least_squares.cc File Reference

#include "least_squares.h"
#include <valarray>
#include <stdexcept>
#include <limits>

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Namespaces
namespace	least_squares
Defines
#define	V(T)   std::valarray< T >
#define	M(T)   std::valarray< V(T) >
Functions
template<class T >
void	least_squares::invert (M(T)&m)
	Invert a matrix, in-place, using Gauss-Jordan elimination.
template void	least_squares::invert (M(float)&m)
template void	least_squares::invert (M(double)&m)
template<class T >
	least_squares::V (T) linearFit(const M(T)&x
	Returns parameters 'a' via ordinary least squares such that y = x·a.
template	least_squares::V (float) linearFit(const M(float)&x
template	least_squares::V (double) linearFit(const M(double)&x

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Define Documentation

#define M

(

T

)

std::valarray< V(T) >

Definition at line 6 of file least_squares.cc.

Referenced by SiftTekkotsu::getModelName(), KnowledgeBase::learn(), KnowledgeBase::learn_newModel(), KnowledgeBase::learn_newObject(), KnowledgeBase::readFromFile(), SiftTekkotsu::setModelName(), KnowledgeBase::unlearn_Model(), and KnowledgeBase::unlearn_Object().

#define V

(

T

)

std::valarray< T >

Definition at line 5 of file least_squares.cc.

Referenced by Homography33::compute(), computePositionKExample(), XWalkMC::computePressure(), and Homography::getMatrix().