/**
* @param NumericMatrix $mA
* @param NumericTypeInterface $start
* @param NumericTypeInterface $target
* @param NumericTypeInterface $limit
*
* @return NumericMatrix
*/
protected function walk(NumericMatrix $mA, NumericTypeInterface $start, NumericTypeInterface $target, NumericTypeInterface $limit)
{
$zero = TypeFactory::createInt(0);
$one = TypeFactory::createInt(1);
$calc = new Calculator();
$comp = new Comparator();
$lim = $calc->sub($limit, $one);
$walk = [$start];
while ($comp->neq($start, $target) && $comp->neq($lim, $zero)) {
$start = $mA('MarkovWeightedRandom', $start);
$walk[] = $start;
$lim = $calc->sub($lim, $one);
}
return new NumericMatrix($walk);
}
/**
* @param $sum
* @param $rowArray
*
* @return mixed
*
* @throws MathMatrixException
*/
protected function getNextRow($sum, $rowArray)
{
return FFor::create(['sum' => $sum, 'rowArray' => $rowArray])->targetWeight(function ($sum) {
return TypeFactory::createInt(mt_rand(1, $sum()));
})->nextRow(function ($targetWeight, $rowArray) {
foreach ($rowArray as $key => $weight) {
if ($this->comp->lt($weight, $this->zero)) {
throw new MathMatrixException('Negative weights not allowed');
}
$targetWeight = $this->calc->sub($targetWeight, $weight);
if ($this->comp->lte($targetWeight, $this->zero)) {
return TypeFactory::createInt($key + 1);
}
}
})->fyield('nextRow');
}
/**
* Subtract a single scalar value from each member of the matrix and return result
* Boolean values are converted to 0 (false) and 1 (true). Use the logical
* computations if required.
* String values do a string replace for the scalar, replacing occurences of
* if with ''
*
* @param NumericMatrix $mA First matrix to act on - required
* @param scalar $extra value to subtract
*
* @return Matrix
*
* @throws Chippyash/Matrix/Exceptions/ComputationException
*/
public function compute(NumericMatrix $mA, $extra = null)
{
if ($mA->is('empty')) {
return $this->createCorrectMatrixType($mA);
}
$scalar = $this->createCorrectScalarType($mA, $extra);
$data = $mA->toArray();
$lx = $mA->columns();
$ly = $mA->rows();
$calc = new Calculator();
for ($row = 0; $row < $ly; $row++) {
for ($col = 0; $col < $lx; $col++) {
$data[$row][$col] = $calc->sub($data[$row][$col], $scalar);
}
}
return $this->createCorrectMatrixType($mA, $data);
}
/**
* @inheritDoc
*/
protected function doCompute(NumericTypeInterface $a, NumericTypeInterface $b, Calculator $calc)
{
return $calc->sub($a, $b);
}
/**
* LU Decomposition constructor.
*
* @param \Chippyash\Math\Matrix\NumericMatrix $mA
*/
protected function LUDecomposition(NumericMatrix $mA)
{
// Use a "left-looking", dot-product, Crout/Doolittle algorithm.
$LU = $mA->toArray();
$m = $this->rows = $mA->rows();
$n = $this->cols = $mA->columns();
for ($i = 0; $i < $m; $i++) {
$this->piv[$i] = $i;
}
$this->pivsign = 1;
$LUrowi = [];
$LUcolj = [];
$calc = new Calculator();
$comp = new Comparator();
$zeroInt = $this->createCorrectScalarType($mA, 0);
// Outer loop.
for ($j = 0; $j < $n; $j++) {
// Make a copy of the j-th column to localize references.
for ($i = 0; $i < $m; $i++) {
$LUcolj[$i] =& $LU[$i][$j];
}
// Apply previous transformations.
for ($i = 0; $i < $m; $i++) {
$LUrowi = $LU[$i];
// Most of the time is spent in the following dot product.
$kmax = min($i, $j);
$s = clone $zeroInt;
for ($k = 0; $k < $kmax; $k++) {
$s = $calc->add($s, $calc->mul($LUrowi[$k], $LUcolj[$k]));
}
$LUcolj[$i] = $calc->sub($LUcolj[$i], $s);
$LUrowi[$j] = $LUcolj[$i];
}
// Find pivot and exchange if necessary.
$p = $j;
for ($i = $j + 1; $i < $m; $i++) {
if ($comp->gt($LUcolj[$i]->abs(), $LUcolj[$p]->abs())) {
$p = $i;
}
}
if ($p != $j) {
for ($k = 0; $k < $n; $k++) {
//swap
$t = $LU[$p][$k];
$LU[$p][$k] = $LU[$j][$k];
$LU[$j][$k] = $t;
}
$k = $this->piv[$p];
$this->piv[$p] = $this->piv[$j];
$this->piv[$j] = $k;
$this->pivsign = $this->pivsign * -1;
}
// Compute multipliers.
if ($j < $m && $comp->neq($LU[$j][$j], $zeroInt)) {
for ($i = $j + 1; $i < $m; $i++) {
$LU[$i][$j] = $calc->div($LU[$i][$j], $LU[$j][$j]);
}
}
}
$this->set('LU', $this->createCorrectMatrixType($mA, $LU));
}
