math.hpp File Reference

#include <Eigen/Core>
#include <limits>
#include <vector>

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Classes
struct	proxsuite::nlp::math_types< _Scalar >
	Typedefs for math (Eigen vectors, matrices) depending on scalar type. More...

Namespaces
namespace	proxsuite
	Main package namespace.
namespace	proxsuite::nlp::math
	Math utilities.

Macros
#define	PROXSUITE_NLP_DYNAMIC_TYPEDEFS(Scalar)

Typedefs
template<typename T, typename T2 = void>
using	proxsuite::nlp::enable_if_eigen_dense = std::enable_if_t<is_eigen_dense_type<T>, T2>

Functions
template<typename MatType>
MatType::Scalar	proxsuite::nlp::math::infty_norm (const Eigen::MatrixBase< MatType > &z)
template<typename MatType>
MatType::Scalar	proxsuite::nlp::math::infty_norm (const std::vector< MatType > &z)
template<typename Scalar>
bool	proxsuite::nlp::math::check_scalar (const Scalar value)
	Check that a scalar is neither inf, nor NaN.
template<typename Scalar>
bool	proxsuite::nlp::math::scalar_close (const Scalar a, const Scalar b, const Scalar prec=std::numeric_limits< Scalar >::epsilon())
	Tests whether a and b are close, within absolute and relative precision prec.
template<typename T, typename = std::enable_if_t<std::is_scalar<T>::value>>
bool	proxsuite::nlp::math::check_value (const T &x)
template<typename MatrixType>
bool	proxsuite::nlp::math::check_value (const Eigen::MatrixBase< MatrixType > &x)
template<typename T>
T	proxsuite::nlp::math::sign (const T &x)

Variables
template<typename T>
constexpr bool	proxsuite::nlp::is_eigen_dense_type
template<typename T>
constexpr bool	proxsuite::nlp::is_eigen_matrix_type

Detailed Description

Copyright

Copyright (C) 2022 LAAS-CNRS, INRIA

Definition in file math.hpp.

Macro Definition Documentation

PROXSUITE_NLP_DYNAMIC_TYPEDEFS

#define PROXSUITE_NLP_DYNAMIC_TYPEDEFS

(

Scalar

)

Value:

  using VectorXs = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;                   \
  using MatrixXs = Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>;      \
  using VectorOfVectors = std::vector<VectorXs>;                               \
  using VectorRef = Eigen::Ref<VectorXs>;                                      \
  using MatrixRef = Eigen::Ref<MatrixXs>;                                      \
  using ConstVectorRef = Eigen::Ref<const VectorXs>;                           \
  using ConstMatrixRef = Eigen::Ref<const MatrixXs>;                           \
  using VectorOfRef = std::vector<VectorRef>;                                  \
  using Vector3s = Eigen::Matrix<Scalar, 3, 1>;                                \
  using Vector6s = Eigen::Matrix<Scalar, 6, 1>;                                \
  using Matrix3Xs = Eigen::Matrix<Scalar, 3, Eigen::Dynamic>;                  \
  using Matrix6Xs = Eigen::Matrix<Scalar, 6, Eigen::Dynamic>;                  \
  using Matrix6s = Eigen::Matrix<Scalar, 6, 6>

Macro typedefs for dynamic-sized vectors/matrices, used for cost funcs, merit funcs because we don't CRTP them and virtual members funcs can't be templated.

Definition at line 26 of file math.hpp.

Typedef Documentation

enable_if_eigen_dense

template<typename T, typename T2 = void>

using proxsuite::nlp::enable_if_eigen_dense = std::enable_if_t<is_eigen_dense_type<T>, T2>

Definition at line 21 of file math.hpp.

Variable Documentation

is_eigen_dense_type

template<typename T>

bool proxsuite::nlp::is_eigen_dense_type

constexpr

Initial value:

=
    std::is_base_of<Eigen::DenseBase<T>, T>::value

Definition at line 13 of file math.hpp.

is_eigen_matrix_type

template<typename T>

bool proxsuite::nlp::is_eigen_matrix_type

constexpr

Initial value:

=
    std::is_base_of<Eigen::MatrixBase<T>, T>::value

Definition at line 17 of file math.hpp.