comms::math Namespace Reference

Functions
bool	cholesky_decompose (double *A, size_t n, double *L)
	Linear algebra operations for sensor calibration and filtering.
void	solve_lower_triangular (const double *L, size_t n, const double *b, double *x)
void	solve_upper_triangular (const double *L, size_t n, const double *b, double *x)
bool	solve_cholesky (const double *A, size_t n, const double *b, double *x)
bool	matrix_inverse_cholesky (const double *A, size_t n, double *A_inv)
bool	weighted_least_squares (const double *X, size_t m, size_t n, const double *y, const double *W_diag, double *beta)
bool	regularized_weighted_least_squares (const double *X, size_t m, size_t n, const double *y, const double *W_diag, double lambda, double *beta)
void	matrix_multiply (const double *A, size_t m, size_t n, const double *B, size_t p, double *C)
	Matrix operations for sensor calibration and filtering.
void	matrix_transpose (const double *A, size_t m, size_t n, double *B)
void	matrix_add (const double *A, const double *B, size_t m, size_t n, double *C)
void	matrix_subtract (const double *A, const double *B, size_t m, size_t n, double *C)
void	matrix_scale (const double *A, double alpha, size_t m, size_t n, double *B)
void	matrix_zeros (double *A, size_t m, size_t n)
void	matrix_identity (double *A, size_t n)
void	matrix_copy (const double *A, size_t m, size_t n, double *B)
void	matrix_vector_multiply (const double *A, size_t m, size_t n, const double *x, double *y)
double	vector_dot (const double *a, const double *b, size_t n)
double	vector_norm (const double *a, size_t n)
double	matrix_trace (const double *A, size_t n)

Function Documentation

cholesky_decompose()

bool comms::math::cholesky_decompose ( double * A, size_t n, double * L )

inline

Linear algebra operations for sensor calibration and filtering.

Standalone implementation for DAQ system. Provides matrix decompositions, solving, and advanced operations needed for Bayesian calibration and filtering algorithms.

Definition at line 24 of file LinearAlgebra.hpp.

References matrix_zeros().

Referenced by matrix_inverse_cholesky(), and solve_cholesky().

matrix_add()

void comms::math::matrix_add ( const double * A, const double * B, size_t m, size_t n, double * C )

inline

Definition at line 47 of file Matrix.hpp.

matrix_copy()

void comms::math::matrix_copy ( const double * A, size_t m, size_t n, double * B )

inline

Definition at line 83 of file Matrix.hpp.

matrix_identity()

void comms::math::matrix_identity ( double * A, size_t n )

inline

Definition at line 75 of file Matrix.hpp.

References matrix_zeros().

matrix_inverse_cholesky()

bool comms::math::matrix_inverse_cholesky ( const double * A, size_t n, double * A_inv )

inline

Definition at line 101 of file LinearAlgebra.hpp.

References b, cholesky_decompose(), solve_lower_triangular(), and solve_upper_triangular().

matrix_multiply()

void comms::math::matrix_multiply ( const double * A, size_t m, size_t n, const double * B, size_t p, double * C )

inline

Matrix operations for sensor calibration and filtering.

Standalone implementation for DAQ system. Provides essential matrix operations needed for calibration algorithms.

Definition at line 22 of file Matrix.hpp.

References p.

matrix_scale()

void comms::math::matrix_scale ( const double * A, double alpha, size_t m, size_t n, double * B )

inline

Definition at line 63 of file Matrix.hpp.

matrix_subtract()

void comms::math::matrix_subtract ( const double * A, const double * B, size_t m, size_t n, double * C )

inline

Definition at line 55 of file Matrix.hpp.

matrix_trace()

double comms::math::matrix_trace ( const double * A, size_t n )

inline

Definition at line 115 of file Matrix.hpp.

matrix_transpose()

void comms::math::matrix_transpose ( const double * A, size_t m, size_t n, double * B )

inline

Definition at line 37 of file Matrix.hpp.

matrix_vector_multiply()

void comms::math::matrix_vector_multiply ( const double * A, size_t m, size_t n, const double * x, double * y )

inline

Definition at line 89 of file Matrix.hpp.

matrix_zeros()

void comms::math::matrix_zeros ( double * A, size_t m, size_t n )

inline

Definition at line 70 of file Matrix.hpp.

Referenced by cholesky_decompose(), matrix_identity(), regularized_weighted_least_squares(), and weighted_least_squares().

regularized_weighted_least_squares()

bool comms::math::regularized_weighted_least_squares ( const double * X, size_t m, size_t n, const double * y, const double * W_diag, double lambda, double * beta )

inline

Definition at line 179 of file LinearAlgebra.hpp.

References matrix_zeros(), solve_cholesky(), and success.

solve_cholesky()

bool comms::math::solve_cholesky ( const double * A, size_t n, const double * b, double * x )

inline

Definition at line 77 of file LinearAlgebra.hpp.

References b, cholesky_decompose(), solve_lower_triangular(), and solve_upper_triangular().

Referenced by regularized_weighted_least_squares(), and weighted_least_squares().

solve_lower_triangular()

void comms::math::solve_lower_triangular ( const double * L, size_t n, const double * b, double * x )

inline

Definition at line 54 of file LinearAlgebra.hpp.

References b.

Referenced by matrix_inverse_cholesky(), and solve_cholesky().

solve_upper_triangular()

void comms::math::solve_upper_triangular ( const double * L, size_t n, const double * b, double * x )

inline

Definition at line 65 of file LinearAlgebra.hpp.

References b.

Referenced by matrix_inverse_cholesky(), and solve_cholesky().

vector_dot()

double comms::math::vector_dot ( const double * a, const double * b, size_t n )

inline

Definition at line 101 of file Matrix.hpp.

References a, and b.

Referenced by vector_norm().

vector_norm()

double comms::math::vector_norm ( const double * a, size_t n )

inline

Definition at line 110 of file Matrix.hpp.

References a, and vector_dot().

weighted_least_squares()

bool comms::math::weighted_least_squares ( const double * X, size_t m, size_t n, const double * y, const double * W_diag, double * beta )

inline

Definition at line 141 of file LinearAlgebra.hpp.

References matrix_zeros(), solve_cholesky(), and success.