kuredev

<?php

class Test{
    public function __call($name, $arguments)
    {
        var_dump($name);
        var_dump($arguments);
    }
}

kuredev

<?php

function test1($n){
    $n++;
}

function test2(&$n){
    $n++;
}

kuredev

<?php

require_once "vendor/autoload.php";

$myData = new CpChart\Data();
$myData->addPoints(array(VOID,3,4,3,5));

$myPicture = new CpChart\Image(700,230,$myData);
$myPicture->setGraphArea(60,40,670,190);
$myPicture->drawScale();

kuredev

<?php

$image = file_get_contents("train-images.idx3-ubyte");

 for($k = 0; $k < 28; $k++){
    $cut_image = substr($image, (16+$k*28), 28);
     for($i = 0; $i < strlen($cut_image); $i++) {
         $value = (int)(ord($cut_image[$i]));
         echo $value === 0 ? "0" :  "1";
     }

kuredev

<?php

class Matrix{
    private $lineArray = array();

    /**
     * Matrix constructor.
     * @param array $lineArray [[1,2],[3,4]]
     * (1,2)
     * (3,4)

kuredev

<?php

$y = [0.1,0.05,0.6,0.0,0.05,0.1,0.0,0.1,0.0,0.0];
$t = [0,0,1,0,0,0,0,0,0,0];

var_dump(meanSquaredError($y, $t));

/**
 * @param array $y
 * @param array $t

kuredev

<?php

/**
 * @param $f function
 * @param $x
 */
function numerical_diff($f, $x){
    $h = 1e-4;
    return (($f($x + $h) - $f($x - $h))/(2*$h));
}

kuredev

<?php

require_once "numerical_diff.php";

/**
 * ２変数を前提
 */
function numerical_gradient($f, $x, $y){
    $grad = array();
    $h = 1e-4;

kuredev

<?php

$f = function($x, $y){
    return pow($x, 2) + pow($y, 2);
};

function numerical_gradient($f, $x, $y){
    $h = 1e-4;
    //x
    $x_ = ($f($x + $h, $y) - $f($x - $h, $y))/(2*$h);

kuredev

require 'matrix'

m = Matrix[[1, 2], [3, 4]]
n = Matrix[[5, 6], [7, 8]]

puts m * n