function alfabetAnalyse($codtxt, $alfa)
{
global $AP, $ks_hilf;
$alfahier = @hauf($codtxt);
for ($t = 0; $t < sizeof($alfahier); $t++) {
$p[] = 100 * prob($alfahier[$t], strlen($codtxt));
}
$alfahier = $p;
$VX = varianz($AP[de]);
$SX = sqrt(varianz($AP[de]));
$VY = varianz($alfahier);
$SY = sqrt(varianz($alfahier));
$cov = covarianz($AP[de], $alfahier);
$r = @abs($cov / sqrt($VX * $VY));
for ($t = 0; $t < sizeof($alfa); $t++) {
$ba1 .= "<img src={$ks_hilf['pfad']}/image/letter" . $t . ".gif border=0><img src={$ks_hilf['pfad']}/image/bar0.jpg width=3 border=0>";
$ba2 .= "<img src={$ks_hilf['pfad']}/image/letter" . ($t + $rotv) % sizeof($alfa) . ".gif border=0><img src={$ks_hilf['pfad']}/image/bar0.jpg width=3 border=0>";
}
$lang_normalalphabet = JTEXT::_('NORMALALPHABET');
$lang_STATISTICALDATA = JTEXT::_('STATISTICALDATA');
$lang_VARIANCE = JTEXT::_('VARIANCE');
$lang_DEFAULTABWEICHUNG = JTEXT::_('DEFAULTABWEICHUNG');
$lang_CURRENTALPHABET = JTEXT::_('CURRENTALPHABET');
$lang_SIGNS = JTEXT::_('SIGNS');
$lang_ENTROPY = JTEXT::_('ENTROPY');
$out .= '<table border=0><tr><td>
<b>' . $lang_normalalphabet . '</b><br>' . $lang_STATISTICALDATA . ':<br>' . '<br>' . $lang_VARIANCE . ': ' . round($VX, 5) . '<br>' . $lang_DEFAULTABWEICHUNG . ': ' . round($SX, 5) . '</td><td valign=middle>' . showakt($AP[de], 50, 1, 5, 3, 0) . '<center><div class=text7 >' . $ba1 . '</div></center>' . '</td></tr>' . '<tr><td>' . '<br><b>' . $lang_CURRENTALPHABET . '</b><br>' . $lang_STATISTICALDATA . ':<br>' . '<br>' . $lang_VARIANCE . ': ' . round($VY, 5) . '<br>' . $lang_DEFAULTABWEICHUNG . ': ' . round($SY, 5) . '<br>' . '</td><td valign=middle><br>' . showakt($alfahier, 50, 1, 5, 3, 0) . '<center><div class=text7 >' . $ba2 . '</div></center>' . '</td></tr><tr><td>' . '<br>' . $lang_SIGNS . ': ' . strlen($codtxt) . '<br>' . $lang_ENTROPY . ': ' . round(entropie($codtxt), 5) . '</td></tr></table>';
return $out;
}
function entropie($text)
{
# binärer Informationsgehalt, bezogen auf den Standardzeichensatz
global $alfa;
$hauf = hauf($text);
for ($t = 0; $t < count($hauf); $t++) {
$p = prob($hauf[$t], strlen($text));
if ($p > 0) {
$z = $p * log($p) / log(2);
} else {
$z = 0;
}
$ent = $ent + $z;
}
$ent = -$ent;
return $ent;
}
function alfabetAnalyse($codtxt, $alfa)
{
global $AP, $ks_hilf;
$alfahier = @hauf($codtxt);
for ($t = 0; $t < sizeof($alfahier); $t++) {
$p[] = 100 * prob($alfahier[$t], strlen($codtxt));
}
$alfahier = $p;
$VX = varianz($AP[de]);
$SX = sqrt(varianz($AP[de]));
$VY = varianz($alfahier);
$SY = sqrt(varianz($alfahier));
$cov = covarianz($AP[de], $alfahier);
$r = @abs($cov / sqrt($VX * $VY));
for ($t = 0; $t < sizeof($alfa); $t++) {
$ba1 .= "<img src={$ks_hilf['pfad']}/image/letter" . $t . ".gif border=0><img src={$ks_hilf['pfad']}/image/bar0.jpg width=3 border=0>";
$ba2 .= "<img src={$ks_hilf['pfad']}/image/letter" . ($t + $rotv) % sizeof($alfa) . ".gif border=0><img src={$ks_hilf['pfad']}/image/bar0.jpg width=3 border=0>";
}
$out .= '<table border=0><tr><td>
<b>Normales Alfabet</b><br>Statistische Daten:<br>' . '<br>Varianz: ' . round($VX, 5) . '<br>StdAbw: ' . round($SX, 5) . '</td><td valign=middle>' . showakt($AP[de], 50, 1, 5, 3, 0) . '<center><div class=text7 >' . $ba1 . '</div></center>' . '</td></tr>' . '<tr><td>' . '<br><b>vorliegendes Alfabet</b><br>Statistische Daten:<br>' . '<br>Varianz: ' . round($VY, 5) . '<br>StdAbw: ' . round($SY, 5) . '<br>' . '</td><td valign=middle><br>' . showakt($alfahier, 50, 1, 5, 3, 0) . '<center><div class=text7 >' . $ba2 . '</div></center>' . '</td></tr><tr><td>' . '<br>Zeichen: ' . strlen($codtxt) . '<br>Entropie: ' . round(entropie($codtxt), 5) . '<br>KI-Index: ' . round(koinzidenzIndex($codtxt), 5) . '</td><td>' . '<br>GV-Maß1: ' . round(gvmass($codtxt, $alfahier), 5) . '<br>GV-Maß2: ' . round(gvmass2($codtxt, $alfahier), 5) . '</td></tr></table><div class=text10><br>Kovarianz: ' . round($cov, 5) . '<br>KorrKoeff: ' . round($r, 5) . '</div>';
return $out;
}
function findmul($text)
{
# Alfabetmultiplikator finden
global $AP;
global $alfa;
$mulzahl = teilerfremde(sizeof($alfa));
$VX = varianz($AP[de]);
$SX = sqrt(varianz($AP[de]));
$sp = hauf($text);
$sps = array_sum($sp);
for ($t = 0; $t < sizeof($sp); $t++) {
$sp[$t] = @round($sp[$t] / $sps * 100, 2);
}
for ($t = 0; $t < sizeof($mulzahl); $t++) {
for ($u = 0; $u < sizeof($sp); $u++) {
$sp2[$u] = $sp[$mulzahl[$t] * $u % sizeof($sp)];
}
$VY = varianz($sp2);
$SY = sqrt(varianz($sp2));
$cov = covarianz($AP[de], $sp2);
$r[$t] = @abs($cov / sqrt($VX * $VY));
}
$b = array_search(max($r), $r);
return $mulzahl[$b];
}