pcgsolver.cpp File Reference

#include <iostream>
#include <fstream>
#include <iomanip>
#include <math.h>
#include "vector.hpp"
#include "matrix.hpp"
#include "sparsemat.hpp"

Include dependency graph for pcgsolver.cpp:

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Functions
void	PCG (const Operator &A, const Operator &B, const Vector &b, Vector &x, int print_iter=0, int max_num_iter=1000, double RTOLERANCE=10e-12, double ATOLERANCE=10e-24, int save=0)
void	SLI (const Operator &A, const Operator &B, const Vector &b, Vector &x, int print_iter=0, int max_num_iter=1000, double RTOLERANCE=10e-12, double ATOLERANCE=10e-24)
	Stationary linear iteration: x <- x + B (b - A x)

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Function Documentation

void PCG	(	const Operator &	A,
		const Operator &	B,
		const Vector &	b,
		Vector &	x,
		int	print_iter = 0,
		int	max_num_iter = 1000,
		double	RTOLERANCE = 10e-12,
		double	ATOLERANCE = 10e-24,
		int	save = 0
	)

Preconditioned conjugate gradient method. Given Matrix A, preconditioner Matrix B, vector b and initial guess x, iteratively solve A x = b. When the default arguments are used PCG doesn't print current residuals and number of iterations, maximum number of iterations is 1000, the relative tolerance is 10e-12 and the absolute tolerance is 10e-24. Remark : if no better initial guess is available, the user may set it as B b (since not done in PCG routine).

Definition at line 22 of file pcgsolver.cpp.

References add(), Operator::Mult(), Vector::Print(), Vector::Size(), and subtract().

Referenced by main().

void SLI	(	const Operator &	A,
		const Operator &	B,
		const Vector &	b,
		Vector &	x,
		int	print_iter = 0,
		int	max_num_iter = 1000,
		double	RTOLERANCE = 10e-12,
		double	ATOLERANCE = 10e-24
	)

Stationary linear iteration: x <- x + B (b - A x)

Definition at line 115 of file pcgsolver.cpp.

References add(), Operator::Mult(), Vector::Size(), and subtract().