Merging r51923 through r52851 from trunk into soc-2011-tomato
[blender.git] / source / blender / blenlib / intern / noise.c
1 /*
2  * ***** BEGIN GPL LICENSE BLOCK *****
3  *
4  * This program is free software; you can redistribute it and/or
5  * modify it under the terms of the GNU General Public License
6  * as published by the Free Software Foundation; either version 2
7  * of the License, or (at your option) any later version.
8  *
9  * This program is distributed in the hope that it will be useful,
10  * but WITHOUT ANY WARRANTY; without even the implied warranty of
11  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
12  * GNU General Public License for more details.
13  *
14  * You should have received a copy of the GNU General Public License
15  * along with this program; if not, write to the Free Software Foundation,
16  * Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
17  *
18  * The Original Code is Copyright (C) 2001-2002 by NaN Holding BV.
19  * All rights reserved.
20  *
21  * The Original Code is: all of this file.
22  *
23  * Contributor(s): none yet.
24  *
25  * ***** END GPL LICENSE BLOCK *****
26  *
27  */
28
29 /** \file blender/blenlib/intern/noise.c
30  *  \ingroup bli
31  */
32
33
34 #ifdef _MSC_VER
35 #  pragma warning (disable:4244)  /* "conversion from double to float" */
36 #  pragma warning (disable:4305)  /* "truncation from const double to float" */
37 #endif
38
39 #include <math.h>
40
41 #include "BLI_noise.h"
42
43 /* local */
44 static float noise3_perlin(float vec[3]);
45 //static float turbulence_perlin(float *point, float lofreq, float hifreq);
46 //static float turbulencep(float noisesize, float x, float y, float z, int nr);
47
48 /* UNUSED */
49 // #define HASHVEC(x, y, z) hashvectf + 3 * hash[(hash[(hash[(z) & 255] + (y)) & 255] + (x)) & 255]
50
51 /* needed for voronoi */
52 #define HASHPNT(x, y, z) hashpntf + 3 * hash[(hash[(hash[(z) & 255] + (y)) & 255] + (x)) & 255]
53 static float hashpntf[768] = {
54         0.536902, 0.020915, 0.501445, 0.216316, 0.517036, 0.822466, 0.965315,
55         0.377313, 0.678764, 0.744545, 0.097731, 0.396357, 0.247202, 0.520897,
56         0.613396, 0.542124, 0.146813, 0.255489, 0.810868, 0.638641, 0.980742,
57         0.292316, 0.357948, 0.114382, 0.861377, 0.629634, 0.722530, 0.714103,
58         0.048549, 0.075668, 0.564920, 0.162026, 0.054466, 0.411738, 0.156897,
59         0.887657, 0.599368, 0.074249, 0.170277, 0.225799, 0.393154, 0.301348,
60         0.057434, 0.293849, 0.442745, 0.150002, 0.398732, 0.184582, 0.915200,
61         0.630984, 0.974040, 0.117228, 0.795520, 0.763238, 0.158982, 0.616211,
62         0.250825, 0.906539, 0.316874, 0.676205, 0.234720, 0.667673, 0.792225,
63         0.273671, 0.119363, 0.199131, 0.856716, 0.828554, 0.900718, 0.705960,
64         0.635923, 0.989433, 0.027261, 0.283507, 0.113426, 0.388115, 0.900176,
65         0.637741, 0.438802, 0.715490, 0.043692, 0.202640, 0.378325, 0.450325,
66         0.471832, 0.147803, 0.906899, 0.524178, 0.784981, 0.051483, 0.893369,
67         0.596895, 0.275635, 0.391483, 0.844673, 0.103061, 0.257322, 0.708390,
68         0.504091, 0.199517, 0.660339, 0.376071, 0.038880, 0.531293, 0.216116,
69         0.138672, 0.907737, 0.807994, 0.659582, 0.915264, 0.449075, 0.627128,
70         0.480173, 0.380942, 0.018843, 0.211808, 0.569701, 0.082294, 0.689488,
71         0.573060, 0.593859, 0.216080, 0.373159, 0.108117, 0.595539, 0.021768,
72         0.380297, 0.948125, 0.377833, 0.319699, 0.315249, 0.972805, 0.792270,
73         0.445396, 0.845323, 0.372186, 0.096147, 0.689405, 0.423958, 0.055675,
74         0.117940, 0.328456, 0.605808, 0.631768, 0.372170, 0.213723, 0.032700,
75         0.447257, 0.440661, 0.728488, 0.299853, 0.148599, 0.649212, 0.498381,
76         0.049921, 0.496112, 0.607142, 0.562595, 0.990246, 0.739659, 0.108633,
77         0.978156, 0.209814, 0.258436, 0.876021, 0.309260, 0.600673, 0.713597,
78         0.576967, 0.641402, 0.853930, 0.029173, 0.418111, 0.581593, 0.008394,
79         0.589904, 0.661574, 0.979326, 0.275724, 0.111109, 0.440472, 0.120839,
80         0.521602, 0.648308, 0.284575, 0.204501, 0.153286, 0.822444, 0.300786,
81         0.303906, 0.364717, 0.209038, 0.916831, 0.900245, 0.600685, 0.890002,
82         0.581660, 0.431154, 0.705569, 0.551250, 0.417075, 0.403749, 0.696652,
83         0.292652, 0.911372, 0.690922, 0.323718, 0.036773, 0.258976, 0.274265,
84         0.225076, 0.628965, 0.351644, 0.065158, 0.080340, 0.467271, 0.130643,
85         0.385914, 0.919315, 0.253821, 0.966163, 0.017439, 0.392610, 0.478792,
86         0.978185, 0.072691, 0.982009, 0.097987, 0.731533, 0.401233, 0.107570,
87         0.349587, 0.479122, 0.700598, 0.481751, 0.788429, 0.706864, 0.120086,
88         0.562691, 0.981797, 0.001223, 0.192120, 0.451543, 0.173092, 0.108960,
89         0.549594, 0.587892, 0.657534, 0.396365, 0.125153, 0.666420, 0.385823,
90         0.890916, 0.436729, 0.128114, 0.369598, 0.759096, 0.044677, 0.904752,
91         0.088052, 0.621148, 0.005047, 0.452331, 0.162032, 0.494238, 0.523349,
92         0.741829, 0.698450, 0.452316, 0.563487, 0.819776, 0.492160, 0.004210,
93         0.647158, 0.551475, 0.362995, 0.177937, 0.814722, 0.727729, 0.867126,
94         0.997157, 0.108149, 0.085726, 0.796024, 0.665075, 0.362462, 0.323124,
95         0.043718, 0.042357, 0.315030, 0.328954, 0.870845, 0.683186, 0.467922,
96         0.514894, 0.809971, 0.631979, 0.176571, 0.366320, 0.850621, 0.505555,
97         0.749551, 0.750830, 0.401714, 0.481216, 0.438393, 0.508832, 0.867971,
98         0.654581, 0.058204, 0.566454, 0.084124, 0.548539, 0.902690, 0.779571,
99         0.562058, 0.048082, 0.863109, 0.079290, 0.713559, 0.783496, 0.265266,
100         0.672089, 0.786939, 0.143048, 0.086196, 0.876129, 0.408708, 0.229312,
101         0.629995, 0.206665, 0.207308, 0.710079, 0.341704, 0.264921, 0.028748,
102         0.629222, 0.470173, 0.726228, 0.125243, 0.328249, 0.794187, 0.741340,
103         0.489895, 0.189396, 0.724654, 0.092841, 0.039809, 0.860126, 0.247701,
104         0.655331, 0.964121, 0.672536, 0.044522, 0.690567, 0.837238, 0.631520,
105         0.953734, 0.352484, 0.289026, 0.034152, 0.852575, 0.098454, 0.795529,
106         0.452181, 0.826159, 0.186993, 0.820725, 0.440328, 0.922137, 0.704592,
107         0.915437, 0.738183, 0.733461, 0.193798, 0.929213, 0.161390, 0.318547,
108         0.888751, 0.430968, 0.740837, 0.193544, 0.872253, 0.563074, 0.274598,
109         0.347805, 0.666176, 0.449831, 0.800991, 0.588727, 0.052296, 0.714761,
110         0.420620, 0.570325, 0.057550, 0.210888, 0.407312, 0.662848, 0.924382,
111         0.895958, 0.775198, 0.688605, 0.025721, 0.301913, 0.791408, 0.500602,
112         0.831984, 0.828509, 0.642093, 0.494174, 0.525880, 0.446365, 0.440063,
113         0.763114, 0.630358, 0.223943, 0.333806, 0.906033, 0.498306, 0.241278,
114         0.427640, 0.772683, 0.198082, 0.225379, 0.503894, 0.436599, 0.016503,
115         0.803725, 0.189878, 0.291095, 0.499114, 0.151573, 0.079031, 0.904618,
116         0.708535, 0.273900, 0.067419, 0.317124, 0.936499, 0.716511, 0.543845,
117         0.939909, 0.826574, 0.715090, 0.154864, 0.750150, 0.845808, 0.648108,
118         0.556564, 0.644757, 0.140873, 0.799167, 0.632989, 0.444245, 0.471978,
119         0.435910, 0.359793, 0.216241, 0.007633, 0.337236, 0.857863, 0.380247,
120         0.092517, 0.799973, 0.919000, 0.296798, 0.096989, 0.854831, 0.165369,
121         0.568475, 0.216855, 0.020457, 0.835511, 0.538039, 0.999742, 0.620226,
122         0.244053, 0.060399, 0.323007, 0.294874, 0.988899, 0.384919, 0.735655,
123         0.773428, 0.549776, 0.292882, 0.660611, 0.593507, 0.621118, 0.175269,
124         0.682119, 0.794493, 0.868197, 0.632150, 0.807823, 0.509656, 0.482035,
125         0.001780, 0.259126, 0.358002, 0.280263, 0.192985, 0.290367, 0.208111,
126         0.917633, 0.114422, 0.925491, 0.981110, 0.255570, 0.974862, 0.016629,
127         0.552599, 0.575741, 0.612978, 0.615965, 0.803615, 0.772334, 0.089745,
128         0.838812, 0.634542, 0.113709, 0.755832, 0.577589, 0.667489, 0.529834,
129         0.325660, 0.817597, 0.316557, 0.335093, 0.737363, 0.260951, 0.737073,
130         0.049540, 0.735541, 0.988891, 0.299116, 0.147695, 0.417271, 0.940811,
131         0.524160, 0.857968, 0.176403, 0.244835, 0.485759, 0.033353, 0.280319,
132         0.750688, 0.755809, 0.924208, 0.095956, 0.962504, 0.275584, 0.173715,
133         0.942716, 0.706721, 0.078464, 0.576716, 0.804667, 0.559249, 0.900611,
134         0.646904, 0.432111, 0.927885, 0.383277, 0.269973, 0.114244, 0.574867,
135         0.150703, 0.241855, 0.272871, 0.199950, 0.079719, 0.868566, 0.962833,
136         0.789122, 0.320025, 0.905554, 0.234876, 0.991356, 0.061913, 0.732911,
137         0.785960, 0.874074, 0.069035, 0.658632, 0.309901, 0.023676, 0.791603,
138         0.764661, 0.661278, 0.319583, 0.829650, 0.117091, 0.903124, 0.982098,
139         0.161631, 0.193576, 0.670428, 0.857390, 0.003760, 0.572578, 0.222162,
140         0.114551, 0.420118, 0.530404, 0.470682, 0.525527, 0.764281, 0.040596,
141         0.443275, 0.501124, 0.816161, 0.417467, 0.332172, 0.447565, 0.614591,
142         0.559246, 0.805295, 0.226342, 0.155065, 0.714630, 0.160925, 0.760001,
143         0.453456, 0.093869, 0.406092, 0.264801, 0.720370, 0.743388, 0.373269,
144         0.403098, 0.911923, 0.897249, 0.147038, 0.753037, 0.516093, 0.739257,
145         0.175018, 0.045768, 0.735857, 0.801330, 0.927708, 0.240977, 0.591870,
146         0.921831, 0.540733, 0.149100, 0.423152, 0.806876, 0.397081, 0.061100,
147         0.811630, 0.044899, 0.460915, 0.961202, 0.822098, 0.971524, 0.867608,
148         0.773604, 0.226616, 0.686286, 0.926972, 0.411613, 0.267873, 0.081937,
149         0.226124, 0.295664, 0.374594, 0.533240, 0.237876, 0.669629, 0.599083,
150         0.513081, 0.878719, 0.201577, 0.721296, 0.495038, 0.079760, 0.965959,
151         0.233090, 0.052496, 0.714748, 0.887844, 0.308724, 0.972885, 0.723337,
152         0.453089, 0.914474, 0.704063, 0.823198, 0.834769, 0.906561, 0.919600,
153         0.100601, 0.307564, 0.901977, 0.468879, 0.265376, 0.885188, 0.683875,
154         0.868623, 0.081032, 0.466835, 0.199087, 0.663437, 0.812241, 0.311337,
155         0.821361, 0.356628, 0.898054, 0.160781, 0.222539, 0.714889, 0.490287,
156         0.984915, 0.951755, 0.964097, 0.641795, 0.815472, 0.852732, 0.862074,
157         0.051108, 0.440139, 0.323207, 0.517171, 0.562984, 0.115295, 0.743103,
158         0.977914, 0.337596, 0.440694, 0.535879, 0.959427, 0.351427, 0.704361,
159         0.010826, 0.131162, 0.577080, 0.349572, 0.774892, 0.425796, 0.072697,
160         0.500001, 0.267322, 0.909654, 0.206176, 0.223987, 0.937698, 0.323423,
161         0.117501, 0.490308, 0.474372, 0.689943, 0.168671, 0.719417, 0.188928,
162         0.330464, 0.265273, 0.446271, 0.171933, 0.176133, 0.474616, 0.140182,
163         0.114246, 0.905043, 0.713870, 0.555261, 0.951333
164 };
165
166 unsigned char hash[512] = {
167         0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE, 0xF3, 0x1C, 0x67, 0x28, 0x1D, 0xED, 0x0,  0xDE, 0x95, 0x2E, 0xDC,
168         0x3F, 0x3A, 0x82, 0x35, 0x4D, 0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC,  0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8,  0x8B, 0x63,
169         0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83, 0xF2, 0x8F, 0x18, 0xC7, 0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8, 0x80,
170         0xB5, 0x40, 0x13, 0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D, 0x86, 0x4C, 0xC8, 0xDB, 0x7C, 0xD5, 0x25, 0x4E,
171         0x5A, 0x55, 0x74, 0x50, 0xCD, 0xB3, 0x7A, 0xBB, 0xC3, 0xCB, 0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98, 0xB,  0x96, 0xD3,
172         0x9E, 0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4, 0x24, 0x72, 0x49, 0x8C, 0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB,
173         0x78, 0xCA, 0x1F, 0x1,  0xD7, 0x93, 0x11, 0xC1, 0x58, 0xA9, 0x31, 0xF9, 0x44, 0x6D, 0xBF, 0x33, 0x9C, 0x5F, 0x9,
174         0x94, 0xA3, 0x85, 0x6,  0xC6, 0x9A, 0x1E, 0x7B, 0x46, 0x15, 0x30, 0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F,
175         0x62, 0xAC, 0x4F, 0xC2, 0xC0, 0xE,  0xB1, 0x23, 0xA7, 0xDF, 0x47, 0xB0, 0x77, 0x69, 0x5,  0xE9, 0xE6, 0xE7, 0x76,
176         0x73, 0xF,  0xFE, 0x6E, 0x9B, 0x56, 0xEF, 0x12, 0xA5, 0x37, 0xFC, 0xAE, 0xD9, 0x3,  0x8E, 0xDD, 0x10, 0xB9, 0xCE,
177         0xC9, 0x8D, 0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4, 0xA,  0xCC, 0xD2, 0xE8, 0x43, 0x3D, 0x70, 0xB7, 0x2,
178         0x7D, 0x99, 0xD8, 0xD,  0x60, 0x8A, 0x4,  0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7,  0xE0, 0x29, 0xA6, 0xC5, 0xE3,
179         0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D, 0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66,
180         0x1A, 0x45, 0x39, 0xCF, 0x75, 0xA4, 0x88, 0xFB, 0x5D, 0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE, 0xF3, 0x1C,
181         0x67, 0x28, 0x1D, 0xED, 0x0,  0xDE, 0x95, 0x2E, 0xDC, 0x3F, 0x3A, 0x82, 0x35, 0x4D, 0x6C, 0xBA, 0x36, 0xD0, 0xF6,
182         0xC,  0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8,  0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83, 0xF2, 0x8F, 0x18, 0xC7,
183         0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8, 0x80, 0xB5, 0x40, 0x13, 0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B,
184         0x9D, 0x86, 0x4C, 0xC8, 0xDB, 0x7C, 0xD5, 0x25, 0x4E, 0x5A, 0x55, 0x74, 0x50, 0xCD, 0xB3, 0x7A, 0xBB, 0xC3, 0xCB,
185         0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98, 0xB,  0x96, 0xD3, 0x9E, 0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4, 0x24,
186         0x72, 0x49, 0x8C, 0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA, 0x1F, 0x1,  0xD7, 0x93, 0x11, 0xC1, 0x58, 0xA9,
187         0x31, 0xF9, 0x44, 0x6D, 0xBF, 0x33, 0x9C, 0x5F, 0x9,  0x94, 0xA3, 0x85, 0x6,  0xC6, 0x9A, 0x1E, 0x7B, 0x46, 0x15,
188         0x30, 0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F, 0x62, 0xAC, 0x4F, 0xC2, 0xC0, 0xE,  0xB1, 0x23, 0xA7, 0xDF,
189         0x47, 0xB0, 0x77, 0x69, 0x5,  0xE9, 0xE6, 0xE7, 0x76, 0x73, 0xF,  0xFE, 0x6E, 0x9B, 0x56, 0xEF, 0x12, 0xA5, 0x37,
190         0xFC, 0xAE, 0xD9, 0x3,  0x8E, 0xDD, 0x10, 0xB9, 0xCE, 0xC9, 0x8D, 0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4,
191         0xA,  0xCC, 0xD2, 0xE8, 0x43, 0x3D, 0x70, 0xB7, 0x2,  0x7D, 0x99, 0xD8, 0xD,  0x60, 0x8A, 0x4,  0x2C, 0x3E, 0x92,
192         0xE5, 0xAF, 0x53, 0x7,  0xE0, 0x29, 0xA6, 0xC5, 0xE3, 0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D,
193         0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A, 0x45, 0x39, 0xCF, 0x75, 0xA4, 0x88, 0xFB, 0x5D,
194 };
195
196
197 float hashvectf[768] = {
198         0.33783, 0.715698, -0.611206, -0.944031, -0.326599, -0.045624, -0.101074, -0.416443, -0.903503, 0.799286, 0.49411,
199         -0.341949, -0.854645, 0.518036, 0.033936, 0.42514, -0.437866, -0.792114, -0.358948, 0.597046, 0.717377, -0.985413,
200         0.144714, 0.089294, -0.601776, -0.33728, -0.723907, -0.449921, 0.594513, 0.666382, 0.208313, -0.10791, 0.972076,
201         0.575317, 0.060425, 0.815643, 0.293365, -0.875702, -0.383453, 0.293762, 0.465759, 0.834686, -0.846008, -0.233398,
202         -0.47934, -0.115814, 0.143036, -0.98291, 0.204681, -0.949036, -0.239532, 0.946716, -0.263947, 0.184326, -0.235596,
203         0.573822, 0.784332, 0.203705, -0.372253, -0.905487, 0.756989, -0.651031, 0.055298, 0.497803, 0.814697, -0.297363,
204         -0.16214, 0.063995, -0.98468, -0.329254, 0.834381, 0.441925, 0.703827, -0.527039, -0.476227, 0.956421, 0.266113,
205         0.119781, 0.480133, 0.482849, 0.7323, -0.18631, 0.961212, -0.203125, -0.748474, -0.656921, -0.090393, -0.085052,
206         -0.165253, 0.982544, -0.76947, 0.628174, -0.115234, 0.383148, 0.537659, 0.751068, 0.616486, -0.668488, -0.415924,
207         -0.259979, -0.630005, 0.73175, 0.570953, -0.087952, 0.816223, -0.458008, 0.023254, 0.888611, -0.196167, 0.976563,
208         -0.088287, -0.263885, -0.69812, -0.665527, 0.437134, -0.892273, -0.112793, -0.621674, -0.230438, 0.748566, 0.232422,
209         0.900574, -0.367249, 0.22229, -0.796143, 0.562744, -0.665497, -0.73764, 0.11377, 0.670135, 0.704803, 0.232605,
210         0.895599, 0.429749, -0.114655, -0.11557, -0.474243, 0.872742, 0.621826, 0.604004, -0.498444, -0.832214, 0.012756,
211         0.55426, -0.702484, 0.705994, -0.089661, -0.692017, 0.649292, 0.315399, -0.175995, -0.977997, 0.111877, 0.096954,
212         -0.04953, 0.994019, 0.635284, -0.606689, -0.477783, -0.261261, -0.607422, -0.750153, 0.983276, 0.165436, 0.075958,
213         -0.29837, 0.404083, -0.864655, -0.638672, 0.507721, 0.578156, 0.388214, 0.412079, 0.824249, 0.556183, -0.208832,
214         0.804352, 0.778442, 0.562012, 0.27951, -0.616577, 0.781921, -0.091522, 0.196289, 0.051056, 0.979187, -0.121216,
215         0.207153, -0.970734, -0.173401, -0.384735, 0.906555, 0.161499, -0.723236, -0.671387, 0.178497, -0.006226, -0.983887,
216         -0.126038, 0.15799, 0.97934, 0.830475, -0.024811, 0.556458, -0.510132, -0.76944, 0.384247, 0.81424, 0.200104,
217         -0.544891, -0.112549, -0.393311, -0.912445, 0.56189, 0.152222, -0.813049, 0.198914, -0.254517, -0.946381, -0.41217,
218         0.690979, -0.593811, -0.407257, 0.324524, 0.853668, -0.690186, 0.366119, -0.624115, -0.428345, 0.844147, -0.322296,
219         -0.21228, -0.297546, -0.930756, -0.273071, 0.516113, 0.811798, 0.928314, 0.371643, 0.007233, 0.785828, -0.479218,
220         -0.390778, -0.704895, 0.058929, 0.706818, 0.173248, 0.203583, 0.963562, 0.422211, -0.904297, -0.062469, -0.363312,
221         -0.182465, 0.913605, 0.254028, -0.552307, -0.793945, -0.28891, -0.765747, -0.574554, 0.058319, 0.291382, 0.954803,
222         0.946136, -0.303925, 0.111267, -0.078156, 0.443695, -0.892731, 0.182098, 0.89389, 0.409515, -0.680298, -0.213318,
223         0.701141, 0.062469, 0.848389, -0.525635, -0.72879, -0.641846, 0.238342, -0.88089, 0.427673, 0.202637, -0.532501,
224         -0.21405, 0.818878, 0.948975, -0.305084, 0.07962, 0.925446, 0.374664, 0.055817, 0.820923, 0.565491, 0.079102,
225         0.25882, 0.099792, -0.960724, -0.294617, 0.910522, 0.289978, 0.137115, 0.320038, -0.937408, -0.908386, 0.345276,
226         -0.235718, -0.936218, 0.138763, 0.322754, 0.366577, 0.925934, -0.090637, 0.309296, -0.686829, -0.657684, 0.66983,
227         0.024445, 0.742065, -0.917999, -0.059113, -0.392059, 0.365509, 0.462158, -0.807922, 0.083374, 0.996399, -0.014801,
228         0.593842, 0.253143, -0.763672, 0.974976, -0.165466, 0.148285, 0.918976, 0.137299, 0.369537, 0.294952, 0.694977,
229         0.655731, 0.943085, 0.152618, -0.295319, 0.58783, -0.598236, 0.544495, 0.203796, 0.678223, 0.705994, -0.478821,
230         -0.661011, 0.577667, 0.719055, -0.1698, -0.673828, -0.132172, -0.965332, 0.225006, -0.981873, -0.14502, 0.121979,
231         0.763458, 0.579742, 0.284546, -0.893188, 0.079681, 0.442474, -0.795776, -0.523804, 0.303802, 0.734955, 0.67804,
232         -0.007446, 0.15506, 0.986267, -0.056183, 0.258026, 0.571503, -0.778931, -0.681549, -0.702087, -0.206116, -0.96286,
233         -0.177185, 0.203613, -0.470978, -0.515106, 0.716095, -0.740326, 0.57135, 0.354095, -0.56012, -0.824982, -0.074982,
234         -0.507874, 0.753204, 0.417969, -0.503113, 0.038147, 0.863342, 0.594025, 0.673553, -0.439758, -0.119873, -0.005524,
235         -0.992737, 0.098267, -0.213776, 0.971893, -0.615631, 0.643951, 0.454163, 0.896851, -0.441071, 0.032166, -0.555023,
236         0.750763, -0.358093, 0.398773, 0.304688, 0.864929, -0.722961, 0.303589, 0.620544, -0.63559, -0.621948, -0.457306,
237         -0.293243, 0.072327, 0.953278, -0.491638, 0.661041, -0.566772, -0.304199, -0.572083, -0.761688, 0.908081, -0.398956,
238         0.127014, -0.523621, -0.549683, -0.650848, -0.932922, -0.19986, 0.299408, 0.099426, 0.140869, 0.984985, -0.020325,
239         -0.999756, -0.002319, 0.952667, 0.280853, -0.11615, -0.971893, 0.082581, 0.220337, 0.65921, 0.705292, -0.260651,
240         0.733063, -0.175537, 0.657043, -0.555206, 0.429504, -0.712189, 0.400421, -0.89859, 0.179352, 0.750885, -0.19696,
241         0.630341, 0.785675, -0.569336, 0.241821, -0.058899, -0.464111, 0.883789, 0.129608, -0.94519, 0.299622, -0.357819,
242         0.907654, 0.219238, -0.842133, -0.439117, -0.312927, -0.313477, 0.84433, 0.434479, -0.241211, 0.053253, 0.968994,
243         0.063873, 0.823273, 0.563965, 0.476288, 0.862152, -0.172516, 0.620941, -0.298126, 0.724915, 0.25238, -0.749359,
244         -0.612122, -0.577545, 0.386566, 0.718994, -0.406342, -0.737976, 0.538696, 0.04718, 0.556305, 0.82959, -0.802856,
245         0.587463, 0.101166, -0.707733, -0.705963, 0.026428, 0.374908, 0.68457, 0.625092, 0.472137, 0.208405, -0.856506,
246         -0.703064, -0.581085, -0.409821, -0.417206, -0.736328, 0.532623, -0.447876, -0.20285, -0.870728, 0.086945,
247         -0.990417, 0.107086, 0.183685, 0.018341, -0.982788, 0.560638, -0.428864, 0.708282, 0.296722, -0.952576, -0.0672,
248         0.135773, 0.990265, 0.030243, -0.068787, 0.654724, 0.752686, 0.762604, -0.551758, 0.337585, -0.819611, -0.407684,
249         0.402466, -0.727844, -0.55072, -0.408539, -0.855774, -0.480011, 0.19281, 0.693176, -0.079285, 0.716339, 0.226013,
250         0.650116, -0.725433, 0.246704, 0.953369, -0.173553, -0.970398, -0.239227, -0.03244, 0.136383, -0.394318, 0.908752,
251         0.813232, 0.558167, 0.164368, 0.40451, 0.549042, -0.731323, -0.380249, -0.566711, 0.730865, 0.022156, 0.932739,
252         0.359741, 0.00824, 0.996552, -0.082306, 0.956635, -0.065338, -0.283722, -0.743561, 0.008209, 0.668579, -0.859589,
253         -0.509674, 0.035767, -0.852234, 0.363678, -0.375977, -0.201965, -0.970795, -0.12915, 0.313477, 0.947327, 0.06546,
254         -0.254028, -0.528259, 0.81015, 0.628052, 0.601105, 0.49411, -0.494385, 0.868378, 0.037933, 0.275635, -0.086426,
255         0.957336, -0.197937, 0.468903, -0.860748, 0.895599, 0.399384, 0.195801, 0.560791, 0.825012, -0.069214, 0.304199,
256         -0.849487, 0.43103, 0.096375, 0.93576, 0.339111, -0.051422, 0.408966, -0.911072, 0.330444, 0.942841, -0.042389,
257         -0.452362, -0.786407, 0.420563, 0.134308, -0.933472, -0.332489, 0.80191, -0.566711, -0.188934, -0.987946, -0.105988,
258         0.112518, -0.24408, 0.892242, -0.379791, -0.920502, 0.229095, -0.316376, 0.7789, 0.325958, 0.535706, -0.912872,
259         0.185211, -0.36377, -0.184784, 0.565369, -0.803833, -0.018463, 0.119537, 0.992615, -0.259247, -0.935608, 0.239532,
260         -0.82373, -0.449127, -0.345947, -0.433105, 0.659515, 0.614349, -0.822754, 0.378845, -0.423676, 0.687195, -0.674835,
261         -0.26889, -0.246582, -0.800842, 0.545715, -0.729187, -0.207794, 0.651978, 0.653534, -0.610443, -0.447388, 0.492584,
262         -0.023346, 0.869934, 0.609039, 0.009094, -0.79306, 0.962494, -0.271088, -0.00885, 0.2659, -0.004913, 0.963959,
263         0.651245, 0.553619, -0.518951, 0.280548, -0.84314, 0.458618, -0.175293, -0.983215, 0.049805, 0.035339, -0.979919,
264         0.196045, -0.982941, 0.164307, -0.082245, 0.233734, -0.97226, -0.005005, -0.747253, -0.611328, 0.260437, 0.645599,
265         0.592773, 0.481384, 0.117706, -0.949524, -0.29068, -0.535004, -0.791901, -0.294312, -0.627167, -0.214447, 0.748718,
266         -0.047974, -0.813477, -0.57959, -0.175537, 0.477264, -0.860992, 0.738556, -0.414246, -0.53183, 0.562561, -0.704071,
267         0.433289, -0.754944, 0.64801, -0.100586, 0.114716, 0.044525, -0.992371, 0.966003, 0.244873, -0.082764,
268 };
269
270 /**************************/
271 /*  IMPROVED PERLIN NOISE */
272 /**************************/
273
274 static float lerp(float t, float a, float b)
275 {
276         return (a + t * (b - a));
277 }
278
279 static float npfade(float t)
280 {
281         return (t * t * t * (t * (t * 6.0f - 15.0f) + 10.0f));
282 }
283
284 static float grad(int hash, float x, float y, float z)
285 {
286         int h = hash & 15;                     /* CONVERT LO 4 BITS OF HASH CODE */
287         float u = h < 8 ? x : y,               /* INTO 12 GRADIENT DIRECTIONS. */
288               v = h < 4 ? y : h == 12 || h == 14 ? x : z;
289         return ((h & 1) == 0 ? u : -u) + ((h & 2) == 0 ? v : -v);
290 }
291
292 /* instead of adding another permutation array, just use hash table defined above */
293 static float newPerlin(float x, float y, float z)
294 {
295         int A, AA, AB, B, BA, BB;
296         float u = floor(x), v = floor(y), w = floor(z);
297         int X = ((int)u) & 255, Y = ((int)v) & 255, Z = ((int)w) & 255;   /* FIND UNIT CUBE THAT CONTAINS POINT */
298         x -= u;             /* FIND RELATIVE X,Y,Z */
299         y -= v;             /* OF POINT IN CUBE. */
300         z -= w;
301         u = npfade(x);      /* COMPUTE FADE CURVES */
302         v = npfade(y);      /* FOR EACH OF X,Y,Z. */
303         w = npfade(z);
304         A = hash[X    ] + Y;  AA = hash[A] + Z;  AB = hash[A + 1] + Z;      /* HASH COORDINATES OF */
305         B = hash[X + 1] + Y;  BA = hash[B] + Z;  BB = hash[B + 1] + Z;      /* THE 8 CUBE CORNERS, */
306         return lerp(w, lerp(v, lerp(u, grad(hash[AA   ],  x,     y,     z    ),   /* AND ADD */
307                                        grad(hash[BA   ],  x - 1, y,     z    )),  /* BLENDED */
308                                lerp(u, grad(hash[AB   ],  x,     y - 1, z    ),   /* RESULTS */
309                                        grad(hash[BB   ],  x - 1, y - 1, z    ))), /* FROM  8 */
310                        lerp(v, lerp(u, grad(hash[AA + 1], x,     y,     z - 1),   /* CORNERS */
311                                        grad(hash[BA + 1], x - 1, y,     z - 1)),  /* OF CUBE */
312                                lerp(u, grad(hash[AB + 1], x,     y - 1, z - 1),
313                                        grad(hash[BB + 1], x - 1, y - 1, z - 1))));
314 }
315
316 /* for use with BLI_gNoise()/BLI_gTurbulence(), returns unsigned improved perlin noise */
317 static float newPerlinU(float x, float y, float z)
318 {
319         return (0.5f + 0.5f * newPerlin(x, y, z));
320 }
321
322
323 /**************************/
324 /* END OF IMPROVED PERLIN */
325 /**************************/
326
327 /* Was BLI_hnoise(), removed noisesize, so other functions can call it without scaling. */
328 static float orgBlenderNoise(float x, float y, float z)
329 {
330         register float cn1, cn2, cn3, cn4, cn5, cn6, i, *h;
331         float fx, fy, fz, ox, oy, oz, jx, jy, jz;
332         float n = 0.5;
333         int ix, iy, iz, b00, b01, b10, b11, b20, b21;
334
335         fx = floor(x);
336         fy = floor(y);
337         fz = floor(z);
338
339         ox = x - fx;
340         oy = y - fy;
341         oz = z - fz;
342
343         ix = (int)fx;
344         iy = (int)fy;
345         iz = (int)fz;
346
347         jx = ox - 1;
348         jy = oy - 1;
349         jz = oz - 1;
350
351         cn1 = ox * ox; cn2 = oy * oy; cn3 = oz * oz;
352         cn4 = jx * jx; cn5 = jy * jy; cn6 = jz * jz;
353
354         cn1 = 1.0f - 3.0f * cn1 + 2.0f * cn1 * ox;
355         cn2 = 1.0f - 3.0f * cn2 + 2.0f * cn2 * oy;
356         cn3 = 1.0f - 3.0f * cn3 + 2.0f * cn3 * oz;
357         cn4 = 1.0f - 3.0f * cn4 - 2.0f * cn4 * jx;
358         cn5 = 1.0f - 3.0f * cn5 - 2.0f * cn5 * jy;
359         cn6 = 1.0f - 3.0f * cn6 - 2.0f * cn6 * jz;
360
361         b00 = hash[hash[ix & 255] + (iy & 255)];
362         b10 = hash[hash[(ix + 1) & 255] + (iy & 255)];
363         b01 = hash[hash[ix & 255] + ((iy + 1) & 255)];
364         b11 = hash[hash[(ix + 1) & 255] + ((iy + 1) & 255)];
365
366         b20 = iz & 255; b21 = (iz + 1) & 255;
367
368         /* 0 */
369         i = (cn1 * cn2 * cn3);
370         h = hashvectf + 3 * hash[b20 + b00];
371         n += i * (h[0] * ox + h[1] * oy + h[2] * oz);
372         /* 1 */
373         i = (cn1 * cn2 * cn6);
374         h = hashvectf + 3 * hash[b21 + b00];
375         n += i * (h[0] * ox + h[1] * oy + h[2] * jz);
376         /* 2 */
377         i = (cn1 * cn5 * cn3);
378         h = hashvectf + 3 * hash[b20 + b01];
379         n += i * (h[0] * ox + h[1] * jy + h[2] * oz);
380         /* 3 */
381         i = (cn1 * cn5 * cn6);
382         h = hashvectf + 3 * hash[b21 + b01];
383         n += i * (h[0] * ox + h[1] * jy + h[2] * jz);
384         /* 4 */
385         i = cn4 * cn2 * cn3;
386         h = hashvectf + 3 * hash[b20 + b10];
387         n += i * (h[0] * jx + h[1] * oy + h[2] * oz);
388         /* 5 */
389         i = cn4 * cn2 * cn6;
390         h = hashvectf + 3 * hash[b21 + b10];
391         n += i * (h[0] * jx + h[1] * oy + h[2] * jz);
392         /* 6 */
393         i = cn4 * cn5 * cn3;
394         h = hashvectf + 3 * hash[b20 + b11];
395         n +=  i * (h[0] * jx + h[1] * jy + h[2] * oz);
396         /* 7 */
397         i = (cn4 * cn5 * cn6);
398         h = hashvectf + 3 * hash[b21 + b11];
399         n += i * (h[0] * jx + h[1] * jy + h[2] * jz);
400
401         if      (n < 0.0f) n = 0.0f;
402         else if (n > 1.0f) n = 1.0f;
403         return n;
404 }
405
406 /* as orgBlenderNoise(), returning signed noise */
407 static float orgBlenderNoiseS(float x, float y, float z)
408 {
409         return (2.0f * orgBlenderNoise(x, y, z) - 1.0f);
410 }
411
412 /* separated from orgBlenderNoise above, with scaling */
413 float BLI_hnoise(float noisesize, float x, float y, float z)
414 {
415         if (noisesize == 0.0f) return 0.0f;
416         x = (1.0f + x) / noisesize;
417         y = (1.0f + y) / noisesize;
418         z = (1.0f + z) / noisesize;
419         return orgBlenderNoise(x, y, z);
420 }
421
422
423 /* original turbulence functions */
424 float BLI_turbulence(float noisesize, float x, float y, float z, int nr)
425 {
426         float s, d = 0.5, div = 1.0;
427
428         s = BLI_hnoise(noisesize, x, y, z);
429         
430         while (nr > 0) {
431         
432                 s += d * BLI_hnoise(noisesize * d, x, y, z);
433                 div += d;
434                 d *= 0.5f;
435
436                 nr--;
437         }
438         return s / div;
439 }
440
441 float BLI_turbulence1(float noisesize, float x, float y, float z, int nr)
442 {
443         float s, d = 0.5, div = 1.0;
444
445         s = fabsf((-1.0f + 2.0f * BLI_hnoise(noisesize, x, y, z)));
446         
447         while (nr > 0) {
448         
449                 s += fabsf(d * (-1.0f + 2.0f * BLI_hnoise(noisesize * d, x, y, z)));
450                 div += d;
451                 d *= 0.5f;
452                 
453                 nr--;
454         }
455         return s / div;
456 }
457
458 /* ********************* FROM PERLIN HIMSELF: ******************** */
459
460 static const char p[512 + 2] = {
461         0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE, 0xF3, 0x1C, 0x67, 0x28,
462         0x1D, 0xED, 0x0,  0xDE, 0x95, 0x2E, 0xDC, 0x3F, 0x3A, 0x82, 0x35, 0x4D,
463         0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC,  0x79, 0x32, 0xD1, 0x59, 0xF4, 0x8,
464         0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83, 0xF2, 0x8F, 0x18, 0xC7,
465         0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8, 0x80, 0xB5, 0x40, 0x13,
466         0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D, 0x86, 0x4C, 0xC8, 0xDB,
467         0x7C, 0xD5, 0x25, 0x4E, 0x5A, 0x55, 0x74, 0x50, 0xCD, 0xB3, 0x7A, 0xBB,
468         0xC3, 0xCB, 0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98, 0xB,  0x96, 0xD3, 0x9E,
469         0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4, 0x24, 0x72, 0x49, 0x8C,
470         0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA, 0x1F, 0x1,  0xD7, 0x93,
471         0x11, 0xC1, 0x58, 0xA9, 0x31, 0xF9, 0x44, 0x6D, 0xBF, 0x33, 0x9C, 0x5F,
472         0x9,  0x94, 0xA3, 0x85, 0x6,  0xC6, 0x9A, 0x1E, 0x7B, 0x46, 0x15, 0x30,
473         0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F, 0x62, 0xAC, 0x4F, 0xC2,
474         0xC0, 0xE,  0xB1, 0x23, 0xA7, 0xDF, 0x47, 0xB0, 0x77, 0x69, 0x5,  0xE9,
475         0xE6, 0xE7, 0x76, 0x73, 0xF,  0xFE, 0x6E, 0x9B, 0x56, 0xEF, 0x12, 0xA5,
476         0x37, 0xFC, 0xAE, 0xD9, 0x3,  0x8E, 0xDD, 0x10, 0xB9, 0xCE, 0xC9, 0x8D,
477         0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4, 0xA,  0xCC, 0xD2, 0xE8,
478         0x43, 0x3D, 0x70, 0xB7, 0x2,  0x7D, 0x99, 0xD8, 0xD,  0x60, 0x8A, 0x4,
479         0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7,  0xE0, 0x29, 0xA6, 0xC5, 0xE3,
480         0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E, 0x52, 0x2D, 0x21, 0xAD,
481         0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A, 0x45, 0x39, 0xCF, 0x75,
482         0xA4, 0x88, 0xFB, 0x5D, 0xA2, 0xA0, 0x19, 0x3B, 0xF8, 0xEB, 0xAA, 0xEE,
483         0xF3, 0x1C, 0x67, 0x28, 0x1D, 0xED, 0x0,  0xDE, 0x95, 0x2E, 0xDC, 0x3F,
484         0x3A, 0x82, 0x35, 0x4D, 0x6C, 0xBA, 0x36, 0xD0, 0xF6, 0xC,  0x79, 0x32,
485         0xD1, 0x59, 0xF4, 0x8,  0x8B, 0x63, 0x89, 0x2F, 0xB8, 0xB4, 0x97, 0x83,
486         0xF2, 0x8F, 0x18, 0xC7, 0x51, 0x14, 0x65, 0x87, 0x48, 0x20, 0x42, 0xA8,
487         0x80, 0xB5, 0x40, 0x13, 0xB2, 0x22, 0x7E, 0x57, 0xBC, 0x7F, 0x6B, 0x9D,
488         0x86, 0x4C, 0xC8, 0xDB, 0x7C, 0xD5, 0x25, 0x4E, 0x5A, 0x55, 0x74, 0x50,
489         0xCD, 0xB3, 0x7A, 0xBB, 0xC3, 0xCB, 0xB6, 0xE2, 0xE4, 0xEC, 0xFD, 0x98,
490         0xB,  0x96, 0xD3, 0x9E, 0x5C, 0xA1, 0x64, 0xF1, 0x81, 0x61, 0xE1, 0xC4,
491         0x24, 0x72, 0x49, 0x8C, 0x90, 0x4B, 0x84, 0x34, 0x38, 0xAB, 0x78, 0xCA,
492         0x1F, 0x1,  0xD7, 0x93, 0x11, 0xC1, 0x58, 0xA9, 0x31, 0xF9, 0x44, 0x6D,
493         0xBF, 0x33, 0x9C, 0x5F, 0x9,  0x94, 0xA3, 0x85, 0x6,  0xC6, 0x9A, 0x1E,
494         0x7B, 0x46, 0x15, 0x30, 0x27, 0x2B, 0x1B, 0x71, 0x3C, 0x5B, 0xD6, 0x6F,
495         0x62, 0xAC, 0x4F, 0xC2, 0xC0, 0xE,  0xB1, 0x23, 0xA7, 0xDF, 0x47, 0xB0,
496         0x77, 0x69, 0x5,  0xE9, 0xE6, 0xE7, 0x76, 0x73, 0xF,  0xFE, 0x6E, 0x9B,
497         0x56, 0xEF, 0x12, 0xA5, 0x37, 0xFC, 0xAE, 0xD9, 0x3,  0x8E, 0xDD, 0x10,
498         0xB9, 0xCE, 0xC9, 0x8D, 0xDA, 0x2A, 0xBD, 0x68, 0x17, 0x9F, 0xBE, 0xD4,
499         0xA,  0xCC, 0xD2, 0xE8, 0x43, 0x3D, 0x70, 0xB7, 0x2,  0x7D, 0x99, 0xD8,
500         0xD,  0x60, 0x8A, 0x4,  0x2C, 0x3E, 0x92, 0xE5, 0xAF, 0x53, 0x7,  0xE0,
501         0x29, 0xA6, 0xC5, 0xE3, 0xF5, 0xF7, 0x4A, 0x41, 0x26, 0x6A, 0x16, 0x5E,
502         0x52, 0x2D, 0x21, 0xAD, 0xF0, 0x91, 0xFF, 0xEA, 0x54, 0xFA, 0x66, 0x1A,
503         0x45, 0x39, 0xCF, 0x75, 0xA4, 0x88, 0xFB, 0x5D, 0xA2, 0xA0
504 };
505
506
507 static float g[512 + 2][3] = {
508         {0.33783, 0.715698, -0.611206},
509         {-0.944031, -0.326599, -0.045624},
510         {-0.101074, -0.416443, -0.903503},
511         {0.799286, 0.49411, -0.341949},
512         {-0.854645, 0.518036, 0.033936},
513         {0.42514, -0.437866, -0.792114},
514         {-0.358948, 0.597046, 0.717377},
515         {-0.985413, 0.144714, 0.089294},
516         {-0.601776, -0.33728, -0.723907},
517         {-0.449921, 0.594513, 0.666382},
518         {0.208313, -0.10791, 0.972076},
519         {0.575317, 0.060425, 0.815643},
520         {0.293365, -0.875702, -0.383453},
521         {0.293762, 0.465759, 0.834686},
522         {-0.846008, -0.233398, -0.47934},
523         {-0.115814, 0.143036, -0.98291},
524         {0.204681, -0.949036, -0.239532},
525         {0.946716, -0.263947, 0.184326},
526         {-0.235596, 0.573822, 0.784332},
527         {0.203705, -0.372253, -0.905487},
528         {0.756989, -0.651031, 0.055298},
529         {0.497803, 0.814697, -0.297363},
530         {-0.16214, 0.063995, -0.98468},
531         {-0.329254, 0.834381, 0.441925},
532         {0.703827, -0.527039, -0.476227},
533         {0.956421, 0.266113, 0.119781},
534         {0.480133, 0.482849, 0.7323},
535         {-0.18631, 0.961212, -0.203125},
536         {-0.748474, -0.656921, -0.090393},
537         {-0.085052, -0.165253, 0.982544},
538         {-0.76947, 0.628174, -0.115234},
539         {0.383148, 0.537659, 0.751068},
540         {0.616486, -0.668488, -0.415924},
541         {-0.259979, -0.630005, 0.73175},
542         {0.570953, -0.087952, 0.816223},
543         {-0.458008, 0.023254, 0.888611},
544         {-0.196167, 0.976563, -0.088287},
545         {-0.263885, -0.69812, -0.665527},
546         {0.437134, -0.892273, -0.112793},
547         {-0.621674, -0.230438, 0.748566},
548         {0.232422, 0.900574, -0.367249},
549         {0.22229, -0.796143, 0.562744},
550         {-0.665497, -0.73764, 0.11377},
551         {0.670135, 0.704803, 0.232605},
552         {0.895599, 0.429749, -0.114655},
553         {-0.11557, -0.474243, 0.872742},
554         {0.621826, 0.604004, -0.498444},
555         {-0.832214, 0.012756, 0.55426},
556         {-0.702484, 0.705994, -0.089661},
557         {-0.692017, 0.649292, 0.315399},
558         {-0.175995, -0.977997, 0.111877},
559         {0.096954, -0.04953, 0.994019},
560         {0.635284, -0.606689, -0.477783},
561         {-0.261261, -0.607422, -0.750153},
562         {0.983276, 0.165436, 0.075958},
563         {-0.29837, 0.404083, -0.864655},
564         {-0.638672, 0.507721, 0.578156},
565         {0.388214, 0.412079, 0.824249},
566         {0.556183, -0.208832, 0.804352},
567         {0.778442, 0.562012, 0.27951},
568         {-0.616577, 0.781921, -0.091522},
569         {0.196289, 0.051056, 0.979187},
570         {-0.121216, 0.207153, -0.970734},
571         {-0.173401, -0.384735, 0.906555},
572         {0.161499, -0.723236, -0.671387},
573         {0.178497, -0.006226, -0.983887},
574         {-0.126038, 0.15799, 0.97934},
575         {0.830475, -0.024811, 0.556458},
576         {-0.510132, -0.76944, 0.384247},
577         {0.81424, 0.200104, -0.544891},
578         {-0.112549, -0.393311, -0.912445},
579         {0.56189, 0.152222, -0.813049},
580         {0.198914, -0.254517, -0.946381},
581         {-0.41217, 0.690979, -0.593811},
582         {-0.407257, 0.324524, 0.853668},
583         {-0.690186, 0.366119, -0.624115},
584         {-0.428345, 0.844147, -0.322296},
585         {-0.21228, -0.297546, -0.930756},
586         {-0.273071, 0.516113, 0.811798},
587         {0.928314, 0.371643, 0.007233},
588         {0.785828, -0.479218, -0.390778},
589         {-0.704895, 0.058929, 0.706818},
590         {0.173248, 0.203583, 0.963562},
591         {0.422211, -0.904297, -0.062469},
592         {-0.363312, -0.182465, 0.913605},
593         {0.254028, -0.552307, -0.793945},
594         {-0.28891, -0.765747, -0.574554},
595         {0.058319, 0.291382, 0.954803},
596         {0.946136, -0.303925, 0.111267},
597         {-0.078156, 0.443695, -0.892731},
598         {0.182098, 0.89389, 0.409515},
599         {-0.680298, -0.213318, 0.701141},
600         {0.062469, 0.848389, -0.525635},
601         {-0.72879, -0.641846, 0.238342},
602         {-0.88089, 0.427673, 0.202637},
603         {-0.532501, -0.21405, 0.818878},
604         {0.948975, -0.305084, 0.07962},
605         {0.925446, 0.374664, 0.055817},
606         {0.820923, 0.565491, 0.079102},
607         {0.25882, 0.099792, -0.960724},
608         {-0.294617, 0.910522, 0.289978},
609         {0.137115, 0.320038, -0.937408},
610         {-0.908386, 0.345276, -0.235718},
611         {-0.936218, 0.138763, 0.322754},
612         {0.366577, 0.925934, -0.090637},
613         {0.309296, -0.686829, -0.657684},
614         {0.66983, 0.024445, 0.742065},
615         {-0.917999, -0.059113, -0.392059},
616         {0.365509, 0.462158, -0.807922},
617         {0.083374, 0.996399, -0.014801},
618         {0.593842, 0.253143, -0.763672},
619         {0.974976, -0.165466, 0.148285},
620         {0.918976, 0.137299, 0.369537},
621         {0.294952, 0.694977, 0.655731},
622         {0.943085, 0.152618, -0.295319},
623         {0.58783, -0.598236, 0.544495},
624         {0.203796, 0.678223, 0.705994},
625         {-0.478821, -0.661011, 0.577667},
626         {0.719055, -0.1698, -0.673828},
627         {-0.132172, -0.965332, 0.225006},
628         {-0.981873, -0.14502, 0.121979},
629         {0.763458, 0.579742, 0.284546},
630         {-0.893188, 0.079681, 0.442474},
631         {-0.795776, -0.523804, 0.303802},
632         {0.734955, 0.67804, -0.007446},
633         {0.15506, 0.986267, -0.056183},
634         {0.258026, 0.571503, -0.778931},
635         {-0.681549, -0.702087, -0.206116},
636         {-0.96286, -0.177185, 0.203613},
637         {-0.470978, -0.515106, 0.716095},
638         {-0.740326, 0.57135, 0.354095},
639         {-0.56012, -0.824982, -0.074982},
640         {-0.507874, 0.753204, 0.417969},
641         {-0.503113, 0.038147, 0.863342},
642         {0.594025, 0.673553, -0.439758},
643         {-0.119873, -0.005524, -0.992737},
644         {0.098267, -0.213776, 0.971893},
645         {-0.615631, 0.643951, 0.454163},
646         {0.896851, -0.441071, 0.032166},
647         {-0.555023, 0.750763, -0.358093},
648         {0.398773, 0.304688, 0.864929},
649         {-0.722961, 0.303589, 0.620544},
650         {-0.63559, -0.621948, -0.457306},
651         {-0.293243, 0.072327, 0.953278},
652         {-0.491638, 0.661041, -0.566772},
653         {-0.304199, -0.572083, -0.761688},
654         {0.908081, -0.398956, 0.127014},
655         {-0.523621, -0.549683, -0.650848},
656         {-0.932922, -0.19986, 0.299408},
657         {0.099426, 0.140869, 0.984985},
658         {-0.020325, -0.999756, -0.002319},
659         {0.952667, 0.280853, -0.11615},
660         {-0.971893, 0.082581, 0.220337},
661         {0.65921, 0.705292, -0.260651},
662         {0.733063, -0.175537, 0.657043},
663         {-0.555206, 0.429504, -0.712189},
664         {0.400421, -0.89859, 0.179352},
665         {0.750885, -0.19696, 0.630341},
666         {0.785675, -0.569336, 0.241821},
667         {-0.058899, -0.464111, 0.883789},
668         {0.129608, -0.94519, 0.299622},
669         {-0.357819, 0.907654, 0.219238},
670         {-0.842133, -0.439117, -0.312927},
671         {-0.313477, 0.84433, 0.434479},
672         {-0.241211, 0.053253, 0.968994},
673         {0.063873, 0.823273, 0.563965},
674         {0.476288, 0.862152, -0.172516},
675         {0.620941, -0.298126, 0.724915},
676         {0.25238, -0.749359, -0.612122},
677         {-0.577545, 0.386566, 0.718994},
678         {-0.406342, -0.737976, 0.538696},
679         {0.04718, 0.556305, 0.82959},
680         {-0.802856, 0.587463, 0.101166},
681         {-0.707733, -0.705963, 0.026428},
682         {0.374908, 0.68457, 0.625092},
683         {0.472137, 0.208405, -0.856506},
684         {-0.703064, -0.581085, -0.409821},
685         {-0.417206, -0.736328, 0.532623},
686         {-0.447876, -0.20285, -0.870728},
687         {0.086945, -0.990417, 0.107086},
688         {0.183685, 0.018341, -0.982788},
689         {0.560638, -0.428864, 0.708282},
690         {0.296722, -0.952576, -0.0672},
691         {0.135773, 0.990265, 0.030243},
692         {-0.068787, 0.654724, 0.752686},
693         {0.762604, -0.551758, 0.337585},
694         {-0.819611, -0.407684, 0.402466},
695         {-0.727844, -0.55072, -0.408539},
696         {-0.855774, -0.480011, 0.19281},
697         {0.693176, -0.079285, 0.716339},
698         {0.226013, 0.650116, -0.725433},
699         {0.246704, 0.953369, -0.173553},
700         {-0.970398, -0.239227, -0.03244},
701         {0.136383, -0.394318, 0.908752},
702         {0.813232, 0.558167, 0.164368},
703         {0.40451, 0.549042, -0.731323},
704         {-0.380249, -0.566711, 0.730865},
705         {0.022156, 0.932739, 0.359741},
706         {0.00824, 0.996552, -0.082306},
707         {0.956635, -0.065338, -0.283722},
708         {-0.743561, 0.008209, 0.668579},
709         {-0.859589, -0.509674, 0.035767},
710         {-0.852234, 0.363678, -0.375977},
711         {-0.201965, -0.970795, -0.12915},
712         {0.313477, 0.947327, 0.06546},
713         {-0.254028, -0.528259, 0.81015},
714         {0.628052, 0.601105, 0.49411},
715         {-0.494385, 0.868378, 0.037933},
716         {0.275635, -0.086426, 0.957336},
717         {-0.197937, 0.468903, -0.860748},
718         {0.895599, 0.399384, 0.195801},
719         {0.560791, 0.825012, -0.069214},
720         {0.304199, -0.849487, 0.43103},
721         {0.096375, 0.93576, 0.339111},
722         {-0.051422, 0.408966, -0.911072},
723         {0.330444, 0.942841, -0.042389},
724         {-0.452362, -0.786407, 0.420563},
725         {0.134308, -0.933472, -0.332489},
726         {0.80191, -0.566711, -0.188934},
727         {-0.987946, -0.105988, 0.112518},
728         {-0.24408, 0.892242, -0.379791},
729         {-0.920502, 0.229095, -0.316376},
730         {0.7789, 0.325958, 0.535706},
731         {-0.912872, 0.185211, -0.36377},
732         {-0.184784, 0.565369, -0.803833},
733         {-0.018463, 0.119537, 0.992615},
734         {-0.259247, -0.935608, 0.239532},
735         {-0.82373, -0.449127, -0.345947},
736         {-0.433105, 0.659515, 0.614349},
737         {-0.822754, 0.378845, -0.423676},
738         {0.687195, -0.674835, -0.26889},
739         {-0.246582, -0.800842, 0.545715},
740         {-0.729187, -0.207794, 0.651978},
741         {0.653534, -0.610443, -0.447388},
742         {0.492584, -0.023346, 0.869934},
743         {0.609039, 0.009094, -0.79306},
744         {0.962494, -0.271088, -0.00885},
745         {0.2659, -0.004913, 0.963959},
746         {0.651245, 0.553619, -0.518951},
747         {0.280548, -0.84314, 0.458618},
748         {-0.175293, -0.983215, 0.049805},
749         {0.035339, -0.979919, 0.196045},
750         {-0.982941, 0.164307, -0.082245},
751         {0.233734, -0.97226, -0.005005},
752         {-0.747253, -0.611328, 0.260437},
753         {0.645599, 0.592773, 0.481384},
754         {0.117706, -0.949524, -0.29068},
755         {-0.535004, -0.791901, -0.294312},
756         {-0.627167, -0.214447, 0.748718},
757         {-0.047974, -0.813477, -0.57959},
758         {-0.175537, 0.477264, -0.860992},
759         {0.738556, -0.414246, -0.53183},
760         {0.562561, -0.704071, 0.433289},
761         {-0.754944, 0.64801, -0.100586},
762         {0.114716, 0.044525, -0.992371},
763         {0.966003, 0.244873, -0.082764},
764         {0.33783, 0.715698, -0.611206},
765         {-0.944031, -0.326599, -0.045624},
766         {-0.101074, -0.416443, -0.903503},
767         {0.799286, 0.49411, -0.341949},
768         {-0.854645, 0.518036, 0.033936},
769         {0.42514, -0.437866, -0.792114},
770         {-0.358948, 0.597046, 0.717377},
771         {-0.985413, 0.144714, 0.089294},
772         {-0.601776, -0.33728, -0.723907},
773         {-0.449921, 0.594513, 0.666382},
774         {0.208313, -0.10791, 0.972076},
775         {0.575317, 0.060425, 0.815643},
776         {0.293365, -0.875702, -0.383453},
777         {0.293762, 0.465759, 0.834686},
778         {-0.846008, -0.233398, -0.47934},
779         {-0.115814, 0.143036, -0.98291},
780         {0.204681, -0.949036, -0.239532},
781         {0.946716, -0.263947, 0.184326},
782         {-0.235596, 0.573822, 0.784332},
783         {0.203705, -0.372253, -0.905487},
784         {0.756989, -0.651031, 0.055298},
785         {0.497803, 0.814697, -0.297363},
786         {-0.16214, 0.063995, -0.98468},
787         {-0.329254, 0.834381, 0.441925},
788         {0.703827, -0.527039, -0.476227},
789         {0.956421, 0.266113, 0.119781},
790         {0.480133, 0.482849, 0.7323},
791         {-0.18631, 0.961212, -0.203125},
792         {-0.748474, -0.656921, -0.090393},
793         {-0.085052, -0.165253, 0.982544},
794         {-0.76947, 0.628174, -0.115234},
795         {0.383148, 0.537659, 0.751068},
796         {0.616486, -0.668488, -0.415924},
797         {-0.259979, -0.630005, 0.73175},
798         {0.570953, -0.087952, 0.816223},
799         {-0.458008, 0.023254, 0.888611},
800         {-0.196167, 0.976563, -0.088287},
801         {-0.263885, -0.69812, -0.665527},
802         {0.437134, -0.892273, -0.112793},
803         {-0.621674, -0.230438, 0.748566},
804         {0.232422, 0.900574, -0.367249},
805         {0.22229, -0.796143, 0.562744},
806         {-0.665497, -0.73764, 0.11377},
807         {0.670135, 0.704803, 0.232605},
808         {0.895599, 0.429749, -0.114655},
809         {-0.11557, -0.474243, 0.872742},
810         {0.621826, 0.604004, -0.498444},
811         {-0.832214, 0.012756, 0.55426},
812         {-0.702484, 0.705994, -0.089661},
813         {-0.692017, 0.649292, 0.315399},
814         {-0.175995, -0.977997, 0.111877},
815         {0.096954, -0.04953, 0.994019},
816         {0.635284, -0.606689, -0.477783},
817         {-0.261261, -0.607422, -0.750153},
818         {0.983276, 0.165436, 0.075958},
819         {-0.29837, 0.404083, -0.864655},
820         {-0.638672, 0.507721, 0.578156},
821         {0.388214, 0.412079, 0.824249},
822         {0.556183, -0.208832, 0.804352},
823         {0.778442, 0.562012, 0.27951},
824         {-0.616577, 0.781921, -0.091522},
825         {0.196289, 0.051056, 0.979187},
826         {-0.121216, 0.207153, -0.970734},
827         {-0.173401, -0.384735, 0.906555},
828         {0.161499, -0.723236, -0.671387},
829         {0.178497, -0.006226, -0.983887},
830         {-0.126038, 0.15799, 0.97934},
831         {0.830475, -0.024811, 0.556458},
832         {-0.510132, -0.76944, 0.384247},
833         {0.81424, 0.200104, -0.544891},
834         {-0.112549, -0.393311, -0.912445},
835         {0.56189, 0.152222, -0.813049},
836         {0.198914, -0.254517, -0.946381},
837         {-0.41217, 0.690979, -0.593811},
838         {-0.407257, 0.324524, 0.853668},
839         {-0.690186, 0.366119, -0.624115},
840         {-0.428345, 0.844147, -0.322296},
841         {-0.21228, -0.297546, -0.930756},
842         {-0.273071, 0.516113, 0.811798},
843         {0.928314, 0.371643, 0.007233},
844         {0.785828, -0.479218, -0.390778},
845         {-0.704895, 0.058929, 0.706818},
846         {0.173248, 0.203583, 0.963562},
847         {0.422211, -0.904297, -0.062469},
848         {-0.363312, -0.182465, 0.913605},
849         {0.254028, -0.552307, -0.793945},
850         {-0.28891, -0.765747, -0.574554},
851         {0.058319, 0.291382, 0.954803},
852         {0.946136, -0.303925, 0.111267},
853         {-0.078156, 0.443695, -0.892731},
854         {0.182098, 0.89389, 0.409515},
855         {-0.680298, -0.213318, 0.701141},
856         {0.062469, 0.848389, -0.525635},
857         {-0.72879, -0.641846, 0.238342},
858         {-0.88089, 0.427673, 0.202637},
859         {-0.532501, -0.21405, 0.818878},
860         {0.948975, -0.305084, 0.07962},
861         {0.925446, 0.374664, 0.055817},
862         {0.820923, 0.565491, 0.079102},
863         {0.25882, 0.099792, -0.960724},
864         {-0.294617, 0.910522, 0.289978},
865         {0.137115, 0.320038, -0.937408},
866         {-0.908386, 0.345276, -0.235718},
867         {-0.936218, 0.138763, 0.322754},
868         {0.366577, 0.925934, -0.090637},
869         {0.309296, -0.686829, -0.657684},
870         {0.66983, 0.024445, 0.742065},
871         {-0.917999, -0.059113, -0.392059},
872         {0.365509, 0.462158, -0.807922},
873         {0.083374, 0.996399, -0.014801},
874         {0.593842, 0.253143, -0.763672},
875         {0.974976, -0.165466, 0.148285},
876         {0.918976, 0.137299, 0.369537},
877         {0.294952, 0.694977, 0.655731},
878         {0.943085, 0.152618, -0.295319},
879         {0.58783, -0.598236, 0.544495},
880         {0.203796, 0.678223, 0.705994},
881         {-0.478821, -0.661011, 0.577667},
882         {0.719055, -0.1698, -0.673828},
883         {-0.132172, -0.965332, 0.225006},
884         {-0.981873, -0.14502, 0.121979},
885         {0.763458, 0.579742, 0.284546},
886         {-0.893188, 0.079681, 0.442474},
887         {-0.795776, -0.523804, 0.303802},
888         {0.734955, 0.67804, -0.007446},
889         {0.15506, 0.986267, -0.056183},
890         {0.258026, 0.571503, -0.778931},
891         {-0.681549, -0.702087, -0.206116},
892         {-0.96286, -0.177185, 0.203613},
893         {-0.470978, -0.515106, 0.716095},
894         {-0.740326, 0.57135, 0.354095},
895         {-0.56012, -0.824982, -0.074982},
896         {-0.507874, 0.753204, 0.417969},
897         {-0.503113, 0.038147, 0.863342},
898         {0.594025, 0.673553, -0.439758},
899         {-0.119873, -0.005524, -0.992737},
900         {0.098267, -0.213776, 0.971893},
901         {-0.615631, 0.643951, 0.454163},
902         {0.896851, -0.441071, 0.032166},
903         {-0.555023, 0.750763, -0.358093},
904         {0.398773, 0.304688, 0.864929},
905         {-0.722961, 0.303589, 0.620544},
906         {-0.63559, -0.621948, -0.457306},
907         {-0.293243, 0.072327, 0.953278},
908         {-0.491638, 0.661041, -0.566772},
909         {-0.304199, -0.572083, -0.761688},
910         {0.908081, -0.398956, 0.127014},
911         {-0.523621, -0.549683, -0.650848},
912         {-0.932922, -0.19986, 0.299408},
913         {0.099426, 0.140869, 0.984985},
914         {-0.020325, -0.999756, -0.002319},
915         {0.952667, 0.280853, -0.11615},
916         {-0.971893, 0.082581, 0.220337},
917         {0.65921, 0.705292, -0.260651},
918         {0.733063, -0.175537, 0.657043},
919         {-0.555206, 0.429504, -0.712189},
920         {0.400421, -0.89859, 0.179352},
921         {0.750885, -0.19696, 0.630341},
922         {0.785675, -0.569336, 0.241821},
923         {-0.058899, -0.464111, 0.883789},
924         {0.129608, -0.94519, 0.299622},
925         {-0.357819, 0.907654, 0.219238},
926         {-0.842133, -0.439117, -0.312927},
927         {-0.313477, 0.84433, 0.434479},
928         {-0.241211, 0.053253, 0.968994},
929         {0.063873, 0.823273, 0.563965},
930         {0.476288, 0.862152, -0.172516},
931         {0.620941, -0.298126, 0.724915},
932         {0.25238, -0.749359, -0.612122},
933         {-0.577545, 0.386566, 0.718994},
934         {-0.406342, -0.737976, 0.538696},
935         {0.04718, 0.556305, 0.82959},
936         {-0.802856, 0.587463, 0.101166},
937         {-0.707733, -0.705963, 0.026428},
938         {0.374908, 0.68457, 0.625092},
939         {0.472137, 0.208405, -0.856506},
940         {-0.703064, -0.581085, -0.409821},
941         {-0.417206, -0.736328, 0.532623},
942         {-0.447876, -0.20285, -0.870728},
943         {0.086945, -0.990417, 0.107086},
944         {0.183685, 0.018341, -0.982788},
945         {0.560638, -0.428864, 0.708282},
946         {0.296722, -0.952576, -0.0672},
947         {0.135773, 0.990265, 0.030243},
948         {-0.068787, 0.654724, 0.752686},
949         {0.762604, -0.551758, 0.337585},
950         {-0.819611, -0.407684, 0.402466},
951         {-0.727844, -0.55072, -0.408539},
952         {-0.855774, -0.480011, 0.19281},
953         {0.693176, -0.079285, 0.716339},
954         {0.226013, 0.650116, -0.725433},
955         {0.246704, 0.953369, -0.173553},
956         {-0.970398, -0.239227, -0.03244},
957         {0.136383, -0.394318, 0.908752},
958         {0.813232, 0.558167, 0.164368},
959         {0.40451, 0.549042, -0.731323},
960         {-0.380249, -0.566711, 0.730865},
961         {0.022156, 0.932739, 0.359741},
962         {0.00824, 0.996552, -0.082306},
963         {0.956635, -0.065338, -0.283722},
964         {-0.743561, 0.008209, 0.668579},
965         {-0.859589, -0.509674, 0.035767},
966         {-0.852234, 0.363678, -0.375977},
967         {-0.201965, -0.970795, -0.12915},
968         {0.313477, 0.947327, 0.06546},
969         {-0.254028, -0.528259, 0.81015},
970         {0.628052, 0.601105, 0.49411},
971         {-0.494385, 0.868378, 0.037933},
972         {0.275635, -0.086426, 0.957336},
973         {-0.197937, 0.468903, -0.860748},
974         {0.895599, 0.399384, 0.195801},
975         {0.560791, 0.825012, -0.069214},
976         {0.304199, -0.849487, 0.43103},
977         {0.096375, 0.93576, 0.339111},
978         {-0.051422, 0.408966, -0.911072},
979         {0.330444, 0.942841, -0.042389},
980         {-0.452362, -0.786407, 0.420563},
981         {0.134308, -0.933472, -0.332489},
982         {0.80191, -0.566711, -0.188934},
983         {-0.987946, -0.105988, 0.112518},
984         {-0.24408, 0.892242, -0.379791},
985         {-0.920502, 0.229095, -0.316376},
986         {0.7789, 0.325958, 0.535706},
987         {-0.912872, 0.185211, -0.36377},
988         {-0.184784, 0.565369, -0.803833},
989         {-0.018463, 0.119537, 0.992615},
990         {-0.259247, -0.935608, 0.239532},
991         {-0.82373, -0.449127, -0.345947},
992         {-0.433105, 0.659515, 0.614349},
993         {-0.822754, 0.378845, -0.423676},
994         {0.687195, -0.674835, -0.26889},
995         {-0.246582, -0.800842, 0.545715},
996         {-0.729187, -0.207794, 0.651978},
997         {0.653534, -0.610443, -0.447388},
998         {0.492584, -0.023346, 0.869934},
999         {0.609039, 0.009094, -0.79306},
1000         {0.962494, -0.271088, -0.00885},
1001         {0.2659, -0.004913, 0.963959},
1002         {0.651245, 0.553619, -0.518951},
1003         {0.280548, -0.84314, 0.458618},
1004         {-0.175293, -0.983215, 0.049805},
1005         {0.035339, -0.979919, 0.196045},
1006         {-0.982941, 0.164307, -0.082245},
1007         {0.233734, -0.97226, -0.005005},
1008         {-0.747253, -0.611328, 0.260437},
1009         {0.645599, 0.592773, 0.481384},
1010         {0.117706, -0.949524, -0.29068},
1011         {-0.535004, -0.791901, -0.294312},
1012         {-0.627167, -0.214447, 0.748718},
1013         {-0.047974, -0.813477, -0.57959},
1014         {-0.175537, 0.477264, -0.860992},
1015         {0.738556, -0.414246, -0.53183},
1016         {0.562561, -0.704071, 0.433289},
1017         {-0.754944, 0.64801, -0.100586},
1018         {0.114716, 0.044525, -0.992371},
1019         {0.966003, 0.244873, -0.082764},
1020         {0.33783, 0.715698, -0.611206},
1021         {-0.944031, -0.326599, -0.045624},
1022 };
1023
1024 #define SETUP(val, b0, b1, r0, r1)                                            \
1025         {                                                                         \
1026                 t = val + 10000.0f;                                                   \
1027                 b0 = ((int)t) & 255;                                                  \
1028                 b1 = (b0 + 1) & 255;                                                  \
1029                 r0 = t - floorf(t);                                                   \
1030                 r1 = r0 - 1.0f;                                                       \
1031         } (void)0
1032
1033
1034 static float noise3_perlin(float vec[3])
1035 {
1036         int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11;
1037         float rx0, rx1, ry0, ry1, rz0, rz1, *q, sx, sy, sz, a, b, c, d, t, u, v;
1038         register int i, j;
1039
1040
1041         SETUP(vec[0],  bx0, bx1,  rx0, rx1);
1042         SETUP(vec[1],  by0, by1,  ry0, ry1);
1043         SETUP(vec[2],  bz0, bz1,  rz0, rz1);
1044
1045         i = p[bx0];
1046         j = p[bx1];
1047
1048         b00 = p[i + by0];
1049         b10 = p[j + by0];
1050         b01 = p[i + by1];
1051         b11 = p[j + by1];
1052
1053 #define VALUE_AT(rx, ry, rz) (rx * q[0] + ry * q[1] + rz * q[2])
1054 #define SURVE(t) (t * t * (3.0f - 2.0f * t))
1055
1056 /* lerp moved to improved perlin above */
1057
1058         sx = SURVE(rx0);
1059         sy = SURVE(ry0);
1060         sz = SURVE(rz0);
1061
1062
1063         q = g[b00 + bz0];
1064         u = VALUE_AT(rx0, ry0, rz0);
1065         q = g[b10 + bz0];
1066         v = VALUE_AT(rx1, ry0, rz0);
1067         a = lerp(sx, u, v);
1068
1069         q = g[b01 + bz0];
1070         u = VALUE_AT(rx0, ry1, rz0);
1071         q = g[b11 + bz0];
1072         v = VALUE_AT(rx1, ry1, rz0);
1073         b = lerp(sx, u, v);
1074
1075         c = lerp(sy, a, b);          /* interpolate in y at lo x */
1076
1077         q = g[b00 + bz1];
1078         u = VALUE_AT(rx0, ry0, rz1);
1079         q = g[b10 + bz1];
1080         v = VALUE_AT(rx1, ry0, rz1);
1081         a = lerp(sx, u, v);
1082
1083         q = g[b01 + bz1];
1084         u = VALUE_AT(rx0, ry1, rz1);
1085         q = g[b11 + bz1];
1086         v = VALUE_AT(rx1, ry1, rz1);
1087         b = lerp(sx, u, v);
1088
1089         d = lerp(sy, a, b);          /* interpolate in y at hi x */
1090
1091         return 1.5f * lerp(sz, c, d); /* interpolate in z */
1092
1093 #undef VALUE_AT
1094 #undef SURVE
1095 }
1096
1097 #if 0
1098 static float turbulence_perlin(float *point, float lofreq, float hifreq)
1099 {
1100         float freq, t, p[3];
1101
1102         p[0] = point[0] + 123.456;
1103         p[1] = point[1];
1104         p[2] = point[2];
1105
1106         t = 0;
1107         for (freq = lofreq; freq < hifreq; freq *= 2.0) {
1108                 t += fabsf(noise3_perlin(p)) / freq;
1109                 p[0] *= 2.0f;
1110                 p[1] *= 2.0f;
1111                 p[2] *= 2.0f;
1112         }
1113         return t - 0.3; /* readjust to make mean value = 0.0 */
1114 }
1115 #endif
1116
1117 /* for use with BLI_gNoise/gTurbulence, returns signed noise */
1118 static float orgPerlinNoise(float x, float y, float z)
1119 {
1120         float v[3];
1121
1122         v[0] = x;
1123         v[1] = y;
1124         v[2] = z;
1125         return noise3_perlin(v);
1126 }
1127
1128 /* for use with BLI_gNoise/gTurbulence, returns unsigned noise */
1129 static float orgPerlinNoiseU(float x, float y, float z)
1130 {
1131         float v[3];
1132
1133         v[0] = x;
1134         v[1] = y;
1135         v[2] = z;
1136         return (0.5f + 0.5f * noise3_perlin(v));
1137 }
1138
1139 /* *************** CALL AS: *************** */
1140
1141 float BLI_hnoisep(float noisesize, float x, float y, float z)
1142 {
1143         float vec[3];
1144
1145         vec[0] = x / noisesize;
1146         vec[1] = y / noisesize;
1147         vec[2] = z / noisesize;
1148
1149         return noise3_perlin(vec);
1150 }
1151
1152 #if 0
1153 static float turbulencep(float noisesize, float x, float y, float z, int nr)
1154 {
1155         float vec[3];
1156
1157         vec[0] = x / noisesize;
1158         vec[1] = y / noisesize;
1159         vec[2] = z / noisesize;
1160         nr++;
1161         return turbulence_perlin(vec, 1.0, (float)(1 << nr));
1162 }
1163 #endif
1164
1165 /******************/
1166 /* VORONOI/WORLEY */
1167 /******************/
1168
1169 /* distance metrics for voronoi, e parameter only used in Minkowski */
1170 /* Camberra omitted, didn't seem useful */
1171
1172 /* distance squared */
1173 static float dist_Squared(float x, float y, float z, float e)
1174 {
1175         (void)e; return (x * x + y * y + z * z);
1176 }
1177 /* real distance */
1178 static float dist_Real(float x, float y, float z, float e)
1179 {
1180         (void)e; return sqrtf(x * x + y * y + z * z);
1181 }
1182 /* manhattan/taxicab/cityblock distance */
1183 static float dist_Manhattan(float x, float y, float z, float e)
1184 {
1185         (void)e; return (fabsf(x) + fabsf(y) + fabsf(z));
1186 }
1187 /* Chebychev */
1188 static float dist_Chebychev(float x, float y, float z, float e)
1189 {
1190         float t;
1191         (void)e;
1192
1193         x = fabsf(x);
1194         y = fabsf(y);
1195         z = fabsf(z);
1196         t = (x > y) ? x : y;
1197         return ((z > t) ? z : t);
1198 }
1199
1200 /* minkowski preset exponent 0.5 */
1201 static float dist_MinkovskyH(float x, float y, float z, float e)
1202 {
1203         float d = sqrtf(fabsf(x)) + sqrtf(fabsf(y)) + sqrtf(fabsf(z));
1204         (void)e;
1205         return (d * d);
1206 }
1207
1208 /* minkowski preset exponent 4 */
1209 static float dist_Minkovsky4(float x, float y, float z, float e)
1210 {
1211         (void)e;
1212         x *= x;
1213         y *= y;
1214         z *= z;
1215         return sqrtf(sqrtf(x * x + y * y + z * z));
1216 }
1217
1218 /* Minkowski, general case, slow, maybe too slow to be useful */
1219 static float dist_Minkovsky(float x, float y, float z, float e)
1220 {
1221         return powf(powf(fabsf(x), e) + powf(fabsf(y), e) + powf(fabsf(z), e), 1.0f / e);
1222 }
1223
1224
1225 /* Not 'pure' Worley, but the results are virtually the same.
1226  * Returns distances in da and point coords in pa */
1227 void voronoi(float x, float y, float z, float *da, float *pa, float me, int dtype)
1228 {
1229         int xx, yy, zz, xi, yi, zi;
1230         float xd, yd, zd, d, *p;
1231
1232         float (*distfunc)(float, float, float, float);
1233         switch (dtype) {
1234                 case 1:
1235                         distfunc = dist_Squared;
1236                         break;
1237                 case 2:
1238                         distfunc = dist_Manhattan;
1239                         break;
1240                 case 3:
1241                         distfunc = dist_Chebychev;
1242                         break;
1243                 case 4:
1244                         distfunc = dist_MinkovskyH;
1245                         break;
1246                 case 5:
1247                         distfunc = dist_Minkovsky4;
1248                         break;
1249                 case 6:
1250                         distfunc = dist_Minkovsky;
1251                         break;
1252                 case 0:
1253                 default:
1254                         distfunc = dist_Real;
1255         }
1256
1257         xi = (int)(floor(x));
1258         yi = (int)(floor(y));
1259         zi = (int)(floor(z));
1260         da[0] = da[1] = da[2] = da[3] = 1e10f;
1261         for (xx = xi - 1; xx <= xi + 1; xx++) {
1262                 for (yy = yi - 1; yy <= yi + 1; yy++) {
1263                         for (zz = zi - 1; zz <= zi + 1; zz++) {
1264                                 p = HASHPNT(xx, yy, zz);
1265                                 xd = x - (p[0] + xx);
1266                                 yd = y - (p[1] + yy);
1267                                 zd = z - (p[2] + zz);
1268                                 d = distfunc(xd, yd, zd, me);
1269                                 if (d < da[0]) {
1270                                         da[3] = da[2];  da[2] = da[1];  da[1] = da[0];  da[0] = d;
1271                                         pa[9] = pa[6];  pa[10] = pa[7];  pa[11] = pa[8];
1272                                         pa[6] = pa[3];  pa[7] = pa[4];  pa[8] = pa[5];
1273                                         pa[3] = pa[0];  pa[4] = pa[1];  pa[5] = pa[2];
1274                                         pa[0] = p[0] + xx;  pa[1] = p[1] + yy;  pa[2] = p[2] + zz;
1275                                 }
1276                                 else if (d < da[1]) {
1277                                         da[3] = da[2];  da[2] = da[1];  da[1] = d;
1278                                         pa[9] = pa[6];  pa[10] = pa[7];  pa[11] = pa[8];
1279                                         pa[6] = pa[3];  pa[7] = pa[4];  pa[8] = pa[5];
1280                                         pa[3] = p[0] + xx;  pa[4] = p[1] + yy;  pa[5] = p[2] + zz;
1281                                 }
1282                                 else if (d < da[2]) {
1283                                         da[3] = da[2];  da[2] = d;
1284                                         pa[9] = pa[6];  pa[10] = pa[7];  pa[11] = pa[8];
1285                                         pa[6] = p[0] + xx;  pa[7] = p[1] + yy;  pa[8] = p[2] + zz;
1286                                 }
1287                                 else if (d < da[3]) {
1288                                         da[3] = d;
1289                                         pa[9] = p[0] + xx;  pa[10] = p[1] + yy;  pa[11] = p[2] + zz;
1290                                 }
1291                         }
1292                 }
1293         }
1294 }
1295
1296 /* returns different feature points for use in BLI_gNoise() */
1297 static float voronoi_F1(float x, float y, float z)
1298 {
1299         float da[4], pa[12];
1300         voronoi(x, y, z, da, pa, 1, 0);
1301         return da[0];
1302 }
1303
1304 static float voronoi_F2(float x, float y, float z)
1305 {
1306         float da[4], pa[12];
1307         voronoi(x, y, z, da, pa, 1, 0);
1308         return da[1];
1309 }
1310
1311 static float voronoi_F3(float x, float y, float z)
1312 {
1313         float da[4], pa[12];
1314         voronoi(x, y, z, da, pa, 1, 0);
1315         return da[2];
1316 }
1317
1318 static float voronoi_F4(float x, float y, float z)
1319 {
1320         float da[4], pa[12];
1321         voronoi(x, y, z, da, pa, 1, 0);
1322         return da[3];
1323 }
1324
1325 static float voronoi_F1F2(float x, float y, float z)
1326 {
1327         float da[4], pa[12];
1328         voronoi(x, y, z, da, pa, 1, 0);
1329         return (da[1] - da[0]);
1330 }
1331
1332 /* Crackle type pattern, just a scale/clamp of F2-F1 */
1333 static float voronoi_Cr(float x, float y, float z)
1334 {
1335         float t = 10 * voronoi_F1F2(x, y, z);
1336         if (t > 1.f) return 1.f;
1337         return t;
1338 }
1339
1340
1341 /* Signed version of all 6 of the above, just 2x-1, not really correct though (range is potentially (0, sqrt(6)).
1342  * Used in the musgrave functions */
1343 static float voronoi_F1S(float x, float y, float z)
1344 {
1345         float da[4], pa[12];
1346         voronoi(x, y, z, da, pa, 1, 0);
1347         return (2.0f * da[0] - 1.0f);
1348 }
1349
1350 static float voronoi_F2S(float x, float y, float z)
1351 {
1352         float da[4], pa[12];
1353         voronoi(x, y, z, da, pa, 1, 0);
1354         return (2.0f * da[1] - 1.0f);
1355 }
1356
1357 static float voronoi_F3S(float x, float y, float z)
1358 {
1359         float da[4], pa[12];
1360         voronoi(x, y, z, da, pa, 1, 0);
1361         return (2.0f * da[2] - 1.0f);
1362 }
1363
1364 static float voronoi_F4S(float x, float y, float z)
1365 {
1366         float da[4], pa[12];
1367         voronoi(x, y, z, da, pa, 1, 0);
1368         return (2.0f * da[3] - 1.0f);
1369 }
1370
1371 static float voronoi_F1F2S(float x, float y, float z)
1372 {
1373         float da[4], pa[12];
1374         voronoi(x, y, z, da, pa, 1, 0);
1375         return (2.0f * (da[1] - da[0]) - 1.0f);
1376 }
1377
1378 /* Crackle type pattern, just a scale/clamp of F2-F1 */
1379 static float voronoi_CrS(float x, float y, float z)
1380 {
1381         float t = 10 * voronoi_F1F2(x, y, z);
1382         if (t > 1.f) return 1.f;
1383         return (2.0f * t - 1.0f);
1384 }
1385
1386
1387 /***************/
1388 /* voronoi end */
1389 /***************/
1390
1391 /*************/
1392 /* CELLNOISE */
1393 /*************/
1394
1395 /* returns unsigned cellnoise */
1396 static float cellNoiseU(float x, float y, float z)
1397 {
1398         int xi = (int)(floor(x));
1399         int yi = (int)(floor(y));
1400         int zi = (int)(floor(z));
1401         unsigned int n = xi + yi * 1301 + zi * 314159;
1402         n ^= (n << 13);
1403         return ((float)(n * (n * n * 15731 + 789221) + 1376312589) / 4294967296.0f);
1404 }
1405
1406 /* idem, signed */
1407 float cellNoise(float x, float y, float z)
1408 {
1409         return (2.0f * cellNoiseU(x, y, z) - 1.0f);
1410 }
1411
1412 /* returns a vector/point/color in ca, using point hasharray directly */
1413 void cellNoiseV(float x, float y, float z, float *ca)
1414 {
1415         int xi = (int)(floor(x));
1416         int yi = (int)(floor(y));
1417         int zi = (int)(floor(z));
1418         float *p = HASHPNT(xi, yi, zi);
1419         ca[0] = p[0];
1420         ca[1] = p[1];
1421         ca[2] = p[2];
1422 }
1423
1424
1425 /*****************/
1426 /* end cellnoise */
1427 /*****************/
1428
1429 /* newnoise: generic noise function for use with different noisebases */
1430 float BLI_gNoise(float noisesize, float x, float y, float z, int hard, int noisebasis)
1431 {
1432         float (*noisefunc)(float, float, float);
1433
1434         switch (noisebasis) {
1435                 case 1:
1436                         noisefunc = orgPerlinNoiseU;
1437                         break;
1438                 case 2:
1439                         noisefunc = newPerlinU;
1440                         break;
1441                 case 3:
1442                         noisefunc = voronoi_F1;
1443                         break;
1444                 case 4:
1445                         noisefunc = voronoi_F2;
1446                         break;
1447                 case 5:
1448                         noisefunc = voronoi_F3;
1449                         break;
1450                 case 6:
1451                         noisefunc = voronoi_F4;
1452                         break;
1453                 case 7:
1454                         noisefunc = voronoi_F1F2;
1455                         break;
1456                 case 8:
1457                         noisefunc = voronoi_Cr;
1458                         break;
1459                 case 14:
1460                         noisefunc = cellNoiseU;
1461                         break;
1462                 case 0:
1463                 default: {
1464                         noisefunc = orgBlenderNoise;
1465                         /* add one to make return value same as BLI_hnoise */
1466                         x += 1;
1467                         y += 1;
1468                         z += 1;
1469                 }
1470         }
1471
1472         if (noisesize != 0.0f) {
1473                 noisesize = 1.0f / noisesize;
1474                 x *= noisesize;
1475                 y *= noisesize;
1476                 z *= noisesize;
1477         }
1478         
1479         if (hard) return fabsf(2.0f * noisefunc(x, y, z) - 1.0f);
1480         return noisefunc(x, y, z);
1481 }
1482
1483 /* newnoise: generic turbulence function for use with different noisebasis */
1484 float BLI_gTurbulence(float noisesize, float x, float y, float z, int oct, int hard, int noisebasis)
1485 {
1486         float (*noisefunc)(float, float, float);
1487         float sum, t, amp = 1, fscale = 1;
1488         int i;
1489         
1490         switch (noisebasis) {
1491                 case 1:
1492                         noisefunc = orgPerlinNoiseU;
1493                         break;
1494                 case 2:
1495                         noisefunc = newPerlinU;
1496                         break;
1497                 case 3:
1498                         noisefunc = voronoi_F1;
1499                         break;
1500                 case 4:
1501                         noisefunc = voronoi_F2;
1502                         break;
1503                 case 5:
1504                         noisefunc = voronoi_F3;
1505                         break;
1506                 case 6:
1507                         noisefunc = voronoi_F4;
1508                         break;
1509                 case 7:
1510                         noisefunc = voronoi_F1F2;
1511                         break;
1512                 case 8:
1513                         noisefunc = voronoi_Cr;
1514                         break;
1515                 case 14:
1516                         noisefunc = cellNoiseU;
1517                         break;
1518                 case 0:
1519                 default:
1520                         noisefunc = orgBlenderNoise;
1521                         x += 1;
1522                         y += 1;
1523                         z += 1;
1524         }
1525
1526         if (noisesize != 0.0f) {
1527                 noisesize = 1.0f / noisesize;
1528                 x *= noisesize;
1529                 y *= noisesize;
1530                 z *= noisesize;
1531         }
1532
1533         sum = 0;
1534         for (i = 0; i <= oct; i++, amp *= 0.5f, fscale *= 2.0f) {
1535                 t = noisefunc(fscale * x, fscale * y, fscale * z);
1536                 if (hard) t = fabsf(2.0f * t - 1.0f);
1537                 sum += t * amp;
1538         }
1539         
1540         sum *= ((float)(1 << oct) / (float)((1 << (oct + 1)) - 1));
1541
1542         return sum;
1543
1544 }
1545
1546
1547 /*
1548  * The following code is based on Ken Musgrave's explanations and sample
1549  * source code in the book "Texturing and Modelling: A procedural approach"
1550  */
1551
1552 /*
1553  * Procedural fBm evaluated at "point"; returns value stored in "value".
1554  *
1555  * Parameters:
1556  *    ``H''  is the fractal increment parameter
1557  *    ``lacunarity''  is the gap between successive frequencies
1558  *    ``octaves''  is the number of frequencies in the fBm
1559  */
1560 float mg_fBm(float x, float y, float z, float H, float lacunarity, float octaves, int noisebasis)
1561 {
1562         float rmd, value = 0.0, pwr = 1.0, pwHL = powf(lacunarity, -H);
1563         int i;
1564
1565         float (*noisefunc)(float, float, float);
1566         switch (noisebasis) {
1567                 case 1:
1568                         noisefunc = orgPerlinNoise;
1569                         break;
1570                 case 2:
1571                         noisefunc = newPerlin;
1572                         break;
1573                 case 3:
1574                         noisefunc = voronoi_F1S;
1575                         break;
1576                 case 4:
1577                         noisefunc = voronoi_F2S;
1578                         break;
1579                 case 5:
1580                         noisefunc = voronoi_F3S;
1581                         break;
1582                 case 6:
1583                         noisefunc = voronoi_F4S;
1584                         break;
1585                 case 7:
1586                         noisefunc = voronoi_F1F2S;
1587                         break;
1588                 case 8:
1589                         noisefunc = voronoi_CrS;
1590                         break;
1591                 case 14:
1592                         noisefunc = cellNoise;
1593                         break;
1594                 case 0:
1595                 default: {
1596                         noisefunc = orgBlenderNoiseS;
1597                 }
1598         }
1599         
1600         for (i = 0; i < (int)octaves; i++) {
1601                 value += noisefunc(x, y, z) * pwr;
1602                 pwr *= pwHL;
1603                 x *= lacunarity;
1604                 y *= lacunarity;
1605                 z *= lacunarity;
1606         }
1607
1608         rmd = octaves - floorf(octaves);
1609         if (rmd != 0.f) value += rmd * noisefunc(x, y, z) * pwr;
1610
1611         return value;
1612
1613 } /* fBm() */
1614
1615
1616 /*
1617  * Procedural multifractal evaluated at "point";
1618  * returns value stored in "value".
1619  *
1620  * Parameters:
1621  *    ``H''  determines the highest fractal dimension
1622  *    ``lacunarity''  is gap between successive frequencies
1623  *    ``octaves''  is the number of frequencies in the fBm
1624  *    ``offset''  is the zero offset, which determines multifractality (NOT USED??)
1625  */
1626
1627 /* this one is in fact rather confusing,
1628  * there seem to be errors in the original source code (in all three versions of proc.text&mod),
1629  * I modified it to something that made sense to me, so it might be wrong... */
1630 float mg_MultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, int noisebasis)
1631 {
1632         float rmd, value = 1.0, pwr = 1.0, pwHL = powf(lacunarity, -H);
1633         int i;
1634
1635         float (*noisefunc)(float, float, float);
1636         switch (noisebasis) {
1637                 case 1:
1638                         noisefunc = orgPerlinNoise;
1639                         break;
1640                 case 2:
1641                         noisefunc = newPerlin;
1642                         break;
1643                 case 3:
1644                         noisefunc = voronoi_F1S;
1645                         break;
1646                 case 4:
1647                         noisefunc = voronoi_F2S;
1648                         break;
1649                 case 5:
1650                         noisefunc = voronoi_F3S;
1651                         break;
1652                 case 6:
1653                         noisefunc = voronoi_F4S;
1654                         break;
1655                 case 7:
1656                         noisefunc = voronoi_F1F2S;
1657                         break;
1658                 case 8:
1659                         noisefunc = voronoi_CrS;
1660                         break;
1661                 case 14:
1662                         noisefunc = cellNoise;
1663                         break;
1664                 case 0:
1665                 default: {
1666                         noisefunc = orgBlenderNoiseS;
1667                 }
1668         }
1669
1670         for (i = 0; i < (int)octaves; i++) {
1671                 value *= (pwr * noisefunc(x, y, z) + 1.0f);
1672                 pwr *= pwHL;
1673                 x *= lacunarity;
1674                 y *= lacunarity;
1675                 z *= lacunarity;
1676         }
1677         rmd = octaves - floorf(octaves);
1678         if (rmd != 0.0f) value *= (rmd * noisefunc(x, y, z) * pwr + 1.0f);
1679
1680         return value;
1681
1682 } /* multifractal() */
1683
1684 /*
1685  * Heterogeneous procedural terrain function: stats by altitude method.
1686  * Evaluated at "point"; returns value stored in "value".
1687  *
1688  * Parameters:
1689  *       ``H''  determines the fractal dimension of the roughest areas
1690  *       ``lacunarity''  is the gap between successive frequencies
1691  *       ``octaves''  is the number of frequencies in the fBm
1692  *       ``offset''  raises the terrain from `sea level'
1693  */
1694 float mg_HeteroTerrain(float x, float y, float z, float H, float lacunarity, float octaves, float offset, int noisebasis)
1695 {
1696         float value, increment, rmd;
1697         int i;
1698         float pwHL = powf(lacunarity, -H);
1699         float pwr = pwHL;   /* starts with i=1 instead of 0 */
1700
1701         float (*noisefunc)(float, float, float);
1702         switch (noisebasis) {
1703                 case 1:
1704                         noisefunc = orgPerlinNoise;
1705                         break;
1706                 case 2:
1707                         noisefunc = newPerlin;
1708                         break;
1709                 case 3:
1710                         noisefunc = voronoi_F1S;
1711                         break;
1712                 case 4:
1713                         noisefunc = voronoi_F2S;
1714                         break;
1715                 case 5:
1716                         noisefunc = voronoi_F3S;
1717                         break;
1718                 case 6:
1719                         noisefunc = voronoi_F4S;
1720                         break;
1721                 case 7:
1722                         noisefunc = voronoi_F1F2S;
1723                         break;
1724                 case 8:
1725                         noisefunc = voronoi_CrS;
1726                         break;
1727                 case 14:
1728                         noisefunc = cellNoise;
1729                         break;
1730                 case 0:
1731                 default: {
1732                         noisefunc = orgBlenderNoiseS;
1733                 }
1734         }
1735
1736         /* first unscaled octave of function; later octaves are scaled */
1737         value = offset + noisefunc(x, y, z);
1738         x *= lacunarity;
1739         y *= lacunarity;
1740         z *= lacunarity;
1741
1742         for (i = 1; i < (int)octaves; i++) {
1743                 increment = (noisefunc(x, y, z) + offset) * pwr * value;
1744                 value += increment;
1745                 pwr *= pwHL;
1746                 x *= lacunarity;
1747                 y *= lacunarity;
1748                 z *= lacunarity;
1749         }
1750
1751         rmd = octaves - floorf(octaves);
1752         if (rmd != 0.0f) {
1753                 increment = (noisefunc(x, y, z) + offset) * pwr * value;
1754                 value += rmd * increment;
1755         }
1756         return value;
1757 }
1758
1759
1760 /* Hybrid additive/multiplicative multifractal terrain model.
1761  *
1762  * Some good parameter values to start with:
1763  *
1764  *      H:           0.25
1765  *      offset:      0.7
1766  */
1767 float mg_HybridMultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, float offset, float gain, int noisebasis)
1768 {
1769         float result, signal, weight, rmd;
1770         int i;
1771         float pwHL = powf(lacunarity, -H);
1772         float pwr = pwHL;   /* starts with i=1 instead of 0 */
1773         float (*noisefunc)(float, float, float);
1774
1775         switch (noisebasis) {
1776                 case 1:
1777                         noisefunc = orgPerlinNoise;
1778                         break;
1779                 case 2:
1780                         noisefunc = newPerlin;
1781                         break;
1782                 case 3:
1783                         noisefunc = voronoi_F1S;
1784                         break;
1785                 case 4:
1786                         noisefunc = voronoi_F2S;
1787                         break;
1788                 case 5:
1789                         noisefunc = voronoi_F3S;
1790                         break;
1791                 case 6:
1792                         noisefunc = voronoi_F4S;
1793                         break;
1794                 case 7:
1795                         noisefunc = voronoi_F1F2S;
1796                         break;
1797                 case 8:
1798                         noisefunc = voronoi_CrS;
1799                         break;
1800                 case 14:
1801                         noisefunc = cellNoise;
1802                         break;
1803                 case 0:
1804                 default: {
1805                         noisefunc = orgBlenderNoiseS;
1806                 }
1807         }
1808
1809         result = noisefunc(x, y, z) + offset;
1810         weight = gain * result;
1811         x *= lacunarity;
1812         y *= lacunarity;
1813         z *= lacunarity;
1814
1815         for (i = 1; (weight > 0.001f) && (i < (int)octaves); i++) {
1816                 if (weight > 1.0f) weight = 1.0f;
1817                 signal = (noisefunc(x, y, z) + offset) * pwr;
1818                 pwr *= pwHL;
1819                 result += weight * signal;
1820                 weight *= gain * signal;
1821                 x *= lacunarity;
1822                 y *= lacunarity;
1823                 z *= lacunarity;
1824         }
1825
1826         rmd = octaves - floorf(octaves);
1827         if (rmd != 0.f) result += rmd * ((noisefunc(x, y, z) + offset) * pwr);
1828
1829         return result;
1830
1831 } /* HybridMultifractal() */
1832
1833
1834 /* Ridged multifractal terrain model.
1835  *
1836  * Some good parameter values to start with:
1837  *
1838  *      H:           1.0
1839  *      offset:      1.0
1840  *      gain:        2.0
1841  */
1842 float mg_RidgedMultiFractal(float x, float y, float z, float H, float lacunarity, float octaves, float offset, float gain, int noisebasis)
1843 {
1844         float result, signal, weight;
1845         int i;
1846         float pwHL = powf(lacunarity, -H);
1847         float pwr = pwHL;   /* starts with i=1 instead of 0 */
1848         
1849         float (*noisefunc)(float, float, float);
1850         switch (noisebasis) {
1851                 case 1:
1852                         noisefunc = orgPerlinNoise;
1853                         break;
1854                 case 2:
1855                         noisefunc = newPerlin;
1856                         break;
1857                 case 3:
1858                         noisefunc = voronoi_F1S;
1859                         break;
1860                 case 4:
1861                         noisefunc = voronoi_F2S;
1862                         break;
1863                 case 5:
1864                         noisefunc = voronoi_F3S;
1865                         break;
1866                 case 6:
1867                         noisefunc = voronoi_F4S;
1868                         break;
1869                 case 7:
1870                         noisefunc = voronoi_F1F2S;
1871                         break;
1872                 case 8:
1873                         noisefunc = voronoi_CrS;
1874                         break;
1875                 case 14:
1876                         noisefunc = cellNoise;
1877                         break;
1878                 case 0:
1879                 default: {
1880                         noisefunc = orgBlenderNoiseS;
1881                 }
1882         }
1883
1884         signal = offset - fabsf(noisefunc(x, y, z));
1885         signal *= signal;
1886         result = signal;
1887
1888
1889         for (i = 1; i < (int)octaves; i++) {
1890                 x *= lacunarity;
1891                 y *= lacunarity;
1892                 z *= lacunarity;
1893                 weight = signal * gain;
1894                 if      (weight > 1.0f) weight = 1.0f;
1895                 else if (weight < 0.0f) weight = 0.0f;
1896                 signal = offset - fabsf(noisefunc(x, y, z));
1897                 signal *= signal;
1898                 signal *= weight;
1899                 result += signal * pwr;
1900                 pwr *= pwHL;
1901         }
1902
1903         return result;
1904 } /* RidgedMultifractal() */
1905
1906 /* "Variable Lacunarity Noise"
1907  * A distorted variety of Perlin noise.
1908  */
1909 float mg_VLNoise(float x, float y, float z, float distortion, int nbas1, int nbas2)
1910 {
1911         float rv[3];
1912         float (*noisefunc1)(float, float, float);
1913         float (*noisefunc2)(float, float, float);
1914
1915         switch (nbas1) {
1916                 case 1:
1917                         noisefunc1 = orgPerlinNoise;
1918                         break;
1919                 case 2:
1920                         noisefunc1 = newPerlin;
1921                         break;
1922                 case 3:
1923                         noisefunc1 = voronoi_F1S;
1924                         break;
1925                 case 4:
1926                         noisefunc1 = voronoi_F2S;
1927                         break;
1928                 case 5:
1929                         noisefunc1 = voronoi_F3S;
1930                         break;
1931                 case 6:
1932                         noisefunc1 = voronoi_F4S;
1933                         break;
1934                 case 7:
1935                         noisefunc1 = voronoi_F1F2S;
1936                         break;
1937                 case 8:
1938                         noisefunc1 = voronoi_CrS;
1939                         break;
1940                 case 14:
1941                         noisefunc1 = cellNoise;
1942                         break;
1943                 case 0:
1944                 default: {
1945                         noisefunc1 = orgBlenderNoiseS;
1946                 }
1947         }
1948
1949         switch (nbas2) {
1950                 case 1:
1951                         noisefunc2 = orgPerlinNoise;
1952                         break;
1953                 case 2:
1954                         noisefunc2 = newPerlin;
1955                         break;
1956                 case 3:
1957                         noisefunc2 = voronoi_F1S;
1958                         break;
1959                 case 4:
1960                         noisefunc2 = voronoi_F2S;
1961                         break;
1962                 case 5:
1963                         noisefunc2 = voronoi_F3S;
1964                         break;
1965                 case 6:
1966                         noisefunc2 = voronoi_F4S;
1967                         break;
1968                 case 7:
1969                         noisefunc2 = voronoi_F1F2S;
1970                         break;
1971                 case 8:
1972                         noisefunc2 = voronoi_CrS;
1973                         break;
1974                 case 14:
1975                         noisefunc2 = cellNoise;
1976                         break;
1977                 case 0:
1978                 default: {
1979                         noisefunc2 = orgBlenderNoiseS;
1980                 }
1981         }
1982
1983         /* get a random vector and scale the randomization */
1984         rv[0] = noisefunc1(x + 13.5f, y + 13.5f, z + 13.5f) * distortion;
1985         rv[1] = noisefunc1(x, y, z) * distortion;
1986         rv[2] = noisefunc1(x - 13.5f, y - 13.5f, z - 13.5f) * distortion;
1987         return noisefunc2(x + rv[0], y + rv[1], z + rv[2]);   /* distorted-domain noise */
1988 }
1989
1990 /****************/
1991 /* musgrave end */
1992 /****************/