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HDIM
1.0.0
Packages for High Dimensional Linear Regression
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HDIM
1.0.0
Packages for High Dimensional Linear Regression
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Generic linear algebra functions. More...
#include <fenv.h>#include <chrono>#include <fstream>#include <vector>#include <eigen3/Eigen/Dense>Go to the source code of this file.
Classes | |
| struct | hdim::Binarize< T > |
| Functor to convert vector of values into support vector. More... | |
| struct | hdim::SoftThres< T > |
| Soft Threshold functor used to apply hdim::soft_threshold to each element in a matrix or vector. More... | |
| struct | hdim::SupportSift< T > |
Functions | |
| template<typename T > | |
| T | hdim::StdDev (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &vect) |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > | hdim::Normalize (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &mat) |
| Set the mean of a matrix to 0 and the standard deviation to 1. More... | |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > | hdim::Normalize (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &mat) |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, 1 > | hdim::Normalize (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &mat) |
| Overloaded version of hdim::Normalize to accomadate vectors. | |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, 1 > | hdim::Normalize (Eigen::Matrix< T, Eigen::Dynamic, 1 > &mat) |
| Overloaded version of hdim::Normalize to accomadate vectors. | |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > | hdim::build_matrix (unsigned int num_rows, unsigned int num_cols, T(*mat_func)(unsigned int, unsigned int)) |
| Generate a matrix using a function that depends on row and column indices. More... | |
| template<typename T > | |
| void | hdim::sweep_matrix (Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &mat, T(*mat_func)(unsigned int, unsigned int)) |
| sweep_matrix More... | |
| template<typename T > | |
| T | hdim::square (T &val) |
| Compute the square of a value. More... | |
| template<typename T > | |
| std::vector< T > | hdim::LogScaleVector (T lower_bound, T upper_bound, unsigned int num_elements) |
| Generate a vector of logarithmically equally spaced points. More... | |
| template<typename T > | |
| T | hdim::sgn (T val) |
| The sign function defined as. More... | |
| template<typename T > | |
| T | hdim::pos_part (T x) |
| The positive part function defined as. More... | |
| template<typename T > | |
| T | hdim::soft_threshold (T x, T y) |
| The proximal ( soft thresholding ) operator defined as. More... | |
| template<typename T > | |
| T | hdim::prox (T x, T lambda) |
| A functional equivalent of hdim::soft_threshold, but possibly faster. | |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, 1 > | hdim::soft_threshold_mat (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &mat, const T lambda) |
| template<typename T > | |
| Eigen::Matrix< int, Eigen::Dynamic, 1 > | hdim::GenerateSupport (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &coefficients, T cut_off) |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > | hdim::negative_index (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &mat_in, int index) |
| template<typename T > | |
| T | hdim::duality_gap (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &X, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &Y, const Eigen::Matrix< T, Eigen::Dynamic, 1 > &Beta, T r_stats_it) |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > | hdim::slice (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &org, const std::vector< unsigned int > &indices) |
| template<typename T > | |
| Eigen::Matrix< T, Eigen::Dynamic, 1 > | hdim::slice (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &org, const std::vector< unsigned int > &indices) |
Generic linear algebra functions.
Definition in file generics.hpp.
| Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> hdim::build_matrix | ( | unsigned int | num_rows, |
| unsigned int | num_cols, | ||
| T(*)(unsigned int, unsigned int) | mat_func | ||
| ) |
Generate a matrix using a function that depends on row and column indices.
That is 
for some function f and an input matrix A.
| num_rows | Number of rows the output matrix should have |
| num_cols | Number of columns the output matrix should have |
Definition at line 131 of file generics.hpp.
| std::vector< T > hdim::LogScaleVector | ( | T | lower_bound, |
| T | upper_bound, | ||
| unsigned int | num_elements | ||
| ) |
Generate a vector of logarithmically equally spaced points.
There will be num_element points, beginning at log10( lower_bound ) and ending at log10( upper_bound ).
This function is semantically equivalent to the R function 'logspace'.
| lower_bound | 10^x for x = smallest element in vector |
| upper_bound | 10^x for x = largest element in vector |
| num_elements | number of elements in the generated vector |
Vector of logarithmically equally spaced points
Definition at line 198 of file generics.hpp.
| Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> hdim::Normalize | ( | const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & | mat | ) |
Set the mean of a matrix to 0 and the standard deviation to 1.
Note this function is done in place, that is the input matrix is modified.
| mat | An n x m matrix to be normalized. |
Definition at line 67 of file generics.hpp.
| T hdim::pos_part | ( | T | x | ) |
| T hdim::sgn | ( | T | val | ) |
| T hdim::soft_threshold | ( | T | x, |
| T | y | ||
| ) |
The proximal ( soft thresholding ) operator defined as.
![\[ \tau( x, y ) \equiv sgn(x) \left( \lvert x \rvert - y \right)^{+} \]](form_3.png)
| val |
Definition at line 276 of file generics.hpp.
| T hdim::square | ( | T & | val | ) |
Compute the square of a value.
| val | value to square |
Definition at line 169 of file generics.hpp.
| void hdim::sweep_matrix | ( | Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & | mat, |
| T(*)(unsigned int, unsigned int) | mat_func | ||
| ) |
1.8.11 ![\[ x^{+} \equiv \begin{cases} x & \text{if } x \geq 0\\ 0 & \text{if } x < 0\\ \end{cases} \]](form_2.png)
![\[ sgn(x) \equiv \begin{cases} 1 & \text{if } x > 0 \\ 0 & \text{if } x = 0 \\ -1& \text{if } x < 0 \end{cases} \]](form_1.png)