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@woosh/meep-engine

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Pure JavaScript game engine. Fully featured and production ready.

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const v2_array = []; const v3_array = []; const v4_array = []; /* Static data ---------------------- */ /* * Permutation table. This is just a random jumble of all numbers 0-255, * repeated twice to avoid wrapping the index at 255 for each lookup. * TODO we can initialize this per instance of noise */ const perm = new Uint8Array([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, 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 ]); /** * Gradient tables. These could be programmed the Ken Perlin way with * some clever bit-twiddling, but this is more clear, and not really slower. * * PORT NOTES: static float grad2lut[8][2] * * @readonly * @type {Int8Array} */ const grad2lut = new Int8Array([ -1.0, -1.0, 1.0, 0.0, -1.0, 0.0, 1.0, 1.0, -1.0, 1.0, 0.0, -1.0, 0.0, 1.0, 1.0, -1.0 ]); /** * Gradient directions for 3D. * These vectors are based on the midpoints of the 12 edges of a cube. * A larger array of random unit length vectors would also do the job, * but these 12 (including 4 repeats to make the array length a power * of two) work better. They are not random, they are carefully chosen * to represent a small, isotropic set of directions. * * PORT NOTES: static float grad3lut[16][3] * * @readonly * @type {Int8Array} */ const grad3lut = new Int8Array([ 1.0, 0.0, 1.0, 0.0, 1.0, 1.0, // 12 cube edges -1.0, 0.0, 1.0, 0.0, -1.0, 1.0, 1.0, 0.0, -1.0, 0.0, 1.0, -1.0, -1.0, 0.0, -1.0, 0.0, -1.0, -1.0, 1.0, -1.0, 0.0, 1.0, 1.0, 0.0, -1.0, 1.0, 0.0, -1.0, -1.0, 0.0, 1.0, 0.0, 1.0, -1.0, 0.0, 1.0, // 4 repeats to make 16 0.0, 1.0, -1.0, 0.0, -1.0, -1.0 ]); /** * PORT NOTES: static float grad3lut[32][4] * * @readonly * @type {Int8Array} */ const grad4lut = new Int8Array([ 0.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, -1.0, 0.0, 1.0, -1.0, 1.0, 0.0, 1.0, -1.0, -1.0, // 32 tesseract edges 0.0, -1.0, 1.0, 1.0, 0.0, -1.0, 1.0, -1.0, 0.0, -1.0, -1.0, 1.0, 0.0, -1.0, -1.0, -1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, 1.0, -1.0, 1.0, 0.0, -1.0, 1.0, 1.0, 0.0, -1.0, -1.0, -1.0, 0.0, 1.0, 1.0, -1.0, 0.0, 1.0, -1.0, -1.0, 0.0, -1.0, 1.0, -1.0, 0.0, -1.0, -1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, -1.0, 1.0, -1.0, 0.0, 1.0, 1.0, -1.0, 0.0, -1.0, -1.0, 1.0, 0.0, 1.0, -1.0, 1.0, 0.0, -1.0, -1.0, -1.0, 0.0, 1.0, -1.0, -1.0, 0.0, -1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, -1.0, 0.0, 1.0, -1.0, 1.0, 0.0, 1.0, -1.0, -1.0, 0.0, -1.0, 1.0, 1.0, 0.0, -1.0, 1.0, -1.0, 0.0, -1.0, -1.0, 1.0, 0.0, -1.0, -1.0, -1.0, 0.0 ]); /** * 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. * TODO: This should not be required, backport it from Bill's GLSL code! * * PORT NOTES: static unsigned char simplex[64][4] * @readonly * @type {Uint8Array} */ const simplex = new Uint8Array([ 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 ]); /* --------------------------------------------------------------------- */ /* * Helper functions to compute gradients in 1D to 4D * and gradients-dot-residualvectors in 2D to 4D. */ /** * * @param {number} hash * @returns {number} */ function grad1(hash) { const h = hash & 15; let gx = 1.0 + (h & 7); // Gradient value is one of 1.0, 2.0, ..., 8.0 if (h & 8) gx = -gx; // Make half of the gradients negative return gx; } /** * * @param {number[]} result * @param {number} hash */ function grad2(result, hash) { const h = hash & 7; const h2 = h * 2; result[0] = grad2lut[h2]; result[1] = grad2lut[h2 + 1]; } /** * * @param {number[]} result * @param {number} hash */ function grad3(result, hash) { const h = hash & 15; const h3 = h * 3; result[0] = grad3lut[h3]; result[1] = grad3lut[h3 + 1]; result[2] = grad3lut[h3 + 2]; } /** * * @param {number[]} result * @param {number} hash */ function grad4(result, hash) { const h = hash & 31; const h4 = h * 4; result[0] = grad4lut[h4]; result[1] = grad4lut[h4 + 1]; result[2] = grad4lut[h4 + 2]; result[3] = grad4lut[h4 + 3]; } /** * 1D simplex noise with derivative. * If the last argument is not null, the analytic derivative * is also calculated. * @param {number} x * @param {number[]} derivatives * @returns {number} */ export function sdnoise1(derivatives, x) { const i0 = x | 0; const i1 = i0 + 1; const x0 = x - i0; const x1 = x0 - 1.0; let gx0, gx1; let n0, n1; let t1, t20, t40, t21, t41, x21; const x20 = x0 * x0; const t0 = 1.0 - x20; // if(t0 < 0.0f) t0 = 0.0f; // Never happens for 1D: x0<=1 always t20 = t0 * t0; t40 = t20 * t20; gx0 = grad1(perm[i0 & 0xff]); n0 = t40 * gx0 * x0; x21 = x1 * x1; t1 = 1.0 - x21; // if(t1 < 0.0f) t1 = 0.0f; // Never happens for 1D: |x1|<=1 always t21 = t1 * t1; t41 = t21 * t21; gx1 = grad1(perm[i1 & 0xff]); n1 = t41 * gx1 * x1; /* Compute derivative, if requested by supplying non-null pointer * for the last argument * Compute derivative according to: * *dnoise_dx = -8.0f * t20 * t0 * x0 * (gx0 * x0) + t40 * gx0; * *dnoise_dx += -8.0f * t21 * t1 * x1 * (gx1 * x1) + t41 * gx1; */ let dnoise_dx = t20 * t0 * gx0 * x20; dnoise_dx += t21 * t1 * gx1 * x21; dnoise_dx *= -8.0; dnoise_dx += t40 * gx0 + t41 * gx1; dnoise_dx *= 0.25; /* Scale derivative to match the noise scaling */ derivatives[0] = dnoise_dx; // The maximum value of this noise is 8*(3/4)^4 = 2.53125 // A factor of 0.395 would scale to fit exactly within [-1,1], but // to better match classic Perlin noise, we scale it down some more. return 0.25 * (n0 + n1); } /* Skewing factors for 2D simplex grid: * F2 = 0.5*(sqrt(3.0)-1.0) * G2 = (3.0-Math.sqrt(3.0))/6.0 */ const F2 = 0.3660254037844386; const G2 = 0.21132486540518713; /** 2D simplex noise with derivatives. * If the last two arguments are not null, the analytic derivative * (the 2D gradient of the scalar noise field) is also calculated. * * @param {number} x * @param {number} y * @param {number[]} derivatives * @returns {number} */ export function sdnoise2(derivatives, x, y) { let n0, n1, n2; /* Noise contributions from the three simplex corners */ let gx0, gy0, gx1, gy1, gx2, gy2; /* Gradients at simplex corners */ let t0, t1, t2, x1, x2, y1, y2; let t20, t40, t21, t41, t22, t42; let temp0, temp1, temp2, noise; /* Skew the input space to determine which simplex cell we're in */ const s = (x + y) * F2; /* Hairy factor for 2D */ const xs = x + s; const ys = y + s; let ii, i = xs | 0; let jj, j = ys | 0; const t = (i + j) * G2; const X0 = i - t; /* Unskew the cell origin back to (x,y) space */ const Y0 = j - t; const x0 = x - X0; /* The x,y distances from the cell origin */ const y0 = y - Y0; /* For the 2D case, the simplex shape is an equilateral triangle. * Determine which simplex we are in. */ let 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 */ x1 = x0 - i1 + G2; /* Offsets for middle corner in (x,y) unskewed coords */ y1 = y0 - j1 + G2; x2 = x0 - 1.0 + 2.0 * G2; /* Offsets for last corner in (x,y) unskewed coords */ y2 = y0 - 1.0 + 2.0 * G2; /* Wrap the integer indices at 256, to avoid indexing perm[] out of bounds */ ii = i % 256; jj = j % 256; /* Calculate the contribution from the three corners */ t0 = 0.5 - x0 * x0 - y0 * y0; if (t0 < 0.0) { t40 = t20 = t0 = n0 = gx0 = gy0 = 0.0; /* No influence */ } else { grad2(v2_array, perm[ii + perm[jj]]); gx0 = v2_array[0]; gy0 = v2_array[1]; t20 = t0 * t0; t40 = t20 * t20; n0 = t40 * (gx0 * x0 + gy0 * y0); } t1 = 0.5 - x1 * x1 - y1 * y1; if (t1 < 0.0) { t21 = t41 = t1 = n1 = gx1 = gy1 = 0.0; /* No influence */ } else { grad2(v2_array, perm[ii + i1 + perm[jj + j1]]); gx1 = v2_array[0]; gy1 = v2_array[1]; t21 = t1 * t1; t41 = t21 * t21; n1 = t41 * (gx1 * x1 + gy1 * y1); } t2 = 0.5 - x2 * x2 - y2 * y2; if (t2 < 0.0) { t42 = t22 = t2 = n2 = gx2 = gy2 = 0.0; /* No influence */ } else { grad2(v2_array, perm[ii + 1 + perm[jj + 1]]); gx2 = v2_array[0]; gy2 = v2_array[1]; t22 = t2 * t2; t42 = t22 * t22; n2 = t42 * (gx2 * x2 + gy2 * y2); } /* Add contributions from each corner to get the final noise value. * The result is scaled to return values in the interval [-1,1]. */ noise = 40.0 * (n0 + n1 + n2); /* Compute derivative, if requested by supplying non-null pointers * for the last two arguments */ /* A straight, unoptimised calculation would be like: * *dnoise_dx = -8.0f * t20 * t0 * x0 * ( gx0 * x0 + gy0 * y0 ) + t40 * gx0; * *dnoise_dy = -8.0f * t20 * t0 * y0 * ( gx0 * x0 + gy0 * y0 ) + t40 * gy0; * *dnoise_dx += -8.0f * t21 * t1 * x1 * ( gx1 * x1 + gy1 * y1 ) + t41 * gx1; * *dnoise_dy += -8.0f * t21 * t1 * y1 * ( gx1 * x1 + gy1 * y1 ) + t41 * gy1; * *dnoise_dx += -8.0f * t22 * t2 * x2 * ( gx2 * x2 + gy2 * y2 ) + t42 * gx2; * *dnoise_dy += -8.0f * t22 * t2 * y2 * ( gx2 * x2 + gy2 * y2 ) + t42 * gy2; */ temp0 = t20 * t0 * (gx0 * x0 + gy0 * y0); let dnoise_dx = temp0 * x0; let dnoise_dy = temp0 * y0; temp1 = t21 * t1 * (gx1 * x1 + gy1 * y1); dnoise_dx += temp1 * x1; dnoise_dy += temp1 * y1; temp2 = t22 * t2 * (gx2 * x2 + gy2 * y2); dnoise_dx += temp2 * x2; dnoise_dy += temp2 * y2; dnoise_dx *= -8.0; dnoise_dy *= -8.0; dnoise_dx += t40 * gx0 + t41 * gx1 + t42 * gx2; dnoise_dy += t40 * gy0 + t41 * gy1 + t42 * gy2; dnoise_dx *= 40.0; /* Scale derivative to match the noise scaling */ dnoise_dy *= 40.0; derivatives[0] = dnoise_dx; derivatives[1] = dnoise_dy; return noise; } /* Skewing factors for 3D simplex grid: * F3 = 1/3 * G3 = 1/6 */ const F3 = 0.3333333333333333; const G3 = 0.16666666666666666; /** 3D simplex noise with derivatives. * If the last tthree arguments are not null, the analytic derivative * (the 3D gradient of the scalar noise field) is also calculated. * * @param {number} x * @param {number} y * @param {number} z * @param {number[]} derivatives * @returns {number} */ export function sdnoise3(derivatives, x, y, z) { let n0, n1, n2, n3; /* Noise contributions from the four simplex corners */ let gx0, gy0, gz0, gx1, gy1, gz1; /* Gradients at simplex corners */ let gx2, gy2, gz2, gx3, gy3, gz3; let t0, t1, t2, t3, t20, t40, t21, t41, t22, t42, t23, t43; let i1, j1, k1; /* Offsets for second corner of simplex in (i,j,k) coords */ let i2, j2, k2; /* Offsets for third corner of simplex in (i,j,k) coords */ /* Skew the input space to determine which simplex cell we're in */ const s = (x + y + z) * F3; /* Very nice and simple skew factor for 3D */ const xs = x + s; const ys = y + s; const zs = z + s; const i = xs | 0; const j = ys | 0; const k = zs | 0; const t = (i + j + k) * G3; const X0 = i - t; /* Unskew the cell origin back to (x,y,z) space */ const Y0 = j - t; const Z0 = k - t; const x0 = x - X0; /* The x,y,z distances from the cell origin */ const y0 = y - Y0; const z0 = z - Z0; /* For the 3D case, the simplex shape is a slightly irregular tetrahedron. * Determine which simplex we are in. */ /* TODO: This code would benefit from a backport from the GLSL version! */ 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 if (y0 < z0) { i1 = 0; j1 = 0; k1 = 1; i2 = 0; j2 = 1; k2 = 1; } /* Z Y X order */ else if (x0 < z0) { i1 = 0; j1 = 1; k1 = 0; i2 = 0; j2 = 1; k2 = 1; } /* Y Z X order */ else { i1 = 0; j1 = 1; k1 = 0; i2 = 1; j2 = 1; k2 = 0; } /* Y X Z order */ } /* A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x,y,z), * a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x,y,z), and * a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x,y,z), where * c = 1/6. */ const x1 = x0 - i1 + G3; /* Offsets for second corner in (x,y,z) coords */ const y1 = y0 - j1 + G3; const z1 = z0 - k1 + G3; const G6 = G3 + G3; const x2 = x0 - i2 + G6; /* Offsets for third corner in (x,y,z) coords */ const y2 = y0 - j2 + G6; const z2 = z0 - k2 + G6; const G9 = G6 + G3; const x3 = x0 - 1.0 + G9; /* Offsets for last corner in (x,y,z) coords */ const y3 = y0 - 1.0 + G9; const z3 = z0 - 1.0 + G9; /* Wrap the integer indices at 256, to avoid indexing perm[] out of bounds */ const ii = i & 255; const jj = j & 255; const kk = k & 255; /* Calculate the contribution from the four corners */ t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0; if (t0 < 0.0) { n0 = t0 = t20 = t40 = gx0 = gy0 = gz0 = 0.0; } else { grad3(v3_array, perm[ii + perm[jj + perm[kk]]]); gx0 = v3_array[0]; gy0 = v3_array[1]; gz0 = v3_array[2]; t20 = t0 * t0; t40 = t20 * t20; n0 = t40 * (gx0 * x0 + gy0 * y0 + gz0 * z0); } t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1; if (t1 < 0.0) { n1 = t1 = t21 = t41 = gx1 = gy1 = gz1 = 0.0; } else { grad3(v3_array, perm[ii + i1 + perm[jj + j1 + perm[kk + k1]]]); gx1 = v3_array[0]; gy1 = v3_array[1]; gz1 = v3_array[2]; t21 = t1 * t1; t41 = t21 * t21; n1 = t41 * (gx1 * x1 + gy1 * y1 + gz1 * z1); } t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2; if (t2 < 0.0) { n2 = t2 = t22 = t42 = gx2 = gy2 = gz2 = 0.0; } else { grad3(v3_array, perm[ii + i2 + perm[jj + j2 + perm[kk + k2]]]); gx2 = v3_array[0]; gy2 = v3_array[1]; gz2 = v3_array[2]; t22 = t2 * t2; t42 = t22 * t22; n2 = t42 * (gx2 * x2 + gy2 * y2 + gz2 * z2); } t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3; if (t3 < 0.0) { n3 = t3 = t23 = t43 = gx3 = gy3 = gz3 = 0.0; } else { grad3(v3_array, perm[ii + 1 + perm[jj + 1 + perm[kk + 1]]]); gx3 = v3_array[0]; gy3 = v3_array[1]; gz3 = v3_array[2]; t23 = t3 * t3; t43 = t23 * t23; n3 = t43 * (gx3 * x3 + gy3 * y3 + gz3 * z3); } /* Add contributions from each corner to get the final noise value. * The result is scaled to return values in the range [-1,1] */ const noise = 28.0 * (n0 + n1 + n2 + n3); /* Compute derivative, if requested by supplying non-null pointers * for the last three arguments */ /* A straight, unoptimised calculation would be like: * *dnoise_dx = -8.0f * t20 * t0 * x0 * dot(gx0, gy0, gz0, x0, y0, z0) + t40 * gx0; * *dnoise_dy = -8.0f * t20 * t0 * y0 * dot(gx0, gy0, gz0, x0, y0, z0) + t40 * gy0; * *dnoise_dz = -8.0f * t20 * t0 * z0 * dot(gx0, gy0, gz0, x0, y0, z0) + t40 * gz0; * *dnoise_dx += -8.0f * t21 * t1 * x1 * dot(gx1, gy1, gz1, x1, y1, z1) + t41 * gx1; * *dnoise_dy += -8.0f * t21 * t1 * y1 * dot(gx1, gy1, gz1, x1, y1, z1) + t41 * gy1; * *dnoise_dz += -8.0f * t21 * t1 * z1 * dot(gx1, gy1, gz1, x1, y1, z1) + t41 * gz1; * *dnoise_dx += -8.0f * t22 * t2 * x2 * dot(gx2, gy2, gz2, x2, y2, z2) + t42 * gx2; * *dnoise_dy += -8.0f * t22 * t2 * y2 * dot(gx2, gy2, gz2, x2, y2, z2) + t42 * gy2; * *dnoise_dz += -8.0f * t22 * t2 * z2 * dot(gx2, gy2, gz2, x2, y2, z2) + t42 * gz2; * *dnoise_dx += -8.0f * t23 * t3 * x3 * dot(gx3, gy3, gz3, x3, y3, z3) + t43 * gx3; * *dnoise_dy += -8.0f * t23 * t3 * y3 * dot(gx3, gy3, gz3, x3, y3, z3) + t43 * gy3; * *dnoise_dz += -8.0f * t23 * t3 * z3 * dot(gx3, gy3, gz3, x3, y3, z3) + t43 * gz3; */ const temp0 = t20 * t0 * (gx0 * x0 + gy0 * y0 + gz0 * z0); let dnoise_dx = temp0 * x0; let dnoise_dy = temp0 * y0; let dnoise_dz = temp0 * z0; const temp1 = t21 * t1 * (gx1 * x1 + gy1 * y1 + gz1 * z1); dnoise_dx += temp1 * x1; dnoise_dy += temp1 * y1; dnoise_dz += temp1 * z1; const temp2 = t22 * t2 * (gx2 * x2 + gy2 * y2 + gz2 * z2); dnoise_dx += temp2 * x2; dnoise_dy += temp2 * y2; dnoise_dz += temp2 * z2; const temp3 = t23 * t3 * (gx3 * x3 + gy3 * y3 + gz3 * z3); dnoise_dx += temp3 * x3; dnoise_dy += temp3 * y3; dnoise_dz += temp3 * z3; dnoise_dx *= -8.0; dnoise_dy *= -8.0; dnoise_dz *= -8.0; dnoise_dx += t40 * gx0 + t41 * gx1 + t42 * gx2 + t43 * gx3; dnoise_dy += t40 * gy0 + t41 * gy1 + t42 * gy2 + t43 * gy3; dnoise_dz += t40 * gz0 + t41 * gz1 + t42 * gz2 + t43 * gz3; /* Scale derivative to match the noise scaling */ dnoise_dx *= 28.0; dnoise_dy *= 28.0; dnoise_dz *= 28.0; derivatives[0] = dnoise_dx; derivatives[1] = dnoise_dy; derivatives[2] = dnoise_dz; return noise; } // The skewing and unskewing factors are hairy again for the 4D case const F4 = 0.30901699437494745;// F4 = (Math.sqrt(5.0)-1.0)/4.0 const G4 = 0.1381966011250105; // G4 = (5.0-Math.sqrt(5.0))/20.0 /** * 4D simplex noise with derivatives. * If the last four arguments are not null, the analytic derivative * (the 4D gradient of the scalar noise field) is also calculated. * @param {number[]} derivatives * @param {number} x * @param {number} y * @param {number} z * @param {number} w * @returns {number} */ export function sdnoise4(derivatives, x, y, z, w) { let n0, n1, n2, n3, n4; // Noise contributions from the five corners let noise; // Return value let gx0, gy0, gz0, gw0, gx1, gy1, gz1, gw1; /* Gradients at simplex corners */ let gx2, gy2, gz2, gw2, gx3, gy3, gz3, gw3, gx4, gy4, gz4, gw4; let t20, t21, t22, t23, t24; let t40, t41, t42, t43, t44; let x1, y1, z1, w1, x2, y2, z2, w2, x3, y3, z3, w3, x4, y4, z4, w4; let t0, t1, t2, t3, t4; let temp0, temp1, temp2, temp3, temp4; // Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in const s = (x + y + z + w) * F4; // Factor for 4D skewing const xs = x + s; const ys = y + s; const zs = z + s; const ws = w + s; let ii, i = xs | 0; let jj, j = ys | 0; let kk, k = zs | 0; let ll, l = ws | 0; const t = (i + j + k + l) * G4; // Factor for 4D unskewing const X0 = i - t; // Unskew the cell origin back to (x,y,z,w) space const Y0 = j - t; const Z0 = k - t; const W0 = l - t; const x0 = x - X0; // The x,y,z,w distances from the cell origin const y0 = y - Y0; const z0 = z - Z0; const w0 = w - W0; // For the 4D case, the simplex is a 4D shape I won't even try to describe. // To find out which of the 24 possible simplices we're in, we need to // determine the magnitude ordering of x0, y0, z0 and w0. // The method below is a reasonable way of finding the ordering of x,y,z,w // and then find the correct traversal order for the simplex we�re in. // First, six pair-wise comparisons are performed between each possible pair // of the four coordinates, and then the results are used to add up binary // bits for an integer index into a precomputed lookup table, simplex[]. const c1 = (x0 > y0) ? 32 : 0; const c2 = (x0 > z0) ? 16 : 0; const c3 = (y0 > z0) ? 8 : 0; const c4 = (x0 > w0) ? 4 : 0; const c5 = (y0 > w0) ? 2 : 0; const c6 = (z0 > w0) ? 1 : 0; const c = c1 | c2 | c3 | c4 | c5 | c6; // '|' is mostly faster than '+' let i1, j1, k1, l1; // The integer offsets for the second simplex corner let i2, j2, k2, l2; // The integer offsets for the third simplex corner let 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<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. // The number 3 in the "simplex" array is at the position of the largest coordinate. const simplex_c = simplex[c]; const simplex_c_0 = simplex_c[0]; const simplex_c_1 = simplex_c[1]; const simplex_c_2 = simplex_c[2]; const simplex_c_3 = simplex_c[3]; i1 = simplex_c_0 >= 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. x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w) coords y1 = y0 - j1 + G4; z1 = z0 - k1 + G4; w1 = w0 - l1 + G4; x2 = x0 - i2 + 2.0 * G4; // Offsets for third corner in (x,y,z,w) coords y2 = y0 - j2 + 2.0 * G4; z2 = z0 - k2 + 2.0 * G4; w2 = w0 - l2 + 2.0 * G4; x3 = x0 - i3 + 3.0 * G4; // Offsets for fourth corner in (x,y,z,w) coords y3 = y0 - j3 + 3.0 * G4; z3 = z0 - k3 + 3.0 * G4; w3 = w0 - l3 + 3.0 * G4; x4 = x0 - 1.0 + 4.0 * G4; // Offsets for last corner in (x,y,z,w) coords y4 = y0 - 1.0 + 4.0 * G4; z4 = z0 - 1.0 + 4.0 * G4; w4 = w0 - 1.0 + 4.0 * G4; // Wrap the integer indices at 256, to avoid indexing perm[] out of bounds ii = i & 0xff; jj = j & 0xff; kk = k & 0xff; ll = l & 0xff; // Calculate the contribution from the five corners t0 = 0.6 - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0; if (t0 < 0.0) { n0 = t0 = t20 = t40 = gx0 = gy0 = gz0 = gw0 = 0.0; } else { t20 = t0 * t0; t40 = t20 * t20; grad4(v4_array, perm[ii + perm[jj + perm[kk + perm[ll]]]]); gx0 = v4_array[0]; gy0 = v4_array[1]; gz0 = v4_array[2]; gw0 = v4_array[3]; n0 = t40 * (gx0 * x0 + gy0 * y0 + gz0 * z0 + gw0 * w0); } t1 = 0.6 - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1; if (t1 < 0.0) { n1 = t1 = t21 = t41 = gx1 = gy1 = gz1 = gw1 = 0.0; } else { t21 = t1 * t1; t41 = t21 * t21; grad4(v4_array, perm[ii + i1 + perm[jj + j1 + perm[kk + k1 + perm[ll + l1]]]]); gx1 = v4_array[0]; gy1 = v4_array[1]; gz1 = v4_array[2]; gw1 = v4_array[3]; n1 = t41 * (gx1 * x1 + gy1 * y1 + gz1 * z1 + gw1 * w1); } t2 = 0.6 - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2; if (t2 < 0.0) { n2 = t2 = t22 = t42 = gx2 = gy2 = gz2 = gw2 = 0.0; } else { t22 = t2 * t2; t42 = t22 * t22; grad4(v4_array, perm[ii + i2 + perm[jj + j2 + perm[kk + k2 + perm[ll + l2]]]]); gx2 = v4_array[0]; gy2 = v4_array[1]; gz2 = v4_array[2]; gw2 = v4_array[3]; n2 = t42 * (gx2 * x2 + gy2 * y2 + gz2 * z2 + gw2 * w2); } t3 = 0.6 - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3; if (t3 < 0.0) { n3 = t3 = t23 = t43 = gx3 = gy3 = gz3 = gw3 = 0.0; } else { t23 = t3 * t3; t43 = t23 * t23; grad4(v4_array, perm[ii + i3 + perm[jj + j3 + perm[kk + k3 + perm[ll + l3]]]]); gx3 = v4_array[0]; gy3 = v4_array[1]; gz3 = v4_array[2]; gw3 = v4_array[3]; n3 = t43 * (gx3 * x3 + gy3 * y3 + gz3 * z3 + gw3 * w3); } t4 = 0.6 - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4; if (t4 < 0.0) { n4 = t4 = t24 = t44 = gx4 = gy4 = gz4 = gw4 = 0.0; } else { t24 = t4 * t4; t44 = t24 * t24; grad4(v4_array, perm[ii + 1 + perm[jj + 1 + perm[kk + 1 + perm[ll + 1]]]]); gx4 = v4_array[0]; gy4 = v4_array[1]; gz4 = v4_array[2]; gw4 = v4_array[3]; n4 = t44 * (gx4 * x4 + gy4 * y4 + gz4 * z4 + gw4 * w4); } // Sum up and scale the result to cover the range [-1,1] noise = 27.0 * (n0 + n1 + n2 + n3 + n4); // TODO: The scale factor is preliminary! /* Compute derivative, if requested by supplying non-null pointers * for the last four arguments */ /* A straight, unoptimised calculation would be like: * *dnoise_dx = -8.0f * t20 * t0 * x0 * dot(gx0, gy0, gz0, gw0, x0, y0, z0, w0) + t40 * gx0; * *dnoise_dy = -8.0f * t20 * t0 * y0 * dot(gx0, gy0, gz0, gw0, x0, y0, z0, w0) + t40 * gy0; * *dnoise_dz = -8.0f * t20 * t0 * z0 * dot(gx0, gy0, gz0, gw0, x0, y0, z0, w0) + t40 * gz0; * *dnoise_dw = -8.0f * t20 * t0 * w0 * dot(gx0, gy0, gz0, gw0, x0, y0, z0, w0) + t40 * gw0; * *dnoise_dx += -8.0f * t21 * t1 * x1 * dot(gx1, gy1, gz1, gw1, x1, y1, z1, w1) + t41 * gx1; * *dnoise_dy += -8.0f * t21 * t1 * y1 * dot(gx1, gy1, gz1, gw1, x1, y1, z1, w1) + t41 * gy1; * *dnoise_dz += -8.0f * t21 * t1 * z1 * dot(gx1, gy1, gz1, gw1, x1, y1, z1, w1) + t41 * gz1; * *dnoise_dw = -8.0f * t21 * t1 * w1 * dot(gx1, gy1, gz1, gw1, x1, y1, z1, w1) + t41 * gw1; * *dnoise_dx += -8.0f * t22 * t2 * x2 * dot(gx2, gy2, gz2, gw2, x2, y2, z2, w2) + t42 * gx2; * *dnoise_dy += -8.0f * t22 * t2 * y2 * dot(gx2, gy2, gz2, gw2, x2, y2, z2, w2) + t42 * gy2; * *dnoise_dz += -8.0f * t22 * t2 * z2 * dot(gx2, gy2, gz2, gw2, x2, y2, z2, w2) + t42 * gz2; * *dnoise_dw += -8.0f * t22 * t2 * w2 * dot(gx2, gy2, gz2, gw2, x2, y2, z2, w2) + t42 * gw2; * *dnoise_dx += -8.0f * t23 * t3 * x3 * dot(gx3, gy3, gz3, gw3, x3, y3, z3, w3) + t43 * gx3; * *dnoise_dy += -8.0f * t23 * t3 * y3 * dot(gx3, gy3, gz3, gw3, x3, y3, z3, w3) + t43 * gy3; * *dnoise_dz += -8.0f * t23 * t3 * z3 * dot(gx3, gy3, gz3, gw3, x3, y3, z3, w3) + t43 * gz3; * *dnoise_dw += -8.0f * t23 * t3 * w3 * dot(gx3, gy3, gz3, gw3, x3, y3, z3, w3) + t43 * gw3; * *dnoise_dx += -8.0f * t24 * t4 * x4 * dot(gx4, gy4, gz4, gw4, x4, y4, z4, w4) + t44 * gx4; * *dnoise_dy += -8.0f * t24 * t4 * y4 * dot(gx4, gy4, gz4, gw4, x4, y4, z4, w4) + t44 * gy4; * *dnoise_dz += -8.0f * t24 * t4 * z4 * dot(gx4, gy4, gz4, gw4, x4, y4, z4, w4) + t44 * gz4; * *dnoise_dw += -8.0f * t24 * t4 * w4 * dot(gx4, gy4, gz4, gw4, x4, y4, z4, w4) + t44 * gw4; */ temp0 = t20 * t0 * (gx0 * x0 + gy0 * y0 + gz0 * z0 + gw0 * w0); let dnoise_dx = temp0 * x0; let dnoise_dy = temp0 * y0; let dnoise_dz = temp0 * z0; let dnoise_dw = temp0 * w0; temp1 = t21 * t1 * (gx1 * x1 + gy1 * y1 + gz1 * z1 + gw1 * w1); dnoise_dx += temp1 * x1; dnoise_dy += temp1 * y1; dnoise_dz += temp1 * z1; dnoise_dw += temp1 * w1; temp2 = t22 * t2 * (gx2 * x2 + gy2 * y2 + gz2 * z2 + gw2 * w2); dnoise_dx += temp2 * x2; dnoise_dy += temp2 * y2; dnoise_dz += temp2 * z2; dnoise_dw += temp2 * w2; temp3 = t23 * t3 * (gx3 * x3 + gy3 * y3 + gz3 * z3 + gw3 * w3); dnoise_dx += temp3 * x3; dnoise_dy += temp3 * y3; dnoise_dz += temp3 * z3; dnoise_dw += temp3 * w3; temp4 = t24 * t4 * (gx4 * x4 + gy4 * y4 + gz4 * z4 + gw4 * w4); dnoise_dx += temp4 * x4; dnoise_dy += temp4 * y4; dnoise_dz += temp4 * z4; dnoise_dw += temp4 * w4; dnoise_dx *= -8.0; dnoise_dy *= -8.0; dnoise_dz *= -8.0; dnoise_dw *= -8.0; dnoise_dx += t40 * gx0 + t41 * gx1 + t42 * gx2 + t43 * gx3 + t44 * gx4; dnoise_dy += t40 * gy0 + t41 * gy1 + t42 * gy2 + t43 * gy3 + t44 * gy4; dnoise_dz += t40 * gz0 + t41 * gz1 + t42 * gz2 + t43 * gz3 + t44 * gz4; dnoise_dw += t40 * gw0 + t41 * gw1 + t42 * gw2 + t43 * gw3 + t44 * gw4; dnoise_dx *= 28.0; /* Scale derivative to match the noise scaling */ dnoise_dy *= 28.0; dnoise_dz *= 28.0; dnoise_dw *= 28.0; derivatives[0] = dnoise_dx; derivatives[1] = dnoise_dy; derivatives[2] = dnoise_dz; derivatives[3] = dnoise_dw; return noise; }