public class SimplexNoise { // Simplex noise in 2D, 3D and 4D /* 2D, 3D and 4D Simplex Noise functions return 'random' values in (-1, 1). This algorithm was originally designed by Ken Perlin, but my code has been adapted from the implementation written by Stefan Gustavson (stegu@itn.liu.se) Raw Simplex noise functions return the value generated by Ken's algorithm. Scaled Raw Simplex noise functions adjust the range of values returned from the traditional (-1, 1) to whichever bounds are passed to the function. Multi-Octave Simplex noise functions compine multiple noise values to create a more complex result. Each successive layer of noise is adjusted and scaled. Scaled Multi-Octave Simplex noise functions scale the values returned from the traditional (-1,1) range to whichever range is passed to the function. In many cases, you may think you only need a 1D noise function, but in practice 2D is almost always better. For instance, if you're using the current frame number as the parameter for the noise, all objects will end up with the same noise value at each frame. By adding a second parameter on the second dimension, you can ensure that each gets a unique noise value and they don't all look identical. */ // 2D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. // The gradients are the midpoints of the vertices of a cube. private static int[][] grad3 = new int[][] { new int[] {1,1,0}, new int[] {-1,1,0}, new int[] {1,-1,0}, new int[] {-1,-1,0}, new int[] {1,0,1}, new int[] {-1,0,1}, new int[] {1,0,-1}, new int[] {-1,0,-1}, new int[] {0,1,1}, new int[] {0,-1,1}, new int[] {0,1,-1}, new int[] {0,-1,-1}}; private static int[][] grad4 = new int[][] {new int[] {0,1,1,1}, new int[] {0,1,1,-1}, new int[] {0,1,-1,1}, new int[] {0,1,-1,-1}, new int[] {0,-1,1,1}, new int[] {0,-1,1,-1}, new int[] {0,-1,-1,1}, new int[] {0,-1,-1,-1}, new int[] {1,0,1,1}, new int[] {1,0,1,-1}, new int[] {1,0,-1,1}, new int[] {1,0,-1,-1}, new int[] {-1,0,1,1}, new int[] {-1,0,1,-1}, new int[] {-1,0,-1,1}, new int[] {-1,0,-1,-1}, new int[] {1,1,0,1}, new int[] {1,1,0,-1}, new int[] {1,-1,0,1}, new int[] {1,-1,0,-1}, new int[] {-1,1,0,1}, new int[] {-1,1,0,-1}, new int[] {-1,-1,0,1}, new int[] {-1,-1,0,-1}, new int[] {1,1,1,0}, new int[] {1,1,-1,0}, new int[] {1,-1,1,0}, new int[] {1,-1,-1,0}, new int[] {-1,1,1,0}, new int[] {-1,1,-1,0}, new int[] {-1,-1,1,0}, new int[] {-1,-1,-1,0}}; private static int[] p = new int[] {151,160,137,91,90,15, 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}; // To remove the need for index wrapping, double the permutation table length private static int[] perm = new int[512]; // A lookup table to traverse the simplex around a given point in 4D. // Details can be found where this table is used, in the 4D noise method. private static int[,] simplex = new int[,] {{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}}; public float octave_noise_2d(float octaves, float persistence, float scale, float x, float y) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_2d(x * frequency, y * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 3D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. public float octave_noise_3d(float octaves, float persistence, float scale, float x, float y, float z) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_3d(x * frequency, y * frequency, z * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 4D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. public float octave_noise_4d(float octaves, float persistence, float scale, float x, float y, float z, float w) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_4d(x * frequency, y * frequency, z * frequency, w * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 2D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_2d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y) { return octave_noise_2d(octaves, persistence, scale, x, y) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 3D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_3d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y, float z) { return octave_noise_3d(octaves, persistence, scale, x, y, z) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 4D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_4d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y, float z, float w) { return octave_noise_4d(octaves, persistence, scale, x, y, z, w) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 2D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_2d(float loBound, float hiBound, float x, float y) { return raw_noise_2d(x, y) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 3D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_3d(float loBound, float hiBound, float x, float y, float z) { return raw_noise_3d(x, y, z) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 4D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_4d(float loBound, float hiBound, float x, float y, float z, float w) { return raw_noise_4d(x, y, z, w) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 2D raw Simplex noise public float raw_noise_2d(float x, float y) { // Noise contributions from the three corners float n0, n1, n2; // Skew the input space to determine which simplex cell we're in float F2 = 0.5f * ((float)Math.Sqrt(3.0f) - 1.0f); // Hairy factor for 2D float s = (x + y) * F2; int i = fastfloor(x + s); int j = fastfloor(y + s); float G2 = (3.0f - (float)Math.Sqrt(3.0f)) / 6.0f; float t = (i + j) * G2; // Unskew the cell origin back to (x,y) space float X0 = i - t; float Y0 = j - t; // The x,y distances from the cell origin float x0 = x - X0; float y0 = y - Y0; // For the 2D case, the simplex shape is an equilateral triangle. // Determine which simplex we are in. int i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords 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 float x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords float y1 = y0 - j1 + G2; float x2 = x0 - 1.0f + 2.0f * G2; // Offsets for last corner in (x,y) unskewed coords float y2 = y0 - 1.0f + 2.0f * G2; // Work out the hashed gradient indices of the three simplex corners int ii = i & 255; int jj = j & 255; int gi0 = perm[ii + perm[jj]] % 12; int gi1 = perm[ii + i1 + perm[jj + j1]] % 12; int gi2 = perm[ii + 1 + perm[jj + 1]] % 12; // Calculate the contribution from the three corners float t0 = 0.5f - x0 * x0 - y0 * y0; if (t0 < 0) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * dot(grad3[gi0], x0, y0); // (x,y) of grad3 used for 2D gradient } float t1 = 0.5f - x1 * x1 - y1 * y1; if (t1 < 0) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * dot(grad3[gi1], x1, y1); } float t2 = 0.5f - x2 * x2 - y2 * y2; if (t2 < 0) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * dot(grad3[gi2], x2, y2); } // Add contributions from each corner to get the final noise value. // The result is scaled to return values in the interval [-1,1]. return 70.0f * (n0 + n1 + n2); } // 3D raw Simplex noise public float raw_noise_3d(float x, float y, float z) { float n0, n1, n2, n3; // Noise contributions from the four corners // Skew the input space to determine which simplex cell we're in float F3 = 1.0f / 3.0f; float s = (x + y + z) * F3; // Very nice and simple skew factor for 3D int i = fastfloor(x + s); int j = fastfloor(y + s); int k = fastfloor(z + s); float G3 = 1.0f / 6.0f; // Very nice and simple unskew factor, too float t = (i + j + k) * G3; float X0 = i - t; // Unskew the cell origin back to (x,y,z) space float Y0 = j - t; float Z0 = k - t; float x0 = x - X0; // The x,y,z distances from the cell origin float y0 = y - Y0; float z0 = z - Z0; // For the 3D case, the simplex shape is a slightly irregular tetrahedron. // Determine which simplex we are in. int i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) coords int i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) coords if (x0 >= y0) { if (y0 >= z0) { i1 = 1; j1 = 0; k1 = 0; i2 = 1; j2 = 1; k2 = 0; } // X Y Z order else if (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) ? 32 : 0; int c2 = (x0 > z0) ? 16 : 0; int c3 = (y0 > z0) ? 8 : 0; int c4 = (x0 > w0) ? 4 : 0; int c5 = (y0 > w0) ? 2 : 0; int c6 = (z0 > w0) ? 1 : 0; int c = c1 + c2 + c3 + c4 + c5 + c6; int i1, j1, k1, l1; // The integer offsets for the second simplex corner int i2, j2, k2, l2; // The integer offsets for the third simplex corner int i3, j3, k3, l3; // 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= 3 ? 1 : 0; j1 = simplex[c, 1] >= 3 ? 1 : 0; k1 = simplex[c, 2] >= 3 ? 1 : 0; l1 = simplex[c, 3] >= 3 ? 1 : 0; // The number 2 in the "simplex" array is at the second largest coordinate. i2 = simplex[c, 0] >= 2 ? 1 : 0; j2 = simplex[c, 1] >= 2 ? 1 : 0; k2 = simplex[c, 2] >= 2 ? 1 : 0; l2 = simplex[c, 3] >= 2 ? 1 : 0; // The number 1 in the "simplex" array is at the second smallest coordinate. i3 = simplex[c, 0] >= 1 ? 1 : 0; j3 = simplex[c, 1] >= 1 ? 1 : 0; k3 = simplex[c, 2] >= 1 ? 1 : 0; l3 = simplex[c, 3] >= 1 ? 1 : 0; // The fifth corner has all coordinate offsets = 1, so no need to look that up. float x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w) coords float y1 = y0 - j1 + G4; float z1 = z0 - k1 + G4; float w1 = w0 - l1 + G4; float x2 = x0 - i2 + 2.0f * G4; // Offsets for third corner in (x,y,z,w) coords float y2 = y0 - j2 + 2.0f * G4; float z2 = z0 - k2 + 2.0f * G4; float w2 = w0 - l2 + 2.0f * G4; float x3 = x0 - i3 + 3.0f * G4; // Offsets for fourth corner in (x,y,z,w) coords float y3 = y0 - j3 + 3.0f * G4; float z3 = z0 - k3 + 3.0f * G4; float w3 = w0 - l3 + 3.0f * G4; float x4 = x0 - 1.0f + 4.0f * G4; // Offsets for last corner in (x,y,z,w) coords float y4 = y0 - 1.0f + 4.0f * G4; float z4 = z0 - 1.0f + 4.0f * G4; float w4 = w0 - 1.0f + 4.0f * G4; // Work out the hashed gradient indices of the five simplex corners int ii = i & 255; int jj = j & 255; int kk = k & 255; int ll = l & 255; int gi0 = perm[ii + perm[jj + perm[kk + perm[ll]]]] % 32; int gi1 = perm[ii + i1 + perm[jj + j1 + perm[kk + k1 + perm[ll + l1]]]] % 32; int gi2 = perm[ii + i2 + perm[jj + j2 + perm[kk + k2 + perm[ll + l2]]]] % 32; int gi3 = perm[ii + i3 + perm[jj + j3 + perm[kk + k3 + perm[ll + l3]]]] % 32; int gi4 = perm[ii + 1 + perm[jj + 1 + perm[kk + 1 + perm[ll + 1]]]] % 32; // Calculate the contribution from the five corners float t0 = 0.6f - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0; if (t0 < 0) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * dot(grad4[gi0], x0, y0, z0, w0); } float t1 = 0.6f - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1; if (t1 < 0) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * dot(grad4[gi1], x1, y1, z1, w1); } float t2 = 0.6f - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2; if (t2 < 0) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * dot(grad4[gi2], x2, y2, z2, w2); } float t3 = 0.6f - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3; if (t3 < 0) n3 = 0.0f; else { t3 *= t3; n3 = t3 * t3 * dot(grad4[gi3], x3, y3, z3, w3); } float t4 = 0.6f - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4; if (t4 < 0) n4 = 0.0f; 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 27.0f * (n0 + n1 + n2 + n3 + n4); } int fastfloor(float x) { return x > 0 ? (int)x : (int)x - 1; } unsafe float dot(int[] g, float x, float y) { return g[0] * x + g[1] * y; } unsafe float dot(int[] g, float x, float y, float z) { return g[0] * x + g[1] * y + g[2] * z; } unsafe float dot(int[] g, float x, float y, float z, float w) { return g[0] * x + g[1] * y + g[2] * z + g[3] * w; } }