<?php
use Aboks\PowerIteration\PowerIteration;
use MathPHP\LinearAlgebra\MatrixFactory;

$power_iteration = new PowerIteration();
$dominant_eigenpair = $power_iteration->getDominantEigenpair(MatrixFactory::create([
    [2, 1],
    [0, 1]
 ]));
var_dump($dominant_eigenpair->getEigenvalue()); // 2
var_dump($dominant_eigenpair->getEigenvector()); // Vector([1, 0]), or a scalar multiple

<?php
use Aboks\PowerIteration\PowerIteration;
use MathPHP\LinearAlgebra\Matrix;

$power_iteration = new PowerIteration();
$dominant_eigenpair = $power_iteration->getLeastDominantEigenpair(MatrixFactory::create([
    [2, 1],
    [0, 1]
 ]));
var_dump($dominant_eigenpair->getEigenvalue()); // 1
var_dump($dominant_eigenpair->getEigenvector()); // Vector([√2, -√2]), or a scalar multiple

<?php
use Aboks\PowerIteration\PowerIteration;
use Aboks\PowerIteration\StoppingCriterion\MaxIterations;
use Aboks\PowerIteration\StoppingCriterion\EigenvectorTolerance;

new PowerIteration(new MaxIterations(10));           // will stop after 10 iterations
new PowerIteration(new EigenvectorTolerance(0.01));  // will stop when ‖Av - λv‖ < 0.01

<?php
use Aboks\PowerIteration\PowerIteration;
use Aboks\PowerIteration\ScalingMethod\NormBased;
use Aboks\PowerIteration\Norm\MaxNorm;

new PowerIteration(null, new NormBased(new MaxNorm()));  // will scale to a unit vector based on the max-norm