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FastNoise.cs
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FastNoise.cs
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// FastNoise.cs
//
// MIT License
//
// Copyright(c) 2017 Jordan Peck
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files(the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and / or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions :
//
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
//
// The developer's email is jorzixdan.me2@gzixmail.com (for great email, take
// off every 'zix'.)
//
// Uncomment the line below to swap all the inputs/outputs/calculations of FastNoise to doubles instead of floats
//#define FN_USE_DOUBLES
#if FN_USE_DOUBLES
using FN_DECIMAL = System.Double;
#else
using FN_DECIMAL = System.Single;
#endif
using System;
using System.Runtime.CompilerServices;
public class FastNoise
{
private const Int16 FN_INLINE = 256; //(Int16)MethodImplOptions.AggressiveInlining;
private const int FN_CELLULAR_INDEX_MAX = 3;
public enum NoiseType { Value, ValueFractal, Perlin, PerlinFractal, Simplex, SimplexFractal, Cellular, WhiteNoise, Cubic, CubicFractal };
public enum Interp { Linear, Hermite, Quintic };
public enum FractalType { FBM, Billow, RigidMulti };
public enum CellularDistanceFunction { Euclidean, Manhattan, Natural };
public enum CellularReturnType { CellValue, NoiseLookup, Distance, Distance2, Distance2Add, Distance2Sub, Distance2Mul, Distance2Div };
private int m_seed = 1337;
private FN_DECIMAL m_frequency = (FN_DECIMAL)0.01;
private Interp m_interp = Interp.Quintic;
private NoiseType m_noiseType = NoiseType.Simplex;
private int m_octaves = 3;
private FN_DECIMAL m_lacunarity = (FN_DECIMAL)2.0;
private FN_DECIMAL m_gain = (FN_DECIMAL)0.5;
private FractalType m_fractalType = FractalType.FBM;
private FN_DECIMAL m_fractalBounding;
private CellularDistanceFunction m_cellularDistanceFunction = CellularDistanceFunction.Euclidean;
private CellularReturnType m_cellularReturnType = CellularReturnType.CellValue;
private FastNoise m_cellularNoiseLookup = null;
private int m_cellularDistanceIndex0 = 0;
private int m_cellularDistanceIndex1 = 1;
private float m_cellularJitter = 0.45f;
private FN_DECIMAL m_gradientPerturbAmp = (FN_DECIMAL)1.0;
public FastNoise(int seed = 1337)
{
m_seed = seed;
CalculateFractalBounding();
}
// Returns a 0 float/double
public static FN_DECIMAL GetDecimalType() { return 0; }
// Returns the seed used by this object
public int GetSeed() { return m_seed; }
// Sets seed used for all noise types
// Default: 1337
public void SetSeed(int seed) { m_seed = seed; }
// Sets frequency for all noise types
// Default: 0.01
public void SetFrequency(FN_DECIMAL frequency) { m_frequency = frequency; }
// Changes the interpolation method used to smooth between noise values
// Possible interpolation methods (lowest to highest quality) :
// - Linear
// - Hermite
// - Quintic
// Used in Value, Gradient Noise and Position Perturbing
// Default: Quintic
public void SetInterp(Interp interp) { m_interp = interp; }
// Sets noise return type of GetNoise(...)
// Default: Simplex
public void SetNoiseType(NoiseType noiseType) { m_noiseType = noiseType; }
// Sets octave count for all fractal noise types
// Default: 3
public void SetFractalOctaves(int octaves) { m_octaves = octaves; CalculateFractalBounding(); }
// Sets octave lacunarity for all fractal noise types
// Default: 2.0
public void SetFractalLacunarity(FN_DECIMAL lacunarity) { m_lacunarity = lacunarity; }
// Sets octave gain for all fractal noise types
// Default: 0.5
public void SetFractalGain(FN_DECIMAL gain) { m_gain = gain; CalculateFractalBounding(); }
// Sets method for combining octaves in all fractal noise types
// Default: FBM
public void SetFractalType(FractalType fractalType) { m_fractalType = fractalType; }
// Sets return type from cellular noise calculations
// Note: NoiseLookup requires another FastNoise object be set with SetCellularNoiseLookup() to function
// Default: CellValue
public void SetCellularDistanceFunction(CellularDistanceFunction cellularDistanceFunction) { m_cellularDistanceFunction = cellularDistanceFunction; }
// Sets distance function used in cellular noise calculations
// Default: Euclidean
public void SetCellularReturnType(CellularReturnType cellularReturnType) { m_cellularReturnType = cellularReturnType; }
// Sets the 2 distance indicies used for distance2 return types
// Default: 0, 1
// Note: index0 should be lower than index1
// Both indicies must be >= 0, index1 must be < 4
public void SetCellularDistance2Indicies(int cellularDistanceIndex0, int cellularDistanceIndex1)
{
m_cellularDistanceIndex0 = Math.Min(cellularDistanceIndex0, cellularDistanceIndex1);
m_cellularDistanceIndex1 = Math.Max(cellularDistanceIndex0, cellularDistanceIndex1);
m_cellularDistanceIndex0 = Math.Min(Math.Max(m_cellularDistanceIndex0, 0), FN_CELLULAR_INDEX_MAX);
m_cellularDistanceIndex1 = Math.Min(Math.Max(m_cellularDistanceIndex1, 0), FN_CELLULAR_INDEX_MAX);
}
// Sets the maximum distance a cellular point can move from it's grid position
// Setting this high will make artifacts more common
// Default: 0.45
public void SetCellularJitter(float cellularJitter) { m_cellularJitter = cellularJitter; }
// Noise used to calculate a cell value if cellular return type is NoiseLookup
// The lookup value is acquired through GetNoise() so ensure you SetNoiseType() on the noise lookup, value, gradient or simplex is recommended
public void SetCellularNoiseLookup(FastNoise noise) { m_cellularNoiseLookup = noise; }
// Sets the maximum perturb distance from original location when using GradientPerturb{Fractal}(...)
// Default: 1.0
public void SetGradientPerturbAmp(FN_DECIMAL gradientPerturbAmp) { m_gradientPerturbAmp = gradientPerturbAmp; }
private struct Float2
{
public readonly FN_DECIMAL x, y;
public Float2(FN_DECIMAL x, FN_DECIMAL y)
{
this.x = x;
this.y = y;
}
}
private struct Float3
{
public readonly FN_DECIMAL x, y, z;
public Float3(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
this.x = x;
this.y = y;
this.z = z;
}
}
private static readonly Float2[] GRAD_2D = {
new Float2(-1,-1), new Float2( 1,-1), new Float2(-1, 1), new Float2( 1, 1),
new Float2( 0,-1), new Float2(-1, 0), new Float2( 0, 1), new Float2( 1, 0),
};
private static readonly Float3[] GRAD_3D = {
new Float3( 1, 1, 0), new Float3(-1, 1, 0), new Float3( 1,-1, 0), new Float3(-1,-1, 0),
new Float3( 1, 0, 1), new Float3(-1, 0, 1), new Float3( 1, 0,-1), new Float3(-1, 0,-1),
new Float3( 0, 1, 1), new Float3( 0,-1, 1), new Float3( 0, 1,-1), new Float3( 0,-1,-1),
new Float3( 1, 1, 0), new Float3( 0,-1, 1), new Float3(-1, 1, 0), new Float3( 0,-1,-1),
};
private static readonly Float2[] CELL_2D =
{
new Float2(-0.2700222198f, -0.9628540911f), new Float2(0.3863092627f, -0.9223693152f), new Float2(0.04444859006f, -0.999011673f), new Float2(-0.5992523158f, -0.8005602176f), new Float2(-0.7819280288f, 0.6233687174f), new Float2(0.9464672271f, 0.3227999196f), new Float2(-0.6514146797f, -0.7587218957f), new Float2(0.9378472289f, 0.347048376f),
new Float2(-0.8497875957f, -0.5271252623f), new Float2(-0.879042592f, 0.4767432447f), new Float2(-0.892300288f, -0.4514423508f), new Float2(-0.379844434f, -0.9250503802f), new Float2(-0.9951650832f, 0.0982163789f), new Float2(0.7724397808f, -0.6350880136f), new Float2(0.7573283322f, -0.6530343002f), new Float2(-0.9928004525f, -0.119780055f),
new Float2(-0.0532665713f, 0.9985803285f), new Float2(0.9754253726f, -0.2203300762f), new Float2(-0.7665018163f, 0.6422421394f), new Float2(0.991636706f, 0.1290606184f), new Float2(-0.994696838f, 0.1028503788f), new Float2(-0.5379205513f, -0.84299554f), new Float2(0.5022815471f, -0.8647041387f), new Float2(0.4559821461f, -0.8899889226f),
new Float2(-0.8659131224f, -0.5001944266f), new Float2(0.0879458407f, -0.9961252577f), new Float2(-0.5051684983f, 0.8630207346f), new Float2(0.7753185226f, -0.6315704146f), new Float2(-0.6921944612f, 0.7217110418f), new Float2(-0.5191659449f, -0.8546734591f), new Float2(0.8978622882f, -0.4402764035f), new Float2(-0.1706774107f, 0.9853269617f),
new Float2(-0.9353430106f, -0.3537420705f), new Float2(-0.9992404798f, 0.03896746794f), new Float2(-0.2882064021f, -0.9575683108f), new Float2(-0.9663811329f, 0.2571137995f), new Float2(-0.8759714238f, -0.4823630009f), new Float2(-0.8303123018f, -0.5572983775f), new Float2(0.05110133755f, -0.9986934731f), new Float2(-0.8558373281f, -0.5172450752f),
new Float2(0.09887025282f, 0.9951003332f), new Float2(0.9189016087f, 0.3944867976f), new Float2(-0.2439375892f, -0.9697909324f), new Float2(-0.8121409387f, -0.5834613061f), new Float2(-0.9910431363f, 0.1335421355f), new Float2(0.8492423985f, -0.5280031709f), new Float2(-0.9717838994f, -0.2358729591f), new Float2(0.9949457207f, 0.1004142068f),
new Float2(0.6241065508f, -0.7813392434f), new Float2(0.662910307f, 0.7486988212f), new Float2(-0.7197418176f, 0.6942418282f), new Float2(-0.8143370775f, -0.5803922158f), new Float2(0.104521054f, -0.9945226741f), new Float2(-0.1065926113f, -0.9943027784f), new Float2(0.445799684f, -0.8951327509f), new Float2(0.105547406f, 0.9944142724f),
new Float2(-0.992790267f, 0.1198644477f), new Float2(-0.8334366408f, 0.552615025f), new Float2(0.9115561563f, -0.4111755999f), new Float2(0.8285544909f, -0.5599084351f), new Float2(0.7217097654f, -0.6921957921f), new Float2(0.4940492677f, -0.8694339084f), new Float2(-0.3652321272f, -0.9309164803f), new Float2(-0.9696606758f, 0.2444548501f),
new Float2(0.08925509731f, -0.996008799f), new Float2(0.5354071276f, -0.8445941083f), new Float2(-0.1053576186f, 0.9944343981f), new Float2(-0.9890284586f, 0.1477251101f), new Float2(0.004856104961f, 0.9999882091f), new Float2(0.9885598478f, 0.1508291331f), new Float2(0.9286129562f, -0.3710498316f), new Float2(-0.5832393863f, -0.8123003252f),
new Float2(0.3015207509f, 0.9534596146f), new Float2(-0.9575110528f, 0.2883965738f), new Float2(0.9715802154f, -0.2367105511f), new Float2(0.229981792f, 0.9731949318f), new Float2(0.955763816f, -0.2941352207f), new Float2(0.740956116f, 0.6715534485f), new Float2(-0.9971513787f, -0.07542630764f), new Float2(0.6905710663f, -0.7232645452f),
new Float2(-0.290713703f, -0.9568100872f), new Float2(0.5912777791f, -0.8064679708f), new Float2(-0.9454592212f, -0.325740481f), new Float2(0.6664455681f, 0.74555369f), new Float2(0.6236134912f, 0.7817328275f), new Float2(0.9126993851f, -0.4086316587f), new Float2(-0.8191762011f, 0.5735419353f), new Float2(-0.8812745759f, -0.4726046147f),
new Float2(0.9953313627f, 0.09651672651f), new Float2(0.9855650846f, -0.1692969699f), new Float2(-0.8495980887f, 0.5274306472f), new Float2(0.6174853946f, -0.7865823463f), new Float2(0.8508156371f, 0.52546432f), new Float2(0.9985032451f, -0.05469249926f), new Float2(0.1971371563f, -0.9803759185f), new Float2(0.6607855748f, -0.7505747292f),
new Float2(-0.03097494063f, 0.9995201614f), new Float2(-0.6731660801f, 0.739491331f), new Float2(-0.7195018362f, -0.6944905383f), new Float2(0.9727511689f, 0.2318515979f), new Float2(0.9997059088f, -0.0242506907f), new Float2(0.4421787429f, -0.8969269532f), new Float2(0.9981350961f, -0.061043673f), new Float2(-0.9173660799f, -0.3980445648f),
new Float2(-0.8150056635f, -0.5794529907f), new Float2(-0.8789331304f, 0.4769450202f), new Float2(0.0158605829f, 0.999874213f), new Float2(-0.8095464474f, 0.5870558317f), new Float2(-0.9165898907f, -0.3998286786f), new Float2(-0.8023542565f, 0.5968480938f), new Float2(-0.5176737917f, 0.8555780767f), new Float2(-0.8154407307f, -0.5788405779f),
new Float2(0.4022010347f, -0.9155513791f), new Float2(-0.9052556868f, -0.4248672045f), new Float2(0.7317445619f, 0.6815789728f), new Float2(-0.5647632201f, -0.8252529947f), new Float2(-0.8403276335f, -0.5420788397f), new Float2(-0.9314281527f, 0.363925262f), new Float2(0.5238198472f, 0.8518290719f), new Float2(0.7432803869f, -0.6689800195f),
new Float2(-0.985371561f, -0.1704197369f), new Float2(0.4601468731f, 0.88784281f), new Float2(0.825855404f, 0.5638819483f), new Float2(0.6182366099f, 0.7859920446f), new Float2(0.8331502863f, -0.553046653f), new Float2(0.1500307506f, 0.9886813308f), new Float2(-0.662330369f, -0.7492119075f), new Float2(-0.668598664f, 0.743623444f),
new Float2(0.7025606278f, 0.7116238924f), new Float2(-0.5419389763f, -0.8404178401f), new Float2(-0.3388616456f, 0.9408362159f), new Float2(0.8331530315f, 0.5530425174f), new Float2(-0.2989720662f, -0.9542618632f), new Float2(0.2638522993f, 0.9645630949f), new Float2(0.124108739f, -0.9922686234f), new Float2(-0.7282649308f, -0.6852956957f),
new Float2(0.6962500149f, 0.7177993569f), new Float2(-0.9183535368f, 0.3957610156f), new Float2(-0.6326102274f, -0.7744703352f), new Float2(-0.9331891859f, -0.359385508f), new Float2(-0.1153779357f, -0.9933216659f), new Float2(0.9514974788f, -0.3076565421f), new Float2(-0.08987977445f, -0.9959526224f), new Float2(0.6678496916f, 0.7442961705f),
new Float2(0.7952400393f, -0.6062947138f), new Float2(-0.6462007402f, -0.7631674805f), new Float2(-0.2733598753f, 0.9619118351f), new Float2(0.9669590226f, -0.254931851f), new Float2(-0.9792894595f, 0.2024651934f), new Float2(-0.5369502995f, -0.8436138784f), new Float2(-0.270036471f, -0.9628500944f), new Float2(-0.6400277131f, 0.7683518247f),
new Float2(-0.7854537493f, -0.6189203566f), new Float2(0.06005905383f, -0.9981948257f), new Float2(-0.02455770378f, 0.9996984141f), new Float2(-0.65983623f, 0.751409442f), new Float2(-0.6253894466f, -0.7803127835f), new Float2(-0.6210408851f, -0.7837781695f), new Float2(0.8348888491f, 0.5504185768f), new Float2(-0.1592275245f, 0.9872419133f),
new Float2(0.8367622488f, 0.5475663786f), new Float2(-0.8675753916f, -0.4973056806f), new Float2(-0.2022662628f, -0.9793305667f), new Float2(0.9399189937f, 0.3413975472f), new Float2(0.9877404807f, -0.1561049093f), new Float2(-0.9034455656f, 0.4287028224f), new Float2(0.1269804218f, -0.9919052235f), new Float2(-0.3819600854f, 0.924178821f),
new Float2(0.9754625894f, 0.2201652486f), new Float2(-0.3204015856f, -0.9472818081f), new Float2(-0.9874760884f, 0.1577687387f), new Float2(0.02535348474f, -0.9996785487f), new Float2(0.4835130794f, -0.8753371362f), new Float2(-0.2850799925f, -0.9585037287f), new Float2(-0.06805516006f, -0.99768156f), new Float2(-0.7885244045f, -0.6150034663f),
new Float2(0.3185392127f, -0.9479096845f), new Float2(0.8880043089f, 0.4598351306f), new Float2(0.6476921488f, -0.7619021462f), new Float2(0.9820241299f, 0.1887554194f), new Float2(0.9357275128f, -0.3527237187f), new Float2(-0.8894895414f, 0.4569555293f), new Float2(0.7922791302f, 0.6101588153f), new Float2(0.7483818261f, 0.6632681526f),
new Float2(-0.7288929755f, -0.6846276581f), new Float2(0.8729032783f, -0.4878932944f), new Float2(0.8288345784f, 0.5594937369f), new Float2(0.08074567077f, 0.9967347374f), new Float2(0.9799148216f, -0.1994165048f), new Float2(-0.580730673f, -0.8140957471f), new Float2(-0.4700049791f, -0.8826637636f), new Float2(0.2409492979f, 0.9705377045f),
new Float2(0.9437816757f, -0.3305694308f), new Float2(-0.8927998638f, -0.4504535528f), new Float2(-0.8069622304f, 0.5906030467f), new Float2(0.06258973166f, 0.9980393407f), new Float2(-0.9312597469f, 0.3643559849f), new Float2(0.5777449785f, 0.8162173362f), new Float2(-0.3360095855f, -0.941858566f), new Float2(0.697932075f, -0.7161639607f),
new Float2(-0.002008157227f, -0.9999979837f), new Float2(-0.1827294312f, -0.9831632392f), new Float2(-0.6523911722f, 0.7578824173f), new Float2(-0.4302626911f, -0.9027037258f), new Float2(-0.9985126289f, -0.05452091251f), new Float2(-0.01028102172f, -0.9999471489f), new Float2(-0.4946071129f, 0.8691166802f), new Float2(-0.2999350194f, 0.9539596344f),
new Float2(0.8165471961f, 0.5772786819f), new Float2(0.2697460475f, 0.962931498f), new Float2(-0.7306287391f, -0.6827749597f), new Float2(-0.7590952064f, -0.6509796216f), new Float2(-0.907053853f, 0.4210146171f), new Float2(-0.5104861064f, -0.8598860013f), new Float2(0.8613350597f, 0.5080373165f), new Float2(0.5007881595f, -0.8655698812f),
new Float2(-0.654158152f, 0.7563577938f), new Float2(-0.8382755311f, -0.545246856f), new Float2(0.6940070834f, 0.7199681717f), new Float2(0.06950936031f, 0.9975812994f), new Float2(0.1702942185f, -0.9853932612f), new Float2(0.2695973274f, 0.9629731466f), new Float2(0.5519612192f, -0.8338697815f), new Float2(0.225657487f, -0.9742067022f),
new Float2(0.4215262855f, -0.9068161835f), new Float2(0.4881873305f, -0.8727388672f), new Float2(-0.3683854996f, -0.9296731273f), new Float2(-0.9825390578f, 0.1860564427f), new Float2(0.81256471f, 0.5828709909f), new Float2(0.3196460933f, -0.9475370046f), new Float2(0.9570913859f, 0.2897862643f), new Float2(-0.6876655497f, -0.7260276109f),
new Float2(-0.9988770922f, -0.047376731f), new Float2(-0.1250179027f, 0.992154486f), new Float2(-0.8280133617f, 0.560708367f), new Float2(0.9324863769f, -0.3612051451f), new Float2(0.6394653183f, 0.7688199442f), new Float2(-0.01623847064f, -0.9998681473f), new Float2(-0.9955014666f, -0.09474613458f), new Float2(-0.81453315f, 0.580117012f),
new Float2(0.4037327978f, -0.9148769469f), new Float2(0.9944263371f, 0.1054336766f), new Float2(-0.1624711654f, 0.9867132919f), new Float2(-0.9949487814f, -0.100383875f), new Float2(-0.6995302564f, 0.7146029809f), new Float2(0.5263414922f, -0.85027327f), new Float2(-0.5395221479f, 0.841971408f), new Float2(0.6579370318f, 0.7530729462f),
new Float2(0.01426758847f, -0.9998982128f), new Float2(-0.6734383991f, 0.7392433447f), new Float2(0.639412098f, -0.7688642071f), new Float2(0.9211571421f, 0.3891908523f), new Float2(-0.146637214f, -0.9891903394f), new Float2(-0.782318098f, 0.6228791163f), new Float2(-0.5039610839f, -0.8637263605f), new Float2(-0.7743120191f, -0.6328039957f),
};
private static readonly Float3[] CELL_3D =
{
new Float3(-0.7292736885f, -0.6618439697f, 0.1735581948f), new Float3(0.790292081f, -0.5480887466f, -0.2739291014f), new Float3(0.7217578935f, 0.6226212466f, -0.3023380997f), new Float3(0.565683137f, -0.8208298145f, -0.0790000257f), new Float3(0.760049034f, -0.5555979497f, -0.3370999617f), new Float3(0.3713945616f, 0.5011264475f, 0.7816254623f), new Float3(-0.1277062463f, -0.4254438999f, -0.8959289049f), new Float3(-0.2881560924f, -0.5815838982f, 0.7607405838f),
new Float3(0.5849561111f, -0.662820239f, -0.4674352136f), new Float3(0.3307171178f, 0.0391653737f, 0.94291689f), new Float3(0.8712121778f, -0.4113374369f, -0.2679381538f), new Float3(0.580981015f, 0.7021915846f, 0.4115677815f), new Float3(0.503756873f, 0.6330056931f, -0.5878203852f), new Float3(0.4493712205f, 0.601390195f, 0.6606022552f), new Float3(-0.6878403724f, 0.09018890807f, -0.7202371714f), new Float3(-0.5958956522f, -0.6469350577f, 0.475797649f),
new Float3(-0.5127052122f, 0.1946921978f, -0.8361987284f), new Float3(-0.9911507142f, -0.05410276466f, -0.1212153153f), new Float3(-0.2149721042f, 0.9720882117f, -0.09397607749f), new Float3(-0.7518650936f, -0.5428057603f, 0.3742469607f), new Float3(0.5237068895f, 0.8516377189f, -0.02107817834f), new Float3(0.6333504779f, 0.1926167129f, -0.7495104896f), new Float3(-0.06788241606f, 0.3998305789f, 0.9140719259f), new Float3(-0.5538628599f, -0.4729896695f, -0.6852128902f),
new Float3(-0.7261455366f, -0.5911990757f, 0.3509933228f), new Float3(-0.9229274737f, -0.1782808786f, 0.3412049336f), new Float3(-0.6968815002f, 0.6511274338f, 0.3006480328f), new Float3(0.9608044783f, -0.2098363234f, -0.1811724921f), new Float3(0.06817146062f, -0.9743405129f, 0.2145069156f), new Float3(-0.3577285196f, -0.6697087264f, -0.6507845481f), new Float3(-0.1868621131f, 0.7648617052f, -0.6164974636f), new Float3(-0.6541697588f, 0.3967914832f, 0.6439087246f),
new Float3(0.6993340405f, -0.6164538506f, 0.3618239211f), new Float3(-0.1546665739f, 0.6291283928f, 0.7617583057f), new Float3(-0.6841612949f, -0.2580482182f, -0.6821542638f), new Float3(0.5383980957f, 0.4258654885f, 0.7271630328f), new Float3(-0.5026987823f, -0.7939832935f, -0.3418836993f), new Float3(0.3202971715f, 0.2834415347f, 0.9039195862f), new Float3(0.8683227101f, -0.0003762656404f, -0.4959995258f), new Float3(0.791120031f, -0.08511045745f, 0.6057105799f),
new Float3(-0.04011016052f, -0.4397248749f, 0.8972364289f), new Float3(0.9145119872f, 0.3579346169f, -0.1885487608f), new Float3(-0.9612039066f, -0.2756484276f, 0.01024666929f), new Float3(0.6510361721f, -0.2877799159f, -0.7023778346f), new Float3(-0.2041786351f, 0.7365237271f, 0.644859585f), new Float3(-0.7718263711f, 0.3790626912f, 0.5104855816f), new Float3(-0.3060082741f, -0.7692987727f, 0.5608371729f), new Float3(0.454007341f, -0.5024843065f, 0.7357899537f),
new Float3(0.4816795475f, 0.6021208291f, -0.6367380315f), new Float3(0.6961980369f, -0.3222197429f, 0.641469197f), new Float3(-0.6532160499f, -0.6781148932f, 0.3368515753f), new Float3(0.5089301236f, -0.6154662304f, -0.6018234363f), new Float3(-0.1635919754f, -0.9133604627f, -0.372840892f), new Float3(0.52408019f, -0.8437664109f, 0.1157505864f), new Float3(0.5902587356f, 0.4983817807f, -0.6349883666f), new Float3(0.5863227872f, 0.494764745f, 0.6414307729f),
new Float3(0.6779335087f, 0.2341345225f, 0.6968408593f), new Float3(0.7177054546f, -0.6858979348f, 0.120178631f), new Float3(-0.5328819713f, -0.5205125012f, 0.6671608058f), new Float3(-0.8654874251f, -0.0700727088f, -0.4960053754f), new Float3(-0.2861810166f, 0.7952089234f, 0.5345495242f), new Float3(-0.04849529634f, 0.9810836427f, -0.1874115585f), new Float3(-0.6358521667f, 0.6058348682f, 0.4781800233f), new Float3(0.6254794696f, -0.2861619734f, 0.7258696564f),
new Float3(-0.2585259868f, 0.5061949264f, -0.8227581726f), new Float3(0.02136306781f, 0.5064016808f, -0.8620330371f), new Float3(0.200111773f, 0.8599263484f, 0.4695550591f), new Float3(0.4743561372f, 0.6014985084f, -0.6427953014f), new Float3(0.6622993731f, -0.5202474575f, -0.5391679918f), new Float3(0.08084972818f, -0.6532720452f, 0.7527940996f), new Float3(-0.6893687501f, 0.0592860349f, 0.7219805347f), new Float3(-0.1121887082f, -0.9673185067f, 0.2273952515f),
new Float3(0.7344116094f, 0.5979668656f, -0.3210532909f), new Float3(0.5789393465f, -0.2488849713f, 0.7764570201f), new Float3(0.6988182827f, 0.3557169806f, -0.6205791146f), new Float3(-0.8636845529f, -0.2748771249f, -0.4224826141f), new Float3(-0.4247027957f, -0.4640880967f, 0.777335046f), new Float3(0.5257722489f, -0.8427017621f, 0.1158329937f), new Float3(0.9343830603f, 0.316302472f, -0.1639543925f), new Float3(-0.1016836419f, -0.8057303073f, -0.5834887393f),
new Float3(-0.6529238969f, 0.50602126f, -0.5635892736f), new Float3(-0.2465286165f, -0.9668205684f, -0.06694497494f), new Float3(-0.9776897119f, -0.2099250524f, -0.007368825344f), new Float3(0.7736893337f, 0.5734244712f, 0.2694238123f), new Float3(-0.6095087895f, 0.4995678998f, 0.6155736747f), new Float3(0.5794535482f, 0.7434546771f, 0.3339292269f), new Float3(-0.8226211154f, 0.08142581855f, 0.5627293636f), new Float3(-0.510385483f, 0.4703667658f, 0.7199039967f),
new Float3(-0.5764971849f, -0.07231656274f, -0.8138926898f), new Float3(0.7250628871f, 0.3949971505f, -0.5641463116f), new Float3(-0.1525424005f, 0.4860840828f, -0.8604958341f), new Float3(-0.5550976208f, -0.4957820792f, 0.667882296f), new Float3(-0.1883614327f, 0.9145869398f, 0.357841725f), new Float3(0.7625556724f, -0.5414408243f, -0.3540489801f), new Float3(-0.5870231946f, -0.3226498013f, -0.7424963803f), new Float3(0.3051124198f, 0.2262544068f, -0.9250488391f),
new Float3(0.6379576059f, 0.577242424f, -0.5097070502f), new Float3(-0.5966775796f, 0.1454852398f, -0.7891830656f), new Float3(-0.658330573f, 0.6555487542f, -0.3699414651f), new Float3(0.7434892426f, 0.2351084581f, 0.6260573129f), new Float3(0.5562114096f, 0.8264360377f, -0.0873632843f), new Float3(-0.3028940016f, -0.8251527185f, 0.4768419182f), new Float3(0.1129343818f, -0.985888439f, -0.1235710781f), new Float3(0.5937652891f, -0.5896813806f, 0.5474656618f),
new Float3(0.6757964092f, -0.5835758614f, -0.4502648413f), new Float3(0.7242302609f, -0.1152719764f, 0.6798550586f), new Float3(-0.9511914166f, 0.0753623979f, -0.2992580792f), new Float3(0.2539470961f, -0.1886339355f, 0.9486454084f), new Float3(0.571433621f, -0.1679450851f, -0.8032795685f), new Float3(-0.06778234979f, 0.3978269256f, 0.9149531629f), new Float3(0.6074972649f, 0.733060024f, -0.3058922593f), new Float3(-0.5435478392f, 0.1675822484f, 0.8224791405f),
new Float3(-0.5876678086f, -0.3380045064f, -0.7351186982f), new Float3(-0.7967562402f, 0.04097822706f, -0.6029098428f), new Float3(-0.1996350917f, 0.8706294745f, 0.4496111079f), new Float3(-0.02787660336f, -0.9106232682f, -0.4122962022f), new Float3(-0.7797625996f, -0.6257634692f, 0.01975775581f), new Float3(-0.5211232846f, 0.7401644346f, -0.4249554471f), new Float3(0.8575424857f, 0.4053272873f, -0.3167501783f), new Float3(0.1045223322f, 0.8390195772f, -0.5339674439f),
new Float3(0.3501822831f, 0.9242524096f, -0.1520850155f), new Float3(0.1987849858f, 0.07647613266f, 0.9770547224f), new Float3(0.7845996363f, 0.6066256811f, -0.1280964233f), new Float3(0.09006737436f, -0.9750989929f, -0.2026569073f), new Float3(-0.8274343547f, -0.542299559f, 0.1458203587f), new Float3(-0.3485797732f, -0.415802277f, 0.840000362f), new Float3(-0.2471778936f, -0.7304819962f, -0.6366310879f), new Float3(-0.3700154943f, 0.8577948156f, 0.3567584454f),
new Float3(0.5913394901f, -0.548311967f, -0.5913303597f), new Float3(0.1204873514f, -0.7626472379f, -0.6354935001f), new Float3(0.616959265f, 0.03079647928f, 0.7863922953f), new Float3(0.1258156836f, -0.6640829889f, -0.7369967419f), new Float3(-0.6477565124f, -0.1740147258f, -0.7417077429f), new Float3(0.6217889313f, -0.7804430448f, -0.06547655076f), new Float3(0.6589943422f, -0.6096987708f, 0.4404473475f), new Float3(-0.2689837504f, -0.6732403169f, -0.6887635427f),
new Float3(-0.3849775103f, 0.5676542638f, 0.7277093879f), new Float3(0.5754444408f, 0.8110471154f, -0.1051963504f), new Float3(0.9141593684f, 0.3832947817f, 0.131900567f), new Float3(-0.107925319f, 0.9245493968f, 0.3654593525f), new Float3(0.377977089f, 0.3043148782f, 0.8743716458f), new Float3(-0.2142885215f, -0.8259286236f, 0.5214617324f), new Float3(0.5802544474f, 0.4148098596f, -0.7008834116f), new Float3(-0.1982660881f, 0.8567161266f, -0.4761596756f),
new Float3(-0.03381553704f, 0.3773180787f, -0.9254661404f), new Float3(-0.6867922841f, -0.6656597827f, 0.2919133642f), new Float3(0.7731742607f, -0.2875793547f, -0.5652430251f), new Float3(-0.09655941928f, 0.9193708367f, -0.3813575004f), new Float3(0.2715702457f, -0.9577909544f, -0.09426605581f), new Float3(0.2451015704f, -0.6917998565f, -0.6792188003f), new Float3(0.977700782f, -0.1753855374f, 0.1155036542f), new Float3(-0.5224739938f, 0.8521606816f, 0.02903615945f),
new Float3(-0.7734880599f, -0.5261292347f, 0.3534179531f), new Float3(-0.7134492443f, -0.269547243f, 0.6467878011f), new Float3(0.1644037271f, 0.5105846203f, -0.8439637196f), new Float3(0.6494635788f, 0.05585611296f, 0.7583384168f), new Float3(-0.4711970882f, 0.5017280509f, -0.7254255765f), new Float3(-0.6335764307f, -0.2381686273f, -0.7361091029f), new Float3(-0.9021533097f, -0.270947803f, -0.3357181763f), new Float3(-0.3793711033f, 0.872258117f, 0.3086152025f),
new Float3(-0.6855598966f, -0.3250143309f, 0.6514394162f), new Float3(0.2900942212f, -0.7799057743f, -0.5546100667f), new Float3(-0.2098319339f, 0.85037073f, 0.4825351604f), new Float3(-0.4592603758f, 0.6598504336f, -0.5947077538f), new Float3(0.8715945488f, 0.09616365406f, -0.4807031248f), new Float3(-0.6776666319f, 0.7118504878f, -0.1844907016f), new Float3(0.7044377633f, 0.312427597f, 0.637304036f), new Float3(-0.7052318886f, -0.2401093292f, -0.6670798253f),
new Float3(0.081921007f, -0.7207336136f, -0.6883545647f), new Float3(-0.6993680906f, -0.5875763221f, -0.4069869034f), new Float3(-0.1281454481f, 0.6419895885f, 0.7559286424f), new Float3(-0.6337388239f, -0.6785471501f, -0.3714146849f), new Float3(0.5565051903f, -0.2168887573f, -0.8020356851f), new Float3(-0.5791554484f, 0.7244372011f, -0.3738578718f), new Float3(0.1175779076f, -0.7096451073f, 0.6946792478f), new Float3(-0.6134619607f, 0.1323631078f, 0.7785527795f),
new Float3(0.6984635305f, -0.02980516237f, -0.715024719f), new Float3(0.8318082963f, -0.3930171956f, 0.3919597455f), new Float3(0.1469576422f, 0.05541651717f, -0.9875892167f), new Float3(0.708868575f, -0.2690503865f, 0.6520101478f), new Float3(0.2726053183f, 0.67369766f, -0.68688995f), new Float3(-0.6591295371f, 0.3035458599f, -0.6880466294f), new Float3(0.4815131379f, -0.7528270071f, 0.4487723203f), new Float3(0.9430009463f, 0.1675647412f, -0.2875261255f),
new Float3(0.434802957f, 0.7695304522f, -0.4677277752f), new Float3(0.3931996188f, 0.594473625f, 0.7014236729f), new Float3(0.7254336655f, -0.603925654f, 0.3301814672f), new Float3(0.7590235227f, -0.6506083235f, 0.02433313207f), new Float3(-0.8552768592f, -0.3430042733f, 0.3883935666f), new Float3(-0.6139746835f, 0.6981725247f, 0.3682257648f), new Float3(-0.7465905486f, -0.5752009504f, 0.3342849376f), new Float3(0.5730065677f, 0.810555537f, -0.1210916791f),
new Float3(-0.9225877367f, -0.3475211012f, -0.167514036f), new Float3(-0.7105816789f, -0.4719692027f, -0.5218416899f), new Float3(-0.08564609717f, 0.3583001386f, 0.929669703f), new Float3(-0.8279697606f, -0.2043157126f, 0.5222271202f), new Float3(0.427944023f, 0.278165994f, 0.8599346446f), new Float3(0.5399079671f, -0.7857120652f, -0.3019204161f), new Float3(0.5678404253f, -0.5495413974f, -0.6128307303f), new Float3(-0.9896071041f, 0.1365639107f, -0.04503418428f),
new Float3(-0.6154342638f, -0.6440875597f, 0.4543037336f), new Float3(0.1074204368f, -0.7946340692f, 0.5975094525f), new Float3(-0.3595449969f, -0.8885529948f, 0.28495784f), new Float3(-0.2180405296f, 0.1529888965f, 0.9638738118f), new Float3(-0.7277432317f, -0.6164050508f, -0.3007234646f), new Float3(0.7249729114f, -0.00669719484f, 0.6887448187f), new Float3(-0.5553659455f, -0.5336586252f, 0.6377908264f), new Float3(0.5137558015f, 0.7976208196f, -0.3160000073f),
new Float3(-0.3794024848f, 0.9245608561f, -0.03522751494f), new Float3(0.8229248658f, 0.2745365933f, -0.4974176556f), new Float3(-0.5404114394f, 0.6091141441f, 0.5804613989f), new Float3(0.8036581901f, -0.2703029469f, 0.5301601931f), new Float3(0.6044318879f, 0.6832968393f, 0.4095943388f), new Float3(0.06389988817f, 0.9658208605f, -0.2512108074f), new Float3(0.1087113286f, 0.7402471173f, -0.6634877936f), new Float3(-0.713427712f, -0.6926784018f, 0.1059128479f),
new Float3(0.6458897819f, -0.5724548511f, -0.5050958653f), new Float3(-0.6553931414f, 0.7381471625f, 0.159995615f), new Float3(0.3910961323f, 0.9188871375f, -0.05186755998f), new Float3(-0.4879022471f, -0.5904376907f, 0.6429111375f), new Float3(0.6014790094f, 0.7707441366f, -0.2101820095f), new Float3(-0.5677173047f, 0.7511360995f, 0.3368851762f), new Float3(0.7858573506f, 0.226674665f, 0.5753666838f), new Float3(-0.4520345543f, -0.604222686f, -0.6561857263f),
new Float3(0.002272116345f, 0.4132844051f, -0.9105991643f), new Float3(-0.5815751419f, -0.5162925989f, 0.6286591339f), new Float3(-0.03703704785f, 0.8273785755f, 0.5604221175f), new Float3(-0.5119692504f, 0.7953543429f, -0.3244980058f), new Float3(-0.2682417366f, -0.9572290247f, -0.1084387619f), new Float3(-0.2322482736f, -0.9679131102f, -0.09594243324f), new Float3(0.3554328906f, -0.8881505545f, 0.2913006227f), new Float3(0.7346520519f, -0.4371373164f, 0.5188422971f),
new Float3(0.9985120116f, 0.04659011161f, -0.02833944577f), new Float3(-0.3727687496f, -0.9082481361f, 0.1900757285f), new Float3(0.91737377f, -0.3483642108f, 0.1925298489f), new Float3(0.2714911074f, 0.4147529736f, -0.8684886582f), new Float3(0.5131763485f, -0.7116334161f, 0.4798207128f), new Float3(-0.8737353606f, 0.18886992f, -0.4482350644f), new Float3(0.8460043821f, -0.3725217914f, 0.3814499973f), new Float3(0.8978727456f, -0.1780209141f, -0.4026575304f),
new Float3(0.2178065647f, -0.9698322841f, -0.1094789531f), new Float3(-0.1518031304f, -0.7788918132f, -0.6085091231f), new Float3(-0.2600384876f, -0.4755398075f, -0.8403819825f), new Float3(0.572313509f, -0.7474340931f, -0.3373418503f), new Float3(-0.7174141009f, 0.1699017182f, -0.6756111411f), new Float3(-0.684180784f, 0.02145707593f, -0.7289967412f), new Float3(-0.2007447902f, 0.06555605789f, -0.9774476623f), new Float3(-0.1148803697f, -0.8044887315f, 0.5827524187f),
new Float3(-0.7870349638f, 0.03447489231f, 0.6159443543f), new Float3(-0.2015596421f, 0.6859872284f, 0.6991389226f), new Float3(-0.08581082512f, -0.10920836f, -0.9903080513f), new Float3(0.5532693395f, 0.7325250401f, -0.396610771f), new Float3(-0.1842489331f, -0.9777375055f, -0.1004076743f), new Float3(0.0775473789f, -0.9111505856f, 0.4047110257f), new Float3(0.1399838409f, 0.7601631212f, -0.6344734459f), new Float3(0.4484419361f, -0.845289248f, 0.2904925424f),
};
[MethodImplAttribute(FN_INLINE)]
private static int FastFloor(FN_DECIMAL f) { return (f >= 0 ? (int)f : (int)f - 1); }
[MethodImplAttribute(FN_INLINE)]
private static int FastRound(FN_DECIMAL f) { return (f >= 0) ? (int)(f + (FN_DECIMAL)0.5) : (int)(f - (FN_DECIMAL)0.5); }
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL Lerp(FN_DECIMAL a, FN_DECIMAL b, FN_DECIMAL t) { return a + t * (b - a); }
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL InterpHermiteFunc(FN_DECIMAL t) { return t * t * (3 - 2 * t); }
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL InterpQuinticFunc(FN_DECIMAL t) { return t * t * t * (t * (t * 6 - 15) + 10); }
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL CubicLerp(FN_DECIMAL a, FN_DECIMAL b, FN_DECIMAL c, FN_DECIMAL d, FN_DECIMAL t)
{
FN_DECIMAL p = (d - c) - (a - b);
return t * t * t * p + t * t * ((a - b) - p) + t * (c - a) + b;
}
private void CalculateFractalBounding()
{
FN_DECIMAL amp = m_gain;
FN_DECIMAL ampFractal = 1;
for (int i = 1; i < m_octaves; i++)
{
ampFractal += amp;
amp *= m_gain;
}
m_fractalBounding = 1 / ampFractal;
}
// Hashing
private const int X_PRIME = 1619;
private const int Y_PRIME = 31337;
private const int Z_PRIME = 6971;
private const int W_PRIME = 1013;
[MethodImplAttribute(FN_INLINE)]
private static int Hash2D(int seed, int x, int y)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
return hash;
}
[MethodImplAttribute(FN_INLINE)]
private static int Hash3D(int seed, int x, int y, int z)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash ^= Z_PRIME * z;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
return hash;
}
[MethodImplAttribute(FN_INLINE)]
private static int Hash4D(int seed, int x, int y, int z, int w)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash ^= Z_PRIME * z;
hash ^= W_PRIME * w;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
return hash;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL ValCoord2D(int seed, int x, int y)
{
int n = seed;
n ^= X_PRIME * x;
n ^= Y_PRIME * y;
return (n * n * n * 60493) / (FN_DECIMAL)2147483648.0;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL ValCoord3D(int seed, int x, int y, int z)
{
int n = seed;
n ^= X_PRIME * x;
n ^= Y_PRIME * y;
n ^= Z_PRIME * z;
return (n * n * n * 60493) / (FN_DECIMAL)2147483648.0;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL ValCoord4D(int seed, int x, int y, int z, int w)
{
int n = seed;
n ^= X_PRIME * x;
n ^= Y_PRIME * y;
n ^= Z_PRIME * z;
n ^= W_PRIME * w;
return (n * n * n * 60493) / (FN_DECIMAL)2147483648.0;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL GradCoord2D(int seed, int x, int y, FN_DECIMAL xd, FN_DECIMAL yd)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
Float2 g = GRAD_2D[hash & 7];
return xd * g.x + yd * g.y;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL GradCoord3D(int seed, int x, int y, int z, FN_DECIMAL xd, FN_DECIMAL yd, FN_DECIMAL zd)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash ^= Z_PRIME * z;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
Float3 g = GRAD_3D[hash & 15];
return xd * g.x + yd * g.y + zd * g.z;
}
[MethodImplAttribute(FN_INLINE)]
private static FN_DECIMAL GradCoord4D(int seed, int x, int y, int z, int w, FN_DECIMAL xd, FN_DECIMAL yd, FN_DECIMAL zd, FN_DECIMAL wd)
{
int hash = seed;
hash ^= X_PRIME * x;
hash ^= Y_PRIME * y;
hash ^= Z_PRIME * z;
hash ^= W_PRIME * w;
hash = hash * hash * hash * 60493;
hash = (hash >> 13) ^ hash;
hash &= 31;
FN_DECIMAL a = yd, b = zd, c = wd; // X,Y,Z
switch (hash >> 3)
{ // OR, DEPENDING ON HIGH ORDER 2 BITS:
case 1: a = wd; b = xd; c = yd; break; // W,X,Y
case 2: a = zd; b = wd; c = xd; break; // Z,W,X
case 3: a = yd; b = zd; c = wd; break; // Y,Z,W
}
return ((hash & 4) == 0 ? -a : a) + ((hash & 2) == 0 ? -b : b) + ((hash & 1) == 0 ? -c : c);
}
public FN_DECIMAL GetNoise(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
x *= m_frequency;
y *= m_frequency;
z *= m_frequency;
switch (m_noiseType)
{
case NoiseType.Value:
return SingleValue(m_seed, x, y, z);
case NoiseType.ValueFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleValueFractalFBM(x, y, z);
case FractalType.Billow:
return SingleValueFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SingleValueFractalRigidMulti(x, y, z);
default:
return 0;
}
case NoiseType.Perlin:
return SinglePerlin(m_seed, x, y, z);
case NoiseType.PerlinFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SinglePerlinFractalFBM(x, y, z);
case FractalType.Billow:
return SinglePerlinFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SinglePerlinFractalRigidMulti(x, y, z);
default:
return 0;
}
case NoiseType.Simplex:
return SingleSimplex(m_seed, x, y, z);
case NoiseType.SimplexFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleSimplexFractalFBM(x, y, z);
case FractalType.Billow:
return SingleSimplexFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SingleSimplexFractalRigidMulti(x, y, z);
default:
return 0;
}
case NoiseType.Cellular:
switch (m_cellularReturnType)
{
case CellularReturnType.CellValue:
case CellularReturnType.NoiseLookup:
case CellularReturnType.Distance:
return SingleCellular(x, y, z);
default:
return SingleCellular2Edge(x, y, z);
}
case NoiseType.WhiteNoise:
return GetWhiteNoise(x, y, z);
case NoiseType.Cubic:
return SingleCubic(m_seed, x, y, z);
case NoiseType.CubicFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleCubicFractalFBM(x, y, z);
case FractalType.Billow:
return SingleCubicFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SingleCubicFractalRigidMulti(x, y, z);
default:
return 0;
}
default:
return 0;
}
}
public FN_DECIMAL GetNoise(FN_DECIMAL x, FN_DECIMAL y)
{
x *= m_frequency;
y *= m_frequency;
switch (m_noiseType)
{
case NoiseType.Value:
return SingleValue(m_seed, x, y);
case NoiseType.ValueFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleValueFractalFBM(x, y);
case FractalType.Billow:
return SingleValueFractalBillow(x, y);
case FractalType.RigidMulti:
return SingleValueFractalRigidMulti(x, y);
default:
return 0;
}
case NoiseType.Perlin:
return SinglePerlin(m_seed, x, y);
case NoiseType.PerlinFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SinglePerlinFractalFBM(x, y);
case FractalType.Billow:
return SinglePerlinFractalBillow(x, y);
case FractalType.RigidMulti:
return SinglePerlinFractalRigidMulti(x, y);
default:
return 0;
}
case NoiseType.Simplex:
return SingleSimplex(m_seed, x, y);
case NoiseType.SimplexFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleSimplexFractalFBM(x, y);
case FractalType.Billow:
return SingleSimplexFractalBillow(x, y);
case FractalType.RigidMulti:
return SingleSimplexFractalRigidMulti(x, y);
default:
return 0;
}
case NoiseType.Cellular:
switch (m_cellularReturnType)
{
case CellularReturnType.CellValue:
case CellularReturnType.NoiseLookup:
case CellularReturnType.Distance:
return SingleCellular(x, y);
default:
return SingleCellular2Edge(x, y);
}
case NoiseType.WhiteNoise:
return GetWhiteNoise(x, y);
case NoiseType.Cubic:
return SingleCubic(m_seed, x, y);
case NoiseType.CubicFractal:
switch (m_fractalType)
{
case FractalType.FBM:
return SingleCubicFractalFBM(x, y);
case FractalType.Billow:
return SingleCubicFractalBillow(x, y);
case FractalType.RigidMulti:
return SingleCubicFractalRigidMulti(x, y);
default:
return 0;
}
default:
return 0;
}
}
// White Noise
[MethodImplAttribute(FN_INLINE)]
private int FloatCast2Int(FN_DECIMAL f)
{
var i = BitConverter.DoubleToInt64Bits(f);
return (int)(i ^ (i >> 32));
}
public FN_DECIMAL GetWhiteNoise(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z, FN_DECIMAL w)
{
int xi = FloatCast2Int(x);
int yi = FloatCast2Int(y);
int zi = FloatCast2Int(z);
int wi = FloatCast2Int(w);
return ValCoord4D(m_seed, xi, yi, zi, wi);
}
public FN_DECIMAL GetWhiteNoise(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int xi = FloatCast2Int(x);
int yi = FloatCast2Int(y);
int zi = FloatCast2Int(z);
return ValCoord3D(m_seed, xi, yi, zi);
}
public FN_DECIMAL GetWhiteNoise(FN_DECIMAL x, FN_DECIMAL y)
{
int xi = FloatCast2Int(x);
int yi = FloatCast2Int(y);
return ValCoord2D(m_seed, xi, yi);
}
public FN_DECIMAL GetWhiteNoiseInt(int x, int y, int z, int w)
{
return ValCoord4D(m_seed, x, y, z, w);
}
public FN_DECIMAL GetWhiteNoiseInt(int x, int y, int z)
{
return ValCoord3D(m_seed, x, y, z);
}
public FN_DECIMAL GetWhiteNoiseInt(int x, int y)
{
return ValCoord2D(m_seed, x, y);
}
// Value Noise
public FN_DECIMAL GetValueFractal(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
x *= m_frequency;
y *= m_frequency;
z *= m_frequency;
switch (m_fractalType)
{
case FractalType.FBM:
return SingleValueFractalFBM(x, y, z);
case FractalType.Billow:
return SingleValueFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SingleValueFractalRigidMulti(x, y, z);
default:
return 0;
}
}
private FN_DECIMAL SingleValueFractalFBM(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = SingleValue(seed, x, y, z);
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum += SingleValue(++seed, x, y, z) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SingleValueFractalBillow(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = Math.Abs(SingleValue(seed, x, y, z)) * 2 - 1;
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum += (Math.Abs(SingleValue(++seed, x, y, z)) * 2 - 1) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SingleValueFractalRigidMulti(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = 1 - Math.Abs(SingleValue(seed, x, y, z));
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum -= (1 - Math.Abs(SingleValue(++seed, x, y, z))) * amp;
}
return sum;
}
public FN_DECIMAL GetValue(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
return SingleValue(m_seed, x * m_frequency, y * m_frequency, z * m_frequency);
}
private FN_DECIMAL SingleValue(int seed, FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int x0 = FastFloor(x);
int y0 = FastFloor(y);
int z0 = FastFloor(z);
int x1 = x0 + 1;
int y1 = y0 + 1;
int z1 = z0 + 1;
FN_DECIMAL xs, ys, zs;
switch (m_interp)
{
default:
case Interp.Linear:
xs = x - x0;
ys = y - y0;
zs = z - z0;
break;
case Interp.Hermite:
xs = InterpHermiteFunc(x - x0);
ys = InterpHermiteFunc(y - y0);
zs = InterpHermiteFunc(z - z0);
break;
case Interp.Quintic:
xs = InterpQuinticFunc(x - x0);
ys = InterpQuinticFunc(y - y0);
zs = InterpQuinticFunc(z - z0);
break;
}
FN_DECIMAL xf00 = Lerp(ValCoord3D(seed, x0, y0, z0), ValCoord3D(seed, x1, y0, z0), xs);
FN_DECIMAL xf10 = Lerp(ValCoord3D(seed, x0, y1, z0), ValCoord3D(seed, x1, y1, z0), xs);
FN_DECIMAL xf01 = Lerp(ValCoord3D(seed, x0, y0, z1), ValCoord3D(seed, x1, y0, z1), xs);
FN_DECIMAL xf11 = Lerp(ValCoord3D(seed, x0, y1, z1), ValCoord3D(seed, x1, y1, z1), xs);
FN_DECIMAL yf0 = Lerp(xf00, xf10, ys);
FN_DECIMAL yf1 = Lerp(xf01, xf11, ys);
return Lerp(yf0, yf1, zs);
}
public FN_DECIMAL GetValueFractal(FN_DECIMAL x, FN_DECIMAL y)
{
x *= m_frequency;
y *= m_frequency;
switch (m_fractalType)
{
case FractalType.FBM:
return SingleValueFractalFBM(x, y);
case FractalType.Billow:
return SingleValueFractalBillow(x, y);
case FractalType.RigidMulti:
return SingleValueFractalRigidMulti(x, y);
default:
return 0;
}
}
private FN_DECIMAL SingleValueFractalFBM(FN_DECIMAL x, FN_DECIMAL y)
{
int seed = m_seed;
FN_DECIMAL sum = SingleValue(seed, x, y);
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
amp *= m_gain;
sum += SingleValue(++seed, x, y) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SingleValueFractalBillow(FN_DECIMAL x, FN_DECIMAL y)
{
int seed = m_seed;
FN_DECIMAL sum = Math.Abs(SingleValue(seed, x, y)) * 2 - 1;
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
amp *= m_gain;
sum += (Math.Abs(SingleValue(++seed, x, y)) * 2 - 1) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SingleValueFractalRigidMulti(FN_DECIMAL x, FN_DECIMAL y)
{
int seed = m_seed;
FN_DECIMAL sum = 1 - Math.Abs(SingleValue(seed, x, y));
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
amp *= m_gain;
sum -= (1 - Math.Abs(SingleValue(++seed, x, y))) * amp;
}
return sum;
}
public FN_DECIMAL GetValue(FN_DECIMAL x, FN_DECIMAL y)
{
return SingleValue(m_seed, x * m_frequency, y * m_frequency);
}
private FN_DECIMAL SingleValue(int seed, FN_DECIMAL x, FN_DECIMAL y)
{
int x0 = FastFloor(x);
int y0 = FastFloor(y);
int x1 = x0 + 1;
int y1 = y0 + 1;
FN_DECIMAL xs, ys;
switch (m_interp)
{
default:
case Interp.Linear:
xs = x - x0;
ys = y - y0;
break;
case Interp.Hermite:
xs = InterpHermiteFunc(x - x0);
ys = InterpHermiteFunc(y - y0);
break;
case Interp.Quintic:
xs = InterpQuinticFunc(x - x0);
ys = InterpQuinticFunc(y - y0);
break;
}
FN_DECIMAL xf0 = Lerp(ValCoord2D(seed, x0, y0), ValCoord2D(seed, x1, y0), xs);
FN_DECIMAL xf1 = Lerp(ValCoord2D(seed, x0, y1), ValCoord2D(seed, x1, y1), xs);
return Lerp(xf0, xf1, ys);
}
// Gradient Noise
public FN_DECIMAL GetPerlinFractal(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
x *= m_frequency;
y *= m_frequency;
z *= m_frequency;
switch (m_fractalType)
{
case FractalType.FBM:
return SinglePerlinFractalFBM(x, y, z);
case FractalType.Billow:
return SinglePerlinFractalBillow(x, y, z);
case FractalType.RigidMulti:
return SinglePerlinFractalRigidMulti(x, y, z);
default:
return 0;
}
}
private FN_DECIMAL SinglePerlinFractalFBM(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = SinglePerlin(seed, x, y, z);
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum += SinglePerlin(++seed, x, y, z) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SinglePerlinFractalBillow(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = Math.Abs(SinglePerlin(seed, x, y, z)) * 2 - 1;
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum += (Math.Abs(SinglePerlin(++seed, x, y, z)) * 2 - 1) * amp;
}
return sum * m_fractalBounding;
}
private FN_DECIMAL SinglePerlinFractalRigidMulti(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int seed = m_seed;
FN_DECIMAL sum = 1 - Math.Abs(SinglePerlin(seed, x, y, z));
FN_DECIMAL amp = 1;
for (int i = 1; i < m_octaves; i++)
{
x *= m_lacunarity;
y *= m_lacunarity;
z *= m_lacunarity;
amp *= m_gain;
sum -= (1 - Math.Abs(SinglePerlin(++seed, x, y, z))) * amp;
}
return sum;
}
public FN_DECIMAL GetPerlin(FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
return SinglePerlin(m_seed, x * m_frequency, y * m_frequency, z * m_frequency);
}
private FN_DECIMAL SinglePerlin(int seed, FN_DECIMAL x, FN_DECIMAL y, FN_DECIMAL z)
{
int x0 = FastFloor(x);
int y0 = FastFloor(y);
int z0 = FastFloor(z);
int x1 = x0 + 1;
int y1 = y0 + 1;
int z1 = z0 + 1;
FN_DECIMAL xs, ys, zs;
switch (m_interp)
{
default:
case Interp.Linear:
xs = x - x0;
ys = y - y0;
zs = z - z0;
break;
case Interp.Hermite:
xs = InterpHermiteFunc(x - x0);
ys = InterpHermiteFunc(y - y0);
zs = InterpHermiteFunc(z - z0);
break;
case Interp.Quintic:
xs = InterpQuinticFunc(x - x0);
ys = InterpQuinticFunc(y - y0);
zs = InterpQuinticFunc(z - z0);
break;
}
FN_DECIMAL xd0 = x - x0;
FN_DECIMAL yd0 = y - y0;
FN_DECIMAL zd0 = z - z0;
FN_DECIMAL xd1 = xd0 - 1;
FN_DECIMAL yd1 = yd0 - 1;
FN_DECIMAL zd1 = zd0 - 1;
FN_DECIMAL xf00 = Lerp(GradCoord3D(seed, x0, y0, z0, xd0, yd0, zd0), GradCoord3D(seed, x1, y0, z0, xd1, yd0, zd0), xs);
FN_DECIMAL xf10 = Lerp(GradCoord3D(seed, x0, y1, z0, xd0, yd1, zd0), GradCoord3D(seed, x1, y1, z0, xd1, yd1, zd0), xs);
FN_DECIMAL xf01 = Lerp(GradCoord3D(seed, x0, y0, z1, xd0, yd0, zd1), GradCoord3D(seed, x1, y0, z1, xd1, yd0, zd1), xs);
FN_DECIMAL xf11 = Lerp(GradCoord3D(seed, x0, y1, z1, xd0, yd1, zd1), GradCoord3D(seed, x1, y1, z1, xd1, yd1, zd1), xs);
FN_DECIMAL yf0 = Lerp(xf00, xf10, ys);