<?php

/*
 *
 *  ____            _        _   __  __ _                  __  __ ____
 * |  _ \ ___   ___| | _____| |_|  \/  (_)_ __   ___      |  \/  |  _ \
 * | |_) / _ \ / __| |/ / _ \ __| |\/| | | '_ \ / _ \_____| |\/| | |_) |
 * |  __/ (_) | (__|   <  __/ |_| |  | | | | | |  __/_____| |  | |  __/
 * |_|   \___/ \___|_|\_\___|\__|_|  |_|_|_| |_|\___|     |_|  |_|_|
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * @author PocketMine Team
 * @link http://www.pocketmine.net/
 *
 *
*/

declare(strict_types=1);

namespace pocketmine\level\generator\noise;

use InvalidArgumentException;
use pocketmine\utils\Random;
use function sqrt;

/**
 * Generates simplex-based noise.
 *
 * This is a modified version of the freely published version in the paper by
 * Stefan Gustavson at
 * http://staffwww.itn.liu.se/~stegu/simplexnoise/simplexnoise.pdf
 */
class Simplex extends Perlin
{
	/** @var float */
	protected static $SQRT_3;
	/** @var float */
	protected static $SQRT_5;
	/** @var float */
	protected static $F2;
	/** @var float */
	protected static $G2;
	/** @var float */
	protected static $G22;
	/** @var float */
	protected static $F3;
	/** @var float */
	protected static $G3;
	/** @var float */
	protected static $F4;
	/** @var float */
	protected static $G4;
	/** @var float */
	protected static $G42;
	/** @var float */
	protected static $G43;
	/** @var float */
	protected static $G44;
	/** @var int[][] */
	protected static $grad4 = [
		[0, 1, 1, 1], [0, 1, 1, -1], [0, 1, -1, 1], [0, 1, -1, -1],
		[0, -1, 1, 1], [0, -1, 1, -1], [0, -1, -1, 1], [0, -1, -1, -1],
		[1, 0, 1, 1], [1, 0, 1, -1], [1, 0, -1, 1], [1, 0, -1, -1],
		[-1, 0, 1, 1], [-1, 0, 1, -1], [-1, 0, -1, 1], [-1, 0, -1, -1],
		[1, 1, 0, 1], [1, 1, 0, -1], [1, -1, 0, 1], [1, -1, 0, -1],
		[-1, 1, 0, 1], [-1, 1, 0, -1], [-1, -1, 0, 1], [-1, -1, 0, -1],
		[1, 1, 1, 0], [1, 1, -1, 0], [1, -1, 1, 0], [1, -1, -1, 0],
		[-1, 1, 1, 0], [-1, 1, -1, 0], [-1, -1, 1, 0], [-1, -1, -1, 0]
	];

	/** @var int[][] */
	protected static $simplex = [
		[0, 1, 2, 3], [0, 1, 3, 2], [0, 0, 0, 0], [0, 2, 3, 1], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [1, 2, 3, 0],
		[0, 2, 1, 3], [0, 0, 0, 0], [0, 3, 1, 2], [0, 3, 2, 1], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [1, 3, 2, 0],
		[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0],
		[1, 2, 0, 3], [0, 0, 0, 0], [1, 3, 0, 2], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [2, 3, 0, 1], [2, 3, 1, 0],
		[1, 0, 2, 3], [1, 0, 3, 2], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [2, 0, 3, 1], [0, 0, 0, 0], [2, 1, 3, 0],
		[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0],
		[2, 0, 1, 3], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [3, 0, 1, 2], [3, 0, 2, 1], [0, 0, 0, 0], [3, 1, 2, 0],
		[2, 1, 0, 3], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [3, 1, 0, 2], [0, 0, 0, 0], [3, 2, 0, 1], [3, 2, 1, 0]
	];

	/** @var float */
	protected $offsetW;

	/**
	 * @param int   $octaves
	 * @param float $persistence
	 * @param float $expansion
	 */
	public function __construct(Random $random, $octaves, $persistence, $expansion = 1)
	{
		parent::__construct($random, $octaves, $persistence, $expansion);
		$this->offsetW = $random->nextFloat() * 256;
		self::$SQRT_3 = sqrt(3);
		self::$SQRT_5 = sqrt(5);
		self::$F2 = 0.5 * (self::$SQRT_3 - 1);
		self::$G2 = (3 - self::$SQRT_3) / 6;
		self::$G22 = self::$G2 * 2.0 - 1;
		self::$F3 = 1.0 / 3.0;
		self::$G3 = 1.0 / 6.0;
		self::$F4 = (self::$SQRT_5 - 1.0) / 4.0;
		self::$G4 = (5.0 - self::$SQRT_5) / 20.0;
		self::$G42 = self::$G4 * 2.0;
		self::$G43 = self::$G4 * 3.0;
		self::$G44 = self::$G4 * 4.0 - 1.0;
	}

	/**
	 * @param int[] $g
	 * @param float $x
	 * @param float $y
	 *
	 * @return float
	 */
	protected static function dot2D($g, $x, $y)
	{
		return $g[0] * $x + $g[1] * $y;
	}

	/**
	 * @param int[] $g
	 * @param float $x
	 * @param float $y
	 * @param float $z
	 *
	 * @return float
	 */
	protected static function dot3D($g, $x, $y, $z)
	{
		return $g[0] * $x + $g[1] * $y + $g[2] * $z;
	}

	/**
	 * @param int[] $g
	 * @param float $x
	 * @param float $y
	 * @param float $z
	 * @param float $w
	 *
	 * @return float
	 */
	protected static function dot4D($g, $x, $y, $z, $w)
	{
		return $g[0] * $x + $g[1] * $y + $g[2] * $z + $g[3] * $w;
	}

	public function getNoise3D($x, $y, $z)
	{
		$x += $this->offsetX;
		$y += $this->offsetY;
		$z += $this->offsetZ;

		// Skew the input space to determine which simplex cell we're in
		$s = ($x + $y + $z) * self::$F3; // Very nice and simple skew factor for 3D
		$i = (int) ($x + $s);
		$j = (int) ($y + $s);
		$k = (int) ($z + $s);
		$t = ($i + $j + $k) * self::$G3;
		// Unskew the cell origin back to (x,y,z) space
		$x0 = $x - ($i - $t); // The x,y,z distances from the cell origin
		$y0 = $y - ($j - $t);
		$z0 = $z - ($k - $t);

		// For the 3D case, the simplex shape is a slightly irregular tetrahedron.

		// Determine which simplex we are in.
		if ($x0 >= $y0) {
			if ($y0 >= $z0) {
				$i1 = 1;
				$j1 = 0;
				$k1 = 0;
				$i2 = 1;
				$j2 = 1;
				$k2 = 0;
			} // X Y Z order
			elseif ($x0 >= $z0) {
				$i1 = 1;
				$j1 = 0;
				$k1 = 0;
				$i2 = 1;
				$j2 = 0;
				$k2 = 1;
			} // X Z Y order
			else {
				$i1 = 0;
				$j1 = 0;
				$k1 = 1;
				$i2 = 1;
				$j2 = 0;
				$k2 = 1;
			}
			// Z X Y order
		} else { // x0<y0
			if ($y0 < $z0) {
				$i1 = 0;
				$j1 = 0;
				$k1 = 1;
				$i2 = 0;
				$j2 = 1;
				$k2 = 1;
			} // Z Y X order
			elseif ($x0 < $z0) {
				$i1 = 0;
				$j1 = 1;
				$k1 = 0;
				$i2 = 0;
				$j2 = 1;
				$k2 = 1;
			} // Y Z X order
			else {
				$i1 = 0;
				$j1 = 1;
				$k1 = 0;
				$i2 = 1;
				$j2 = 1;
				$k2 = 0;
			}
			// Y X Z order
		}

		// A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
		// a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
		// a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
		// c = 1/6.
		$x1 = $x0 - $i1 + self::$G3; // Offsets for second corner in (x,y,z) coords
		$y1 = $y0 - $j1 + self::$G3;
		$z1 = $z0 - $k1 + self::$G3;
		$x2 = $x0 - $i2 + 2.0 * self::$G3; // Offsets for third corner in (x,y,z) coords
		$y2 = $y0 - $j2 + 2.0 * self::$G3;
		$z2 = $z0 - $k2 + 2.0 * self::$G3;
		$x3 = $x0 - 1.0 + 3.0 * self::$G3; // Offsets for last corner in (x,y,z) coords
		$y3 = $y0 - 1.0 + 3.0 * self::$G3;
		$z3 = $z0 - 1.0 + 3.0 * self::$G3;

		// Work out the hashed gradient indices of the four simplex corners
		$ii = $i & 255;
		$jj = $j & 255;
		$kk = $k & 255;

		$n = 0;

		// Calculate the contribution from the four corners
		$t0 = 0.6 - $x0 * $x0 - $y0 * $y0 - $z0 * $z0;
		if ($t0 > 0) {
			$gi0 = self::$grad3[$this->perm[$ii + $this->perm[$jj + $this->perm[$kk]]] % 12];
			$n += $t0 * $t0 * $t0 * $t0 * ($gi0[0] * $x0 + $gi0[1] * $y0 + $gi0[2] * $z0);
		}

		$t1 = 0.6 - $x1 * $x1 - $y1 * $y1 - $z1 * $z1;
		if ($t1 > 0) {
			$gi1 = self::$grad3[$this->perm[$ii + $i1 + $this->perm[$jj + $j1 + $this->perm[$kk + $k1]]] % 12];
			$n += $t1 * $t1 * $t1 * $t1 * ($gi1[0] * $x1 + $gi1[1] * $y1 + $gi1[2] * $z1);
		}

		$t2 = 0.6 - $x2 * $x2 - $y2 * $y2 - $z2 * $z2;
		if ($t2 > 0) {
			$gi2 = self::$grad3[$this->perm[$ii + $i2 + $this->perm[$jj + $j2 + $this->perm[$kk + $k2]]] % 12];
			$n += $t2 * $t2 * $t2 * $t2 * ($gi2[0] * $x2 + $gi2[1] * $y2 + $gi2[2] * $z2);
		}

		$t3 = 0.6 - $x3 * $x3 - $y3 * $y3 - $z3 * $z3;
		if ($t3 > 0) {
			$gi3 = self::$grad3[$this->perm[$ii + 1 + $this->perm[$jj + 1 + $this->perm[$kk + 1]]] % 12];
			$n += $t3 * $t3 * $t3 * $t3 * ($gi3[0] * $x3 + $gi3[1] * $y3 + $gi3[2] * $z3);
		}

		// Add contributions from each corner to get the noise value.
		// The result is scaled to stay just inside [-1,1]
		return 32.0 * $n;
	}

	/**
	 * @param float $x
	 * @param float $y
	 *
	 * @return float
	 */
	public function getNoise2D($x, $y)
	{
		$x += $this->offsetX;
		$y += $this->offsetY;

		// Skew the input space to determine which simplex cell we're in
		$s = ($x + $y) * self::$F2; // Hairy factor for 2D
		$i = (int) ($x + $s);
		$j = (int) ($y + $s);
		$t = ($i + $j) * self::$G2;
		// Unskew the cell origin back to (x,y) space
		$x0 = $x - ($i - $t); // The x,y distances from the cell origin
		$y0 = $y - ($j - $t);

		// For the 2D case, the simplex shape is an equilateral triangle.

		// Determine which simplex we are in.
		if ($x0 > $y0) {
			$i1 = 1;
			$j1 = 0;
		} // lower triangle, XY order: (0,0)->(1,0)->(1,1)
		else {
			$i1 = 0;
			$j1 = 1;
		}
		// upper triangle, YX order: (0,0)->(0,1)->(1,1)

		// A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
		// a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
		// c = (3-sqrt(3))/6

		$x1 = $x0 - $i1 + self::$G2; // Offsets for middle corner in (x,y) unskewed coords
		$y1 = $y0 - $j1 + self::$G2;
		$x2 = $x0 + self::$G22; // Offsets for last corner in (x,y) unskewed coords
		$y2 = $y0 + self::$G22;

		// Work out the hashed gradient indices of the three simplex corners
		$ii = $i & 255;
		$jj = $j & 255;

		$n = 0;

		// Calculate the contribution from the three corners
		$t0 = 0.5 - $x0 * $x0 - $y0 * $y0;
		if ($t0 > 0) {
			$gi0 = self::$grad3[$this->perm[$ii + $this->perm[$jj]] % 12];
			$n += $t0 * $t0 * $t0 * $t0 * ($gi0[0] * $x0 + $gi0[1] * $y0); // (x,y) of grad3 used for 2D gradient
		}

		$t1 = 0.5 - $x1 * $x1 - $y1 * $y1;
		if ($t1 > 0) {
			$gi1 = self::$grad3[$this->perm[$ii + $i1 + $this->perm[$jj + $j1]] % 12];
			$n += $t1 * $t1 * $t1 * $t1 * ($gi1[0] * $x1 + $gi1[1] * $y1);
		}

		$t2 = 0.5 - $x2 * $x2 - $y2 * $y2;
		if ($t2 > 0) {
			$gi2 = self::$grad3[$this->perm[$ii + 1 + $this->perm[$jj + 1]] % 12];
			$n += $t2 * $t2 * $t2 * $t2 * ($gi2[0] * $x2 + $gi2[1] * $y2);
		}

		// Add contributions from each corner to get the noise value.
		// The result is scaled to return values in the interval [-1,1].
		return 70.0 * $n;
	}

	/**
	 * Computes and returns the 4D simplex noise for the given coordinates in
	 * 4D space
	 *
	 * @param float $x X coordinate
	 * @param float $y Y coordinate
	 * @param float $z Z coordinate
	 * @param float $w W coordinate
	 *
	 * @return float Noise at given location, from range -1 to 1
	 */
	public function getNoise4D($x, $y, $z, $w)
	{
		$x += $this->offsetX;
		$y += $this->offsetY;
		$z += $this->offsetZ;
		$w += $this->offsetW;

		$n0 = 0;
		$n1 = 0;
		$n2 = 0;
		$n3 = 0;
		$n4 = 0;

		// Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in
		$s = ($x + $y + $z + $w) * self::$F4; // Factor for 4D skewing
		$i = (int)($x + $s);
		$j = (int)($y + $s);
		$k = (int)($z + $s);
		$l = (int)($w + $s);

		$t = ($i + $j + $k + $l) * self::$G4; // Factor for 4D unskewing
		$X0 = $i - $t; // Unskew the cell origin back to (x,y,z,w) space
		$Y0 = $j - $t;
		$Z0 = $k - $t;
		$W0 = $l - $t;
		$x0 = $x - $X0; // The x,y,z,w distances from the cell origin
		$y0 = $y - $Y0;
		$z0 = $z - $Z0;
		$w0 = $w - $W0;

		// For the 4D case, the simplex is a 4D shape I won't even try to describe.
		// To find out which of the 24 possible simplices we're in, we need to
		// determine the magnitude ordering of x0, y0, z0 and w0.
		// The method below is a good way of finding the ordering of x,y,z,w and
		// then find the correct traversal order for the simplex we’re in.
		// First, six pair-wise comparisons are performed between each possible pair
		// of the four coordinates, and the results are used to add up binary bits
		// for an integer index.
		$c1 = ($x0 > $y0) ? 32 : 0;
		$c2 = ($x0 > $z0) ? 16 : 0;
		$c3 = ($y0 > $z0) ? 8 : 0;
		$c4 = ($x0 > $w0) ? 4 : 0;
		$c5 = ($y0 > $w0) ? 2 : 0;
		$c6 = ($z0 > $w0) ? 1 : 0;
		$c = $c1 + $c2 + $c3 + $c4 + $c5 + $c6;
		$i1 = self::$simplex[$c][0] >= 3 ? 1 : 0;
		$j1 = self::$simplex[$c][1] >= 3 ? 1 : 0;
		$k1 = self::$simplex[$c][2] >= 3 ? 1 : 0;
		$l1 = self::$simplex[$c][3] >= 3 ? 1 : 0;
		$i2 = self::$simplex[$c][0] >= 2 ? 1 : 0;
		$j2 = self::$simplex[$c][1] >= 2 ? 1 : 0;
		$k2 = self::$simplex[$c][2] >= 2 ? 1 : 0;
		$l2 = self::$simplex[$c][3] >= 2 ? 1 : 0;
		$i3 = self::$simplex[$c][0] >= 1 ? 1 : 0;
		$j3 = self::$simplex[$c][1] >= 1 ? 1 : 0;
		$k3 = self::$simplex[$c][2] >= 1 ? 1 : 0;
		$l3 = self::$simplex[$c][3] >= 1 ? 1 : 0;
		$i4 = self::$simplex[$c][0] >= 0 ? 1 : 0;
		$j4 = self::$simplex[$c][1] >= 0 ? 1 : 0;
		$k4 = self::$simplex[$c][2] >= 0 ? 1 : 0;
		$l4 = self::$simplex[$c][3] >= 0 ? 1 : 0;

		$x1 = $x0 - $i1 + self::$G4; // Offsets for second corner in (x,y,z,w) coords
		$y1 = $y0 - $j1 + self::$G4;
		$z1 = $z0 - $k1 + self::$G4;
		$w1 = $w0 - $l1 + self::$G4;

		$x2 = $x0 - $i2 + 2.0 * self::$G4; // Offsets for third corner in (x,y,z,w) coords
		$y2 = $y0 - $j2 + 2.0 * self::$G4;
		$z2 = $z0 - $k2 + 2.0 * self::$G4;
		$w2 = $w0 - $l2 + 2.0 * self::$G4;

		$x3 = $x0 - $i3 + 3.0 * self::$G4; // Offsets for fourth corner in (x,y,z,w) coords
		$y3 = $y0 - $j3 + 3.0 * self::$G4;
		$z3 = $z0 - $k3 + 3.0 * self::$G4;
		$w3 = $w0 - $l3 + 3.0 * self::$G4;

		$x4 = $x0 - 1.0 + 4.0 * self::$G4; // Offsets for last corner in (x,y,z,w) coords
		$y4 = $y0 - 1.0 + 4.0 * self::$G4;
		$z4 = $z0 - 1.0 + 4.0 * self::$G4;
		$w4 = $w0 - 1.0 + 4.0 * self::$G4;

		// Work out the hashed gradient indices of the five simplex corners
		$ii = $i & 255;
		$jj = $j & 255;
		$kk = $k & 255;
		$ll = $l & 255;

		$gi0 = $this->perm[$ii + $this->perm[$jj + $this->perm[$kk + $this->perm[$ll]]]] % 32;
		$gi1 = $this->perm[$ii + $i1 + $this->perm[$jj + $j1 + $this->perm[$kk + $k1 + $this->perm[$ll + $l1]]]] % 32;
		$gi2 = $this->perm[$ii + $i2 + $this->perm[$jj + $j2 + $this->perm[$kk + $k2 + $this->perm[$ll + $l2]]]] % 32;
		$gi3 = $this->perm[$ii + $i3 + $this->perm[$jj + $j3 + $this->perm[$kk + $k3 + $this->perm[$ll + $l3]]]] % 32;
		$gi4 = $this->perm[$ii + $i4 + $this->perm[$jj + $j4 + $this->perm[$kk + $k4 + $this->perm[$ll + $l4]]]] % 32;

		// Calculate the contribution from the five corners
		$t0 = 0.6 - $x0 * $x0 - $y0 * $y0 - $z0 * $z0 - $w0 * $w0;
		if ($t0 > 0) {
			$n0 = $t0 * $t0 * $t0 * $t0 * self::dot4D(self::$grad4[$gi0], $x0, $y0, $z0, $w0);
		}

		$t1 = 0.6 - $x1 * $x1 - $y1 * $y1 - $z1 * $z1 - $w1 * $w1;
		if ($t1 > 0) {
			$n1 = $t1 * $t1 * $t1 * $t1 * self::dot4D(self::$grad4[$gi1], $x1, $y1, $z1, $w1);
		}

		$t2 = 0.6 - $x2 * $x2 - $y2 * $y2 - $z2 * $z2 - $w2 * $w2;
		if ($t2 > 0) {
			$n2 = $t2 * $t2 * $t2 * $t2 * self::dot4D(self::$grad4[$gi2], $x2, $y2, $z2, $w2);
		}

		$t3 = 0.6 - $x3 * $x3 - $y3 * $y3 - $z3 * $z3 - $w3 * $w3;
		if ($t3 > 0) {
			$n3 = $t3 * $t3 * $t3 * $t3 * self::dot4D(self::$grad4[$gi3], $x3, $y3, $z3, $w3);
		}

		$t4 = 0.6 - $x4 * $x4 - $y4 * $y4 - $z4 * $z4 - $w4 * $w4;
		if ($t4 > 0) {
			$n4 = $t4 * $t4 * $t4 * $t4 * self::dot4D(self::$grad4[$gi4], $x4, $y4, $z4, $w4);
		}

		// Sum up and scale the result to cover the range [-1,1]
		return 27.0 * ($n0 + $n1 + $n2 + $n3 + $n4);
	}

	public function noise4D($x, $y, $z, $w, $normalized = false)
	{
		$result = 0;
		$amp = 1;
		$freq = 1;
		$max = 0;

		$x *= $this->expansion;
		$y *= $this->expansion;
		$z *= $this->expansion;
		$w *= $this->expansion;

		for ($i = 0; $i < $this->octaves; ++$i) {
			$result += $this->getNoise4D($x * $freq, $y * $freq, $z * $freq, $w * $freq) * $amp;
			$max += $amp;
			$freq *= 2;
			$amp *= $this->persistence;
		}

		if ($normalized === true) {
			$result /= $max;
		}

		return $result;
	}

	public function getFastNoise4D(int $xSize, int $ySize, int $zSize, $wSize, int $xSamplingRate, int $ySamplingRate, int $zSamplingRate, int $wSamplingRate, int $x, int $y, int $z, $w): array
	{
		assert($xSamplingRate !== 0, new InvalidArgumentException("xSamplingRate cannot be 0"));
		assert($ySamplingRate !== 0, new InvalidArgumentException("ySamplingRate cannot be 0"));
		assert($zSamplingRate !== 0, new InvalidArgumentException("zSamplingRate cannot be 0"));
		assert($wSamplingRate !== 0, new InvalidArgumentException("wSamplingRate cannot be 0"));

		assert($xSize % $xSamplingRate === 0, new InvalidArgumentException("xSize % xSamplingRate must return 0"));
		assert($ySize % $ySamplingRate === 0, new InvalidArgumentException("ySize % ySamplingRate must return 0"));
		assert($zSize % $zSamplingRate === 0, new InvalidArgumentException("zSize % zSamplingRate must return 0"));
		assert($wSize % $wSamplingRate === 0, new InvalidArgumentException("wSize % wSamplingRate must return 0"));

		$noiseArray = array_fill(0, intval($xSize / $xSamplingRate), array_fill(0, intval($zSize / $zSamplingRate), array_fill(0, intval($wSize / $wSamplingRate), array_fill(0, intval($ySize / $ySamplingRate), null))));

		for ($xx = 0; $xx <= $xSize; $xx += $xSamplingRate) {
			for ($zz = 0; $zz <= $zSize; $zz += $zSamplingRate) {
				for ($yy = 0; $yy <= $ySize; $yy += $ySamplingRate) {
					for ($ww = 0; $ww <= $wSize; $ww += $wSamplingRate) {
						$noiseArray[intdiv($xx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($ww, $wSamplingRate)][intdiv($yy, $ySamplingRate)] = $this->noise4D($xx + $x, $yy + $y, $zz + $z, $ww + $w, true);
					}
				}
			}
		}

		for ($xx = 0; $xx < $xSize; ++$xx) {
			for ($zz = 0; $zz < $zSize; ++$zz) {
				for ($yy = 0; $yy < $ySize; ++$yy) {
					for ($ww = 0; $ww < $wSize; ++$ww) {
						if ($xx % $xSamplingRate !== 0 or $zz % $zSamplingRate !== 0 or $yy % $ySamplingRate !== 0 or $ww % $wSamplingRate !== 0) {
							$nx = (int) ($xx / $xSamplingRate) * $xSamplingRate;
							$ny = (int) ($yy / $ySamplingRate) * $ySamplingRate;
							$nz = (int) ($zz / $zSamplingRate) * $zSamplingRate;
							$nw = (int) ($ww / $wSamplingRate) * $wSamplingRate;

							$nnx = $nx + $xSamplingRate;
							$nny = $ny + $ySamplingRate;
							$nnz = $nz + $zSamplingRate;
							$nnw = $nw + $wSamplingRate;

							$dx1 = (($nnx - $xx) / ($nnx - $nx));
							$dx2 = (($xx - $nx) / ($nnx - $nx));
							$dy1 = (($nny - $yy) / ($nny - $ny));
							$dy2 = (($yy - $ny) / ($nny - $ny));
							$dz1 = (($nnz - $zz) / ($nnz - $nz));
							$dz2 = (($zz - $nz) / ($nnz - $nz));
							$dw1 = (($nnw - $ww) / ($nnw - $nw));
							$dw2 = (($ww - $nw) / ($nnw - $nw)); // res

							$noiseArray[intdiv($xx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($ww, $wSamplingRate)][intdiv($yy, $ySamplingRate)] =
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)])) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) * (1.0 - $dw1) * (1.0 - $dz1) * (1.0 - $dy1) * (1.0 - $dx1)) +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) * (1.0 - $dw1) * (1.0 - $dz1) * (1.0 - $dy1) * $dx1 +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * (1.0 - $dw1) * (1.0 - $dz1) * $dy1 * (1.0 - $dx1) +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * (1.0 - $dw1) * (1.0 - $dz1) * $dy1 * $dx1 +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * $dw1 * (1.0 - $dz1) * (1.0 - $dy1) * (1.0 - $dx1) +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * $dw1 * (1.0 - $dz1) * (1.0 - $dy1) * $dx1 +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * $dw1 * $dz1 * (1.0 - $dy1) * (1.0 - $dx1) +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]))) * $dw1 * $dz1 * (1.0 - $dy1) * $dx1 +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($zz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * $dw1 * $dz1 * $dy1 * (1.0 - $dx1) +
								($dw1 * ($dz1 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) + $dz2 * ($dy1 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($nny, $ySamplingRate)]) + $dy2 * ($dx1 * $noiseArray[intdiv($nx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)] + $dx2 * $noiseArray[intdiv($nnx, $xSamplingRate)][intdiv($nnz, $zSamplingRate)][intdiv($nnw, $wSamplingRate)][intdiv($ny, $ySamplingRate)]))) * $dw1 * $dz1 * $dy1 * $dx1;
						}
					}
				}
			}
		}

		return $noiseArray;
	}
}
