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synced 2026-03-09 21:31:51 +09:00
COPYING update
This commit is contained in:
minjaesong
@@ -1,24 +1,12 @@
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package net.torvald.terrarum
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import net.torvald.terrarum.langpack.Lang
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object CreditSingleton {
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val credit: List<String>; get() =
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("${Lang["CREDITS_PROGRAMMER"]}\n\nCuriousTorvald (minjaesong)\n\n\n" +
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"${Lang["CREDITS_ARTIST_PLURAL"]}\n\nCuriousTorvald (minjaesong)\nRoundworld (leedonggeun)\n\n\n" +
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"${Lang["CREDITS_POLYGLOT"]}\n\n\n" +
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"${Lang["CREDITS_SOUNDTRACK"]}: FreeSound.org\n" +
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("Programming, Arts, Directed by CuriousTorvald (minjaesong)\n" +
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"Sound Effects by FreeSound.org and Klankbeeld\n" +
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"Translation Database by the Polyglot Project\n" +
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"""
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Klankbeeld
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Copyright Information
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Terrarum
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@@ -1,73 +0,0 @@
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package net.torvald.terrarum.modulebasegame.worldgenerator
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import net.torvald.random.HQRNG
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import com.jme3.math.FastMath
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class SimplexNoise
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/**
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* @param largestFeature
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* *
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* @param persistence higher the value, rougher the output
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* *
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* @param seed
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*/
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(internal var largestFeature: Int, internal var persistence: Float, internal var seed: Long) {
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internal var octaves: Array<SimplexNoise_octave>
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internal var frequencys: FloatArray
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internal var amplitudes: FloatArray
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init {
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//receives a number (e.g. 128) and calculates what power of 2 it is (e.g. 2^7)
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val numberOfOctaves = FastMath.intLog2(largestFeature)
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val rnd = HQRNG(seed)
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octaves = Array<SimplexNoise_octave>(numberOfOctaves, {i -> SimplexNoise_octave(rnd.nextInt())})
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frequencys = FloatArray(numberOfOctaves)
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amplitudes = FloatArray(numberOfOctaves)
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for (i in 0..numberOfOctaves - 1) {
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octaves[i] = SimplexNoise_octave(rnd.nextInt())
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frequencys[i] = FastMath.pow(2f, i.toFloat())
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amplitudes[i] = FastMath.pow(persistence, (octaves.size - i).toFloat())
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}
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}
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fun getNoise(x: Int, y: Int): Float {
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var result = 0f
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for (i in octaves.indices) {
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//float frequency = FastMath.pow(2,i);
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//float amplitude = FastMath.pow(persistence,octaves.length-i);
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result += (octaves[i].noise((x / frequencys[i]).toDouble(), (y / frequencys[i]).toDouble()) * amplitudes[i]).toFloat()
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}
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return result
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}
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fun getNoise(x: Int, y: Int, z: Int): Float {
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var result = 0f
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for (i in octaves.indices) {
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val frequency = FastMath.pow(2f, i.toFloat())
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val amplitude = FastMath.pow(persistence, (octaves.size - i).toFloat())
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result += (octaves[i].noise((x / frequency).toDouble(), (y / frequency).toDouble(), (z / frequency).toDouble()) * amplitude).toFloat()
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}
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return result
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}
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}
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@@ -1,457 +0,0 @@
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package net.torvald.terrarum.modulebasegame.worldgenerator
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/*
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* A speed-improved simplex noise algorithm for 2D, 3D and 4D in Java.
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*
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* Based on example code by Stefan Gustavson (stegu@itn.liu.se).
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* Optimisations by Peter Eastman (peastman@drizzle.stanford.edu).
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* Better rank ordering method by Stefan Gustavson in 2012.
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*
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* This could be speeded up even further, but it's useful as it is.
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*
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* Version 2012-03-09
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*
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* This code was placed in the public domain by its original author,
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* Stefan Gustavson. You may use it as you see fit, but
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* attribution is appreciated.
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*
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*/
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import net.torvald.random.HQRNG
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class SimplexNoise_octave(seed: Int) { // Simplex noise in 2D, 3D and 4D
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private var p = ShortArray(p_supply.size)
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// To remove the need for index wrapping, double the permutation table length
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private val perm = ShortArray(512)
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private val permMod12 = ShortArray(512)
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init {
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p = p_supply.clone()
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if (seed == RANDOMSEED) {
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throw IllegalArgumentException("Seed cannot be zero.")
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}
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//the random for the swaps
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val rand = HQRNG(seed.toLong())
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//the seed determines the swaps that occur between the default order and the order we're actually going to use
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for (i in 0..NUMBEROFSWAPS - 1) {
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val swapFrom = rand.nextInt(p.size)
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val swapTo = rand.nextInt(p.size)
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val temp = p[swapFrom]
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p[swapFrom] = p[swapTo]
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p[swapTo] = temp
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}
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for (i in 0..511) {
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perm[i] = p[i and 255]
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permMod12[i] = (perm[i] % 12).toShort()
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}
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}
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// 2D simplex noise
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fun noise(xin: Double, yin: Double): Double {
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val n0: Double
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val n1: Double
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val n2: Double // Noise contributions from the three corners
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// Skew the input space to determine which simplex cell we're in
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val s = (xin + yin) * F2 // Hairy factor for 2D
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val i = fastfloor(xin + s)
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val j = fastfloor(yin + s)
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val t = (i + j) * G2
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val X0 = i - t // Unskew the cell origin back to (x,y) space
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val Y0 = j - t
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val x0 = xin - X0 // The x,y distances from the cell origin
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val y0 = yin - Y0
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// For the 2D case, the simplex shape is an equilateral triangle.
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// Determine which simplex we are in.
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val i1: Int
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val j1: Int // Offsets for second (middle) corner of simplex in (i,j) coords
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if (x0 > y0) {
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i1 = 1
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j1 = 0
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} // lower triangle, XY order: (0,0)->(1,0)->(1,1)
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else {
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i1 = 0
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j1 = 1
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} // upper triangle, YX order: (0,0)->(0,1)->(1,1)
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// A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
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// a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
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// c = (3-sqrt(3))/6
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val x1 = x0 - i1 + G2 // Offsets for middle corner in (x,y) unskewed coords
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val y1 = y0 - j1 + G2
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val x2 = x0 - 1.0 + 2.0 * G2 // Offsets for last corner in (x,y) unskewed coords
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val y2 = y0 - 1.0 + 2.0 * G2
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// Work out the hashed gradient indices of the three simplex corners
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val ii = i and 255
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val jj = j and 255
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val gi0 = permMod12[ii + perm[jj]].toInt()
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val gi1 = permMod12[ii + i1 + perm[jj + j1].toInt()].toInt()
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val gi2 = permMod12[ii + 1 + perm[jj + 1].toInt()].toInt()
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// Calculate the contribution from the three corners
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var t0 = 0.5 - x0 * x0 - y0 * y0
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if (t0 < 0)
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n0 = 0.0
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else {
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t0 *= t0
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n0 = t0 * t0 * dot(grad3[gi0], x0, y0) // (x,y) of grad3 used for 2D gradient
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}
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var t1 = 0.5 - x1 * x1 - y1 * y1
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if (t1 < 0)
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n1 = 0.0
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else {
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t1 *= t1
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n1 = t1 * t1 * dot(grad3[gi1], x1, y1)
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}
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var t2 = 0.5 - x2 * x2 - y2 * y2
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if (t2 < 0)
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n2 = 0.0
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else {
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t2 *= t2
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n2 = t2 * t2 * dot(grad3[gi2], x2, y2)
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}
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// Add contributions from each corner to get the final noise value.
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// The result is scaled to return values in the interval [-1,1].
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return 70.0 * (n0 + n1 + n2)
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}
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// 3D simplex noise
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fun noise(xin: Double, yin: Double, zin: Double): Double {
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val n0: Double
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val n1: Double
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val n2: Double
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val n3: Double // Noise contributions from the four corners
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// Skew the input space to determine which simplex cell we're in
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val s = (xin + yin + zin) * F3 // Very nice and simple skew factor for 3D
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val i = fastfloor(xin + s)
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val j = fastfloor(yin + s)
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val k = fastfloor(zin + s)
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val t = (i + j + k) * G3
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val X0 = i - t // Unskew the cell origin back to (x,y,z) space
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val Y0 = j - t
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val Z0 = k - t
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val x0 = xin - X0 // The x,y,z distances from the cell origin
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val y0 = yin - Y0
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val z0 = zin - Z0
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// For the 3D case, the simplex shape is a slightly irregular tetrahedron.
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// Determine which simplex we are in.
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val i1: Int
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val j1: Int
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val k1: Int // Offsets for second corner of simplex in (i,j,k) coords
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val i2: Int
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val j2: Int
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val k2: Int // Offsets for third corner of simplex in (i,j,k) coords
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if (x0 >= y0) {
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if (y0 >= z0) {
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i1 = 1
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j1 = 0
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k1 = 0
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i2 = 1
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j2 = 1
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k2 = 0
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} // X Y Z order
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else if (x0 >= z0) {
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i1 = 1
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j1 = 0
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k1 = 0
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i2 = 1
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j2 = 0
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k2 = 1
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} // X Z Y order
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else {
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i1 = 0
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j1 = 0
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k1 = 1
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i2 = 1
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j2 = 0
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k2 = 1
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} // Z X Y order
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}
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else {
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// x0<y0
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if (y0 < z0) {
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i1 = 0
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j1 = 0
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k1 = 1
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i2 = 0
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j2 = 1
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k2 = 1
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} // Z Y X order
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else if (x0 < z0) {
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i1 = 0
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j1 = 1
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k1 = 0
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i2 = 0
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j2 = 1
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k2 = 1
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} // Y Z X order
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else {
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i1 = 0
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j1 = 1
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k1 = 0
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i2 = 1
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j2 = 1
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k2 = 0
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} // Y X Z order
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}
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// A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z),
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// a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and
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// a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where
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// c = 1/6.
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val x1 = x0 - i1 + G3 // Offsets for second corner in (x,y,z) coords
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val y1 = y0 - j1 + G3
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val z1 = z0 - k1 + G3
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val x2 = x0 - i2 + 2.0 * G3 // Offsets for third corner in (x,y,z) coords
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val y2 = y0 - j2 + 2.0 * G3
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val z2 = z0 - k2 + 2.0 * G3
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val x3 = x0 - 1.0 + 3.0 * G3 // Offsets for last corner in (x,y,z) coords
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val y3 = y0 - 1.0 + 3.0 * G3
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val z3 = z0 - 1.0 + 3.0 * G3
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// Work out the hashed gradient indices of the four simplex corners
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val ii = i and 255
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val jj = j and 255
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val kk = k and 255
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val gi0 = permMod12[ii + perm[jj + perm[kk]]].toInt()
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val gi1 = permMod12[ii + i1 + perm[jj + j1 + perm[kk + k1].toInt()].toInt()].toInt()
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val gi2 = permMod12[ii + i2 + perm[jj + j2 + perm[kk + k2].toInt()].toInt()].toInt()
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val gi3 = permMod12[ii + 1 + perm[jj + 1 + perm[kk + 1].toInt()].toInt()].toInt()
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// Calculate the contribution from the four corners
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var t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0
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if (t0 < 0)
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n0 = 0.0
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else {
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t0 *= t0
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n0 = t0 * t0 * dot(grad3[gi0], x0, y0, z0)
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}
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var t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1
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if (t1 < 0)
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n1 = 0.0
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else {
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t1 *= t1
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n1 = t1 * t1 * dot(grad3[gi1], x1, y1, z1)
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}
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var t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2
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if (t2 < 0)
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n2 = 0.0
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else {
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t2 *= t2
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n2 = t2 * t2 * dot(grad3[gi2], x2, y2, z2)
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}
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var t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3
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if (t3 < 0)
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n3 = 0.0
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else {
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t3 *= t3
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n3 = t3 * t3 * dot(grad3[gi3], x3, y3, z3)
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}
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// Add contributions from each corner to get the final noise value.
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// The result is scaled to stay just inside [-1,1]
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return 32.0 * (n0 + n1 + n2 + n3)
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}
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// 4D simplex noise, better simplex rank ordering method 2012-03-09
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fun noise(x: Double, y: Double, z: Double, w: Double): Double {
|
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val n0: Double
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val n1: Double
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val n2: Double
|
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val n3: Double
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val n4: Double // Noise contributions from the five corners
|
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// Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in
|
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val s = (x + y + z + w) * F4 // Factor for 4D skewing
|
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val i = fastfloor(x + s)
|
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val j = fastfloor(y + s)
|
||||
val k = fastfloor(z + s)
|
||||
val l = fastfloor(w + s)
|
||||
val t = (i + j + k + l) * G4 // Factor for 4D unskewing
|
||||
val X0 = i - t // Unskew the cell origin back to (x,y,z,w) space
|
||||
val Y0 = j - t
|
||||
val Z0 = k - t
|
||||
val W0 = l - t
|
||||
val x0 = x - X0 // The x,y,z,w distances from the cell origin
|
||||
val y0 = y - Y0
|
||||
val z0 = z - Z0
|
||||
val 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.
|
||||
// Six pair-wise comparisons are performed between each possible pair
|
||||
// of the four coordinates, and the results are used to rank the numbers.
|
||||
var rankx = 0
|
||||
var ranky = 0
|
||||
var rankz = 0
|
||||
var rankw = 0
|
||||
if (x0 > y0) rankx++ else ranky++
|
||||
if (x0 > z0) rankx++ else rankz++
|
||||
if (x0 > w0) rankx++ else rankw++
|
||||
if (y0 > z0) ranky++ else rankz++
|
||||
if (y0 > w0) ranky++ else rankw++
|
||||
if (z0 > w0) rankz++ else rankw++
|
||||
val i1: Int
|
||||
val j1: Int
|
||||
val k1: Int
|
||||
val l1: Int // The integer offsets for the second simplex corner
|
||||
val i2: Int
|
||||
val j2: Int
|
||||
val k2: Int
|
||||
val l2: Int // The integer offsets for the third simplex corner
|
||||
val i3: Int
|
||||
val j3: Int
|
||||
val k3: Int
|
||||
val l3: Int // The integer offsets for the fourth simplex corner
|
||||
// simplex[c] is a 4-vector with the numbers 0, 1, 2 and 3 in some order.
|
||||
// Many values of c will never occur, since e.g. x>y>z>w makes x<z, y<w and x<w
|
||||
// impossible. Only the 24 indices which have non-zero entries make any sense.
|
||||
// We use a thresholding to set the coordinates in turn from the largest magnitude.
|
||||
// Rank 3 denotes the largest coordinate.
|
||||
i1 = if (rankx >= 3) 1 else 0
|
||||
j1 = if (ranky >= 3) 1 else 0
|
||||
k1 = if (rankz >= 3) 1 else 0
|
||||
l1 = if (rankw >= 3) 1 else 0
|
||||
// Rank 2 denotes the second largest coordinate.
|
||||
i2 = if (rankx >= 2) 1 else 0
|
||||
j2 = if (ranky >= 2) 1 else 0
|
||||
k2 = if (rankz >= 2) 1 else 0
|
||||
l2 = if (rankw >= 2) 1 else 0
|
||||
// Rank 1 denotes the second smallest coordinate.
|
||||
i3 = if (rankx >= 1) 1 else 0
|
||||
j3 = if (ranky >= 1) 1 else 0
|
||||
k3 = if (rankz >= 1) 1 else 0
|
||||
l3 = if (rankw >= 1) 1 else 0
|
||||
// The fifth corner has all coordinate offsets = 1, so no need to compute that.
|
||||
val x1 = x0 - i1 + G4 // Offsets for second corner in (x,y,z,w) coords
|
||||
val y1 = y0 - j1 + G4
|
||||
val z1 = z0 - k1 + G4
|
||||
val w1 = w0 - l1 + G4
|
||||
val x2 = x0 - i2 + 2.0 * G4 // Offsets for third corner in (x,y,z,w) coords
|
||||
val y2 = y0 - j2 + 2.0 * G4
|
||||
val z2 = z0 - k2 + 2.0 * G4
|
||||
val w2 = w0 - l2 + 2.0 * G4
|
||||
val x3 = x0 - i3 + 3.0 * G4 // Offsets for fourth corner in (x,y,z,w) coords
|
||||
val y3 = y0 - j3 + 3.0 * G4
|
||||
val z3 = z0 - k3 + 3.0 * G4
|
||||
val w3 = w0 - l3 + 3.0 * G4
|
||||
val x4 = x0 - 1.0 + 4.0 * G4 // Offsets for last corner in (x,y,z,w) coords
|
||||
val y4 = y0 - 1.0 + 4.0 * G4
|
||||
val z4 = z0 - 1.0 + 4.0 * G4
|
||||
val w4 = w0 - 1.0 + 4.0 * G4
|
||||
// Work out the hashed gradient indices of the five simplex corners
|
||||
val ii = i and 255
|
||||
val jj = j and 255
|
||||
val kk = k and 255
|
||||
val ll = l and 255
|
||||
val gi0 = perm[ii + perm[jj + perm[kk + perm[ll]]]] % 32
|
||||
val gi1 = perm[ii + i1 + perm[jj + j1 + perm[kk + k1 + perm[ll + l1].toInt()].toInt()].toInt()] % 32
|
||||
val gi2 = perm[ii + i2 + perm[jj + j2 + perm[kk + k2 + perm[ll + l2].toInt()].toInt()].toInt()] % 32
|
||||
val gi3 = perm[ii + i3 + perm[jj + j3 + perm[kk + k3 + perm[ll + l3].toInt()].toInt()].toInt()] % 32
|
||||
val gi4 = perm[ii + 1 + perm[jj + 1 + perm[kk + 1 + perm[ll + 1].toInt()].toInt()].toInt()] % 32
|
||||
// Calculate the contribution from the five corners
|
||||
var t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0
|
||||
if (t0 < 0)
|
||||
n0 = 0.0
|
||||
else {
|
||||
t0 *= t0
|
||||
n0 = t0 * t0 * dot(grad4[gi0], x0, y0, z0, w0)
|
||||
}
|
||||
var t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1
|
||||
if (t1 < 0)
|
||||
n1 = 0.0
|
||||
else {
|
||||
t1 *= t1
|
||||
n1 = t1 * t1 * dot(grad4[gi1], x1, y1, z1, w1)
|
||||
}
|
||||
var t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2
|
||||
if (t2 < 0)
|
||||
n2 = 0.0
|
||||
else {
|
||||
t2 *= t2
|
||||
n2 = t2 * t2 * dot(grad4[gi2], x2, y2, z2, w2)
|
||||
}
|
||||
var t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3
|
||||
if (t3 < 0)
|
||||
n3 = 0.0
|
||||
else {
|
||||
t3 *= t3
|
||||
n3 = t3 * t3 * dot(grad4[gi3], x3, y3, z3, w3)
|
||||
}
|
||||
var t4 = 0.6 - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4
|
||||
if (t4 < 0)
|
||||
n4 = 0.0
|
||||
else {
|
||||
t4 *= t4
|
||||
n4 = t4 * t4 * dot(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)
|
||||
}
|
||||
|
||||
// Inner class to speed upp gradient computations
|
||||
// (array access is a lot slower than member access)
|
||||
private class Grad {
|
||||
internal var x: Double = 0.toDouble()
|
||||
internal var y: Double = 0.toDouble()
|
||||
internal var z: Double = 0.toDouble()
|
||||
internal var w: Double = 0.toDouble()
|
||||
|
||||
internal constructor(x: Double, y: Double, z: Double) {
|
||||
this.x = x
|
||||
this.y = y
|
||||
this.z = z
|
||||
}
|
||||
|
||||
internal constructor(x: Double, y: Double, z: Double, w: Double) {
|
||||
this.x = x
|
||||
this.y = y
|
||||
this.z = z
|
||||
this.w = w
|
||||
}
|
||||
}
|
||||
|
||||
companion object {
|
||||
|
||||
var RANDOMSEED = 0
|
||||
private val NUMBEROFSWAPS = 400
|
||||
|
||||
private val grad3 = arrayOf(Grad(1.0, 1.0, 0.0), Grad(-1.0, 1.0, 0.0), Grad(1.0, -1.0, 0.0), Grad(-1.0, -1.0, 0.0), Grad(1.0, 0.0, 1.0), Grad(-1.0, 0.0, 1.0), Grad(1.0, 0.0, -1.0), Grad(-1.0, 0.0, -1.0), Grad(0.0, 1.0, 1.0), Grad(0.0, -1.0, 1.0), Grad(0.0, 1.0, -1.0), Grad(0.0, -1.0, -1.0))
|
||||
|
||||
private val grad4 = arrayOf(Grad(0.0, 1.0, 1.0, 1.0), Grad(0.0, 1.0, 1.0, -1.0), Grad(0.0, 1.0, -1.0, 1.0), Grad(0.0, 1.0, -1.0, -1.0), Grad(0.0, -1.0, 1.0, 1.0), Grad(0.0, -1.0, 1.0, -1.0), Grad(0.0, -1.0, -1.0, 1.0), Grad(0.0, -1.0, -1.0, -1.0), Grad(1.0, 0.0, 1.0, 1.0), Grad(1.0, 0.0, 1.0, -1.0), Grad(1.0, 0.0, -1.0, 1.0), Grad(1.0, 0.0, -1.0, -1.0), Grad(-1.0, 0.0, 1.0, 1.0), Grad(-1.0, 0.0, 1.0, -1.0), Grad(-1.0, 0.0, -1.0, 1.0), Grad(-1.0, 0.0, -1.0, -1.0), Grad(1.0, 1.0, 0.0, 1.0), Grad(1.0, 1.0, 0.0, -1.0), Grad(1.0, -1.0, 0.0, 1.0), Grad(1.0, -1.0, 0.0, -1.0), Grad(-1.0, 1.0, 0.0, 1.0), Grad(-1.0, 1.0, 0.0, -1.0), Grad(-1.0, -1.0, 0.0, 1.0), Grad(-1.0, -1.0, 0.0, -1.0), Grad(1.0, 1.0, 1.0, 0.0), Grad(1.0, 1.0, -1.0, 0.0), Grad(1.0, -1.0, 1.0, 0.0), Grad(1.0, -1.0, -1.0, 0.0), Grad(-1.0, 1.0, 1.0, 0.0), Grad(-1.0, 1.0, -1.0, 0.0), Grad(-1.0, -1.0, 1.0, 0.0), Grad(-1.0, -1.0, -1.0, 0.0))
|
||||
|
||||
private val p_supply = shortArrayOf(151, 160, 137, 91, 90, 15, //this contains all the numbers between 0 and 255, these are put in a random order depending upon the seed
|
||||
131, 13, 201, 95, 96, 53, 194, 233, 7, 225, 140, 36, 103, 30, 69, 142, 8, 99, 37, 240, 21, 10, 23, 190, 6, 148, 247, 120, 234, 75, 0, 26, 197, 62, 94, 252, 219, 203, 117, 35, 11, 32, 57, 177, 33, 88, 237, 149, 56, 87, 174, 20, 125, 136, 171, 168, 68, 175, 74, 165, 71, 134, 139, 48, 27, 166, 77, 146, 158, 231, 83, 111, 229, 122, 60, 211, 133, 230, 220, 105, 92, 41, 55, 46, 245, 40, 244, 102, 143, 54, 65, 25, 63, 161, 1, 216, 80, 73, 209, 76, 132, 187, 208, 89, 18, 169, 200, 196, 135, 130, 116, 188, 159, 86, 164, 100, 109, 198, 173, 186, 3, 64, 52, 217, 226, 250, 124, 123, 5, 202, 38, 147, 118, 126, 255, 82, 85, 212, 207, 206, 59, 227, 47, 16, 58, 17, 182, 189, 28, 42, 223, 183, 170, 213, 119, 248, 152, 2, 44, 154, 163, 70, 221, 153, 101, 155, 167, 43, 172, 9, 129, 22, 39, 253, 19, 98, 108, 110, 79, 113, 224, 232, 178, 185, 112, 104, 218, 246, 97, 228, 251, 34, 242, 193, 238, 210, 144, 12, 191, 179, 162, 241, 81, 51, 145, 235, 249, 14, 239, 107, 49, 192, 214, 31, 181, 199, 106, 157, 184, 84, 204, 176, 115, 121, 50, 45, 127, 4, 150, 254, 138, 236, 205, 93, 222, 114, 67, 29, 24, 72, 243, 141, 128, 195, 78, 66, 215, 61, 156, 180)
|
||||
|
||||
// Skewing and unskewing factors for 2, 3, and 4 dimensions
|
||||
private val F2 = 0.5 * (Math.sqrt(3.0) - 1.0)
|
||||
private val G2 = (3.0 - Math.sqrt(3.0)) / 6.0
|
||||
private val F3 = 1.0 / 3.0
|
||||
private val G3 = 1.0 / 6.0
|
||||
private val F4 = (Math.sqrt(5.0) - 1.0) / 4.0
|
||||
private val G4 = (5.0 - Math.sqrt(5.0)) / 20.0
|
||||
|
||||
// This method is a *lot* faster than using (int)Math.floor(x)
|
||||
private fun fastfloor(x: Double): Int {
|
||||
val xi = x.toInt()
|
||||
return if (x < xi) xi - 1 else xi
|
||||
}
|
||||
|
||||
private fun dot(g: Grad, x: Double, y: Double): Double {
|
||||
return g.x * x + g.y * y
|
||||
}
|
||||
|
||||
private fun dot(g: Grad, x: Double, y: Double, z: Double): Double {
|
||||
return g.x * x + g.y * y + g.z * z
|
||||
}
|
||||
|
||||
private fun dot(g: Grad, x: Double, y: Double, z: Double, w: Double): Double {
|
||||
return g.x * x + g.y * y + g.z * z + g.w * w
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user