-: matfaust::factparams::StoppingCriterion Class Reference

This class defines a StoppingCriterion for the FAuST's algorithms. More...

Public Member Functions
function	display (self)
	Displays a StoppingCriterion instance. More...

function	StoppingCriterion (varargin)
	Constructor. More...

Public Attributes
Property	num_its
	see matfaust.factparams.StoppingCriterion More...

Property	tol
	see matfaust.factparams.StoppingCriterion More...

Property	maxiter
	see matfaust.factparams.StoppingCriterion More...

Property	relerr
	see matfaust.factparams.StoppingCriterion More...

Property	erreps
	see matfaust.factparams.StoppingCriterion More...

Constant Property	DEFAULT_MAXITER = 10000

Constant Property	DEFAULT_NUMITS = 500

Constant Property	DEFAULT_TOL = .3

Detailed Description

This class defines a StoppingCriterion for the FAuST's algorithms.

A stopping criterion can be of two kinds:

- number of iterations,
- error treshold for the approximation of the matrix.

Constructor & Destructor Documentation

◆ StoppingCriterion()

function matfaust::factparams::StoppingCriterion::StoppingCriterion ( varargin )

Constructor.

Parameters

'numits',int	the fixed number of iterations of the algorithm. By default the value is DEFAULT_NUMITS. If arguments num_its and tol are used together only the last one in the argument list is taken into account.
'tol',real	error target according to the algorithm is stopped. If arguments num_its and tol are used together only the last one in the argument list is taken into account.
'maxiter',int	the maximum number of iterations to run the algorithm, whatever is the criterion used (tol or num_its).
'relerr',bool	false to define a absolute error with tol, true for a relative error (in this case the 'relmat' matrix will be used to convert internally the given 'tol' to the corresponding absolute error).
'relmat',matrix	the matrix against which is defined the relative error. if relerr is True, this argument is mandatory.

Example:

>> import matfaust.factparams.StoppingCriterion
>> s = StoppingCriterion(5)
num_its 5:
maxiter 10000:
>> s = StoppingCriterion(.5)
tol: 0.500000
relerr: 0
maxiter: 10000
>> s = StoppingCriterion('tol', .5)
tol: 0.500000
relerr: 0
maxiter: 10000
>> s = StoppingCriterion('numits', 5)
num_its 500:
maxiter 10000:
>> s = StoppingCriterion('tol', .2, 'relerr', true, 'relmat', rand(10,10))
tol: 1.210149
relerr: 1
maxiter: 10000