public function testRandomize()
{
$hmm = new slHiddenMarkovModel(4, array(1, 2, 3));
$hmm->randomize();
$size = count($hmm);
for ($x = 0; $x < $size; ++$x) {
$rowSum = 0;
for ($y = 0; $y < $size; ++$y) {
$rowSum += $hmm->getTransition($x, $y);
}
$this->assertEquals(1.0, $rowSum, null, 0.001);
}
}
/**
* Train the HMM with the given input sequence
*
* @param slHiddenMarkovModel $hmm
* @param array $sequence
* @return void
*/
public function train(slHiddenMarkovModel $hmm, array $sequence)
{
$sequence = $hmm->mapLabels($sequence);
$sequenceLength = count($sequence);
$oldHmm = clone $hmm;
$states = count($hmm);
$labels = $hmm->countLabels();
// Calculate forward and backwards variables, first
$forward = $this->calcForward($oldHmm, $sequence);
$backward = $this->calcBackwards($oldHmm, $sequence);
// Reevaluate the start probabilities
for ($i = 0; $i < $states; ++$i) {
$hmm->setStart($i, $this->calcGamma($oldHmm, $i, 0, $sequence, $forward, $backward));
}
// Reevaluate the transistion probabilities
for ($i = 0; $i < $states; ++$i) {
for ($j = 0; $j < $states; ++$j) {
$numerator = 0;
$denominator = 0;
for ($t = 0; $t <= $sequenceLength - 1; ++$t) {
$numerator += $this->calcP($oldHmm, $t, $i, $j, $sequence, $forward, $backward);
$denominator += $this->calcGamma($oldHmm, $i, $t, $sequence, $forward, $backward);
}
$hmm->setTransition($i, $j, $this->divide($numerator, $denominator));
}
}
// Reevaluate the emission probabilities
for ($i = 0; $i < $states; ++$i) {
for ($k = 0; $k < $labels; ++$k) {
for ($t = 0; $t <= $sequenceLength - 1; ++$t) {
$gamma = $this->calcGamma($oldHmm, $i, $t, $sequence, $forward, $backward);
$numerator += $gamma * ($k == $sequence[$t] ? 1 : 0);
$denominator += $gamma;
}
$hmm->setEmission($i, $k, $this->divide($numerator, $denominator));
}
}
}
/**
* Test example train
*
* As documented here:
* http://www.indiana.edu/~iulg/moss/hmmcalculations.pdf
*
* @return void
*/
public function testSimpleTrain()
{
$hmm = new slHiddenMarkovModel(2, array('A', 'B'));
// Initialize the model
$hmm->setStart(0, 0.85);
$hmm->setStart(1, 0.15);
$hmm->setTransition(0, 0, 0.3);
$hmm->setTransition(0, 1, 0.7);
$hmm->setTransition(1, 0, 0.1);
$hmm->setTransition(1, 1, 0.9);
$hmm->setEmission(0, 0, 0.4);
$hmm->setEmission(0, 1, 0.6);
$hmm->setEmission(1, 0, 0.5);
$hmm->setEmission(1, 1, 0.5);
$trainer = new slBaumWelchTrainer();
$trainer->trainCycle($hmm, array('A', 'B', 'B', 'A'), 1);
$trainer->trainCycle($hmm, array('B', 'A', 'B'), 1);
}
