(Scalar(1)));
/* mask will be zero for NaNs, so they will be ignored. */
Packet mask = pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
};
// Propagate NaNs. If the matrix contains NaN, the location of the first NaN
// will be returned in row and col.
template <typename Derived, bool is_min, int NaNPropagation>
struct minmax_coeff_visitor<Derived, is_min, NaNPropagation, false> : coeff_visitor<Derived> {
typedef typename Derived::Scalar Scalar;
using Packet = typename packet_traits<Scalar>::type;
using Comparator = minmax_compare<Scalar, PropagateNaN, is_min>;
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index i, Index j) {
const bool value_is_nan = (numext::isnan)(value);
if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
this->res = value;
this->row = i;
this->col = j;
}
}
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index i, Index j) {
const Index PacketSize = packet_traits<Scalar>::size;
Scalar value = Comparator::predux(p);
const bool value_is_nan = (numext::isnan)(value);
if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
const Packet range = preverse(plset<Packet>(Scalar(1)));
// If the value is NaN, pick the first position of a NaN, otherwise pick the first extremal value.
Packet mask = value_is_nan ? pnot(pcmp_eq(p, p)) : pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
}
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index i, Index j) {
const Index PacketSize = packet_traits<Scalar>::size;
Scalar value = Comparator::predux(p);
const bool value_is_nan = (numext::isnan)(value);
const Packet range = preverse(plset<Packet>(Scalar(1)));
// If the value is NaN, pick the first position of a NaN, otherwise pick the first extremal value.
Packet mask = value_is_nan ? pnot(pcmp_eq(p, p)) : pcmp_eq(pset1<Packet>(value), p);
Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
this->res = value;
this->row = Derived::IsRowMajor ? i : i + max_idx;
this->col = Derived::IsRowMajor ? j + max_idx : j;
}
};
template <typename Derived, bool is_min, int NaNPropagation>
struct functor_traits<minmax_coeff_visitor<Derived, is_min, NaNPropagation>> {
using Scalar = typename Derived::Scalar;
enum { Cost = NumTraits<Scalar>::AddCost, LinearAccess = false, PacketAccess = packet_traits<Scalar>::HasCmp };
};
template <typename Scalar>
struct all_visitor {
using result_type = bool;
using Packet = typename packet_traits<Scalar>::type;
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index, Index) { res = (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index) { res = (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline bool all_predux(const Packet& p) const { return !predux_any(pcmp_eq(p, pzero(p))); }
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index, Index) { res = all_predux(p); }
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index) { res = all_predux(p); }
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index, Index) { res = res && (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index) { res = res && (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index, Index) { res = res && all_predux(p); }
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index) { res = res && all_predux(p); }
EIGEN_DEVICE_FUNC inline bool done() const { return !res; }
bool res = true;
};
template <typename Scalar>
struct functor_traits<all_visitor<Scalar>> {
enum { Cost = NumTraits<Scalar>::ReadCost, LinearAccess = true, PacketAccess = packet_traits<Scalar>::HasCmp };
};
template <typename Scalar>
struct any_visitor {
using result_type = bool;
using Packet = typename packet_traits<Scalar>::type;
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index, Index) { res = (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index) { res = (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline bool any_predux(const Packet& p) const {
return predux_any(pandnot(ptrue(p), pcmp_eq(p, pzero(p))));
}
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index, Index) { res = any_predux(p); }
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index) { res = any_predux(p); }
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index, Index) { res = res || (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index) { res = res || (value != Scalar(0)); }
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index, Index) { res = res || any_predux(p); }
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index) { res = res || any_predux(p); }
EIGEN_DEVICE_FUNC inline bool done() const { return res; }
bool res = false;
};
template <typename Scalar>
struct functor_traits<any_visitor<Scalar>> {
enum { Cost = NumTraits<Scalar>::ReadCost, LinearAccess = true, PacketAccess = packet_traits<Scalar>::HasCmp };
};
template <typename Scalar>
struct count_visitor {
using result_type = Index;
using Packet = typename packet_traits<Scalar>::type;
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index, Index) { res = value != Scalar(0) ? 1 : 0; }
EIGEN_DEVICE_FUNC inline void init(const Scalar& value, Index) { res = value != Scalar(0) ? 1 : 0; }
EIGEN_DEVICE_FUNC inline Index count_redux(const Packet& p) const {
const Packet cst_one = pset1<Packet>(Scalar(1));
Packet true_vals = pandnot(cst_one, pcmp_eq(p, pzero(p)));
Scalar num_true = predux(true_vals);
return static_cast<Index>(num_true);
}
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index, Index) { res = count_redux(p); }
EIGEN_DEVICE_FUNC inline void initpacket(const Packet& p, Index) { res = count_redux(p); }
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index, Index) {
if (value != Scalar(0)) res++;
}
EIGEN_DEVICE_FUNC inline void operator()(const Scalar& value, Index) {
if (value != Scalar(0)) res++;
}
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index, Index) { res += count_redux(p); }
EIGEN_DEVICE_FUNC inline void packet(const Packet& p, Index) { res += count_redux(p); }
Index res = 0;
};
template <typename Scalar>
struct functor_traits<count_visitor<Scalar>> {
enum {
Cost = NumTraits<Scalar>::AddCost,
LinearAccess = true,
// predux is problematic for bool
PacketAccess = packet_traits<Scalar>::HasCmp && packet_traits<Scalar>::HasAdd && !is_same<Scalar, bool>::value
};
};
} // end namespace internal
/** \fn DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
* \returns the minimum of all coefficients of *this and puts in *row and *col its location.
*
* In case \c *this contains NaN, NaNPropagation determines the behavior:
* NaNPropagation == PropagateFast : undefined
* NaNPropagation == PropagateNaN : result is NaN
* NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
* \warning the matrix must be not empty, otherwise an assertion is triggered.
*
* \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
*/
template <typename Derived>
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::minCoeff(IndexType* rowId,
IndexType* colId) const {
eigen_assert(this->rows() > 0 && this->cols() > 0 && "you are using an empty matrix");
internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
this->visit(minVisitor);
*rowId = minVisitor.row;
if (colId) *colId = minVisitor.col;
return minVisitor.res;
}
/** \returns the minimum of all coefficients of *this and puts in *index its location.
*
* In case \c *this contains NaN, NaNPropagation determines the behavior:
* NaNPropagation == PropagateFast : undefined
* NaNPropagation == PropagateNaN : result is NaN
* NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
* \warning the matrix must be not empty, otherwise an assertion is triggered.
*
* \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(),
* DenseBase::minCoeff()
*/
template <typename Derived>
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::minCoeff(IndexType* index) const {
eigen_assert(this->rows() > 0 && this->cols() > 0 && "you are using an empty matrix");
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
this->visit(minVisitor);
*index = IndexType((RowsAtCompileTime == 1) ? minVisitor.col : minVisitor.row);
return minVisitor.res;
}
/** \fn DenseBase<Derived>::maxCoeff(IndexType* rowId, IndexType* colId) const
* \returns the maximum of all coefficients of *this and puts in *row and *col its location.
*
* In case \c *this contains NaN, NaNPropagation determines the behavior:
* NaNPropagation == PropagateFast : undefined
* NaNPropagation == PropagateNaN : result is NaN
* NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
* \warning the matrix must be not empty, otherwise an assertion is triggered.
*
* \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()
*/
template <typename Derived>
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::maxCoeff(IndexType* rowPtr,
IndexType* colPtr) const {
eigen_assert(this->rows() > 0 && this->cols() > 0 && "you are using an empty matrix");
internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
this->visit(maxVisitor);
*rowPtr = maxVisitor.row;
if (colPtr) *colPtr = maxVisitor.col;
return maxVisitor.res;
}
/** \returns the maximum of all coefficients of *this and puts in *index its location.
*
* In case \c *this contains NaN, NaNPropagation determines the behavior:
* NaNPropagation == PropagateFast : undefined
* NaNPropagation == PropagateNaN : result is NaN
* NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
* \warning the matrix must be not empty, otherwise an assertion is triggered.
*
* \sa DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(),
* DenseBase::maxCoeff()
*/
template <typename Derived>
template <int NaNPropagation, typename IndexType>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::maxCoeff(IndexType* index) const {
eigen_assert(this->rows() > 0 && this->cols() > 0 && "you are using an empty matrix");
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
this->visit(maxVisitor);
*index = (RowsAtCompileTime == 1) ? maxVisitor.col : maxVisitor.row;
return maxVisitor.res;
}
/** \returns true if all coefficients are true
*
* Example: \include MatrixBase_all.cpp
* Output: \verbinclude MatrixBase_all.out
*
* \sa any(), Cwise::operator<()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::all() const {
using Visitor = internal::all_visitor<Scalar>;
using impl = internal::visit_impl<Derived, Visitor, /*ShortCircuitEvaulation*/ true>;
Visitor visitor;
impl::run(derived(), visitor);
return visitor.res;
}
/** \returns true if at least one coefficient is true
*
* \sa all()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::any() const {
using Visitor = internal::any_visitor<Scalar>;
using impl = internal::visit_impl<Derived, Visitor, /*ShortCircuitEvaulation*/ true>;
Visitor visitor;
impl::run(derived(), visitor);
return visitor.res;
}
/** \returns the number of coefficients which evaluate to true
*
* \sa all(), any()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC Index DenseBase<Derived>::count() const {
using Visitor = internal::count_visitor<Scalar>;
using impl = internal::visit_impl<Derived, Visitor, /*ShortCircuitEvaulation*/ false>;
Visitor visitor;
impl::run(derived(), visitor);
return visitor.res;
}
template <typename Derived>
EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::hasNaN() const {
return derived().cwiseTypedNotEqual(derived()).any();
}
/** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values.
*
* \sa hasNaN()
*/
template <typename Derived>
EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::allFinite() const {
return derived().array().isFinite().all();
}
} // end namespace Eigen
#endif // EIGEN_VISITOR_H