/**
* Compute standard deviation.
*
* @param array $a The array of data to find the standard deviation for.
* Note that all values of the array will be cast to float.
* @param bool $is_sample [Optional] Indicates if $a represents a sample of the
* population (otherwise its the population); Defaults to false.
* @return string|bool The standard deviation or false on error.
*/
function stddev(array $a, $is_sample = false)
{
if (math_count($a) < 2) {
trigger_error("The array has too few elements", E_USER_NOTICE);
return false;
}
return bcsqrt(variance($a, $is_sample));
}
function stddev($values)
{
return sqrt(variance($values));
}
function ecart_type($tabval) {
return(sqrt(variance($tabval)));
}
function stdev($array)
{
$stdev = sqrt(variance($array));
return $stdev;
}
function stdev($a)
{
return sqrt(variance($a));
}
function standard_deviation($nums)
{
return sqrt(variance($nums));
}
echo ' </ul>' . "\n";
} else {
if ($nbcards != 0 && $nbimages == 0) {
echo ' <strong>All</strong>' . "\n";
} else {
echo ' <i>None</i>' . "\n";
}
}
echo ' </td>' . "\n";
if ($nbimages == 0) {
echo ' <td colspan="3">N/A</td>' . "\n";
} else {
$meansize = round($foldersize / $nbimages);
echo ' <td>' . human_filesize($foldersize) . '</td>' . "\n";
echo ' <td style="background-color: ' . nb2html(round($meansize / 1024)) . ' !important ;">' . human_filesize($meansize) . '</td>' . "\n";
$variance = round(variance($filesizes));
$cv = round((5000 - $variance) / 20);
echo ' <td style="background-color: ' . nb2html($cv) . ' !important ;">' . $variance . '</td>' . "\n";
}
echo ' </tr>' . "\n";
unset($exts[$arr['se']]);
}
function nb2html($nb, $max = 255)
{
$nb = min($nb, $max);
// $nb can't be > $max
$mid = $max / 2;
$r = $g = $b = 0;
if ($nb <= $mid) {
$r = 255;
$g = 2 * $nb;
