public static NoiseSample Noise2D(Vector2 point, float frequency, ENormal normalType)
{
var noiseStart = System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
point *= frequency;
int ix0 = (int)math.floor(point.x);
int iy0 = (int)math.floor(point.y);
float tx0 = point.x - ix0;
float ty0 = point.y - iy0;
float tx1 = tx0 - 1f;
float ty1 = ty0 - 1f;
ix0 &= MASK;
iy0 &= MASK;
int ix1 = ix0 + 1;
int iy1 = iy0 + 1;
int h0 = PERMUTATION[ix0];
int h1 = PERMUTATION[ix1];
Vector3 g00 = GRADIENT_2D[PERMUTATION[h0 + iy0] & MASK2D];
Vector3 g10 = GRADIENT_2D[PERMUTATION[h1 + iy0] & MASK2D];
Vector3 g01 = GRADIENT_2D[PERMUTATION[h0 + iy1] & MASK2D];
Vector3 g11 = GRADIENT_2D[PERMUTATION[h1 + iy1] & MASK2D];
float v00 = Dot(g00, tx0, ty0);
float v10 = Dot(g10, tx1, ty0);
float v01 = Dot(g01, tx0, ty1);
float v11 = Dot(g11, tx1, ty1);
float tx = Smooth(tx0);
float ty = Smooth(ty0);
float a = v00;
float b = v10 - v00;
float c = v01 - v00;
float d = v11 - v01 - v10 + v00;
NoiseSample sample;
sample.m_Value = MapTo1(a + b * tx + (c + d * tx) * ty);
sample.m_ColorValue = sample.m_Value;
sample.m_Derivative = Vector3.zero;
if (normalType == ENormal.Analytical)
{
var startDerivative = System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
float dtx = SmoothDerivative(tx0);
float dty = SmoothDerivative(ty0);
Vector2 da = g00;
Vector2 db = g10 - g00;
Vector2 dc = g01 - g00;
Vector2 dd = g11 - g01 - g10 + g00;
sample.m_Derivative = da + db * tx + (dc + dd * tx) * ty;
sample.m_Derivative.x += (b + d * ty) * dtx;
sample.m_Derivative.y += (c + d * tx) * dty;
sample.m_Derivative.z = 0f;
m_DerivativeCalculationDuration += System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds() - startDerivative;
}
else if (normalType == ENormal.GeometricDinamic)
{
var startGeometrical = System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
var x1 = GetValue(new Vector2(point.x + 0.1f, point.y));
var x2 = GetValue(new Vector2(point.x - 0.1f, point.y));
var y1 = GetValue(new Vector2(point.x, point.y + 0.1f));
var y2 = GetValue(new Vector2(point.x, point.y - 0.1f));
sample.m_Derivative.x = (x1 - x2) * 0.5f;
sample.m_Derivative.y = (y1 - x2) * 0.5f;
m_GeometricalDerivativeDuration += System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds() - startGeometrical;
}
sample.m_Derivative *= frequency;
m_NoiseCalculationDuration += System.DateTimeOffset.UtcNow.ToUnixTimeMilliseconds() - noiseStart;
return(sample);
}
public static NoiseSample Sample(Vector2 pos, float frequency, int octaves, float strength, float lacunarity, float persistance, float amplitude, float damping, float strColoring, ENormal normalType)
{
bool bDamping = math.abs(damping - 1f) < 0.0001f;
bool bColoring = math.abs(strColoring - 1f) < 0.0001f;
float amp = bDamping ? strength / frequency : strength;
var noiseSample = SumNoise(pos, frequency, octaves, lacunarity, persistance, amplitude, normalType);
noiseSample.m_ColorValue = math.saturate(bColoring ? noiseSample.m_Value * strength * amplitude : noiseSample.m_Value);
noiseSample.m_Value *= strength * amp;
noiseSample.m_Derivative = Vector3.Normalize(noiseSample.m_Derivative * strength * amp);
return(noiseSample);
}
public static NoiseSample SumNoise(Vector2 pos, float frequency, int octaves, float lacunarity, float persistance, float amplitude, ENormal normalType)
{
var noiseSample = Noise2D(pos, frequency, normalType);
float range = amplitude;
for (int i = 0; i < octaves; ++i)
{
frequency *= lacunarity;
amplitude *= persistance;
range += amplitude;
noiseSample += Noise2D(pos, frequency, normalType) * amplitude;
}
return(noiseSample * (1f / range));
}
