/**
* Get D - the diagonal matrix.
*
* @return matrix D
*/
public function getD()
{
$D = new Matrix($this->_matrix->rows(), $this->_matrix->columns());
for ($i = 0; $i < $D->rows(); $i++) {
$D->set($i, $i, $this->_matrix->get($i, $i));
}
return $D;
}
/**
* Get the U of the decomposition.
*
* @return matrix U
*/
public function getU()
{
$U = $this->_matrix->copy();
for ($i = 0; $i < $U->rows(); $i++) {
for ($j = 0; $j < $i; $j++) {
$U->set($i, $j, 0);
}
}
return $U;
}
/**
* Gets the upper triangular matrix R.
*/
public function getR()
{
$R = $this->_matrix->copy();
$n = min($R->rows(), $R->columns());
for ($i = 0; $i < $R->rows(); $i++) {
for ($j = 0; $j < $i and $j < $n; $j++) {
$R->set($i, $j, 0);
}
}
return $R;
}
/**
* QR Decomposition computed by Householder reflections.
*
* @param matrix $A Rectangular matrix
* @return Structure to access R and the Householder vectors and compute Q.
*/
public function __construct($A)
{
if ($A instanceof PHPExcel_Shared_JAMA_Matrix) {
// Initialize.
$this->QR = $A->getArrayCopy();
$this->m = $A->getRowDimension();
$this->n = $A->getColumnDimension();
// Main loop.
for ($k = 0; $k < $this->n; ++$k) {
// Compute 2-norm of k-th column without under/overflow.
$nrm = 0.0;
for ($i = $k; $i < $this->m; ++$i) {
$nrm = hypo($nrm, $this->QR[$i][$k]);
}
if ($nrm != 0.0) {
// Form k-th Householder vector.
if ($this->QR[$k][$k] < 0) {
$nrm = -$nrm;
}
for ($i = $k; $i < $this->m; ++$i) {
$this->QR[$i][$k] /= $nrm;
}
$this->QR[$k][$k] += 1.0;
// Apply transformation to remaining columns.
for ($j = $k + 1; $j < $this->n; ++$j) {
$s = 0.0;
for ($i = $k; $i < $this->m; ++$i) {
$s += $this->QR[$i][$k] * $this->QR[$i][$j];
}
$s = -$s / $this->QR[$k][$k];
for ($i = $k; $i < $this->m; ++$i) {
$this->QR[$i][$j] += $s * $this->QR[$i][$k];
}
}
}
$this->Rdiag[$k] = -$nrm;
}
} else {
throw new Exception(PHPExcel_Shared_JAMA_Matrix::ArgumentTypeException);
}
}
/**
* Gets the upper triangular matrix R.
*/
public function getR()
{
$R = $this->_matrix->copy();
for ($i = 0; $i < $R->rows(); $i++) {
for ($j = 0; $j < $i; $j++) {
$R->set($i, $j, 0);
}
}
// Resize R to a square matrix.
$n = min($R->rows(), $R->columns());
return $R->resize($n, $n);
}
/**
* Add to matrices.
*
* @param matrix $a
* @param matrix $b
* @return matrix $a + $b
*/
public static function add($a, $b)
{
new Assertion($a instanceof Matrix, 'Given first matrix not of class Matrix.');
new Assertion($b instanceof Matrix, 'Given second matrix not of class Matrix.');
new Assertion($a->rows() == $b->rows(), 'Given dimensions are not compatible.');
new Assertion($a->columns() == $b->columns(), 'Given dimensions are not compatible.');
$rows = $a->rows();
$columns = $a->columns();
$matrix = $a->copy();
for ($i = 0; $i < $rows; $i++) {
for ($j = 0; $j < $columns; $j++) {
$matrix->set($i, $j, $matrix->get($i, $j) + $b->get($i, $j));
}
}
return $matrix;
}
$i += 1;
}
/*menghitung rata-rata */
$average_pegawai = mean($a);
$average_barang = mean($b);
$average_modal = mean($c);
/*menghitung standar deviasi */
$standard_deviation_pegawai = standard_deviation_population($a);
$standard_deviation_barang = standard_deviation_population($b);
$standard_deviation_modal = standard_deviation_population($c);
}
//while
$dataX = $ind;
$dataY = $tot;
$M = new matrix($dataX);
$X = $M->ArrayData;
$M = new matrix($dataY);
$Y = $M->ArrayData;
$Xt = $M->Transpose($X);
$XtX = $M->MultiplyMatrix($Xt, $X);
$XtY = $M->MultiplyMatrix($Xt, $Y);
$XtXi = $M->InverseMatrix($XtX);
$b = $M->MultiplyMatrix($XtXi, $XtY);
$usql = "update kelompok_kegiatan set " . "koefisien_1=" . (empty($b[1][0]) ? 'null' : sprintf("%01.3f", $b[1][0])) . ",koefisien_2=" . (empty($b[2][0]) ? 'null' : sprintf("%01.3f", $b[2][0])) . ",koefisien_3=" . (empty($b[3][0]) ? 'null' : sprintf("%01.3f", $b[3][0])) . ",koefisien_4=" . (empty($b[4][0]) ? 'null' : sprintf("%01.3f", $b[4][0])) . ",konstanta=" . (empty($b[0][0]) ? 'null' : sprintf("%01.3f", $b[0][0])) . ",rata_pegawai=" . (empty($average_pegawai) ? 'null' : sprintf("%01.3f", $average_pegawai)) . ",rata_barang=" . (empty($average_barang) ? 'null' : sprintf("%01.3f", $average_barang)) . ",rata_modal=" . (empty($average_modal) ? 'null' : sprintf("%01.3f", $average_modal)) . ",std_deviasi_pegawai=" . (empty($standard_deviation_pegawai) ? 'null' : sprintf("%01.3f", $standard_deviation_pegawai)) . ",std_deviasi_barang=" . (empty($standard_deviation_barang) ? 'null' : sprintf("%01.3f", $standard_deviation_barang)) . ",std_deviasi_modal=" . (empty($standard_deviation_modal) ? 'null' : sprintf("%01.3f", $standard_deviation_modal)) . " where id=" . $_REQUEST[gid];
gcms_query($usql);
echo $usql;
?>
/**
* Check norm of difference of "matrices".
* @param matrix $X
* @param matrix $Y
*/
function checkMatrices($X = null, $Y = null)
{
if ($X == null || $Y == null) {
return false;
}
$eps = pow(2.0, -52.0);
if ($X->norm1() == 0.0 & $Y->norm1() < 10 * $eps) {
return true;
}
if ($Y->norm1() == 0.0 & $X->norm1() < 10 * $eps) {
return true;
}
$A = $X->minus($Y);
if ($A->norm1() > 1000 * $eps * max($X->norm1(), $Y->norm1())) {
die("The norm of (X-Y) is too large: " . $A->norm1());
} else {
return true;
}
}
$clean_matrix = array();
for ($i = 0; $i < count($matrix); $i++) {
for ($j = 0; $j < count($matrix[$i]); $j++) {
$clean_matrix[$i][$j] = clone $matrix[$i][$j];
}
}
return $clean_matrix;
}
// If a solution found add it to the solution array
private function addSolution($s)
{
array_push($this->solution, $s);
}
// getSolutions
public function getSolution()
{
return $this->solution;
}
}
// And fire the application
$matrixObj = new matrix();
$matrixObj->loopMatrix($matrix, false);
$solutions = $matrixObj->getSolution();
echo "Problem to solve: How many combinations are there which leads to a sum of 10? From every field you can go to a neighboring field: top, down, left, right and diagonal is allowed. <br />";
$matrixObj->printMatrix($matrix);
echo "<br />There are " . count($solutions) . " combinations which leads to a sum of 10.<br /><br />Solutions:<br />";
for ($i = 0; $i < count($solutions); $i++) {
$clean_matrix = $matrixObj->cloneMatrix($matrix);
echo '<br />' . ($i + 1) . '.';
$matrixObj->printMatrix($clean_matrix, $solutions[$i]);
}
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<link rel="stylesheet" href="style.css" />
<script src="jquery.min.js"></script>
<script src="script.js"></script>
</head>
<body id="top">
<h1>Лабораторная работа №1 по ДиВМ</h1>
<a href="#new" id="set-new"><h2 <? if (isset($_POST['accept'])) {?>style="border-bottom-color:#036;"<? }?>>Задание новой СЛАУ</h2></a>
<? if (isset($_POST['accept'])) {?><a href="#resh" id="set-resh"><h2>Решение СЛАУ</h2></a><? }?>
<?
if (isset($_POST['accept'])) {
?>
<div id="accept-cont">
<div id="accept">
<?
$matr = new matrix($_POST['n-mer']);
?>
</div>
<input type="button" id="hide-accept" value="Скрыть" class="button"> <input type="button" id="show-accept" value="Показать" class="button">
</div>
<?
}
?>
<form action="" id="new" method="post" <? if (isset($_POST['accept'])) {?> style="display:none;"<? }?>>
<label for="n-mer">Размерность матрицы:</label> <input name="n-mer" id="n-mer" type="number" min="1" value="3"> <input type="button" id="table_but" value="Сгенерировать матрицу" class="button"> <input type="button" id="gener_but" value="Заполнить случайными числами" class="button">
<br>
<label for="method">Выберите метод:</label>
<select name="method">
<option value="method_hauss" selected>1. Гаусса</option>
<option value="method_holeck">2. Холецкого</option>
<option value="method_zeidel">3. Зейделя</option>
