Developer
<?php
namespace Matrix\Decomposition;
use Matrix\Exception;
use Matrix\Matrix;
class LU
{
private $luMatrix;
private $rows;
private $columns;
private $pivot = [];
public function __construct(Matrix $matrix)
{
$this->luMatrix = $matrix->toArray();
$this->rows = $matrix->rows;
$this->columns = $matrix->columns;
$this->buildPivot();
}
/**
* Get lower triangular factor.
*
* @return Matrix Lower triangular factor
*/
public function getL(): Matrix
{
$lower = [];
$columns = min($this->rows, $this->columns);
for ($row = 0; $row < $this->rows; ++$row) {
for ($column = 0; $column < $columns; ++$column) {
if ($row > $column) {
$lower[$row][$column] = $this->luMatrix[$row][$column];
} elseif ($row === $column) {
$lower[$row][$column] = 1.0;
} else {
$lower[$row][$column] = 0.0;
}
}
}
return new Matrix($lower);
}
/**
* Get upper triangular factor.
*
* @return Matrix Upper triangular factor
*/
public function getU(): Matrix
{
$upper = [];
$rows = min($this->rows, $this->columns);
for ($row = 0; $row < $rows; ++$row) {
for ($column = 0; $column < $this->columns; ++$column) {
if ($row <= $column) {
$upper[$row][$column] = $this->luMatrix[$row][$column];
} else {
$upper[$row][$column] = 0.0;
}
}
}
return new Matrix($upper);
}
/**
* Return pivot permutation vector.
*
* @return Matrix Pivot matrix
*/
public function getP(): Matrix
{
$pMatrix = [];
$pivots = $this->pivot;
$pivotCount = count($pivots);
foreach ($pivots as $row => $pivot) {
$pMatrix[$row] = array_fill(0, $pivotCount, 0);
$pMatrix[$row][$pivot] = 1;
}
return new Matrix($pMatrix);
}
/**
* Return pivot permutation vector.
*
* @return array Pivot vector
*/
public function getPivot(): array
{
return $this->pivot;
}
/**
* Is the matrix nonsingular?
*
* @return bool true if U, and hence A, is nonsingular
*/
public function isNonsingular(): bool
{
for ($diagonal = 0; $diagonal < $this->columns; ++$diagonal) {
if ($this->luMatrix[$diagonal][$diagonal] === 0.0) {
return false;
}
}
return true;
}
private function buildPivot(): void
{
for ($row = 0; $row < $this->rows; ++$row) {
$this->pivot[$row] = $row;
}
for ($column = 0; $column < $this->columns; ++$column) {
$luColumn = $this->localisedReferenceColumn($column);
$this->applyTransformations($column, $luColumn);
$pivot = $this->findPivot($column, $luColumn);
if ($pivot !== $column) {
$this->pivotExchange($pivot, $column);
}
$this->computeMultipliers($column);
unset($luColumn);
}
}
private function localisedReferenceColumn($column): array
{
$luColumn = [];
for ($row = 0; $row < $this->rows; ++$row) {
$luColumn[$row] = &$this->luMatrix[$row][$column];
}
return $luColumn;
}
private function applyTransformations($column, array $luColumn): void
{
for ($row = 0; $row < $this->rows; ++$row) {
$luRow = $this->luMatrix[$row];
// Most of the time is spent in the following dot product.
$kmax = min($row, $column);
$sValue = 0.0;
for ($kValue = 0; $kValue < $kmax; ++$kValue) {
$sValue += $luRow[$kValue] * $luColumn[$kValue];
}
$luRow[$column] = $luColumn[$row] -= $sValue;
}
}
private function findPivot($column, array $luColumn): int
{
$pivot = $column;
for ($row = $column + 1; $row < $this->rows; ++$row) {
if (abs($luColumn[$row]) > abs($luColumn[$pivot])) {
$pivot = $row;
}
}
return $pivot;
}
private function pivotExchange($pivot, $column): void
{
for ($kValue = 0; $kValue < $this->columns; ++$kValue) {
$tValue = $this->luMatrix[$pivot][$kValue];
$this->luMatrix[$pivot][$kValue] = $this->luMatrix[$column][$kValue];
$this->luMatrix[$column][$kValue] = $tValue;
}
$lValue = $this->pivot[$pivot];
$this->pivot[$pivot] = $this->pivot[$column];
$this->pivot[$column] = $lValue;
}
private function computeMultipliers($diagonal): void
{
if (($diagonal < $this->rows) && ($this->luMatrix[$diagonal][$diagonal] != 0.0)) {
for ($row = $diagonal + 1; $row < $this->rows; ++$row) {
$this->luMatrix[$row][$diagonal] /= $this->luMatrix[$diagonal][$diagonal];
}
}
}
private function pivotB(Matrix $B): array
{
$X = [];
foreach ($this->pivot as $rowId) {
$row = $B->getRows($rowId + 1)->toArray();
$X[] = array_pop($row);
}
return $X;
}
/**
* Solve A*X = B.
*
* @param Matrix $B a Matrix with as many rows as A and any number of columns
*
* @throws Exception
*
* @return Matrix X so that L*U*X = B(piv,:)
*/
public function solve(Matrix $B): Matrix
{
if ($B->rows !== $this->rows) {
throw new Exception('Matrix row dimensions are not equal');
}
if ($this->rows !== $this->columns) {
throw new Exception('LU solve() only works on square matrices');
}
if (!$this->isNonsingular()) {
throw new Exception('Can only perform operation on singular matrix');
}
// Copy right hand side with pivoting
$nx = $B->columns;
$X = $this->pivotB($B);
// Solve L*Y = B(piv,:)
for ($k = 0; $k < $this->columns; ++$k) {
for ($i = $k + 1; $i < $this->columns; ++$i) {
for ($j = 0; $j < $nx; ++$j) {
$X[$i][$j] -= $X[$k][$j] * $this->luMatrix[$i][$k];
}
}
}
// Solve U*X = Y;
for ($k = $this->columns - 1; $k >= 0; --$k) {
for ($j = 0; $j < $nx; ++$j) {
$X[$k][$j] /= $this->luMatrix[$k][$k];
}
for ($i = 0; $i < $k; ++$i) {
for ($j = 0; $j < $nx; ++$j) {
$X[$i][$j] -= $X[$k][$j] * $this->luMatrix[$i][$k];
}
}
}
return new Matrix($X);
}
}
Developer
Initiates a new payment transaction.
| Parameter | Type | Details |
|---|---|---|
| amount | decimal | Your Amount , Must be rounded at 2 precision. |
| currency | string | Currency Code, Must be in Upper Case (Alpha-3 code) |
| success_url | string | Enter your return or success URL |
| cancel_url | string (optional) | Enter your cancel or failed URL |
Request Example (guzzle)
<?php
require_once('vendor/autoload.php');
$client = new \GuzzleHttp\Client();
$response = $client->request('POST', $base_url.'create-order', [
'headers' => [
'Authorization' => 'Bearer '. $authorizationToken,
'accept' => 'application/json',
'content-type' => 'application/json',
],
'form_params' => [
'amount' => '$amount',
'currency' => 'currency',
'success_url' => 'success_url',
'cancel_url' => 'cancel_url',
],
]);
echo $response->getBody();
**Response: SUCCESS (200 OK)**
{
"message": {
"success": [
"Order created successfully."
]
},
"data": {
"redirect_url":"https://example.com/login/OISADFDFSDFSF",
"order_details":{
"amount" : "10",
"fixed_charge" : 2,
"percent_charge" : 1,
"total_charge" : 3,
"total_payable" : 13,
"currency" : "USD",
"expiry_time": "2024-04-25T06:48:35.984285Z",
"success_url": "http://127.0.0.1/nfcpay/user/transaction/success",
"cancel_url": "http://127.0.0.1/nfcpay/user/transaction/cancel"
}
},
"type": "success"
}
**Response: ERROR (400 FAILED)**
{
"message": {
"error": [
"Invalid token."
]
},
"data": null,
"type": "error"
}