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5c30bc285cd017daaccf4ccc7eb1d1d62cad94c9
blender-archive/source/blender/blenlib/intern/noise.c
Brecht Van Lommel 5c30bc285c Fix T52034: cell noise renders different. 
Tweak the bias from the previous fix a bit to be more backwards compatible in
some scene. In the end which way we round is quite arbitrary, but keeping the
case where the texture coordinate is exactly zero the same seems better.
2017-07-16 01:27:55 +02:00

2019 lines
67 KiB
C
Raw Blame History

/*
* ***** 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
*/
#include <math.h>
#include "BLI_noise.h"
/* local */
static float noise3_perlin(float vec[3]);
//static float turbulence_perlin(const float point[3], 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 const 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,
0.447257, 0.440661, 0.728488, 0.299853, 0.148599, 0.649212, 0.498381,
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,
0.562691, 0.981797, 0.001223, 0.192120, 0.451543, 0.173092, 0.108960,
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,
0.562058, 0.048082, 0.863109, 0.079290, 0.713559, 0.783496, 0.265266,
0.672089, 0.786939, 0.143048, 0.086196, 0.876129, 0.408708, 0.229312,
0.629995, 0.206665, 0.207308, 0.710079, 0.341704, 0.264921, 0.028748,
0.629222, 0.470173, 0.726228, 0.125243, 0.328249, 0.794187, 0.741340,
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,
0.452181, 0.826159, 0.186993, 0.820725, 0.440328, 0.922137, 0.704592,
0.915437, 0.738183, 0.733461, 0.193798, 0.929213, 0.161390, 0.318547,
0.888751, 0.430968, 0.740837, 0.193544, 0.872253, 0.563074, 0.274598,
0.347805, 0.666176, 0.449831, 0.800991, 0.588727, 0.052296, 0.714761,
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,
0.831984, 0.828509, 0.642093, 0.494174, 0.525880, 0.446365, 0.440063,
0.763114, 0.630358, 0.223943, 0.333806, 0.906033, 0.498306, 0.241278,
0.427640, 0.772683, 0.198082, 0.225379, 0.503894, 0.436599, 0.016503,
0.803725, 0.189878, 0.291095, 0.499114, 0.151573, 0.079031, 0.904618,
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
};
const 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,
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,
};
const 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. */
float 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;
register const float *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 g_perlin_data_ub[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 const float g_perlin_data_v3[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])
{
const char *p = g_perlin_data_ub;
const float (*g)[3] = g_perlin_data_v3;
int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11;
float rx0, rx1, ry0, ry1, rz0, rz1, sx, sy, sz, a, b, c, d, t, u, v;
const float *q;
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(const float point[3], 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;
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;
break;
}
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++) {
const float *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)
{
/* avoid precision issues on unit coordinates */
x = (x + 0.000001f)*1.00001f;
y = (y + 0.000001f)*1.00001f;
z = (z + 0.000001f)*1.00001f;
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[3])
{
/* avoid precision issues on unit coordinates */
x = (x + 0.000001f)*1.00001f;
y = (y + 0.000001f)*1.00001f;
z = (z + 0.000001f)*1.00001f;
int xi = (int)(floor(x));
int yi = (int)(floor(y));
int zi = (int)(floor(z));
const 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;
break;
}
}
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;
break;
}
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 Modeling: 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;
break;
}
}
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;
break;
}
}
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;
break;
}
}
/* 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;
break;
}
}
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;
break;
}
}
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;
break;
}
}
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;
break;
}
}
/* 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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