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1
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+#if 1
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2
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+/*
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3
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+* libtcod 1.5.0
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4
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+* Copyright (c) 2008,2009,2010 Jice
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5
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+* All rights reserved.
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6
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+*
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7
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+* Redistribution and use in source and binary forms, with or without
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+* modification, are permitted provided that the following conditions are met:
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+* * Redistributions of source code must retain the above copyright
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10
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+* notice, this list of conditions and the following disclaimer.
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+* * Redistributions in binary form must reproduce the above copyright
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12
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+* notice, this list of conditions and the following disclaimer in the
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+* documentation and/or other materials provided with the distribution.
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+* * The name of Jice may not be used to endorse or promote products
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+* derived from this software without specific prior written permission.
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16
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+*
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+* THIS SOFTWARE IS PROVIDED BY Jice ``AS IS'' AND ANY
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+* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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+* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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+* DISCLAIMED. IN NO EVENT SHALL Jice BE LIABLE FOR ANY
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+* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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+* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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+* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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+* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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+* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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26
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+* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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27
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+*/
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+
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29
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+#include <math.h>
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30
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+#include <stdlib.h>
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31
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+#include <string.h>
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32
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+#include "SFMT.h"
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33
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+#include "libtcod.h"
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34
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+#include "noise.h"
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35
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+
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36
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+#define WAVELET_TILE_SIZE 32
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37
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+#define WAVELET_ARAD 16
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38
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+
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39
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+#define SIMPLEX_SCALE 0.5f
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40
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+#define WAVELET_SCALE 2.0f
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41
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+
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42
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+typedef struct {
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43
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+ int ndim;
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44
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+ unsigned char map[256]; // Randomized map of indexes into buffer
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45
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+ float buffer[256][TCOD_NOISE_MAX_DIMENSIONS]; // Random 256 x ndim buffer
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46
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+ // fractal stuff
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47
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+ float H;
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48
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+ float lacunarity;
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49
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+ float exponent[TCOD_NOISE_MAX_OCTAVES];
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50
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+ float *waveletTileData;
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51
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+} perlin_data_t;
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52
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+
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53
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+static float lattice( perlin_data_t *data, int ix, float fx, int iy, float fy, int iz, float fz, int iw, float fw)
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54
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+{
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55
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+ int n[4] = {ix, iy, iz, iw};
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56
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+ float f[4] = {fx, fy, fz, fw};
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57
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+ int nIndex = 0;
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58
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+ int i;
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59
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+ float value = 0;
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60
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+ for(i=0; i<data->ndim; i++)
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61
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+ nIndex = data->map[(nIndex + n[i]) & 0xFF];
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62
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+ for(i=0; i<data->ndim; i++)
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+ value += data->buffer[nIndex][i] * f[i];
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+ return value;
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+}
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66
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+
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67
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+#define DEFAULT_SEED 0x15687436
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68
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+#define DELTA 1e-6f
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69
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+#define SWAP(a, b, t) t = a; a = b; b = t
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70
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+
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71
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+#define FLOOR(a) ((a)> 0 ? ((int)a) : (((int)a)-1) )
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72
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+#define CUBIC(a) ( a * a * (3 - 2*a) )
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+
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+static void normalize(perlin_data_t *data, float *f)
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+{
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+ float magnitude = 0;
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+ int i;
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+ for(i=0; i<data->ndim; i++)
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+ magnitude += f[i]*f[i];
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80
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+ magnitude = 1 / sqrtf(magnitude);
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+ for(i=0; i<data->ndim; i++)
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+ f[i] *= magnitude;
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+}
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+
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+
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86
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+TCOD_noise_t TCOD_noise_new(int ndim, float hurst, float lacunarity)
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87
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+{
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88
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+ perlin_data_t *data=(perlin_data_t *)calloc(sizeof(perlin_data_t),1);
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89
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+ int i, j;
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90
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+ unsigned char tmp;
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+ float f = 1;
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+ data->ndim = ndim;
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+ for(i=0; i<256; i++)
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+ {
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+ data->map[i] = (unsigned char)i;
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+ for(j=0; j<data->ndim; j++)
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+ data->buffer[i][j] = genrand_real(-0.5, 0.5);
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+ normalize(data,data->buffer[i]);
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+ }
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+
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101
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+ while(--i)
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102
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+ {
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103
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+ j = rand_div(256);
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104
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+ SWAP(data->map[i], data->map[j], tmp);
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105
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+ }
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106
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+
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107
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+ data->H = hurst;
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108
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+ data->lacunarity = lacunarity;
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109
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+ for(i=0; i<TCOD_NOISE_MAX_OCTAVES; i++)
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110
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+ {
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111
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+ //exponent[i] = powf(f, -H);
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112
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+ data->exponent[i] = 1.0f / f;
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+ f *= lacunarity;
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+ }
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+ return (TCOD_noise_t)data;
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116
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+}
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117
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+
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118
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+float TCOD_noise_perlin( TCOD_noise_t noise, float *f )
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119
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+{
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120
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+ perlin_data_t *data=(perlin_data_t *)noise;
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121
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+ int n[TCOD_NOISE_MAX_DIMENSIONS]; // Indexes to pass to lattice function
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122
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+ int i;
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123
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+ float r[TCOD_NOISE_MAX_DIMENSIONS]; // Remainders to pass to lattice function
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124
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+ float w[TCOD_NOISE_MAX_DIMENSIONS]; // Cubic values to pass to interpolation function
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125
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+ float value;
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126
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+
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127
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+ for(i=0; i<data->ndim; i++)
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128
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+ {
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129
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+ n[i] = FLOOR(f[i]);
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130
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+ r[i] = f[i] - n[i];
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131
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+ w[i] = CUBIC(r[i]);
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132
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+ }
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133
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+
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134
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+ switch(data->ndim)
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135
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+ {
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136
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+ case 1:
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137
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+ value = LERP(lattice(data,n[0], r[0],0,0,0,0,0,0),
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138
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+ lattice(data,n[0]+1, r[0]-1,0,0,0,0,0,0),
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139
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+ w[0]);
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140
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+ break;
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141
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+ case 2:
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142
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+ value = LERP(LERP(lattice(data,n[0], r[0], n[1], r[1],0,0,0,0),
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1],0,0,0,0),
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144
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+ w[0]),
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145
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1,0,0,0,0),
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146
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1,0,0,0,0),
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147
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+ w[0]),
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148
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+ w[1]);
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149
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+ break;
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150
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+ case 3:
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151
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+ value = LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2],0,0),
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152
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2],0,0),
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153
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+ w[0]),
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154
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2],0,0),
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155
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2],0,0),
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+ w[0]),
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+ w[1]),
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158
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+ LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1,0,0),
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159
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1,0,0),
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160
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+ w[0]),
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161
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
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162
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
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163
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+ w[0]),
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164
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+ w[1]),
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165
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+ w[2]);
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166
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+ break;
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167
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+ case 4:
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+ default:
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169
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+ value = LERP(LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2], n[3], r[3]),
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170
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2], n[3], r[3]),
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171
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+ w[0]),
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172
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2], n[3], r[3]),
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173
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2], n[3], r[3]),
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174
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+ w[0]),
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175
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+ w[1]),
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176
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+ LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1, n[3], r[3]),
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177
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1, n[3], r[3]),
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178
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+ w[0]),
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179
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
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|
180
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1, n[3], r[3]),
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181
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+ w[0]),
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182
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+ w[1]),
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183
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+ w[2]),
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184
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+ LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2], n[3]+1, r[3]-1),
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185
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2], n[3]+1, r[3]-1),
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186
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+ w[0]),
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187
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2], n[3]+1, r[3]-1),
|
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188
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2], n[3]+1, r[3]-1),
|
|
189
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+ w[0]),
|
|
190
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+ w[1]),
|
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191
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+ LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1, n[3]+1, r[3]-1),
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|
192
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+ lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1, n[3]+1, r[3]-1),
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193
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+ w[0]),
|
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194
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+ LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
|
|
195
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+ lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1, n[3]+1, r[3]-1),
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196
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+ w[0]),
|
|
197
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+ w[1]),
|
|
198
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+ w[2]),
|
|
199
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+ w[3]);
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|
200
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+ break;
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|
201
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+ }
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|
202
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+ return CLAMP(-0.99999f, 0.99999f, value);
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|
203
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+}
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|
204
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+
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|
205
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+typedef float (*TCOD_noise_func_t)( TCOD_noise_t noise, float *f );
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|
206
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+
|
|
207
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+static float TCOD_noise_fbm_int(TCOD_noise_t noise, float *f, float octaves, TCOD_noise_func_t func ) {
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|
208
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+ float tf[TCOD_NOISE_MAX_DIMENSIONS];
|
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209
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+ perlin_data_t *data=(perlin_data_t *)noise;
|
|
210
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+ // Initialize locals
|
|
211
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+ double value = 0;
|
|
212
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+ int i,j;
|
|
213
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+ memcpy(tf,f,sizeof(float)*data->ndim);
|
|
214
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+
|
|
215
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+ // Inner loop of spectral construction, where the fractal is built
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|
216
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+ for(i=0; i<(int)octaves; i++)
|
|
217
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+ {
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|
218
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+ value += (double)(func(noise,tf)) * data->exponent[i];
|
|
219
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+ for (j=0; j < data->ndim; j++) tf[j] *= data->lacunarity;
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|
220
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+ }
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|
221
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+
|
|
222
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+ // Take care of remainder in octaves
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|
223
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+ octaves -= (int)octaves;
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|
224
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+ if(octaves > DELTA)
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|
225
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+ value += (double)(octaves * func(noise,tf)) * data->exponent[i];
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|
226
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+ return CLAMP(-0.99999f, 0.99999f, (float)value);
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|
227
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+}
|
|
228
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+
|
|
229
|
+float TCOD_noise_fbm_perlin( TCOD_noise_t noise, float *f, float octaves )
|
|
230
|
+{
|
|
231
|
+ return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_perlin);
|
|
232
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+/*
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|
233
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+ float tf[TCOD_NOISE_MAX_DIMENSIONS];
|
|
234
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+ perlin_data_t *data=(perlin_data_t *)noise;
|
|
235
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+ // Initialize locals
|
|
236
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+ double value = 0;
|
|
237
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+ int i,j;
|
|
238
|
+ memcpy(tf,f,sizeof(float)*data->ndim);
|
|
239
|
+
|
|
240
|
+ // Inner loop of spectral construction, where the fractal is built
|
|
241
|
+ for(i=0; i<(int)octaves; i++)
|
|
242
|
+ {
|
|
243
|
+ value += (double)(TCOD_noise_simplex(noise,tf)) * data->exponent[i];
|
|
244
|
+ for (j=0; j < data->ndim; j++) tf[j] *= data->lacunarity;
|
|
245
|
+ }
|
|
246
|
+
|
|
247
|
+ // Take care of remainder in octaves
|
|
248
|
+ octaves -= (int)octaves;
|
|
249
|
+ if(octaves > DELTA)
|
|
250
|
+ value += (double)(octaves * TCOD_noise_simplex(noise,tf)) * data->exponent[i];
|
|
251
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+ return CLAMP(-0.99999f, 0.99999f, (float)value);
|
|
252
|
+*/
|
|
253
|
+}
|
|
254
|
+
|
|
255
|
+float TCOD_noise_fbm_simplex( TCOD_noise_t noise, float *f, float octaves )
|
|
256
|
+{
|
|
257
|
+ return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_simplex);
|
|
258
|
+}
|
|
259
|
+
|
|
260
|
+static float TCOD_noise_turbulence_int( TCOD_noise_t noise, float *f, float octaves, TCOD_noise_func_t func )
|
|
261
|
+{
|
|
262
|
+ float tf[TCOD_NOISE_MAX_DIMENSIONS];
|
|
263
|
+ perlin_data_t *data=(perlin_data_t *)noise;
|
|
264
|
+ // Initialize locals
|
|
265
|
+ double value = 0;
|
|
266
|
+ int i,j;
|
|
267
|
+ memcpy(tf,f,sizeof(float)*data->ndim);
|
|
268
|
+
|
|
269
|
+ // Inner loop of spectral construction, where the fractal is built
|
|
270
|
+ for(i=0; i<(int)octaves; i++)
|
|
271
|
+ {
|
|
272
|
+ float nval=func(noise,tf);
|
|
273
|
+ value += (double)(ABS(nval)) * data->exponent[i];
|
|
274
|
+ for (j=0; j < data->ndim; j++) tf[j] *= data->lacunarity;
|
|
275
|
+ }
|
|
276
|
+
|
|
277
|
+ // Take care of remainder in octaves
|
|
278
|
+ octaves -= (int)octaves;
|
|
279
|
+ if(octaves > DELTA) {
|
|
280
|
+ float nval=func(noise,tf);
|
|
281
|
+ value += (double)(octaves * ABS(nval)) * data->exponent[i];
|
|
282
|
+ }
|
|
283
|
+ return CLAMP(-0.99999f, 0.99999f, (float)value);
|
|
284
|
+}
|
|
285
|
+
|
|
286
|
+float TCOD_noise_turbulence_perlin( TCOD_noise_t noise, float *f, float octaves ) {
|
|
287
|
+ return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_perlin);
|
|
288
|
+}
|
|
289
|
+
|
|
290
|
+float TCOD_noise_turbulence_simplex( TCOD_noise_t noise, float *f, float octaves ) {
|
|
291
|
+ return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_simplex);
|
|
292
|
+}
|
|
293
|
+
|
|
294
|
+// simplex noise, adapted from Ken Perlin's presentation at Siggraph 2001
|
|
295
|
+// and Stefan Gustavson implementation
|
|
296
|
+
|
|
297
|
+#define TCOD_NOISE_SIMPLEX_GRADIENT_1D(n,h,x) { \
|
|
298
|
+ float grad; \
|
|
299
|
+ h &= 0xF; \
|
|
300
|
+ grad=1.0f+(h & 7); \
|
|
301
|
+ if ( h & 8 ) grad = -grad; \
|
|
302
|
+ n = grad * x; \
|
|
303
|
+}
|
|
304
|
+
|
|
305
|
+#define TCOD_NOISE_SIMPLEX_GRADIENT_2D(n,h,x,y) { \
|
|
306
|
+ float u,v; \
|
|
307
|
+ h &= 0x7; \
|
|
308
|
+ if ( h < 4 ) { \
|
|
309
|
+ u=x; \
|
|
310
|
+ v=2.0f*y; \
|
|
311
|
+ } else { \
|
|
312
|
+ u=y; \
|
|
313
|
+ v=2.0f*x; \
|
|
314
|
+ } \
|
|
315
|
+ n = ((h & 1) ? -u : u) + ((h & 2) ? -v :v ); \
|
|
316
|
+}
|
|
317
|
+
|
|
318
|
+#define TCOD_NOISE_SIMPLEX_GRADIENT_3D(n,h,x,y,z) { \
|
|
319
|
+ float u,v; \
|
|
320
|
+ h &= 0xF; \
|
|
321
|
+ u = (h < 8 ? x : y); \
|
|
322
|
+ v = (h < 4 ? y : ( h == 12 || h == 14 ? x : z ) ); \
|
|
323
|
+ n= ((h & 1) ? -u : u ) + ((h & 2) ? -v : v); \
|
|
324
|
+}
|
|
325
|
+
|
|
326
|
+#define TCOD_NOISE_SIMPLEX_GRADIENT_4D(n,h,x,y,z,t) { \
|
|
327
|
+ float u,v,w; \
|
|
328
|
+ h &= 0x1F; \
|
|
329
|
+ u = (h < 24 ? x:y); \
|
|
330
|
+ v = (h < 16 ? y:z); \
|
|
331
|
+ w = (h < 8 ? z:t); \
|
|
332
|
+ n= ((h & 1) ? -u : u ) + ((h & 2) ? -v : v) + ((h & 4) ? -w : w);\
|
|
333
|
+}
|
|
334
|
+
|
|
335
|
+static float simplex[64][4] = {
|
|
336
|
+ {0,1,2,3},{0,1,3,2},{0,0,0,0},{0,2,3,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,2,3,0},
|
|
337
|
+ {0,2,1,3},{0,0,0,0},{0,3,1,2},{0,3,2,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,3,2,0},
|
|
338
|
+ {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},
|
|
339
|
+ {1,2,0,3},{0,0,0,0},{1,3,0,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,3,0,1},{2,3,1,0},
|
|
340
|
+ {1,0,2,3},{1,0,3,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,0,3,1},{0,0,0,0},{2,1,3,0},
|
|
341
|
+ {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},
|
|
342
|
+ {2,0,1,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,0,1,2},{3,0,2,1},{0,0,0,0},{3,1,2,0},
|
|
343
|
+ {2,1,0,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,1,0,2},{0,0,0,0},{3,2,0,1},{3,2,1,0},
|
|
344
|
+
|
|
345
|
+};
|
|
346
|
+
|
|
347
|
+float TCOD_noise_simplex(TCOD_noise_t noise, float *f) {
|
|
348
|
+ perlin_data_t *data=(perlin_data_t *)noise;
|
|
349
|
+ switch(data->ndim) {
|
|
350
|
+ case 1 :
|
|
351
|
+ {
|
|
352
|
+ int i0=(int)FLOOR(f[0]*SIMPLEX_SCALE);
|
|
353
|
+ int i1=i0+1;
|
|
354
|
+ float x0 = f[0]*SIMPLEX_SCALE - i0;
|
|
355
|
+ float x1 = x0 - 1.0f;
|
|
356
|
+ float t0 = 1.0f - x0*x0;
|
|
357
|
+ float t1 = 1.0f - x1*x1;
|
|
358
|
+ float n0,n1;
|
|
359
|
+ t0 = t0*t0;
|
|
360
|
+ t1 = t1*t1;
|
|
361
|
+ i0=data->map[i0&0xFF];
|
|
362
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_1D(n0,i0,x0);
|
|
363
|
+ n0*=t0*t0;
|
|
364
|
+ i1=data->map[i1&0xFF];
|
|
365
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_1D(n1,i1,x1);
|
|
366
|
+ n1*=t1*t1;
|
|
367
|
+ return 0.25f * (n0+n1);
|
|
368
|
+ }
|
|
369
|
+ break;
|
|
370
|
+ case 2 :
|
|
371
|
+ {
|
|
372
|
+ #define F2 0.366025403f // 0.5f * (sqrtf(3.0f)-1.0f);
|
|
373
|
+ #define G2 0.211324865f // (3.0f - sqrtf(3.0f))/6.0f;
|
|
374
|
+
|
|
375
|
+ float s = (f[0]+f[1])*F2*SIMPLEX_SCALE;
|
|
376
|
+ float xs = f[0]*SIMPLEX_SCALE+s;
|
|
377
|
+ float ys = f[1]*SIMPLEX_SCALE+s;
|
|
378
|
+ int i=FLOOR(xs);
|
|
379
|
+ int j=FLOOR(ys);
|
|
380
|
+ float t = (i+j)*G2;
|
|
381
|
+ float xo = i-t;
|
|
382
|
+ float yo = j-t;
|
|
383
|
+ float x0 = f[0]*SIMPLEX_SCALE-xo;
|
|
384
|
+ float y0 = f[1]*SIMPLEX_SCALE-yo;
|
|
385
|
+ int i1,j1,ii = i%256,jj = j%256;
|
|
386
|
+ float n0,n1,n2,x1,y1,x2,y2,t0,t1,t2;
|
|
387
|
+ if ( x0 > y0 ) {
|
|
388
|
+ i1=1;j1=0;
|
|
389
|
+ } else {
|
|
390
|
+ i1=0;j1=1;
|
|
391
|
+ }
|
|
392
|
+ x1 = x0 - i1 + G2;
|
|
393
|
+ y1 = y0 - j1 + G2;
|
|
394
|
+ x2 = x0 - 1.0f + 2.0f * G2;
|
|
395
|
+ y2 = y0 - 1.0f + 2.0f * G2;
|
|
396
|
+ t0 = 0.5f - x0*x0 - y0*y0;
|
|
397
|
+ if ( t0 < 0.0f ) {
|
|
398
|
+ n0 = 0.0f;
|
|
399
|
+ } else {
|
|
400
|
+ int idx = (ii + data->map[jj])&0xFF;
|
|
401
|
+ t0 *= t0;
|
|
402
|
+ idx=data->map[idx];
|
|
403
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_2D(n0,idx,x0,y0);
|
|
404
|
+ n0 *= t0*t0;
|
|
405
|
+ }
|
|
406
|
+ t1 = 0.5f - x1*x1 -y1*y1;
|
|
407
|
+ if ( t1 < 0.0f ) {
|
|
408
|
+ n1 = 0.0f;
|
|
409
|
+ } else {
|
|
410
|
+ int idx = (ii + i1 + data->map[(jj+j1)&0xFF]) & 0xFF;
|
|
411
|
+ t1 *= t1;
|
|
412
|
+ idx=data->map[idx];
|
|
413
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_2D(n1,idx,x1,y1);
|
|
414
|
+ n1 *= t1*t1;
|
|
415
|
+ }
|
|
416
|
+ t2 = 0.5f - x2*x2 -y2*y2;
|
|
417
|
+ if ( t2 < 0.0f ) {
|
|
418
|
+ n2 = 0.0f;
|
|
419
|
+ } else {
|
|
420
|
+ int idx = (ii + 1 + data->map[(jj+1)&0xFF]) & 0xFF;
|
|
421
|
+ t2 *= t2;
|
|
422
|
+ idx=data->map[idx];
|
|
423
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_2D(n2,idx,x2,y2);
|
|
424
|
+ n2 *= t2*t2;
|
|
425
|
+ }
|
|
426
|
+ return 40.0f * (n0+n1+n2);
|
|
427
|
+ }
|
|
428
|
+ break;
|
|
429
|
+ case 3 :
|
|
430
|
+ {
|
|
431
|
+ #define F3 0.333333333f
|
|
432
|
+ #define G3 0.166666667f
|
|
433
|
+ float n0,n1,n2,n3;
|
|
434
|
+ float s =(f[0]+f[1]+f[2])*F3*SIMPLEX_SCALE;
|
|
435
|
+ float xs=f[0]*SIMPLEX_SCALE+s;
|
|
436
|
+ float ys=f[1]*SIMPLEX_SCALE+s;
|
|
437
|
+ float zs=f[2]*SIMPLEX_SCALE+s;
|
|
438
|
+ int i=FLOOR(xs);
|
|
439
|
+ int j=FLOOR(ys);
|
|
440
|
+ int k=FLOOR(zs);
|
|
441
|
+ float t=(float)(i+j+k)*G3;
|
|
442
|
+ float xo = i-t;
|
|
443
|
+ float yo = j-t;
|
|
444
|
+ float zo = k-t;
|
|
445
|
+ float x0 = f[0]*SIMPLEX_SCALE-xo;
|
|
446
|
+ float y0 = f[1]*SIMPLEX_SCALE-yo;
|
|
447
|
+ float z0 = f[2]*SIMPLEX_SCALE-zo;
|
|
448
|
+ int i1,j1,k1,i2,j2,k2,ii,jj,kk;
|
|
449
|
+ float x1,y1,z1,x2,y2,z2,x3,y3,z3,t0,t1,t2,t3;
|
|
450
|
+ if ( x0 >= y0 ) {
|
|
451
|
+ if ( y0 >= z0 ) {
|
|
452
|
+ i1=1;j1=0;k1=0;i2=1;j2=1;k2=0;
|
|
453
|
+ } else if ( x0 >= z0 ) {
|
|
454
|
+ i1=1;j1=0;k1=0;i2=1;j2=0;k2=1;
|
|
455
|
+ } else {
|
|
456
|
+ i1=0;j1=0;k1=1;i2=1;j2=0;k2=1;
|
|
457
|
+ }
|
|
458
|
+ } else {
|
|
459
|
+ if ( y0 < z0 ) {
|
|
460
|
+ i1=0;j1=0;k1=1;i2=0;j2=1;k2=1;
|
|
461
|
+ } else if ( x0 < z0 ) {
|
|
462
|
+ i1=0;j1=1;k1=0;i2=0;j2=1;k2=1;
|
|
463
|
+ } else {
|
|
464
|
+ i1=0;j1=1;k1=0;i2=1;j2=1;k2=0;
|
|
465
|
+ }
|
|
466
|
+ }
|
|
467
|
+ x1 = x0 -i1 + G3;
|
|
468
|
+ y1 = y0 -j1 + G3;
|
|
469
|
+ z1 = z0 -k1 + G3;
|
|
470
|
+ x2 = x0 -i2 + 2.0f*G3;
|
|
471
|
+ y2 = y0 -j2 + 2.0f*G3;
|
|
472
|
+ z2 = z0 -k2 + 2.0f*G3;
|
|
473
|
+ x3 = x0 - 1.0f +3.0f * G3;
|
|
474
|
+ y3 = y0 - 1.0f +3.0f * G3;
|
|
475
|
+ z3 = z0 - 1.0f +3.0f * G3;
|
|
476
|
+ ii = i%256;
|
|
477
|
+ jj = j%256;
|
|
478
|
+ kk = k%256;
|
|
479
|
+ t0 = 0.6f - x0*x0 -y0*y0 -z0*z0;
|
|
480
|
+ if ( t0 < 0.0f ) n0 = 0.0f;
|
|
481
|
+ else {
|
|
482
|
+ int idx = data->map[ (ii + data->map[ (jj + data->map[ kk ]) &0xFF ])& 0xFF ];
|
|
483
|
+ t0 *= t0;
|
|
484
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_3D(n0,idx,x0,y0,z0);
|
|
485
|
+ n0 *= t0*t0;
|
|
486
|
+ }
|
|
487
|
+ t1 = 0.6f - x1*x1 -y1*y1 -z1*z1;
|
|
488
|
+ if ( t1 < 0.0f ) n1 = 0.0f;
|
|
489
|
+ else {
|
|
490
|
+ int idx = data->map[ (ii + i1 + data->map[ (jj + j1 + data->map[ (kk + k1)& 0xFF ]) &0xFF ])& 0xFF ];
|
|
491
|
+ t1 *= t1;
|
|
492
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_3D(n1,idx,x1,y1,z1);
|
|
493
|
+ n1 *= t1*t1;
|
|
494
|
+ }
|
|
495
|
+ t2 = 0.6f - x2*x2 -y2*y2 -z2*z2;
|
|
496
|
+ if ( t2 < 0.0f ) n2 = 0.0f;
|
|
497
|
+ else {
|
|
498
|
+ int idx = data->map[ (ii + i2 + data->map[ (jj + j2 + data->map[ (kk + k2)& 0xFF ]) &0xFF ])& 0xFF ];
|
|
499
|
+ t2 *= t2;
|
|
500
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_3D(n2,idx,x2,y2,z2);
|
|
501
|
+ n2 *= t2*t2;
|
|
502
|
+ }
|
|
503
|
+ t3 = 0.6f - x3*x3 -y3*y3 -z3*z3;
|
|
504
|
+ if ( t3 < 0.0f ) n3 = 0.0f;
|
|
505
|
+ else {
|
|
506
|
+ int idx = data->map[ (ii + 1 + data->map[ (jj + 1 + data->map[ (kk + 1)& 0xFF ]) &0xFF ])& 0xFF ];
|
|
507
|
+ t3 *= t3;
|
|
508
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_3D(n3,idx,x3,y3,z3);
|
|
509
|
+ n3 *= t3*t3;
|
|
510
|
+ }
|
|
511
|
+ return 32.0f * (n0+n1+n2+n3);
|
|
512
|
+
|
|
513
|
+ }
|
|
514
|
+ break;
|
|
515
|
+ case 4 :
|
|
516
|
+ {
|
|
517
|
+ #define F4 0.309016994f // (sqrtf(5.0f)-1.0f)/4.0f
|
|
518
|
+ #define G4 0.138196601f // (5.0f - sqrtf(5.0f))/20.0f
|
|
519
|
+ float n0,n1,n2,n3,n4;
|
|
520
|
+ float s = (f[0]+f[1]+f[2]+f[3])*F4 * SIMPLEX_SCALE;
|
|
521
|
+ float xs=f[0]*SIMPLEX_SCALE+s;
|
|
522
|
+ float ys=f[1]*SIMPLEX_SCALE+s;
|
|
523
|
+ float zs=f[2]*SIMPLEX_SCALE+s;
|
|
524
|
+ float ws=f[3]*SIMPLEX_SCALE+s;
|
|
525
|
+ int i=FLOOR(xs);
|
|
526
|
+ int j=FLOOR(ys);
|
|
527
|
+ int k=FLOOR(zs);
|
|
528
|
+ int l=FLOOR(ws);
|
|
529
|
+ float t=(float)(i+j+k+l)*G4;
|
|
530
|
+ float xo = i-t;
|
|
531
|
+ float yo = j-t;
|
|
532
|
+ float zo = k-t;
|
|
533
|
+ float wo = l-t;
|
|
534
|
+ float x0 = f[0]*SIMPLEX_SCALE-xo;
|
|
535
|
+ float y0 = f[1]*SIMPLEX_SCALE-yo;
|
|
536
|
+ float z0 = f[2]*SIMPLEX_SCALE-zo;
|
|
537
|
+ float w0 = f[3]*SIMPLEX_SCALE-wo;
|
|
538
|
+ int c1 = (x0 > y0 ? 32 : 0);
|
|
539
|
+ int c2 = (x0 > z0 ? 16 : 0);
|
|
540
|
+ int c3 = (y0 > z0 ? 8 : 0);
|
|
541
|
+ int c4 = (x0 > w0 ? 4 : 0);
|
|
542
|
+ int c5 = (y0 > w0 ? 2 : 0);
|
|
543
|
+ int c6 = (z0 > w0 ? 1 : 0);
|
|
544
|
+ int c = c1+c2+c3+c4+c5+c6;
|
|
545
|
+
|
|
546
|
+
|
|
547
|
+ int i1,j1,k1,l1,i2,j2,k2,l2,i3,j3,k3,l3,ii,jj,kk,ll;
|
|
548
|
+ float x1,y1,z1,w1,x2,y2,z2,w2,x3,y3,z3,w3,x4,y4,z4,w4,t0,t1,t2,t3,t4;
|
|
549
|
+ i1 = simplex[c][0] >= 3 ? 1:0;
|
|
550
|
+ j1 = simplex[c][1] >= 3 ? 1:0;
|
|
551
|
+ k1 = simplex[c][2] >= 3 ? 1:0;
|
|
552
|
+ l1 = simplex[c][3] >= 3 ? 1:0;
|
|
553
|
+
|
|
554
|
+ i2 = simplex[c][0] >= 2 ? 1:0;
|
|
555
|
+ j2 = simplex[c][1] >= 2 ? 1:0;
|
|
556
|
+ k2 = simplex[c][2] >= 2 ? 1:0;
|
|
557
|
+ l2 = simplex[c][3] >= 2 ? 1:0;
|
|
558
|
+
|
|
559
|
+ i3 = simplex[c][0] >= 1 ? 1:0;
|
|
560
|
+ j3 = simplex[c][1] >= 1 ? 1:0;
|
|
561
|
+ k3 = simplex[c][2] >= 1 ? 1:0;
|
|
562
|
+ l3 = simplex[c][3] >= 1 ? 1:0;
|
|
563
|
+
|
|
564
|
+ x1 = x0 -i1 + G4;
|
|
565
|
+ y1 = y0 -j1 + G4;
|
|
566
|
+ z1 = z0 -k1 + G4;
|
|
567
|
+ w1 = w0 -l1 + G4;
|
|
568
|
+ x2 = x0 -i2 + 2.0f*G4;
|
|
569
|
+ y2 = y0 -j2 + 2.0f*G4;
|
|
570
|
+ z2 = z0 -k2 + 2.0f*G4;
|
|
571
|
+ w2 = w0 -l2 + 2.0f*G4;
|
|
572
|
+ x3 = x0 -i3 + 3.0f*G4;
|
|
573
|
+ y3 = y0 -j3 + 3.0f*G4;
|
|
574
|
+ z3 = z0 -k3 + 3.0f*G4;
|
|
575
|
+ w3 = w0 -l3 + 3.0f*G4;
|
|
576
|
+ x4 = x0 - 1.0f +4.0f * G4;
|
|
577
|
+ y4 = y0 - 1.0f +4.0f * G4;
|
|
578
|
+ z4 = z0 - 1.0f +4.0f * G4;
|
|
579
|
+ w4 = w0 - 1.0f +4.0f * G4;
|
|
580
|
+
|
|
581
|
+ ii = i%256;
|
|
582
|
+ jj = j%256;
|
|
583
|
+ kk = k%256;
|
|
584
|
+ ll = l%256;
|
|
585
|
+
|
|
586
|
+ t0 = 0.6f - x0*x0 -y0*y0 -z0*z0 -w0*w0;
|
|
587
|
+ if ( t0 < 0.0f ) n0 = 0.0f;
|
|
588
|
+ else {
|
|
589
|
+ int idx = data->map[ (ii + data->map[ (jj + data->map[ (kk + data->map[ ll ] ) &0xFF]) &0xFF ])& 0xFF ];
|
|
590
|
+ t0 *= t0;
|
|
591
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_4D(n0,idx,x0,y0,z0,w0);
|
|
592
|
+ n0 *= t0*t0;
|
|
593
|
+ }
|
|
594
|
+ t1 = 0.6f - x1*x1 -y1*y1 -z1*z1 -w1*w1;
|
|
595
|
+ if ( t1 < 0.0f ) n1 = 0.0f;
|
|
596
|
+ else {
|
|
597
|
+ int idx = data->map[ (ii + i1 + data->map[ (jj + j1 + data->map[ (kk + k1 + data->map[ (ll+l1)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
|
|
598
|
+ t1 *= t1;
|
|
599
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_4D(n1,idx,x1,y1,z1,w1);
|
|
600
|
+ n1 *= t1*t1;
|
|
601
|
+ }
|
|
602
|
+ t2 = 0.6f - x2*x2 -y2*y2 -z2*z2 -w2*w2;
|
|
603
|
+ if ( t2 < 0.0f ) n2 = 0.0f;
|
|
604
|
+ else {
|
|
605
|
+ int idx = data->map[ (ii + i2 + data->map[ (jj + j2 + data->map[ (kk + k2 + data->map[(ll+l2)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
|
|
606
|
+ t2 *= t2;
|
|
607
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_4D(n2,idx,x2,y2,z2,w2);
|
|
608
|
+ n2 *= t2*t2;
|
|
609
|
+ }
|
|
610
|
+ t3 = 0.6f - x3*x3 -y3*y3 -z3*z3 -w3*w3;
|
|
611
|
+ if ( t3 < 0.0f ) n3 = 0.0f;
|
|
612
|
+ else {
|
|
613
|
+ int idx = data->map[ (ii + i3 + data->map[ (jj + j3 + data->map[ (kk + k3 + data->map[(ll+l3)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
|
|
614
|
+ t3 *= t3;
|
|
615
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_4D(n3,idx,x3,y3,z3,w3);
|
|
616
|
+ n3 *= t3*t3;
|
|
617
|
+ }
|
|
618
|
+ t4 = 0.6f - x4*x4 -y4*y4 -z4*z4 -w4*w4;
|
|
619
|
+ if ( t4 < 0.0f ) n4 = 0.0f;
|
|
620
|
+ else {
|
|
621
|
+ int idx = data->map[ (ii + 1 + data->map[ (jj + 1 + data->map[ (kk + 1 + data->map[(ll+1)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
|
|
622
|
+ t4 *= t4;
|
|
623
|
+ TCOD_NOISE_SIMPLEX_GRADIENT_4D(n4,idx,x4,y4,z4,w4);
|
|
624
|
+ n4 *= t4*t4;
|
|
625
|
+ }
|
|
626
|
+ return 27.0f * (n0+n1+n2+n3+n4);
|
|
627
|
+
|
|
628
|
+ }
|
|
629
|
+ break;
|
|
630
|
+ }
|
|
631
|
+ return 0.0f;
|
|
632
|
+}
|
|
633
|
+
|
|
634
|
+// wavelet noise, adapted from Robert L. Cook and Tony Derose 'Wavelet noise' paper
|
|
635
|
+
|
|
636
|
+static int absmod(int x, int n) {
|
|
637
|
+ int m=x%n;
|
|
638
|
+ return m < 0 ? m+n : m;
|
|
639
|
+}
|
|
640
|
+
|
|
641
|
+static void TCOD_noise_wavelet_downsample(float *from, float *to, int stride) {
|
|
642
|
+ static float acoeffs[2*WAVELET_ARAD]= {
|
|
643
|
+ 0.000334f, -0.001528f, 0.000410f, 0.003545f, -0.000938f, -0.008233f, 0.002172f, 0.019120f,
|
|
644
|
+ -0.005040f,-0.044412f, 0.011655f, 0.103311f, -0.025936f, -0.243780f, 0.033979f, 0.655340f,
|
|
645
|
+ 0.655340f, 0.033979f,-0.243780f,-0.025936f, 0.103311f, 0.011655f,-0.044412f,-0.005040f,
|
|
646
|
+ 0.019120f, 0.002172f,-0.008233f,-0.000938f, 0.003546f, 0.000410f,-0.001528f, 0.000334f,
|
|
647
|
+ };
|
|
648
|
+ static float *a = &acoeffs[WAVELET_ARAD];
|
|
649
|
+ int i;
|
|
650
|
+ for (i=0; i < WAVELET_TILE_SIZE/2; i++) {
|
|
651
|
+ int k;
|
|
652
|
+ to[i*stride]=0;
|
|
653
|
+ for (k=2*i-WAVELET_ARAD; k <2*i+WAVELET_ARAD; k++) {
|
|
654
|
+ to[i*stride] += a[k-2*i]* from[ absmod(k,WAVELET_TILE_SIZE) * stride ];
|
|
655
|
+ }
|
|
656
|
+ }
|
|
657
|
+}
|
|
658
|
+
|
|
659
|
+static void TCOD_noise_wavelet_upsample(float *from, float *to, int stride) {
|
|
660
|
+ static float pcoeffs[4]= { 0.25f, 0.75f, 0.75f, 0.25f };
|
|
661
|
+ static float *p = &pcoeffs[2];
|
|
662
|
+ int i;
|
|
663
|
+ for (i=0; i < WAVELET_TILE_SIZE; i++) {
|
|
664
|
+ int k;
|
|
665
|
+ to[i*stride]=0;
|
|
666
|
+ for (k=i/2; k <i/2+1; k++) {
|
|
667
|
+ to[i*stride] += p[i-2*k]* from[ absmod(k,WAVELET_TILE_SIZE/2) * stride ];
|
|
668
|
+ }
|
|
669
|
+ }
|
|
670
|
+}
|
|
671
|
+
|
|
672
|
+static void TCOD_noise_wavelet_init(TCOD_noise_t pnoise) {
|
|
673
|
+ perlin_data_t *data=(perlin_data_t *)pnoise;
|
|
674
|
+ int ix,iy,iz,i,sz=WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*sizeof(float);
|
|
675
|
+ float *temp1=(float *)malloc(sz);
|
|
676
|
+ float *temp2=(float *)malloc(sz);
|
|
677
|
+ float *noise=(float *)malloc(sz);
|
|
678
|
+ int offset;
|
|
679
|
+ for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
|
|
680
|
+ noise[i]=genrand_real(-1.0f,1.0f);
|
|
681
|
+ }
|
|
682
|
+ for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
|
|
683
|
+ for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
|
|
684
|
+ i = iy * WAVELET_TILE_SIZE + iz * WAVELET_TILE_SIZE * WAVELET_TILE_SIZE;
|
|
685
|
+ TCOD_noise_wavelet_downsample(&noise[i], &temp1[i], 1);
|
|
686
|
+ TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], 1);
|
|
687
|
+ }
|
|
688
|
+ }
|
|
689
|
+ for (ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
|
|
690
|
+ for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
|
|
691
|
+ i = ix + iz * WAVELET_TILE_SIZE * WAVELET_TILE_SIZE;
|
|
692
|
+ TCOD_noise_wavelet_downsample(&temp2[i], &temp1[i], WAVELET_TILE_SIZE);
|
|
693
|
+ TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], WAVELET_TILE_SIZE);
|
|
694
|
+ }
|
|
695
|
+ }
|
|
696
|
+ for (ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
|
|
697
|
+ for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
|
|
698
|
+ i = ix + iy * WAVELET_TILE_SIZE;
|
|
699
|
+ TCOD_noise_wavelet_downsample(&temp2[i], &temp1[i], WAVELET_TILE_SIZE * WAVELET_TILE_SIZE);
|
|
700
|
+ TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], WAVELET_TILE_SIZE * WAVELET_TILE_SIZE);
|
|
701
|
+ }
|
|
702
|
+ }
|
|
703
|
+ for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
|
|
704
|
+ noise[i] -= temp2[i];
|
|
705
|
+ }
|
|
706
|
+ offset = WAVELET_TILE_SIZE/2;
|
|
707
|
+ if ( (offset & 1) == 0 ) offset++;
|
|
708
|
+ for (i=0,ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
|
|
709
|
+ for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
|
|
710
|
+ for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
|
|
711
|
+ temp1[i++]=noise[ absmod(ix+offset,WAVELET_TILE_SIZE)
|
|
712
|
+ + absmod(iy+offset,WAVELET_TILE_SIZE)*WAVELET_TILE_SIZE
|
|
713
|
+ + absmod(iz+offset,WAVELET_TILE_SIZE)*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE
|
|
714
|
+ ];
|
|
715
|
+ }
|
|
716
|
+ }
|
|
717
|
+ }
|
|
718
|
+ for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
|
|
719
|
+ noise[i] += temp1[i];
|
|
720
|
+ }
|
|
721
|
+ data->waveletTileData=noise;
|
|
722
|
+ free(temp1);
|
|
723
|
+ free(temp2);
|
|
724
|
+}
|
|
725
|
+
|
|
726
|
+float TCOD_noise_wavelet (TCOD_noise_t noise, float *f) {
|
|
727
|
+ perlin_data_t *data=(perlin_data_t *)noise;
|
|
728
|
+ float pf[3];
|
|
729
|
+ int i;
|
|
730
|
+ int p[3],c[3],mid[3],n=WAVELET_TILE_SIZE;
|
|
731
|
+ float w[3][3],t,result=0.0f;
|
|
732
|
+ if ( data->ndim > 3 ) return 0.0f; // not supported
|
|
733
|
+ if (! data->waveletTileData ) TCOD_noise_wavelet_init(noise);
|
|
734
|
+ for (i=0; i < data->ndim; i++ ) pf[i]=f[i]*WAVELET_SCALE;
|
|
735
|
+ for (i=data->ndim; i < 3; i++ ) pf[i]=0.0f;
|
|
736
|
+ for (i=0; i < 3; i++ ) {
|
|
737
|
+ mid[i]=(int)ceilf(pf[i]-0.5f);
|
|
738
|
+ t=mid[i] - (pf[i]-0.5f);
|
|
739
|
+ w[i][0]=t*t*0.5f;
|
|
740
|
+ w[i][2]=(1.0f-t)*(1.0f-t)*0.5f;
|
|
741
|
+ w[i][1]=1.0f - w[i][0]-w[i][2];
|
|
742
|
+ }
|
|
743
|
+ for (p[2]=-1; p[2]<=1; p[2]++) {
|
|
744
|
+ for (p[1]=-1; p[1]<=1; p[1]++) {
|
|
745
|
+ for (p[0]=-1; p[0]<=1; p[0]++) {
|
|
746
|
+ float weight=1.0f;
|
|
747
|
+ for (i=0;i<3;i++) {
|
|
748
|
+ c[i]=absmod(mid[i]+p[i],n);
|
|
749
|
+ weight *= w[i][p[i]+1];
|
|
750
|
+ }
|
|
751
|
+ result += weight * data->waveletTileData[ c[2]*n*n + c[1]*n + c[0] ];
|
|
752
|
+ }
|
|
753
|
+ }
|
|
754
|
+ }
|
|
755
|
+ return CLAMP(-1.0f,1.0f,result);
|
|
756
|
+}
|
|
757
|
+
|
|
758
|
+float TCOD_noise_fbm_wavelet(TCOD_noise_t noise, float *f, float octaves) {
|
|
759
|
+ return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_wavelet);
|
|
760
|
+}
|
|
761
|
+
|
|
762
|
+float TCOD_noise_turbulence_wavelet(TCOD_noise_t noise, float *f, float octaves) {
|
|
763
|
+ return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_wavelet);
|
|
764
|
+}
|
|
765
|
+
|
|
766
|
+
|
|
767
|
+void TCOD_noise_delete(TCOD_noise_t noise) {
|
|
768
|
+ free((perlin_data_t *)noise);
|
|
769
|
+}
|
|
770
|
+
|
|
771
|
+#endif |
...
|
...
|
|