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2efea8cf03f9bcb923d969b9ba4c905503e306dc
blender-archive/source/blender/blenlib/intern/noise.c

2001 lines
66 KiB
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/*
* ***** BEGIN GPL LICENSE BLOCK *****
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*
* The Original Code is Copyright (C) 2001-2002 by NaN Holding BV.
* All rights reserved.
*
* The Original Code is: all of this file.
*
* Contributor(s): none yet.
*
* ***** END GPL LICENSE BLOCK *****
*
*/
/** \file blender/blenlib/intern/noise.c
* \ingroup bli
*/
#ifdef _MSC_VER
# pragma warning (disable:4244) /* "conversion from double to float" */
# pragma warning (disable:4305) /* "truncation from const double to float" */
#endif
#include <math.h>
#include "BLI_noise.h"
/* local */
static float noise3_perlin(float vec[3]);
//static float turbulence_perlin(float *point, float lofreq, float hifreq);
//static float turbulencep(float noisesize, float x, float y, float z, int nr);
/* UNUSED */
// #define HASHVEC(x, y, z) hashvectf + 3 * hash[(hash[(hash[(z) & 255] + (y)) & 255] + (x)) & 255]
/* needed for voronoi */
#define HASHPNT(x, y, z) hashpntf + 3 * hash[(hash[(hash[(z) & 255] + (y)) & 255] + (x)) & 255]
static float hashpntf[768] = {
0.536902, 0.020915, 0.501445, 0.216316, 0.517036, 0.822466, 0.965315,
0.377313, 0.678764, 0.744545, 0.097731, 0.396357, 0.247202, 0.520897,
0.613396, 0.542124, 0.146813, 0.255489, 0.810868, 0.638641, 0.980742,
0.292316, 0.357948, 0.114382, 0.861377, 0.629634, 0.722530, 0.714103,
0.048549, 0.075668, 0.564920, 0.162026, 0.054466, 0.411738, 0.156897,
0.887657, 0.599368, 0.074249, 0.170277, 0.225799, 0.393154, 0.301348,
0.057434, 0.293849, 0.442745, 0.150002, 0.398732, 0.184582, 0.915200,
0.630984, 0.974040, 0.117228, 0.795520, 0.763238, 0.158982, 0.616211,
0.250825, 0.906539, 0.316874, 0.676205, 0.234720, 0.667673, 0.792225,
0.273671, 0.119363, 0.199131, 0.856716, 0.828554, 0.900718, 0.705960,
0.635923, 0.989433, 0.027261, 0.283507, 0.113426, 0.388115, 0.900176,
0.637741, 0.438802, 0.715490, 0.043692, 0.202640, 0.378325, 0.450325,
0.471832, 0.147803, 0.906899, 0.524178, 0.784981, 0.051483, 0.893369,
0.596895, 0.275635, 0.391483, 0.844673, 0.103061, 0.257322, 0.708390,
0.504091, 0.199517, 0.660339, 0.376071, 0.038880, 0.531293, 0.216116,
0.138672, 0.907737, 0.807994, 0.659582, 0.915264, 0.449075, 0.627128,
0.480173, 0.380942, 0.018843, 0.211808, 0.569701, 0.082294, 0.689488,
0.573060, 0.593859, 0.216080, 0.373159, 0.108117, 0.595539, 0.021768,
0.380297, 0.948125, 0.377833, 0.319699, 0.315249, 0.972805, 0.792270,
0.445396, 0.845323, 0.372186, 0.096147, 0.689405, 0.423958, 0.055675,
0.117940, 0.328456, 0.605808, 0.631768, 0.372170, 0.213723, 0.032700,
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0.049921, 0.496112, 0.607142, 0.562595, 0.990246, 0.739659, 0.108633,
0.978156, 0.209814, 0.258436, 0.876021, 0.309260, 0.600673, 0.713597,
0.576967, 0.641402, 0.853930, 0.029173, 0.418111, 0.581593, 0.008394,
0.589904, 0.661574, 0.979326, 0.275724, 0.111109, 0.440472, 0.120839,
0.521602, 0.648308, 0.284575, 0.204501, 0.153286, 0.822444, 0.300786,
0.303906, 0.364717, 0.209038, 0.916831, 0.900245, 0.600685, 0.890002,
0.581660, 0.431154, 0.705569, 0.551250, 0.417075, 0.403749, 0.696652,
0.292652, 0.911372, 0.690922, 0.323718, 0.036773, 0.258976, 0.274265,
0.225076, 0.628965, 0.351644, 0.065158, 0.080340, 0.467271, 0.130643,
0.385914, 0.919315, 0.253821, 0.966163, 0.017439, 0.392610, 0.478792,
0.978185, 0.072691, 0.982009, 0.097987, 0.731533, 0.401233, 0.107570,
0.349587, 0.479122, 0.700598, 0.481751, 0.788429, 0.706864, 0.120086,
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0.549594, 0.587892, 0.657534, 0.396365, 0.125153, 0.666420, 0.385823,
0.890916, 0.436729, 0.128114, 0.369598, 0.759096, 0.044677, 0.904752,
0.088052, 0.621148, 0.005047, 0.452331, 0.162032, 0.494238, 0.523349,
0.741829, 0.698450, 0.452316, 0.563487, 0.819776, 0.492160, 0.004210,
0.647158, 0.551475, 0.362995, 0.177937, 0.814722, 0.727729, 0.867126,
0.997157, 0.108149, 0.085726, 0.796024, 0.665075, 0.362462, 0.323124,
0.043718, 0.042357, 0.315030, 0.328954, 0.870845, 0.683186, 0.467922,
0.514894, 0.809971, 0.631979, 0.176571, 0.366320, 0.850621, 0.505555,
0.749551, 0.750830, 0.401714, 0.481216, 0.438393, 0.508832, 0.867971,
0.654581, 0.058204, 0.566454, 0.084124, 0.548539, 0.902690, 0.779571,
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0.489895, 0.189396, 0.724654, 0.092841, 0.039809, 0.860126, 0.247701,
0.655331, 0.964121, 0.672536, 0.044522, 0.690567, 0.837238, 0.631520,
0.953734, 0.352484, 0.289026, 0.034152, 0.852575, 0.098454, 0.795529,
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0.420620, 0.570325, 0.057550, 0.210888, 0.407312, 0.662848, 0.924382,
0.895958, 0.775198, 0.688605, 0.025721, 0.301913, 0.791408, 0.500602,
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0.708535, 0.273900, 0.067419, 0.317124, 0.936499, 0.716511, 0.543845,
0.939909, 0.826574, 0.715090, 0.154864, 0.750150, 0.845808, 0.648108,
0.556564, 0.644757, 0.140873, 0.799167, 0.632989, 0.444245, 0.471978,
0.435910, 0.359793, 0.216241, 0.007633, 0.337236, 0.857863, 0.380247,
0.092517, 0.799973, 0.919000, 0.296798, 0.096989, 0.854831, 0.165369,
0.568475, 0.216855, 0.020457, 0.835511, 0.538039, 0.999742, 0.620226,
0.244053, 0.060399, 0.323007, 0.294874, 0.988899, 0.384919, 0.735655,
0.773428, 0.549776, 0.292882, 0.660611, 0.593507, 0.621118, 0.175269,
0.682119, 0.794493, 0.868197, 0.632150, 0.807823, 0.509656, 0.482035,
0.001780, 0.259126, 0.358002, 0.280263, 0.192985, 0.290367, 0.208111,
0.917633, 0.114422, 0.925491, 0.981110, 0.255570, 0.974862, 0.016629,
0.552599, 0.575741, 0.612978, 0.615965, 0.803615, 0.772334, 0.089745,
0.838812, 0.634542, 0.113709, 0.755832, 0.577589, 0.667489, 0.529834,
0.325660, 0.817597, 0.316557, 0.335093, 0.737363, 0.260951, 0.737073,
0.049540, 0.735541, 0.988891, 0.299116, 0.147695, 0.417271, 0.940811,
0.524160, 0.857968, 0.176403, 0.244835, 0.485759, 0.033353, 0.280319,
0.750688, 0.755809, 0.924208, 0.095956, 0.962504, 0.275584, 0.173715,
0.942716, 0.706721, 0.078464, 0.576716, 0.804667, 0.559249, 0.900611,
0.646904, 0.432111, 0.927885, 0.383277, 0.269973, 0.114244, 0.574867,
0.150703, 0.241855, 0.272871, 0.199950, 0.079719, 0.868566, 0.962833,
0.789122, 0.320025, 0.905554, 0.234876, 0.991356, 0.061913, 0.732911,
0.785960, 0.874074, 0.069035, 0.658632, 0.309901, 0.023676, 0.791603,
0.764661, 0.661278, 0.319583, 0.829650, 0.117091, 0.903124, 0.982098,
0.161631, 0.193576, 0.670428, 0.857390, 0.003760, 0.572578, 0.222162,
0.114551, 0.420118, 0.530404, 0.470682, 0.525527, 0.764281, 0.040596,
0.443275, 0.501124, 0.816161, 0.417467, 0.332172, 0.447565, 0.614591,
0.559246, 0.805295, 0.226342, 0.155065, 0.714630, 0.160925, 0.760001,
0.453456, 0.093869, 0.406092, 0.264801, 0.720370, 0.743388, 0.373269,
0.403098, 0.911923, 0.897249, 0.147038, 0.753037, 0.516093, 0.739257,
0.175018, 0.045768, 0.735857, 0.801330, 0.927708, 0.240977, 0.591870,
0.921831, 0.540733, 0.149100, 0.423152, 0.806876, 0.397081, 0.061100,
0.811630, 0.044899, 0.460915, 0.961202, 0.822098, 0.971524, 0.867608,
0.773604, 0.226616, 0.686286, 0.926972, 0.411613, 0.267873, 0.081937,
0.226124, 0.295664, 0.374594, 0.533240, 0.237876, 0.669629, 0.599083,
0.513081, 0.878719, 0.201577, 0.721296, 0.495038, 0.079760, 0.965959,
0.233090, 0.052496, 0.714748, 0.887844, 0.308724, 0.972885, 0.723337,
0.453089, 0.914474, 0.704063, 0.823198, 0.834769, 0.906561, 0.919600,
0.100601, 0.307564, 0.901977, 0.468879, 0.265376, 0.885188, 0.683875,
0.868623, 0.081032, 0.466835, 0.199087, 0.663437, 0.812241, 0.311337,
0.821361, 0.356628, 0.898054, 0.160781, 0.222539, 0.714889, 0.490287,
0.984915, 0.951755, 0.964097, 0.641795, 0.815472, 0.852732, 0.862074,
0.051108, 0.440139, 0.323207, 0.517171, 0.562984, 0.115295, 0.743103,
0.977914, 0.337596, 0.440694, 0.535879, 0.959427, 0.351427, 0.704361,
0.010826, 0.131162, 0.577080, 0.349572, 0.774892, 0.425796, 0.072697,
0.500001, 0.267322, 0.909654, 0.206176, 0.223987, 0.937698, 0.323423,
0.117501, 0.490308, 0.474372, 0.689943, 0.168671, 0.719417, 0.188928,
0.330464, 0.265273, 0.446271, 0.171933, 0.176133, 0.474616, 0.140182,
0.114246, 0.905043, 0.713870, 0.555261, 0.951333
};
unsigned char hash[512] = {
0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE, 0xF3, 0x1C, 0x67, 0x28, 0x1D, 0xED, 0x0, 0xDE, 0x95, 0x2E, 0xDC,
0x3F, 0x3A, 0x82, 0x35, 0x4D, 0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC, 0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8, 0x8B, 0x63,
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0xB5, 0x40, 0x13, 0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D, 0x86, 0x4C, 0xC8, 0xDB, 0x7C, 0xD5, 0x25, 0x4E,
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0x7D, 0x99, 0xD8, 0xD, 0x60, 0x8A, 0x4, 0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7, 0xE0, 0x29, 0xA6, 0xC5, 0xE3,
0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D, 0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66,
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0xC, 0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8, 0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83, 0xF2, 0x8F, 0x18, 0xC7,
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0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98, 0xB, 0x96, 0xD3, 0x9E, 0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4, 0x24,
0x72, 0x49, 0x8C, 0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA, 0x1F, 0x1, 0xD7, 0x93, 0x11, 0xC1, 0x58, 0xA9,
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0x30, 0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F, 0x62, 0xAC, 0x4F, 0xC2, 0xC0, 0xE, 0xB1, 0x23, 0xA7, 0xDF,
0x47, 0xB0, 0x77, 0x69, 0x5, 0xE9, 0xE6, 0xE7, 0x76, 0x73, 0xF, 0xFE, 0x6E, 0x9B, 0x56, 0xEF, 0x12, 0xA5, 0x37,
0xFC, 0xAE, 0xD9, 0x3, 0x8E, 0xDD, 0x10, 0xB9, 0xCE, 0xC9, 0x8D, 0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4,
0xA, 0xCC, 0xD2, 0xE8, 0x43, 0x3D, 0x70, 0xB7, 0x2, 0x7D, 0x99, 0xD8, 0xD, 0x60, 0x8A, 0x4, 0x2C, 0x3E, 0x92,
0xE5, 0xAF, 0x53, 0x7, 0xE0, 0x29, 0xA6, 0xC5, 0xE3, 0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D,
0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A, 0x45, 0x39, 0xCF, 0x75, 0xA4, 0x88, 0xFB, 0x5D,
};
float hashvectf[768] = {
0.33783, 0.715698, -0.611206, -0.944031, -0.326599, -0.045624, -0.101074, -0.416443, -0.903503, 0.799286, 0.49411,
-0.341949, -0.854645, 0.518036, 0.033936, 0.42514, -0.437866, -0.792114, -0.358948, 0.597046, 0.717377, -0.985413,
0.144714, 0.089294, -0.601776, -0.33728, -0.723907, -0.449921, 0.594513, 0.666382, 0.208313, -0.10791, 0.972076,
0.575317, 0.060425, 0.815643, 0.293365, -0.875702, -0.383453, 0.293762, 0.465759, 0.834686, -0.846008, -0.233398,
-0.47934, -0.115814, 0.143036, -0.98291, 0.204681, -0.949036, -0.239532, 0.946716, -0.263947, 0.184326, -0.235596,
0.573822, 0.784332, 0.203705, -0.372253, -0.905487, 0.756989, -0.651031, 0.055298, 0.497803, 0.814697, -0.297363,
-0.16214, 0.063995, -0.98468, -0.329254, 0.834381, 0.441925, 0.703827, -0.527039, -0.476227, 0.956421, 0.266113,
0.119781, 0.480133, 0.482849, 0.7323, -0.18631, 0.961212, -0.203125, -0.748474, -0.656921, -0.090393, -0.085052,
-0.165253, 0.982544, -0.76947, 0.628174, -0.115234, 0.383148, 0.537659, 0.751068, 0.616486, -0.668488, -0.415924,
-0.259979, -0.630005, 0.73175, 0.570953, -0.087952, 0.816223, -0.458008, 0.023254, 0.888611, -0.196167, 0.976563,
-0.088287, -0.263885, -0.69812, -0.665527, 0.437134, -0.892273, -0.112793, -0.621674, -0.230438, 0.748566, 0.232422,
0.900574, -0.367249, 0.22229, -0.796143, 0.562744, -0.665497, -0.73764, 0.11377, 0.670135, 0.704803, 0.232605,
0.895599, 0.429749, -0.114655, -0.11557, -0.474243, 0.872742, 0.621826, 0.604004, -0.498444, -0.832214, 0.012756,
0.55426, -0.702484, 0.705994, -0.089661, -0.692017, 0.649292, 0.315399, -0.175995, -0.977997, 0.111877, 0.096954,
-0.04953, 0.994019, 0.635284, -0.606689, -0.477783, -0.261261, -0.607422, -0.750153, 0.983276, 0.165436, 0.075958,
-0.29837, 0.404083, -0.864655, -0.638672, 0.507721, 0.578156, 0.388214, 0.412079, 0.824249, 0.556183, -0.208832,
0.804352, 0.778442, 0.562012, 0.27951, -0.616577, 0.781921, -0.091522, 0.196289, 0.051056, 0.979187, -0.121216,
0.207153, -0.970734, -0.173401, -0.384735, 0.906555, 0.161499, -0.723236, -0.671387, 0.178497, -0.006226, -0.983887,
-0.126038, 0.15799, 0.97934, 0.830475, -0.024811, 0.556458, -0.510132, -0.76944, 0.384247, 0.81424, 0.200104,
-0.544891, -0.112549, -0.393311, -0.912445, 0.56189, 0.152222, -0.813049, 0.198914, -0.254517, -0.946381, -0.41217,
0.690979, -0.593811, -0.407257, 0.324524, 0.853668, -0.690186, 0.366119, -0.624115, -0.428345, 0.844147, -0.322296,
-0.21228, -0.297546, -0.930756, -0.273071, 0.516113, 0.811798, 0.928314, 0.371643, 0.007233, 0.785828, -0.479218,
-0.390778, -0.704895, 0.058929, 0.706818, 0.173248, 0.203583, 0.963562, 0.422211, -0.904297, -0.062469, -0.363312,
-0.182465, 0.913605, 0.254028, -0.552307, -0.793945, -0.28891, -0.765747, -0.574554, 0.058319, 0.291382, 0.954803,
0.946136, -0.303925, 0.111267, -0.078156, 0.443695, -0.892731, 0.182098, 0.89389, 0.409515, -0.680298, -0.213318,
0.701141, 0.062469, 0.848389, -0.525635, -0.72879, -0.641846, 0.238342, -0.88089, 0.427673, 0.202637, -0.532501,
-0.21405, 0.818878, 0.948975, -0.305084, 0.07962, 0.925446, 0.374664, 0.055817, 0.820923, 0.565491, 0.079102,
0.25882, 0.099792, -0.960724, -0.294617, 0.910522, 0.289978, 0.137115, 0.320038, -0.937408, -0.908386, 0.345276,
-0.235718, -0.936218, 0.138763, 0.322754, 0.366577, 0.925934, -0.090637, 0.309296, -0.686829, -0.657684, 0.66983,
0.024445, 0.742065, -0.917999, -0.059113, -0.392059, 0.365509, 0.462158, -0.807922, 0.083374, 0.996399, -0.014801,
0.593842, 0.253143, -0.763672, 0.974976, -0.165466, 0.148285, 0.918976, 0.137299, 0.369537, 0.294952, 0.694977,
0.655731, 0.943085, 0.152618, -0.295319, 0.58783, -0.598236, 0.544495, 0.203796, 0.678223, 0.705994, -0.478821,
-0.661011, 0.577667, 0.719055, -0.1698, -0.673828, -0.132172, -0.965332, 0.225006, -0.981873, -0.14502, 0.121979,
0.763458, 0.579742, 0.284546, -0.893188, 0.079681, 0.442474, -0.795776, -0.523804, 0.303802, 0.734955, 0.67804,
-0.007446, 0.15506, 0.986267, -0.056183, 0.258026, 0.571503, -0.778931, -0.681549, -0.702087, -0.206116, -0.96286,
-0.177185, 0.203613, -0.470978, -0.515106, 0.716095, -0.740326, 0.57135, 0.354095, -0.56012, -0.824982, -0.074982,
-0.507874, 0.753204, 0.417969, -0.503113, 0.038147, 0.863342, 0.594025, 0.673553, -0.439758, -0.119873, -0.005524,
-0.992737, 0.098267, -0.213776, 0.971893, -0.615631, 0.643951, 0.454163, 0.896851, -0.441071, 0.032166, -0.555023,
0.750763, -0.358093, 0.398773, 0.304688, 0.864929, -0.722961, 0.303589, 0.620544, -0.63559, -0.621948, -0.457306,
-0.293243, 0.072327, 0.953278, -0.491638, 0.661041, -0.566772, -0.304199, -0.572083, -0.761688, 0.908081, -0.398956,
0.127014, -0.523621, -0.549683, -0.650848, -0.932922, -0.19986, 0.299408, 0.099426, 0.140869, 0.984985, -0.020325,
-0.999756, -0.002319, 0.952667, 0.280853, -0.11615, -0.971893, 0.082581, 0.220337, 0.65921, 0.705292, -0.260651,
0.733063, -0.175537, 0.657043, -0.555206, 0.429504, -0.712189, 0.400421, -0.89859, 0.179352, 0.750885, -0.19696,
0.630341, 0.785675, -0.569336, 0.241821, -0.058899, -0.464111, 0.883789, 0.129608, -0.94519, 0.299622, -0.357819,
0.907654, 0.219238, -0.842133, -0.439117, -0.312927, -0.313477, 0.84433, 0.434479, -0.241211, 0.053253, 0.968994,
0.063873, 0.823273, 0.563965, 0.476288, 0.862152, -0.172516, 0.620941, -0.298126, 0.724915, 0.25238, -0.749359,
-0.612122, -0.577545, 0.386566, 0.718994, -0.406342, -0.737976, 0.538696, 0.04718, 0.556305, 0.82959, -0.802856,
0.587463, 0.101166, -0.707733, -0.705963, 0.026428, 0.374908, 0.68457, 0.625092, 0.472137, 0.208405, -0.856506,
-0.703064, -0.581085, -0.409821, -0.417206, -0.736328, 0.532623, -0.447876, -0.20285, -0.870728, 0.086945,
-0.990417, 0.107086, 0.183685, 0.018341, -0.982788, 0.560638, -0.428864, 0.708282, 0.296722, -0.952576, -0.0672,
0.135773, 0.990265, 0.030243, -0.068787, 0.654724, 0.752686, 0.762604, -0.551758, 0.337585, -0.819611, -0.407684,
0.402466, -0.727844, -0.55072, -0.408539, -0.855774, -0.480011, 0.19281, 0.693176, -0.079285, 0.716339, 0.226013,
0.650116, -0.725433, 0.246704, 0.953369, -0.173553, -0.970398, -0.239227, -0.03244, 0.136383, -0.394318, 0.908752,
0.813232, 0.558167, 0.164368, 0.40451, 0.549042, -0.731323, -0.380249, -0.566711, 0.730865, 0.022156, 0.932739,
0.359741, 0.00824, 0.996552, -0.082306, 0.956635, -0.065338, -0.283722, -0.743561, 0.008209, 0.668579, -0.859589,
-0.509674, 0.035767, -0.852234, 0.363678, -0.375977, -0.201965, -0.970795, -0.12915, 0.313477, 0.947327, 0.06546,
-0.254028, -0.528259, 0.81015, 0.628052, 0.601105, 0.49411, -0.494385, 0.868378, 0.037933, 0.275635, -0.086426,
0.957336, -0.197937, 0.468903, -0.860748, 0.895599, 0.399384, 0.195801, 0.560791, 0.825012, -0.069214, 0.304199,
-0.849487, 0.43103, 0.096375, 0.93576, 0.339111, -0.051422, 0.408966, -0.911072, 0.330444, 0.942841, -0.042389,
-0.452362, -0.786407, 0.420563, 0.134308, -0.933472, -0.332489, 0.80191, -0.566711, -0.188934, -0.987946, -0.105988,
0.112518, -0.24408, 0.892242, -0.379791, -0.920502, 0.229095, -0.316376, 0.7789, 0.325958, 0.535706, -0.912872,
0.185211, -0.36377, -0.184784, 0.565369, -0.803833, -0.018463, 0.119537, 0.992615, -0.259247, -0.935608, 0.239532,
-0.82373, -0.449127, -0.345947, -0.433105, 0.659515, 0.614349, -0.822754, 0.378845, -0.423676, 0.687195, -0.674835,
-0.26889, -0.246582, -0.800842, 0.545715, -0.729187, -0.207794, 0.651978, 0.653534, -0.610443, -0.447388, 0.492584,
-0.023346, 0.869934, 0.609039, 0.009094, -0.79306, 0.962494, -0.271088, -0.00885, 0.2659, -0.004913, 0.963959,
0.651245, 0.553619, -0.518951, 0.280548, -0.84314, 0.458618, -0.175293, -0.983215, 0.049805, 0.035339, -0.979919,
0.196045, -0.982941, 0.164307, -0.082245, 0.233734, -0.97226, -0.005005, -0.747253, -0.611328, 0.260437, 0.645599,
0.592773, 0.481384, 0.117706, -0.949524, -0.29068, -0.535004, -0.791901, -0.294312, -0.627167, -0.214447, 0.748718,
-0.047974, -0.813477, -0.57959, -0.175537, 0.477264, -0.860992, 0.738556, -0.414246, -0.53183, 0.562561, -0.704071,
0.433289, -0.754944, 0.64801, -0.100586, 0.114716, 0.044525, -0.992371, 0.966003, 0.244873, -0.082764,
};
/**************************/
/* IMPROVED PERLIN NOISE */
/**************************/
static float lerp(float t, float a, float b)
{
return (a + t * (b - a));
}
static float npfade(float t)
{
return (t * t * t * (t * (t * 6.0f - 15.0f) + 10.0f));
}
static float grad(int hash_val, float x, float y, float z)
{
int h = hash_val & 15; /* CONVERT LO 4 BITS OF HASH CODE */
float u = h < 8 ? x : y, /* INTO 12 GRADIENT DIRECTIONS. */
v = h < 4 ? y : h == 12 || h == 14 ? x : z;
return ((h & 1) == 0 ? u : -u) + ((h & 2) == 0 ? v : -v);
}
/* instead of adding another permutation array, just use hash table defined above */
static float newPerlin(float x, float y, float z)
{
int A, AA, AB, B, BA, BB;
float u = floor(x), v = floor(y), w = floor(z);
int X = ((int)u) & 255, Y = ((int)v) & 255, Z = ((int)w) & 255; /* FIND UNIT CUBE THAT CONTAINS POINT */
x -= u; /* FIND RELATIVE X,Y,Z */
y -= v; /* OF POINT IN CUBE. */
z -= w;
u = npfade(x); /* COMPUTE FADE CURVES */
v = npfade(y); /* FOR EACH OF X,Y,Z. */
w = npfade(z);
A = hash[X ] + Y; AA = hash[A] + Z; AB = hash[A + 1] + Z; /* HASH COORDINATES OF */
B = hash[X + 1] + Y; BA = hash[B] + Z; BB = hash[B + 1] + Z; /* THE 8 CUBE CORNERS, */
return lerp(w, lerp(v, lerp(u, grad(hash[AA ], x, y, z ), /* AND ADD */
grad(hash[BA ], x - 1, y, z )), /* BLENDED */
lerp(u, grad(hash[AB ], x, y - 1, z ), /* RESULTS */
grad(hash[BB ], x - 1, y - 1, z ))), /* FROM 8 */
lerp(v, lerp(u, grad(hash[AA + 1], x, y, z - 1), /* CORNERS */
grad(hash[BA + 1], x - 1, y, z - 1)), /* OF CUBE */
lerp(u, grad(hash[AB + 1], x, y - 1, z - 1),
grad(hash[BB + 1], x - 1, y - 1, z - 1))));
}
/* for use with BLI_gNoise()/BLI_gTurbulence(), returns unsigned improved perlin noise */
static float newPerlinU(float x, float y, float z)
{
return (0.5f + 0.5f * newPerlin(x, y, z));
}
/**************************/
/* END OF IMPROVED PERLIN */
/**************************/
/* Was BLI_hnoise(), removed noisesize, so other functions can call it without scaling. */
static float orgBlenderNoise(float x, float y, float z)
{
register float cn1, cn2, cn3, cn4, cn5, cn6, i, *h;
float fx, fy, fz, ox, oy, oz, jx, jy, jz;
float n = 0.5;
int ix, iy, iz, b00, b01, b10, b11, b20, b21;
fx = floor(x);
fy = floor(y);
fz = floor(z);
ox = x - fx;
oy = y - fy;
oz = z - fz;
ix = (int)fx;
iy = (int)fy;
iz = (int)fz;
jx = ox - 1;
jy = oy - 1;
jz = oz - 1;
cn1 = ox * ox; cn2 = oy * oy; cn3 = oz * oz;
cn4 = jx * jx; cn5 = jy * jy; cn6 = jz * jz;
cn1 = 1.0f - 3.0f * cn1 + 2.0f * cn1 * ox;
cn2 = 1.0f - 3.0f * cn2 + 2.0f * cn2 * oy;
cn3 = 1.0f - 3.0f * cn3 + 2.0f * cn3 * oz;
cn4 = 1.0f - 3.0f * cn4 - 2.0f * cn4 * jx;
cn5 = 1.0f - 3.0f * cn5 - 2.0f * cn5 * jy;
cn6 = 1.0f - 3.0f * cn6 - 2.0f * cn6 * jz;
b00 = hash[hash[ix & 255] + (iy & 255)];
b10 = hash[hash[(ix + 1) & 255] + (iy & 255)];
b01 = hash[hash[ix & 255] + ((iy + 1) & 255)];
b11 = hash[hash[(ix + 1) & 255] + ((iy + 1) & 255)];
b20 = iz & 255; b21 = (iz + 1) & 255;
/* 0 */
i = (cn1 * cn2 * cn3);
h = hashvectf + 3 * hash[b20 + b00];
n += i * (h[0] * ox + h[1] * oy + h[2] * oz);
/* 1 */
i = (cn1 * cn2 * cn6);
h = hashvectf + 3 * hash[b21 + b00];
n += i * (h[0] * ox + h[1] * oy + h[2] * jz);
/* 2 */
i = (cn1 * cn5 * cn3);
h = hashvectf + 3 * hash[b20 + b01];
n += i * (h[0] * ox + h[1] * jy + h[2] * oz);
/* 3 */
i = (cn1 * cn5 * cn6);
h = hashvectf + 3 * hash[b21 + b01];
n += i * (h[0] * ox + h[1] * jy + h[2] * jz);
/* 4 */
i = cn4 * cn2 * cn3;
h = hashvectf + 3 * hash[b20 + b10];
n += i * (h[0] * jx + h[1] * oy + h[2] * oz);
/* 5 */
i = cn4 * cn2 * cn6;
h = hashvectf + 3 * hash[b21 + b10];
n += i * (h[0] * jx + h[1] * oy + h[2] * jz);
/* 6 */
i = cn4 * cn5 * cn3;
h = hashvectf + 3 * hash[b20 + b11];
n += i * (h[0] * jx + h[1] * jy + h[2] * oz);
/* 7 */
i = (cn4 * cn5 * cn6);
h = hashvectf + 3 * hash[b21 + b11];
n += i * (h[0] * jx + h[1] * jy + h[2] * jz);
if (n < 0.0f) n = 0.0f;
else if (n > 1.0f) n = 1.0f;
return n;
}
/* as orgBlenderNoise(), returning signed noise */
static float orgBlenderNoiseS(float x, float y, float z)
{
return (2.0f * orgBlenderNoise(x, y, z) - 1.0f);
}
/* separated from orgBlenderNoise above, with scaling */
float BLI_hnoise(float noisesize, float x, float y, float z)
{
if (noisesize == 0.0f) return 0.0f;
x = (1.0f + x) / noisesize;
y = (1.0f + y) / noisesize;
z = (1.0f + z) / noisesize;
return orgBlenderNoise(x, y, z);
}
/* original turbulence functions */
float BLI_turbulence(float noisesize, float x, float y, float z, int nr)
{
float s, d = 0.5, div = 1.0;
s = BLI_hnoise(noisesize, x, y, z);
while (nr > 0) {
s += d * BLI_hnoise(noisesize * d, x, y, z);
div += d;
d *= 0.5f;
nr--;
}
return s / div;
}
float BLI_turbulence1(float noisesize, float x, float y, float z, int nr)
{
float s, d = 0.5, div = 1.0;
s = fabsf((-1.0f + 2.0f * BLI_hnoise(noisesize, x, y, z)));
while (nr > 0) {
s += fabsf(d * (-1.0f + 2.0f * BLI_hnoise(noisesize * d, x, y, z)));
div += d;
d *= 0.5f;
nr--;
}
return s / div;
}
/* ********************* FROM PERLIN HIMSELF: ******************** */
static const char p[512 + 2] = {
0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE, 0xF3, 0x1C, 0x67, 0x28,
0x1D, 0xED, 0x0, 0xDE, 0x95, 0x2E, 0xDC, 0x3F, 0x3A, 0x82, 0x35, 0x4D,
0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC, 0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8,
0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83, 0xF2, 0x8F, 0x18, 0xC7,
0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8, 0x80, 0xB5, 0x40, 0x13,
0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D, 0x86, 0x4C, 0xC8, 0xDB,
0x7C, 0xD5, 0x25, 0x4E, 0x5A, 0x55, 0x74, 0x50, 0xCD, 0xB3, 0x7A, 0xBB,
0xC3, 0xCB, 0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98, 0xB, 0x96, 0xD3, 0x9E,
0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4, 0x24, 0x72, 0x49, 0x8C,
0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA, 0x1F, 0x1, 0xD7, 0x93,
0x11, 0xC1, 0x58, 0xA9, 0x31, 0xF9, 0x44, 0x6D, 0xBF, 0x33, 0x9C, 0x5F,
0x9, 0x94, 0xA3, 0x85, 0x6, 0xC6, 0x9A, 0x1E, 0x7B, 0x46, 0x15, 0x30,
0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F, 0x62, 0xAC, 0x4F, 0xC2,
0xC0, 0xE, 0xB1, 0x23, 0xA7, 0xDF, 0x47, 0xB0, 0x77, 0x69, 0x5, 0xE9,
0xE6, 0xE7, 0x76, 0x73, 0xF, 0xFE, 0x6E, 0x9B, 0x56, 0xEF, 0x12, 0xA5,
0x37, 0xFC, 0xAE, 0xD9, 0x3, 0x8E, 0xDD, 0x10, 0xB9, 0xCE, 0xC9, 0x8D,
0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4, 0xA, 0xCC, 0xD2, 0xE8,
0x43, 0x3D, 0x70, 0xB7, 0x2, 0x7D, 0x99, 0xD8, 0xD, 0x60, 0x8A, 0x4,
0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7, 0xE0, 0x29, 0xA6, 0xC5, 0xE3,
0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D, 0x21, 0xAD,
0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A, 0x45, 0x39, 0xCF, 0x75,
0xA4, 0x88, 0xFB, 0x5D, 0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE,
0xF3, 0x1C, 0x67, 0x28, 0x1D, 0xED, 0x0, 0xDE, 0x95, 0x2E, 0xDC, 0x3F,
0x3A, 0x82, 0x35, 0x4D, 0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC, 0x79, 0x32,
0xD1, 0x59, 0xF4, 0x8, 0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83,
0xF2, 0x8F, 0x18, 0xC7, 0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8,
0x80, 0xB5, 0x40, 0x13, 0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D,
0x86, 0x4C, 0xC8, 0xDB, 0x7C, 0xD5, 0x25, 0x4E, 0x5A, 0x55, 0x74, 0x50,
0xCD, 0xB3, 0x7A, 0xBB, 0xC3, 0xCB, 0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98,
0xB, 0x96, 0xD3, 0x9E, 0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4,
0x24, 0x72, 0x49, 0x8C, 0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA,
0x1F, 0x1, 0xD7, 0x93, 0x11, 0xC1, 0x58, 0xA9, 0x31, 0xF9, 0x44, 0x6D,
0xBF, 0x33, 0x9C, 0x5F, 0x9, 0x94, 0xA3, 0x85, 0x6, 0xC6, 0x9A, 0x1E,
0x7B, 0x46, 0x15, 0x30, 0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F,
0x62, 0xAC, 0x4F, 0xC2, 0xC0, 0xE, 0xB1, 0x23, 0xA7, 0xDF, 0x47, 0xB0,
0x77, 0x69, 0x5, 0xE9, 0xE6, 0xE7, 0x76, 0x73, 0xF, 0xFE, 0x6E, 0x9B,
0x56, 0xEF, 0x12, 0xA5, 0x37, 0xFC, 0xAE, 0xD9, 0x3, 0x8E, 0xDD, 0x10,
0xB9, 0xCE, 0xC9, 0x8D, 0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4,
0xA, 0xCC, 0xD2, 0xE8, 0x43, 0x3D, 0x70, 0xB7, 0x2, 0x7D, 0x99, 0xD8,
0xD, 0x60, 0x8A, 0x4, 0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7, 0xE0,
0x29, 0xA6, 0xC5, 0xE3, 0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E,
0x52, 0x2D, 0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A,
0x45, 0x39, 0xCF, 0x75, 0xA4, 0x88, 0xFB, 0x5D, 0xA2, 0xA0
};
static float g[512 + 2][3] = {
{0.33783, 0.715698, -0.611206},
{-0.944031, -0.326599, -0.045624},
{-0.101074, -0.416443, -0.903503},
{0.799286, 0.49411, -0.341949},
{-0.854645, 0.518036, 0.033936},
{0.42514, -0.437866, -0.792114},
{-0.358948, 0.597046, 0.717377},
{-0.985413, 0.144714, 0.089294},
{-0.601776, -0.33728, -0.723907},
{-0.449921, 0.594513, 0.666382},
{0.208313, -0.10791, 0.972076},
{0.575317, 0.060425, 0.815643},
{0.293365, -0.875702, -0.383453},
{0.293762, 0.465759, 0.834686},
{-0.846008, -0.233398, -0.47934},
{-0.115814, 0.143036, -0.98291},
{0.204681, -0.949036, -0.239532},
{0.946716, -0.263947, 0.184326},
{-0.235596, 0.573822, 0.784332},
{0.203705, -0.372253, -0.905487},
{0.756989, -0.651031, 0.055298},
{0.497803, 0.814697, -0.297363},
{-0.16214, 0.063995, -0.98468},
{-0.329254, 0.834381, 0.441925},
{0.703827, -0.527039, -0.476227},
{0.956421, 0.266113, 0.119781},
{0.480133, 0.482849, 0.7323},
{-0.18631, 0.961212, -0.203125},
{-0.748474, -0.656921, -0.090393},
{-0.085052, -0.165253, 0.982544},
{-0.76947, 0.628174, -0.115234},
{0.383148, 0.537659, 0.751068},
{0.616486, -0.668488, -0.415924},
{-0.259979, -0.630005, 0.73175},
{0.570953, -0.087952, 0.816223},
{-0.458008, 0.023254, 0.888611},
{-0.196167, 0.976563, -0.088287},
{-0.263885, -0.69812, -0.665527},
{0.437134, -0.892273, -0.112793},
{-0.621674, -0.230438, 0.748566},
{0.232422, 0.900574, -0.367249},
{0.22229, -0.796143, 0.562744},
{-0.665497, -0.73764, 0.11377},
{0.670135, 0.704803, 0.232605},
{0.895599, 0.429749, -0.114655},
{-0.11557, -0.474243, 0.872742},
{0.621826, 0.604004, -0.498444},
{-0.832214, 0.012756, 0.55426},
{-0.702484, 0.705994, -0.089661},
{-0.692017, 0.649292, 0.315399},
{-0.175995, -0.977997, 0.111877},
{0.096954, -0.04953, 0.994019},
{0.635284, -0.606689, -0.477783},
{-0.261261, -0.607422, -0.750153},
{0.983276, 0.165436, 0.075958},
{-0.29837, 0.404083, -0.864655},
{-0.638672, 0.507721, 0.578156},
{0.388214, 0.412079, 0.824249},
{0.556183, -0.208832, 0.804352},
{0.778442, 0.562012, 0.27951},
{-0.616577, 0.781921, -0.091522},
{0.196289, 0.051056, 0.979187},
{-0.121216, 0.207153, -0.970734},
{-0.173401, -0.384735, 0.906555},
{0.161499, -0.723236, -0.671387},
{0.178497, -0.006226, -0.983887},
{-0.126038, 0.15799, 0.97934},
{0.830475, -0.024811, 0.556458},
{-0.510132, -0.76944, 0.384247},
{0.81424, 0.200104, -0.544891},
{-0.112549, -0.393311, -0.912445},
{0.56189, 0.152222, -0.813049},
{0.198914, -0.254517, -0.946381},
{-0.41217, 0.690979, -0.593811},
{-0.407257, 0.324524, 0.853668},
{-0.690186, 0.366119, -0.624115},
{-0.428345, 0.844147, -0.322296},
{-0.21228, -0.297546, -0.930756},
{-0.273071, 0.516113, 0.811798},
{0.928314, 0.371643, 0.007233},
{0.785828, -0.479218, -0.390778},
{-0.704895, 0.058929, 0.706818},
{0.173248, 0.203583, 0.963562},
{0.422211, -0.904297, -0.062469},
{-0.363312, -0.182465, 0.913605},
{0.254028, -0.552307, -0.793945},
{-0.28891, -0.765747, -0.574554},
{0.058319, 0.291382, 0.954803},
{0.946136, -0.303925, 0.111267},
{-0.078156, 0.443695, -0.892731},
{0.182098, 0.89389, 0.409515},
{-0.680298, -0.213318, 0.701141},
{0.062469, 0.848389, -0.525635},
{-0.72879, -0.641846, 0.238342},
{-0.88089, 0.427673, 0.202637},
{-0.532501, -0.21405, 0.818878},
{0.948975, -0.305084, 0.07962},
{0.925446, 0.374664, 0.055817},
{0.820923, 0.565491, 0.079102},
{0.25882, 0.099792, -0.960724},
{-0.294617, 0.910522, 0.289978},
{0.137115, 0.320038, -0.937408},
{-0.908386, 0.345276, -0.235718},
{-0.936218, 0.138763, 0.322754},
{0.366577, 0.925934, -0.090637},
{0.309296, -0.686829, -0.657684},
{0.66983, 0.024445, 0.742065},
{-0.917999, -0.059113, -0.392059},
{0.365509, 0.462158, -0.807922},
{0.083374, 0.996399, -0.014801},
{0.593842, 0.253143, -0.763672},
{0.974976, -0.165466, 0.148285},
{0.918976, 0.137299, 0.369537},
{0.294952, 0.694977, 0.655731},
{0.943085, 0.152618, -0.295319},
{0.58783, -0.598236, 0.544495},
{0.203796, 0.678223, 0.705994},
{-0.478821, -0.661011, 0.577667},
{0.719055, -0.1698, -0.673828},
{-0.132172, -0.965332, 0.225006},
{-0.981873, -0.14502, 0.121979},
{0.763458, 0.579742, 0.284546},
{-0.893188, 0.079681, 0.442474},
{-0.795776, -0.523804, 0.303802},
{0.734955, 0.67804, -0.007446},
{0.15506, 0.986267, -0.056183},
{0.258026, 0.571503, -0.778931},
{-0.681549, -0.702087, -0.206116},
{-0.96286, -0.177185, 0.203613},
{-0.470978, -0.515106, 0.716095},
{-0.740326, 0.57135, 0.354095},
{-0.56012, -0.824982, -0.074982},
{-0.507874, 0.753204, 0.417969},
{-0.503113, 0.038147, 0.863342},
{0.594025, 0.673553, -0.439758},
{-0.119873, -0.005524, -0.992737},
{0.098267, -0.213776, 0.971893},
{-0.615631, 0.643951, 0.454163},
{0.896851, -0.441071, 0.032166},
{-0.555023, 0.750763, -0.358093},
{0.398773, 0.304688, 0.864929},
{-0.722961, 0.303589, 0.620544},
{-0.63559, -0.621948, -0.457306},
{-0.293243, 0.072327, 0.953278},
{-0.491638, 0.661041, -0.566772},
{-0.304199, -0.572083, -0.761688},
{0.908081, -0.398956, 0.127014},
{-0.523621, -0.549683, -0.650848},
{-0.932922, -0.19986, 0.299408},
{0.099426, 0.140869, 0.984985},
{-0.020325, -0.999756, -0.002319},
{0.952667, 0.280853, -0.11615},
{-0.971893, 0.082581, 0.220337},
{0.65921, 0.705292, -0.260651},
{0.733063, -0.175537, 0.657043},
{-0.555206, 0.429504, -0.712189},
{0.400421, -0.89859, 0.179352},
{0.750885, -0.19696, 0.630341},
{0.785675, -0.569336, 0.241821},
{-0.058899, -0.464111, 0.883789},
{0.129608, -0.94519, 0.299622},
{-0.357819, 0.907654, 0.219238},
{-0.842133, -0.439117, -0.312927},
{-0.313477, 0.84433, 0.434479},
{-0.241211, 0.053253, 0.968994},
{0.063873, 0.823273, 0.563965},
{0.476288, 0.862152, -0.172516},
{0.620941, -0.298126, 0.724915},
{0.25238, -0.749359, -0.612122},
{-0.577545, 0.386566, 0.718994},
{-0.406342, -0.737976, 0.538696},
{0.04718, 0.556305, 0.82959},
{-0.802856, 0.587463, 0.101166},
{-0.707733, -0.705963, 0.026428},
{0.374908, 0.68457, 0.625092},
{0.472137, 0.208405, -0.856506},
{-0.703064, -0.581085, -0.409821},
{-0.417206, -0.736328, 0.532623},
{-0.447876, -0.20285, -0.870728},
{0.086945, -0.990417, 0.107086},
{0.183685, 0.018341, -0.982788},
{0.560638, -0.428864, 0.708282},
{0.296722, -0.952576, -0.0672},
{0.135773, 0.990265, 0.030243},
{-0.068787, 0.654724, 0.752686},
{0.762604, -0.551758, 0.337585},
{-0.819611, -0.407684, 0.402466},
{-0.727844, -0.55072, -0.408539},
{-0.855774, -0.480011, 0.19281},
{0.693176, -0.079285, 0.716339},
{0.226013, 0.650116, -0.725433},
{0.246704, 0.953369, -0.173553},
{-0.970398, -0.239227, -0.03244},
{0.136383, -0.394318, 0.908752},
{0.813232, 0.558167, 0.164368},
{0.40451, 0.549042, -0.731323},
{-0.380249, -0.566711, 0.730865},
{0.022156, 0.932739, 0.359741},
{0.00824, 0.996552, -0.082306},
{0.956635, -0.065338, -0.283722},
{-0.743561, 0.008209, 0.668579},
{-0.859589, -0.509674, 0.035767},
{-0.852234, 0.363678, -0.375977},
{-0.201965, -0.970795, -0.12915},
{0.313477, 0.947327, 0.06546},
{-0.254028, -0.528259, 0.81015},
{0.628052, 0.601105, 0.49411},
{-0.494385, 0.868378, 0.037933},
{0.275635, -0.086426, 0.957336},
{-0.197937, 0.468903, -0.860748},
{0.895599, 0.399384, 0.195801},
{0.560791, 0.825012, -0.069214},
{0.304199, -0.849487, 0.43103},
{0.096375, 0.93576, 0.339111},
{-0.051422, 0.408966, -0.911072},
{0.330444, 0.942841, -0.042389},
{-0.452362, -0.786407, 0.420563},
{0.134308, -0.933472, -0.332489},
{0.80191, -0.566711, -0.188934},
{-0.987946, -0.105988, 0.112518},
{-0.24408, 0.892242, -0.379791},
{-0.920502, 0.229095, -0.316376},
{0.7789, 0.325958, 0.535706},
{-0.912872, 0.185211, -0.36377},
{-0.184784, 0.565369, -0.803833},
{-0.018463, 0.119537, 0.992615},
{-0.259247, -0.935608, 0.239532},
{-0.82373, -0.449127, -0.345947},
{-0.433105, 0.659515, 0.614349},
{-0.822754, 0.378845, -0.423676},
{0.687195, -0.674835, -0.26889},
{-0.246582, -0.800842, 0.545715},
{-0.729187, -0.207794, 0.651978},
{0.653534, -0.610443, -0.447388},
{0.492584, -0.023346, 0.869934},
{0.609039, 0.009094, -0.79306},
{0.962494, -0.271088, -0.00885},
{0.2659, -0.004913, 0.963959},
{0.651245, 0.553619, -0.518951},
{0.280548, -0.84314, 0.458618},
{-0.175293, -0.983215, 0.049805},
{0.035339, -0.979919, 0.196045},
{-0.982941, 0.164307, -0.082245},
{0.233734, -0.97226, -0.005005},
{-0.747253, -0.611328, 0.260437},
{0.645599, 0.592773, 0.481384},
{0.117706, -0.949524, -0.29068},
{-0.535004, -0.791901, -0.294312},
{-0.627167, -0.214447, 0.748718},
{-0.047974, -0.813477, -0.57959},
{-0.175537, 0.477264, -0.860992},
{0.738556, -0.414246, -0.53183},
{0.562561, -0.704071, 0.433289},
{-0.754944, 0.64801, -0.100586},
{0.114716, 0.044525, -0.992371},
{0.966003, 0.244873, -0.082764},
{0.33783, 0.715698, -0.611206},
{-0.944031, -0.326599, -0.045624},
{-0.101074, -0.416443, -0.903503},
{0.799286, 0.49411, -0.341949},
{-0.854645, 0.518036, 0.033936},
{0.42514, -0.437866, -0.792114},
{-0.358948, 0.597046, 0.717377},
{-0.985413, 0.144714, 0.089294},
{-0.601776, -0.33728, -0.723907},
{-0.449921, 0.594513, 0.666382},
{0.208313, -0.10791, 0.972076},
{0.575317, 0.060425, 0.815643},
{0.293365, -0.875702, -0.383453},
{0.293762, 0.465759, 0.834686},
{-0.846008, -0.233398, -0.47934},
{-0.115814, 0.143036, -0.98291},
{0.204681, -0.949036, -0.239532},
{0.946716, -0.263947, 0.184326},
{-0.235596, 0.573822, 0.784332},
{0.203705, -0.372253, -0.905487},
{0.756989, -0.651031, 0.055298},
{0.497803, 0.814697, -0.297363},
{-0.16214, 0.063995, -0.98468},
{-0.329254, 0.834381, 0.441925},
{0.703827, -0.527039, -0.476227},
{0.956421, 0.266113, 0.119781},
{0.480133, 0.482849, 0.7323},
{-0.18631, 0.961212, -0.203125},
{-0.748474, -0.656921, -0.090393},
{-0.085052, -0.165253, 0.982544},
{-0.76947, 0.628174, -0.115234},
{0.383148, 0.537659, 0.751068},
{0.616486, -0.668488, -0.415924},
{-0.259979, -0.630005, 0.73175},
{0.570953, -0.087952, 0.816223},
{-0.458008, 0.023254, 0.888611},
{-0.196167, 0.976563, -0.088287},
{-0.263885, -0.69812, -0.665527},
{0.437134, -0.892273, -0.112793},
{-0.621674, -0.230438, 0.748566},
{0.232422, 0.900574, -0.367249},
{0.22229, -0.796143, 0.562744},
{-0.665497, -0.73764, 0.11377},
{0.670135, 0.704803, 0.232605},
{0.895599, 0.429749, -0.114655},
{-0.11557, -0.474243, 0.872742},
{0.621826, 0.604004, -0.498444},
{-0.832214, 0.012756, 0.55426},
{-0.702484, 0.705994, -0.089661},
{-0.692017, 0.649292, 0.315399},
{-0.175995, -0.977997, 0.111877},
{0.096954, -0.04953, 0.994019},
{0.635284, -0.606689, -0.477783},
{-0.261261, -0.607422, -0.750153},
{0.983276, 0.165436, 0.075958},
{-0.29837, 0.404083, -0.864655},
{-0.638672, 0.507721, 0.578156},
{0.388214, 0.412079, 0.824249},
{0.556183, -0.208832, 0.804352},
{0.778442, 0.562012, 0.27951},
{-0.616577, 0.781921, -0.091522},
{0.196289, 0.051056, 0.979187},
{-0.121216, 0.207153, -0.970734},
{-0.173401, -0.384735, 0.906555},
{0.161499, -0.723236, -0.671387},
{0.178497, -0.006226, -0.983887},
{-0.126038, 0.15799, 0.97934},
{0.830475, -0.024811, 0.556458},
{-0.510132, -0.76944, 0.384247},
{0.81424, 0.200104, -0.544891},
{-0.112549, -0.393311, -0.912445},
{0.56189, 0.152222, -0.813049},
{0.198914, -0.254517, -0.946381},
{-0.41217, 0.690979, -0.593811},
{-0.407257, 0.324524, 0.853668},
{-0.690186, 0.366119, -0.624115},
{-0.428345, 0.844147, -0.322296},
{-0.21228, -0.297546, -0.930756},
{-0.273071, 0.516113, 0.811798},
{0.928314, 0.371643, 0.007233},
{0.785828, -0.479218, -0.390778},
{-0.704895, 0.058929, 0.706818},
{0.173248, 0.203583, 0.963562},
{0.422211, -0.904297, -0.062469},
{-0.363312, -0.182465, 0.913605},
{0.254028, -0.552307, -0.793945},
{-0.28891, -0.765747, -0.574554},
{0.058319, 0.291382, 0.954803},
{0.946136, -0.303925, 0.111267},
{-0.078156, 0.443695, -0.892731},
{0.182098, 0.89389, 0.409515},
{-0.680298, -0.213318, 0.701141},
{0.062469, 0.848389, -0.525635},
{-0.72879, -0.641846, 0.238342},
{-0.88089, 0.427673, 0.202637},
{-0.532501, -0.21405, 0.818878},
{0.948975, -0.305084, 0.07962},
{0.925446, 0.374664, 0.055817},
{0.820923, 0.565491, 0.079102},
{0.25882, 0.099792, -0.960724},
{-0.294617, 0.910522, 0.289978},
{0.137115, 0.320038, -0.937408},
{-0.908386, 0.345276, -0.235718},
{-0.936218, 0.138763, 0.322754},
{0.366577, 0.925934, -0.090637},
{0.309296, -0.686829, -0.657684},
{0.66983, 0.024445, 0.742065},
{-0.917999, -0.059113, -0.392059},
{0.365509, 0.462158, -0.807922},
{0.083374, 0.996399, -0.014801},
{0.593842, 0.253143, -0.763672},
{0.974976, -0.165466, 0.148285},
{0.918976, 0.137299, 0.369537},
{0.294952, 0.694977, 0.655731},
{0.943085, 0.152618, -0.295319},
{0.58783, -0.598236, 0.544495},
{0.203796, 0.678223, 0.705994},
{-0.478821, -0.661011, 0.577667},
{0.719055, -0.1698, -0.673828},
{-0.132172, -0.965332, 0.225006},
{-0.981873, -0.14502, 0.121979},
{0.763458, 0.579742, 0.284546},
{-0.893188, 0.079681, 0.442474},
{-0.795776, -0.523804, 0.303802},
{0.734955, 0.67804, -0.007446},
{0.15506, 0.986267, -0.056183},
{0.258026, 0.571503, -0.778931},
{-0.681549, -0.702087, -0.206116},
{-0.96286, -0.177185, 0.203613},
{-0.470978, -0.515106, 0.716095},
{-0.740326, 0.57135, 0.354095},
{-0.56012, -0.824982, -0.074982},
{-0.507874, 0.753204, 0.417969},
{-0.503113, 0.038147, 0.863342},
{0.594025, 0.673553, -0.439758},
{-0.119873, -0.005524, -0.992737},
{0.098267, -0.213776, 0.971893},
{-0.615631, 0.643951, 0.454163},
{0.896851, -0.441071, 0.032166},
{-0.555023, 0.750763, -0.358093},
{0.398773, 0.304688, 0.864929},
{-0.722961, 0.303589, 0.620544},
{-0.63559, -0.621948, -0.457306},
{-0.293243, 0.072327, 0.953278},
{-0.491638, 0.661041, -0.566772},
{-0.304199, -0.572083, -0.761688},
{0.908081, -0.398956, 0.127014},
{-0.523621, -0.549683, -0.650848},
{-0.932922, -0.19986, 0.299408},
{0.099426, 0.140869, 0.984985},
{-0.020325, -0.999756, -0.002319},
{0.952667, 0.280853, -0.11615},
{-0.971893, 0.082581, 0.220337},
{0.65921, 0.705292, -0.260651},
{0.733063, -0.175537, 0.657043},
{-0.555206, 0.429504, -0.712189},
{0.400421, -0.89859, 0.179352},
{0.750885, -0.19696, 0.630341},
{0.785675, -0.569336, 0.241821},
{-0.058899, -0.464111, 0.883789},
{0.129608, -0.94519, 0.299622},
{-0.357819, 0.907654, 0.219238},
{-0.842133, -0.439117, -0.312927},
{-0.313477, 0.84433, 0.434479},
{-0.241211, 0.053253, 0.968994},
{0.063873, 0.823273, 0.563965},
{0.476288, 0.862152, -0.172516},
{0.620941, -0.298126, 0.724915},
{0.25238, -0.749359, -0.612122},
{-0.577545, 0.386566, 0.718994},
{-0.406342, -0.737976, 0.538696},
{0.04718, 0.556305, 0.82959},
{-0.802856, 0.587463, 0.101166},
{-0.707733, -0.705963, 0.026428},
{0.374908, 0.68457, 0.625092},
{0.472137, 0.208405, -0.856506},
{-0.703064, -0.581085, -0.409821},
{-0.417206, -0.736328, 0.532623},
{-0.447876, -0.20285, -0.870728},
{0.086945, -0.990417, 0.107086},
{0.183685, 0.018341, -0.982788},
{0.560638, -0.428864, 0.708282},
{0.296722, -0.952576, -0.0672},
{0.135773, 0.990265, 0.030243},
{-0.068787, 0.654724, 0.752686},
{0.762604, -0.551758, 0.337585},
{-0.819611, -0.407684, 0.402466},
{-0.727844, -0.55072, -0.408539},
{-0.855774, -0.480011, 0.19281},
{0.693176, -0.079285, 0.716339},
{0.226013, 0.650116, -0.725433},
{0.246704, 0.953369, -0.173553},
{-0.970398, -0.239227, -0.03244},
{0.136383, -0.394318, 0.908752},
{0.813232, 0.558167, 0.164368},
{0.40451, 0.549042, -0.731323},
{-0.380249, -0.566711, 0.730865},
{0.022156, 0.932739, 0.359741},
{0.00824, 0.996552, -0.082306},
{0.956635, -0.065338, -0.283722},
{-0.743561, 0.008209, 0.668579},
{-0.859589, -0.509674, 0.035767},
{-0.852234, 0.363678, -0.375977},
{-0.201965, -0.970795, -0.12915},
{0.313477, 0.947327, 0.06546},
{-0.254028, -0.528259, 0.81015},
{0.628052, 0.601105, 0.49411},
{-0.494385, 0.868378, 0.037933},
{0.275635, -0.086426, 0.957336},
{-0.197937, 0.468903, -0.860748},
{0.895599, 0.399384, 0.195801},
{0.560791, 0.825012, -0.069214},
{0.304199, -0.849487, 0.43103},
{0.096375, 0.93576, 0.339111},
{-0.051422, 0.408966, -0.911072},
{0.330444, 0.942841, -0.042389},
{-0.452362, -0.786407, 0.420563},
{0.134308, -0.933472, -0.332489},
{0.80191, -0.566711, -0.188934},
{-0.987946, -0.105988, 0.112518},
{-0.24408, 0.892242, -0.379791},
{-0.920502, 0.229095, -0.316376},
{0.7789, 0.325958, 0.535706},
{-0.912872, 0.185211, -0.36377},
{-0.184784, 0.565369, -0.803833},
{-0.018463, 0.119537, 0.992615},
{-0.259247, -0.935608, 0.239532},
{-0.82373, -0.449127, -0.345947},
{-0.433105, 0.659515, 0.614349},
{-0.822754, 0.378845, -0.423676},
{0.687195, -0.674835, -0.26889},
{-0.246582, -0.800842, 0.545715},
{-0.729187, -0.207794, 0.651978},
{0.653534, -0.610443, -0.447388},
{0.492584, -0.023346, 0.869934},
{0.609039, 0.009094, -0.79306},
{0.962494, -0.271088, -0.00885},
{0.2659, -0.004913, 0.963959},
{0.651245, 0.553619, -0.518951},
{0.280548, -0.84314, 0.458618},
{-0.175293, -0.983215, 0.049805},
{0.035339, -0.979919, 0.196045},
{-0.982941, 0.164307, -0.082245},
{0.233734, -0.97226, -0.005005},
{-0.747253, -0.611328, 0.260437},
{0.645599, 0.592773, 0.481384},
{0.117706, -0.949524, -0.29068},
{-0.535004, -0.791901, -0.294312},
{-0.627167, -0.214447, 0.748718},
{-0.047974, -0.813477, -0.57959},
{-0.175537, 0.477264, -0.860992},
{0.738556, -0.414246, -0.53183},
{0.562561, -0.704071, 0.433289},
{-0.754944, 0.64801, -0.100586},
{0.114716, 0.044525, -0.992371},
{0.966003, 0.244873, -0.082764},
{0.33783, 0.715698, -0.611206},
{-0.944031, -0.326599, -0.045624},
};
#define SETUP(val, b0, b1, r0, r1) \
{ \
t = val + 10000.0f; \
b0 = ((int)t) & 255; \
b1 = (b0 + 1) & 255; \
r0 = t - floorf(t); \
r1 = r0 - 1.0f; \
} (void)0
static float noise3_perlin(float vec[3])
{
int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11;
float rx0, rx1, ry0, ry1, rz0, rz1, *q, sx, sy, sz, a, b, c, d, t, u, v;
register int i, j;
SETUP(vec[0], bx0, bx1, rx0, rx1);
SETUP(vec[1], by0, by1, ry0, ry1);
SETUP(vec[2], bz0, bz1, rz0, rz1);
i = p[bx0];
j = p[bx1];
b00 = p[i + by0];
b10 = p[j + by0];
b01 = p[i + by1];
b11 = p[j + by1];
#define VALUE_AT(rx, ry, rz) (rx * q[0] + ry * q[1] + rz * q[2])
#define SURVE(t) (t * t * (3.0f - 2.0f * t))
/* lerp moved to improved perlin above */
sx = SURVE(rx0);
sy = SURVE(ry0);
sz = SURVE(rz0);
q = g[b00 + bz0];
u = VALUE_AT(rx0, ry0, rz0);
q = g[b10 + bz0];
v = VALUE_AT(rx1, ry0, rz0);
a = lerp(sx, u, v);
q = g[b01 + bz0];
u = VALUE_AT(rx0, ry1, rz0);
q = g[b11 + bz0];
v = VALUE_AT(rx1, ry1, rz0);
b = lerp(sx, u, v);
c = lerp(sy, a, b); /* interpolate in y at lo x */
q = g[b00 + bz1];
u = VALUE_AT(rx0, ry0, rz1);
q = g[b10 + bz1];
v = VALUE_AT(rx1, ry0, rz1);
a = lerp(sx, u, v);
q = g[b01 + bz1];
u = VALUE_AT(rx0, ry1, rz1);
q = g[b11 + bz1];
v = VALUE_AT(rx1, ry1, rz1);
b = lerp(sx, u, v);
d = lerp(sy, a, b); /* interpolate in y at hi x */
return 1.5f * lerp(sz, c, d); /* interpolate in z */
#undef VALUE_AT
#undef SURVE
}
#if 0
static float turbulence_perlin(float *point, float lofreq, float hifreq)
{
float freq, t, p[3];
p[0] = point[0] + 123.456;
p[1] = point[1];
p[2] = point[2];
t = 0;
for (freq = lofreq; freq < hifreq; freq *= 2.0) {
t += fabsf(noise3_perlin(p)) / freq;
p[0] *= 2.0f;
p[1] *= 2.0f;
p[2] *= 2.0f;
}
return t - 0.3; /* readjust to make mean value = 0.0 */
}
#endif
/* for use with BLI_gNoise/gTurbulence, returns signed noise */
static float orgPerlinNoise(float x, float y, float z)
{
float v[3];
v[0] = x;
v[1] = y;
v[2] = z;
return noise3_perlin(v);
}
/* for use with BLI_gNoise/gTurbulence, returns unsigned noise */
static float orgPerlinNoiseU(float x, float y, float z)
{
float v[3];
v[0] = x;
v[1] = y;
v[2] = z;
return (0.5f + 0.5f * noise3_perlin(v));
}
/* *************** CALL AS: *************** */
float BLI_hnoisep(float noisesize, float x, float y, float z)
{
float vec[3];
vec[0] = x / noisesize;
vec[1] = y / noisesize;
vec[2] = z / noisesize;
return noise3_perlin(vec);
}
#if 0
static float turbulencep(float noisesize, float x, float y, float z, int nr)
{
float vec[3];
vec[0] = x / noisesize;
vec[1] = y / noisesize;
vec[2] = z / noisesize;
nr++;
return turbulence_perlin(vec, 1.0, (float)(1 << nr));
}
#endif
/******************/
/* VORONOI/WORLEY */
/******************/
/* distance metrics for voronoi, e parameter only used in Minkowski */
/* Camberra omitted, didn't seem useful */
/* distance squared */
static float dist_Squared(float x, float y, float z, float e)
{
(void)e; return (x * x + y * y + z * z);
}
/* real distance */
static float dist_Real(float x, float y, float z, float e)
{
(void)e; return sqrtf(x * x + y * y + z * z);
}
/* manhattan/taxicab/cityblock distance */
static float dist_Manhattan(float x, float y, float z, float e)
{
(void)e; return (fabsf(x) + fabsf(y) + fabsf(z));
}
/* Chebychev */
static float dist_Chebychev(float x, float y, float z, float e)
{
float t;
(void)e;
x = fabsf(x);
y = fabsf(y);
z = fabsf(z);
t = (x > y) ? x : y;
return ((z > t) ? z : t);
}
/* minkowski preset exponent 0.5 */
static float dist_MinkovskyH(float x, float y, float z, float e)
{
float d = sqrtf(fabsf(x)) + sqrtf(fabsf(y)) + sqrtf(fabsf(z));
(void)e;
return (d * d);
}
/* minkowski preset exponent 4 */
static float dist_Minkovsky4(float x, float y, float z, float e)
{
(void)e;
x *= x;
y *= y;
z *= z;
return sqrtf(sqrtf(x * x + y * y + z * z));
}
/* Minkowski, general case, slow, maybe too slow to be useful */
static float dist_Minkovsky(float x, float y, float z, float e)
{
return powf(powf(fabsf(x), e) + powf(fabsf(y), e) + powf(fabsf(z), e), 1.0f / e);
}
/* Not 'pure' Worley, but the results are virtually the same.
* Returns distances in da and point coords in pa */
void voronoi(float x, float y, float z, float *da, float *pa, float me, int dtype)
{
int xx, yy, zz, xi, yi, zi;
float xd, yd, zd, d, *p;
float (*distfunc)(float, float, float, float);
switch (dtype) {
case 1:
distfunc = dist_Squared;
break;
case 2:
distfunc = dist_Manhattan;
break;
case 3:
distfunc = dist_Chebychev;
break;
case 4:
distfunc = dist_MinkovskyH;
break;
case 5:
distfunc = dist_Minkovsky4;
break;
case 6:
distfunc = dist_Minkovsky;
break;
case 0:
default:
distfunc = dist_Real;
}
xi = (int)(floor(x));
yi = (int)(floor(y));
zi = (int)(floor(z));
da[0] = da[1] = da[2] = da[3] = 1e10f;
for (xx = xi - 1; xx <= xi + 1; xx++) {
for (yy = yi - 1; yy <= yi + 1; yy++) {
for (zz = zi - 1; zz <= zi + 1; zz++) {
p = HASHPNT(xx, yy, zz);
xd = x - (p[0] + xx);
yd = y - (p[1] + yy);
zd = z - (p[2] + zz);
d = distfunc(xd, yd, zd, me);
if (d < da[0]) {
da[3] = da[2]; da[2] = da[1]; da[1] = da[0]; da[0] = d;
pa[9] = pa[6]; pa[10] = pa[7]; pa[11] = pa[8];
pa[6] = pa[3]; pa[7] = pa[4]; pa[8] = pa[5];
pa[3] = pa[0]; pa[4] = pa[1]; pa[5] = pa[2];
pa[0] = p[0] + xx; pa[1] = p[1] + yy; pa[2] = p[2] + zz;
}
else if (d < da[1]) {
da[3] = da[2]; da[2] = da[1]; da[1] = d;
pa[9] = pa[6]; pa[10] = pa[7]; pa[11] = pa[8];
pa[6] = pa[3]; pa[7] = pa[4]; pa[8] = pa[5];
pa[3] = p[0] + xx; pa[4] = p[1] + yy; pa[5] = p[2] + zz;
}
else if (d < da[2]) {
da[3] = da[2]; da[2] = d;
pa[9] = pa[6]; pa[10] = pa[7]; pa[11] = pa[8];
pa[6] = p[0] + xx; pa[7] = p[1] + yy; pa[8] = p[2] + zz;
}
else if (d < da[3]) {
da[3] = d;
pa[9] = p[0] + xx; pa[10] = p[1] + yy; pa[11] = p[2] + zz;
}
}
}
}
}
/* returns different feature points for use in BLI_gNoise() */
static float voronoi_F1(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return da[0];
}
static float voronoi_F2(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return da[1];
}
static float voronoi_F3(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return da[2];
}
static float voronoi_F4(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return da[3];
}
static float voronoi_F1F2(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (da[1] - da[0]);
}
/* Crackle type pattern, just a scale/clamp of F2-F1 */
static float voronoi_Cr(float x, float y, float z)
{
float t = 10 * voronoi_F1F2(x, y, z);
if (t > 1.f) return 1.f;
return t;
}
/* Signed version of all 6 of the above, just 2x-1, not really correct though (range is potentially (0, sqrt(6)).
* Used in the musgrave functions */
static float voronoi_F1S(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (2.0f * da[0] - 1.0f);
}
static float voronoi_F2S(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (2.0f * da[1] - 1.0f);
}
static float voronoi_F3S(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (2.0f * da[2] - 1.0f);
}
static float voronoi_F4S(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (2.0f * da[3] - 1.0f);
}
static float voronoi_F1F2S(float x, float y, float z)
{
float da[4], pa[12];
voronoi(x, y, z, da, pa, 1, 0);
return (2.0f * (da[1] - da[0]) - 1.0f);
}
/* Crackle type pattern, just a scale/clamp of F2-F1 */
static float voronoi_CrS(float x, float y, float z)
{
float t = 10 * voronoi_F1F2(x, y, z);
if (t > 1.f) return 1.f;
return (2.0f * t - 1.0f);
}
/***************/
/* voronoi end */
/***************/
/*************/
/* CELLNOISE */
/*************/
/* returns unsigned cellnoise */
static float cellNoiseU(float x, float y, float z)
{
int xi = (int)(floor(x));
int yi = (int)(floor(y));
int zi = (int)(floor(z));
unsigned int n = xi + yi * 1301 + zi * 314159;
n ^= (n << 13);
return ((float)(n * (n * n * 15731 + 789221) + 1376312589) / 4294967296.0f);
}
/* idem, signed */
float cellNoise(float x, float y, float z)
{
return (2.0f * cellNoiseU(x, y, z) - 1.0f);
}
/* returns a vector/point/color in ca, using point hasharray directly */
void cellNoiseV(float x, float y, float z, float *ca)
{
int xi = (int)(floor(x));
int yi = (int)(floor(y));
int zi = (int)(floor(z));
float *p = HASHPNT(xi, yi, zi);
ca[0] = p[0];
ca[1] = p[1];
ca[2] = p[2];
}
/*****************/
/* end cellnoise */
/*****************/
/* newnoise: generic noise function for use with different noisebases */
float BLI_gNoise(float noisesize, float x, float y, float z, int hard, int noisebasis)
{
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoiseU;
break;
case 2:
noisefunc = newPerlinU;
break;
case 3:
noisefunc = voronoi_F1;
break;
case 4:
noisefunc = voronoi_F2;
break;
case 5:
noisefunc = voronoi_F3;
break;
case 6:
noisefunc = voronoi_F4;
break;
case 7:
noisefunc = voronoi_F1F2;
break;
case 8:
noisefunc = voronoi_Cr;
break;
case 14:
noisefunc = cellNoiseU;
break;
case 0:
default:
{
noisefunc = orgBlenderNoise;
/* add one to make return value same as BLI_hnoise */
x += 1;
y += 1;
z += 1;
}
}
if (noisesize != 0.0f) {
noisesize = 1.0f / noisesize;
x *= noisesize;
y *= noisesize;
z *= noisesize;
}
if (hard) return fabsf(2.0f * noisefunc(x, y, z) - 1.0f);
return noisefunc(x, y, z);
}
/* newnoise: generic turbulence function for use with different noisebasis */
float BLI_gTurbulence(float noisesize, float x, float y, float z, int oct, int hard, int noisebasis)
{
float (*noisefunc)(float, float, float);
float sum, t, amp = 1, fscale = 1;
int i;
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoiseU;
break;
case 2:
noisefunc = newPerlinU;
break;
case 3:
noisefunc = voronoi_F1;
break;
case 4:
noisefunc = voronoi_F2;
break;
case 5:
noisefunc = voronoi_F3;
break;
case 6:
noisefunc = voronoi_F4;
break;
case 7:
noisefunc = voronoi_F1F2;
break;
case 8:
noisefunc = voronoi_Cr;
break;
case 14:
noisefunc = cellNoiseU;
break;
case 0:
default:
noisefunc = orgBlenderNoise;
x += 1;
y += 1;
z += 1;
}
if (noisesize != 0.0f) {
noisesize = 1.0f / noisesize;
x *= noisesize;
y *= noisesize;
z *= noisesize;
}
sum = 0;
for (i = 0; i <= oct; i++, amp *= 0.5f, fscale *= 2.0f) {
t = noisefunc(fscale * x, fscale * y, fscale * z);
if (hard) t = fabsf(2.0f * t - 1.0f);
sum += t * amp;
}
sum *= ((float)(1 << oct) / (float)((1 << (oct + 1)) - 1));
return sum;
}
/*
* The following code is based on Ken Musgrave's explanations and sample
* source code in the book "Texturing and Modelling: A procedural approach"
*/
/*
* Procedural fBm evaluated at "point"; returns value stored in "value".
*
* Parameters:
* ``H'' is the fractal increment parameter
* ``lacunarity'' is the gap between successive frequencies
* ``octaves'' is the number of frequencies in the fBm
*/
float mg_fBm(float x, float y, float z, float H, float lacunarity, float octaves, int noisebasis)
{
float rmd, value = 0.0, pwr = 1.0, pwHL = powf(lacunarity, -H);
int i;
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoise;
break;
case 2:
noisefunc = newPerlin;
break;
case 3:
noisefunc = voronoi_F1S;
break;
case 4:
noisefunc = voronoi_F2S;
break;
case 5:
noisefunc = voronoi_F3S;
break;
case 6:
noisefunc = voronoi_F4S;
break;
case 7:
noisefunc = voronoi_F1F2S;
break;
case 8:
noisefunc = voronoi_CrS;
break;
case 14:
noisefunc = cellNoise;
break;
case 0:
default:
{
noisefunc = orgBlenderNoiseS;
}
}
for (i = 0; i < (int)octaves; i++) {
value += noisefunc(x, y, z) * pwr;
pwr *= pwHL;
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
}
rmd = octaves - floorf(octaves);
if (rmd != 0.f) value += rmd * noisefunc(x, y, z) * pwr;
return value;
} /* fBm() */
/*
* Procedural multifractal evaluated at "point";
* returns value stored in "value".
*
* Parameters:
* ``H'' determines the highest fractal dimension
* ``lacunarity'' is gap between successive frequencies
* ``octaves'' is the number of frequencies in the fBm
* ``offset'' is the zero offset, which determines multifractality (NOT USED??)
*/
/* this one is in fact rather confusing,
* there seem to be errors in the original source code (in all three versions of proc.text&mod),
* I modified it to something that made sense to me, so it might be wrong... */
float mg_MultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, int noisebasis)
{
float rmd, value = 1.0, pwr = 1.0, pwHL = powf(lacunarity, -H);
int i;
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoise;
break;
case 2:
noisefunc = newPerlin;
break;
case 3:
noisefunc = voronoi_F1S;
break;
case 4:
noisefunc = voronoi_F2S;
break;
case 5:
noisefunc = voronoi_F3S;
break;
case 6:
noisefunc = voronoi_F4S;
break;
case 7:
noisefunc = voronoi_F1F2S;
break;
case 8:
noisefunc = voronoi_CrS;
break;
case 14:
noisefunc = cellNoise;
break;
case 0:
default:
{
noisefunc = orgBlenderNoiseS;
}
}
for (i = 0; i < (int)octaves; i++) {
value *= (pwr * noisefunc(x, y, z) + 1.0f);
pwr *= pwHL;
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
}
rmd = octaves - floorf(octaves);
if (rmd != 0.0f) value *= (rmd * noisefunc(x, y, z) * pwr + 1.0f);
return value;
} /* multifractal() */
/*
* Heterogeneous procedural terrain function: stats by altitude method.
* Evaluated at "point"; returns value stored in "value".
*
* Parameters:
* ``H'' determines the fractal dimension of the roughest areas
* ``lacunarity'' is the gap between successive frequencies
* ``octaves'' is the number of frequencies in the fBm
* ``offset'' raises the terrain from `sea level'
*/
float mg_HeteroTerrain(float x, float y, float z, float H, float lacunarity, float octaves, float offset, int noisebasis)
{
float value, increment, rmd;
int i;
float pwHL = powf(lacunarity, -H);
float pwr = pwHL; /* starts with i=1 instead of 0 */
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoise;
break;
case 2:
noisefunc = newPerlin;
break;
case 3:
noisefunc = voronoi_F1S;
break;
case 4:
noisefunc = voronoi_F2S;
break;
case 5:
noisefunc = voronoi_F3S;
break;
case 6:
noisefunc = voronoi_F4S;
break;
case 7:
noisefunc = voronoi_F1F2S;
break;
case 8:
noisefunc = voronoi_CrS;
break;
case 14:
noisefunc = cellNoise;
break;
case 0:
default:
{
noisefunc = orgBlenderNoiseS;
}
}
/* first unscaled octave of function; later octaves are scaled */
value = offset + noisefunc(x, y, z);
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
for (i = 1; i < (int)octaves; i++) {
increment = (noisefunc(x, y, z) + offset) * pwr * value;
value += increment;
pwr *= pwHL;
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
}
rmd = octaves - floorf(octaves);
if (rmd != 0.0f) {
increment = (noisefunc(x, y, z) + offset) * pwr * value;
value += rmd * increment;
}
return value;
}
/* Hybrid additive/multiplicative multifractal terrain model.
*
* Some good parameter values to start with:
*
* H: 0.25
* offset: 0.7
*/
float mg_HybridMultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, float offset, float gain, int noisebasis)
{
float result, signal, weight, rmd;
int i;
float pwHL = powf(lacunarity, -H);
float pwr = pwHL; /* starts with i=1 instead of 0 */
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoise;
break;
case 2:
noisefunc = newPerlin;
break;
case 3:
noisefunc = voronoi_F1S;
break;
case 4:
noisefunc = voronoi_F2S;
break;
case 5:
noisefunc = voronoi_F3S;
break;
case 6:
noisefunc = voronoi_F4S;
break;
case 7:
noisefunc = voronoi_F1F2S;
break;
case 8:
noisefunc = voronoi_CrS;
break;
case 14:
noisefunc = cellNoise;
break;
case 0:
default:
{
noisefunc = orgBlenderNoiseS;
}
}
result = noisefunc(x, y, z) + offset;
weight = gain * result;
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
for (i = 1; (weight > 0.001f) && (i < (int)octaves); i++) {
if (weight > 1.0f) weight = 1.0f;
signal = (noisefunc(x, y, z) + offset) * pwr;
pwr *= pwHL;
result += weight * signal;
weight *= gain * signal;
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
}
rmd = octaves - floorf(octaves);
if (rmd != 0.f) result += rmd * ((noisefunc(x, y, z) + offset) * pwr);
return result;
} /* HybridMultifractal() */
/* Ridged multifractal terrain model.
*
* Some good parameter values to start with:
*
* H: 1.0
* offset: 1.0
* gain: 2.0
*/
float mg_RidgedMultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, float offset, float gain, int noisebasis)
{
float result, signal, weight;
int i;
float pwHL = powf(lacunarity, -H);
float pwr = pwHL; /* starts with i=1 instead of 0 */
float (*noisefunc)(float, float, float);
switch (noisebasis) {
case 1:
noisefunc = orgPerlinNoise;
break;
case 2:
noisefunc = newPerlin;
break;
case 3:
noisefunc = voronoi_F1S;
break;
case 4:
noisefunc = voronoi_F2S;
break;
case 5:
noisefunc = voronoi_F3S;
break;
case 6:
noisefunc = voronoi_F4S;
break;
case 7:
noisefunc = voronoi_F1F2S;
break;
case 8:
noisefunc = voronoi_CrS;
break;
case 14:
noisefunc = cellNoise;
break;
case 0:
default:
{
noisefunc = orgBlenderNoiseS;
}
}
signal = offset - fabsf(noisefunc(x, y, z));
signal *= signal;
result = signal;
for (i = 1; i < (int)octaves; i++) {
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
weight = signal * gain;
if (weight > 1.0f) weight = 1.0f;
else if (weight < 0.0f) weight = 0.0f;
signal = offset - fabsf(noisefunc(x, y, z));
signal *= signal;
signal *= weight;
result += signal * pwr;
pwr *= pwHL;
}
return result;
} /* RidgedMultifractal() */
/* "Variable Lacunarity Noise"
* A distorted variety of Perlin noise.
*/
float mg_VLNoise(float x, float y, float z, float distortion, int nbas1, int nbas2)
{
float rv[3];
float (*noisefunc1)(float, float, float);
float (*noisefunc2)(float, float, float);
switch (nbas1) {
case 1:
noisefunc1 = orgPerlinNoise;
break;
case 2:
noisefunc1 = newPerlin;
break;
case 3:
noisefunc1 = voronoi_F1S;
break;
case 4:
noisefunc1 = voronoi_F2S;
break;
case 5:
noisefunc1 = voronoi_F3S;
break;
case 6:
noisefunc1 = voronoi_F4S;
break;
case 7:
noisefunc1 = voronoi_F1F2S;
break;
case 8:
noisefunc1 = voronoi_CrS;
break;
case 14:
noisefunc1 = cellNoise;
break;
case 0:
default:
{
noisefunc1 = orgBlenderNoiseS;
}
}
switch (nbas2) {
case 1:
noisefunc2 = orgPerlinNoise;
break;
case 2:
noisefunc2 = newPerlin;
break;
case 3:
noisefunc2 = voronoi_F1S;
break;
case 4:
noisefunc2 = voronoi_F2S;
break;
case 5:
noisefunc2 = voronoi_F3S;
break;
case 6:
noisefunc2 = voronoi_F4S;
break;
case 7:
noisefunc2 = voronoi_F1F2S;
break;
case 8:
noisefunc2 = voronoi_CrS;
break;
case 14:
noisefunc2 = cellNoise;
break;
case 0:
default:
{
noisefunc2 = orgBlenderNoiseS;
}
}
/* get a random vector and scale the randomization */
rv[0] = noisefunc1(x + 13.5f, y + 13.5f, z + 13.5f) * distortion;
rv[1] = noisefunc1(x, y, z) * distortion;
rv[2] = noisefunc1(x - 13.5f, y - 13.5f, z - 13.5f) * distortion;
return noisefunc2(x + rv[0], y + rv[1], z + rv[2]); /* distorted-domain noise */
}
/****************/
/* musgrave end */
/****************/
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