math.h File Reference

Mathematical support functions for the slope package. More...

#include "clusters.h"
#include "jit_normalization.h"
#include <Eigen/Core>
#include <Eigen/SparseCore>
#include <numeric>
#include <vector>

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Namespaces
namespace	slope
	Namespace containing SLOPE regression implementation.

Functions
template<typename T >
int	slope::sign (T val)
	Returns the sign of a given value.
template<typename T >
Eigen::ArrayXd	slope::cumSum (const T &x)
template<typename T >
T	slope::sigmoid (const T &x)
template<typename T >
T	slope::logit (const T &x)
template<typename T >
T	slope::clamp (const T &x, const T &lo, const T &hi)
Eigen::VectorXd	slope::logSumExp (const Eigen::MatrixXd &a)
Eigen::MatrixXd	slope::softmax (const Eigen::MatrixXd &a)
template<typename T >
Eigen::MatrixXd	slope::linearPredictor (const T &x, const std::vector< int > &active_set, const Eigen::VectorXd &beta0, const Eigen::VectorXd &beta, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const JitNormalization jit_normalization, const bool intercept)
template<typename T >
void	slope::updateGradient (Eigen::VectorXd &gradient, const T &x, const Eigen::MatrixXd &residual, const std::vector< int > &active_set, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const Eigen::VectorXd &w, const JitNormalization jit_normalization)
template<typename T >
void	slope::offsetGradient (Eigen::VectorXd &gradient, const T &x, const Eigen::VectorXd &offset, const std::vector< int > &active_set, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const JitNormalization jit_normalization)
std::vector< int >	slope::setUnion (const std::vector< int > &a, const std::vector< int > &b)
	Computes the union of two sorted integer vectors.
std::vector< int >	slope::setDiff (const std::vector< int > &a, const std::vector< int > &b)
	Computes the set difference of two sorted integer vectors.
template<typename T >
int	slope::whichMax (const T &x)
	Returns the index of the maximum element in a container.
template<typename T >
int	slope::whichMin (const T &x)
	Returns the index of the minimum element in a container.
template<typename T , typename Comparator >
int	slope::whichBest (const T &x, const Comparator &comp)
	Returns the index of the minimum element in a container.
Eigen::ArrayXd	slope::geomSpace (const double start, const double end, const int n)
	Creates an array of n numbers in geometric progression from start to end.
template<typename T >
Eigen::VectorXd	slope::l1Norms (const T &x)
	Computes the L1 (Manhattan) norms for each column of a matrix.
Eigen::VectorXd	slope::l2Norms (const Eigen::SparseMatrix< double > &x)
	Computes the L2 (Euclidean) norms for each column of a sparse matrix.
Eigen::VectorXd	slope::l2Norms (const Eigen::MatrixXd &x)
	Computes the L2 (Euclidean) norms for each column of a dense matrix.
Eigen::VectorXd	slope::maxAbs (const Eigen::SparseMatrix< double > &x)
	Computes the maximum absolute value for each column of a matrix.
Eigen::VectorXd	slope::maxAbs (const Eigen::MatrixXd &x)
	Computes the maximum absolute value for each column of a dense matrix.
Eigen::VectorXd	slope::means (const Eigen::SparseMatrix< double > &x)
	Computes the arithmetic mean for each column of a sparse matrix.
Eigen::VectorXd	slope::means (const Eigen::MatrixXd &x)
	Computes the arithmetic mean for each column of a dense matrix.
Eigen::VectorXd	slope::stdDevs (const Eigen::SparseMatrix< double > &x)
	Computes the standard deviation for each column of a matrix.
Eigen::VectorXd	slope::stdDevs (const Eigen::MatrixXd &x)
	Computes the standard deviation for each column of a matrix.
Eigen::VectorXd	slope::ranges (const Eigen::SparseMatrix< double > &x)
	Computes the range (max - min) for each column of a matrix.
Eigen::VectorXd	slope::ranges (const Eigen::MatrixXd &x)
	Computes the range (max - min) for each column of a dense matrix.
Eigen::VectorXd	slope::mins (const Eigen::SparseMatrix< double > &x)
	Computes the minimum value for each column of a sparse matrix.
Eigen::VectorXd	slope::mins (const Eigen::MatrixXd &x)
	Computes the minimum value for each column of a dense matrix.
template<typename T >
Eigen::VectorXd	slope::clusterGradient (Eigen::VectorXd &beta, Eigen::VectorXd &residual, Clusters &clusters, const T &x, const Eigen::VectorXd &w, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, const JitNormalization jit_normalization)

Detailed Description

Mathematical support functions for the slope package.

Definition in file math.h.