<?php
// 標準偏差の関数
function stats_standard_deviation($ary)
{
// 平均取得
$avg = round(array_sum($ary) / count($ary), 1);
// 各値の平均値との差の二乗【(値-平均値)^2】を算出
$diff_ary = array();
foreach ($ary as $val) {
$diff = $val - $avg;
$diff_ary[] = pow($diff, 2);
}
// 上記差の二乗の合計を算出
$diff_total = array_sum($diff_ary);
// 平均を算出
$diff_avg = $diff_total / count($diff_ary);
// 平方根を取る(標準偏差)
$stdev = sqrt($diff_avg);
// 標準偏差を返す
return $stdev;
}
// N個の整数をセット
$Numbers = array(90, 30, 53, 45, 60);
$count = count($Numbers);
$sum = array_sum($Numbers);
$max = max($Numbers);
$min = min($Numbers);
$average = round($sum / $count, 1);
echo "セットされた数字の<BR>個数:" . $count . "最大:" . $max . "最小:" . $min . "平均:" . $average . "標準偏差:" . round(stats_standard_deviation($Numbers), 1);
/**
* @param array $a
* @param bool $sample [optional] Defaults to false
* @return float|bool The standard deviation or false on error.
*/
public static function standardDeviation(array $a, $sample = false)
{
return stats_standard_deviation($a, $sample);
}
function retSD($x)
{
$answer = stats_standard_deviation($x);
return $answer;
}
$a = [[1, 2], [3, 4], [5, 6]];
print_r($a);
$b = array_filter($a, function ($k) {
return $k[0];
});
print_r($b);
function get_heights($i, $k)
{
return $i[0];
}
$c = array_walk($a, 'get_heights');
print_r($c);
$d = array();
foreach ($a as $e) {
array_push($d, $e[0]);
}
print_r($d);
function sum($g)
{
return $g[0] + $g[1];
}
$f = array_map('sum', $a);
print_r($f);
$ret = array();
$mean = array_sum($f) / count($f);
$stddev = stats_standard_deviation($f);
$outlier = 3 * $stddev;
print_r($mean);
?>
</pre>
$d = (double) $val - $mean;
$carry += $d * $d;
}
if ($sample) {
--$n;
}
return sqrt($carry / $n);
}
$input = array($_POST);
// カンマ区切り、PHP、配列
// N個の数値を入力し、配列に取得する方法がわからない。。。
$N = count($input);
$max = max($input);
$min = min($input);
$ave = array_sum($input) / $N;
$sd = stats_standard_deviation($input);
var_dump($input);
?>
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>統計量の計算</title>
</head>
<body>
<h1>統計量の計算</h1>
<form action="" method="post">
<input type="text" name="n" min="0">
<input type="submit" value="送信"><br>
データ個数:<?php
function GetView()
{
global $TMP_PATH;
$req = $this->req->CreateDataRequest();
$x = $req->GetProp("view_x", false);
if (!$x) {
throw new ADEIException(translate("Parameter view_x is not set"));
}
list($x_gid, $x_id) = explode(":", $x);
if ($this->object) {
$width = $req->GetProp($this->object . "_width", $this->min_width + 20) - 20;
if ($width < $this->min_width) {
$width = $this->min_width;
}
$height = $width - 40;
//$req->GetProp($this->object . "_height", $this->min_height);
} else {
$width = $req->GetProp("page_width", $this->min_width + 5) - 5;
$height = $req->GetProp("page_height", $this->min_height);
if ($width < $this->min_width) {
$width = $this->min_width;
}
if ($height < $this->min_height) {
$height = $this->min_height;
}
}
$rdr = $req->CreateReader();
$group = $rdr->CreateGroup();
$caches = $rdr->CreateCacheSet($group, $mask);
$myreq = $this->req->CreateDataRequest();
$iv = $caches->CreateInterval($req, true);
$window_size = $iv->GetWindowSize();
$window_start = $iv->GetWindowStart();
$window_end = $iv->GetWindowEnd();
$rescfg = array('limit' => $this->max_points, 'resolution' => $res);
$gid = 0;
$res = array();
foreach ($caches as $key => $cachewrap) {
if ($gid != $x_gid) {
$gid++;
continue;
}
$resolution = $cachewrap->GetResolution();
$r = $resolution->Get($iv, $width);
$size = $resolution->GetWindowSize($r);
if ($size > 0 && $window_size / $size > $this->max_points) {
$new_r = $resolution->Larger($r);
if ($new_r !== false) {
$r = $new_r;
}
$size = $resolution->GetWindowSize($r);
}
$rescfg['resolution'] = $r;
$points = $cachewrap->GetIntervals($iv, $rescfg, CACHE::TRUNCATE_INTERVALS);
$operation_info = $points->GetOperationInfo();
if ($gid == $x_gid) {
$res_x = $size;
}
foreach ($points as $t => $v) {
/* if (($t < $window_start)||(($t + $size) > $window_end)) {
continue;
}*/
if ($gid == $x_gid && is_numeric($v['mean' . $x_id])) {
if (!is_array($res[$t])) {
$res[$t] = array();
}
$res[$t]['x'] = $v['mean' . $x_id];
$res[$t]['t'] = $t;
}
}
$gid++;
}
$x = array();
$t = array();
foreach ($res as $val) {
if (isset($val['x'])) {
array_push($x, $val['x']);
}
}
if (!$x) {
throw new ADEIException(translate("No data found"));
}
$bins = $req->GetProp("view_bins", 0);
if (!$bins) {
$bins = ceil(sqrt(sizeof($x)));
}
$norm = $req->GetProp("view_hist_norm", 0);
$fit = $req->GetProp("view_hist_fit", 0);
$min = min($x);
$max = max($x);
$step = ($max - $min) / $bins;
$coef = $norm ? 1 / ($step * sizeof($x)) : 1;
$h = array_fill(0, $bins, 0);
foreach ($x as $val) {
$idx = ($val - $min) / $step;
if ($idx == $bins) {
$idx--;
}
$h[$idx] += $coef;
}
for ($i = 0; $i < $bins; $i++) {
array_push($t, sprintf("%3.1e", $min + $i * $step));
}
$tmp_file = ADEI::GetTmpFile();
$graph = new Graph($width, $height);
/* $title = "Resolution: $res_x";
$graph->title->SetFont(FF_ARIAL,FS_BOLD,10);
$graph->title->Set($title);*/
$graph->SetTickDensity(TICKD_SPARSE, TICKD_SPARSE);
$graph->img->SetMargin(55, 5, 10, 20);
$graph->SetScale("textlin");
$graph->xaxis->SetPos("min");
$graph->yaxis->SetPos("min");
// $graph->xaxis->SetLabelFormat('%3.1e');
// if (abs(max($h))<9999 && (abs(min($h))>0.01)) $graph->yaxis->SetLabelFormat('%01.2f');
// else $graph->yaxis->SetLabelFormat('%3.1e');
$graph->xaxis->SetFont(FF_ARIAL, FS_NORMAL, 8);
$graph->yaxis->SetFont(FF_ARIAL, FS_NORMAL, 8);
// $graph->yaxis->HideFirstTickLabel();
$graph->xaxis->title->SetFont(FF_ARIAL, FS_BOLD);
$graph->yaxis->title->SetFont(FF_ARIAL, FS_BOLD);
//$graph->xaxis->title->Set($arr[0]['select']['options'][$x_idg]['label']);
if ($bins > 8) {
$graph->xaxis->SetTextLabelInterval(ceil($bins / 6));
}
$graph->xaxis->SetTickLabels($t);
$bplot = new BarPlot($h);
$bplot->SetWidth(1);
$graph->Add($bplot);
$graph->yaxis->scale->SetGrace(14);
$mean = array_sum($x) / sizeof($x);
$stddev = stats_standard_deviation($x);
$var = stats_variance($x);
$sigma = sqrt($var);
$re = 100 * $sigma / $mean;
sort($x);
if (sizeof($x) % 2) {
$median = $x[(sizeof($x) - 1) / 2];
} else {
$median = ($x[sizeof($x) / 2 - 1] + $x[sizeof($x) / 2]) / 2;
}
// Gaussian fitting
if ($fit) {
$ydata = array();
$xdata = array();
if ($norm) {
$coef = 1 / sqrt(2 * pi() * $var);
} else {
$coef = sizeof($x) * $step / sqrt(2 * pi() * $var);
}
$xi2 = 0;
for ($i = 0; $i <= $bins; $i++) {
$offset = $i * $step;
$y = $coef * exp(-pow($min + $offset - $mean, 2) / (2 * $var));
array_push($xdata, $i);
array_push($ydata, $y);
$xi2 += pow($y - $h[$i], 2) / $y;
}
$xi2 /= $bins;
$lineplot = new LinePlot($ydata, $xdata);
$graph->Add($lineplot);
}
$char_sigma = SymChar::Get('sigma', false);
/*
$txt = new Text();
$txt->SetFont(FF_ARIAL,FS_BOLD,10);
if( $req->GetProp("view_GFit", false) == "true")
$txt->Set("m=$mean\n$char_sigma=$sigma\nRE=$RE%\nx^2=$xi2");//\ns=$stdDev
else
$txt->Set("m=$mean\n$char_sigma=$sigma\nRE=$RE%");//\ns=$stdDev
$txt->ParagraphAlign('right');
$txt->SetPos(0.96,0.1,'right');
//$txt->SetBox('white');
$graph->Add($txt);
*/
$graph->Stroke("{$TMP_PATH}/{$tmp_file}");
if ($this->object) {
$res = array(array("img" => array("id" => $tmp_file)), array("info" => array(array("title" => _("From"), "value" => date('c', $iv->GetWindowStart())), array("title" => _("To"), "value" => date('c', $iv->GetWindowEnd())), array("title" => _("Resolution"), "value" => $res_x), array("title" => _("Bins"), "value" => $bins), array("title" => _("First Bin"), "value" => $min), array("title" => _("Last Bin"), "value" => $min + $bins * $step), array("title" => _("Mean"), "value" => $mean), array("title" => _("Median"), "value" => $median), array("title" => _("StdDev"), "value" => $stddev), array("title" => _("Sigma"), "value" => $sigma), array("title" => _("RE"), "value" => $re . "%"))));
if ($fit) {
array_push($res[1]["info"], array("title" => _("xi2"), "value" => $xi2));
}
return $res;
} else {
return array("img" => array("id" => $tmp_file));
}
}
function calculateRegression($project_id, $time, $trend_value)
{
$trends = getTrendsTimeArray($project_id);
$times = getTrendsTimeArray($project_id);
$sx = stats_standard_deviation($times);
$sy = stats_standard_deviation($trends);
$r = Corr($x, $y);
$b = $r * ($sy / $sx);
$a = $trend_value - $b * $time;
return $b * $time + $a;
}
function calculateRegression($project_id, $time, $trend_value)
{
$trends = getTrendsTimeArray($project_id);
$times = getTrendsTimeArray($project_id);
$sx = stats_standard_deviation($times);
$sy = stats_standard_deviation($trends);
$r = Corr($sx, $sy);
//removed to check error can be uncomment later.
//$r = 2;//random value need to remove
$b = $r * ($sy / $sx);
$a = $trend_value - $b * $time;
return $b * $time + $a;
}
