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1 /*
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2 * Coherent noise function over 1 or 2 dimensions.
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3 */
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4 #include "dmlib.h"
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5 #include <math.h>
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6
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7 #define B (0x100)
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8 #define BM (0x0ff)
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9 #define NP (12)
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10 #define N (0x1000)
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11 #define NM (0x0fff)
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12
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13
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14 #define DM_PERLIN_SETUP(i, b0, b1, r0, r1) { \
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15 t = (vec[i] + N); \
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16 b0 = (((int) t) & BM); \
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17 b1 = ((b0 + 1) & BM); \
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18 r0 = (t - ((int) t)); \
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19 r1 = (r0 - 1.0f); \
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20 }
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21
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22
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23 #define DM_PERLIN_AT2(rx,ry) ((rx) * q[0] + (ry) * q[1])
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24
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25
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26 static int p[B + B + 2];
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27 static DMFloat g2[B + B + 2][2];
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28 static DMFloat g1[B + B + 2];
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29
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30
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31 static DMFloat dmPerlinDoNoise2(DMFloat vec[2])
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32 {
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33 int bx0, bx1, by0, by1, b00, b10, b01, b11;
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34 DMFloat rx0, rx1, ry0, ry1, *q, sx, sy, a, b, t, u, v;
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35 int i, j;
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36
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37 DM_PERLIN_SETUP(0, bx0, bx1, rx0, rx1);
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38 DM_PERLIN_SETUP(1, by0, by1, ry0, ry1);
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39
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40 i = p[bx0];
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41 j = p[bx1];
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42
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43 b00 = p[i + by0];
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44 b10 = p[j + by0];
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45 b01 = p[i + by1];
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46 b11 = p[j + by1];
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47
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48 sx = DMM_S_CURVE(rx0);
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49 sy = DMM_S_CURVE(ry0);
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50
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51 q = g2[b00];
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52 u = DM_PERLIN_AT2(rx0, ry0);
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53 q = g2[b10];
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54 v = DM_PERLIN_AT2(rx1, ry0);
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55 a = DMM_LERP(sx, u, v);
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56
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57 q = g2[b01];
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58 u = DM_PERLIN_AT2(rx0, ry1);
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59 q = g2[b11];
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60 v = DM_PERLIN_AT2(rx1, ry1);
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61 b = DMM_LERP(sx, u, v);
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62
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63 return DMM_LERP(sy, a, b);
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64 }
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65
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66
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67 static void dmPerlinNormalize2(DMFloat v[2])
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68 {
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69 DMFloat s;
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70
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71 s = sqrt(v[0] * v[0] + v[1] * v[1]);
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72
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73 v[0] /= s;
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74 v[1] /= s;
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75 }
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76
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77
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78 void dmPerlinInit(void)
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79 {
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80 int i, j, k;
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81
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82 srand(32);
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83
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84 for (i = 0; i < B; i++)
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85 {
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86 p[i] = i;
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87 g1[i] = (DMFloat) ((rand() % (B + B)) - B) / B;
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88
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89 for (j = 0; j < 2; j++)
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90 g2[i][j] = (DMFloat) ((rand() % (B + B)) - B) / B;
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91
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92 dmPerlinNormalize2(g2[i]);
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93 }
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94
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95 while (--i)
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96 {
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97 k = p[i];
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98 p[i] = p[j = rand() % B];
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99 p[j] = k;
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100 }
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101
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102 for (i = 0; i < B + 2; i++)
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103 {
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104 p[B + i] = p[i];
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105 g1[B + i] = g1[i];
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106
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107 for (j = 0; j < 2; j++)
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108 g2[B + i][j] = g2[i][j];
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109 }
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110 }
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111
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112
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113 /* Harmonic summing functions - PDB
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114 * In what follows "alpha" is the weight when the sum is formed.
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115 * Typically it is 2, As this approaches 1 the function is noisier.
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116 * "beta" is the harmonic scaling/spacing, typically 2.
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117 */
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118 DMFloat dmPerlinNoise2D(DMFloat x, DMFloat y, DMFloat alpha, DMFloat beta, int n)
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119 {
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120 int i;
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121 DMFloat val, sum = 0;
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122 DMFloat p[2], scale = 1;
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123
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124 p[0] = x;
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125 p[1] = y;
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126 for (i = 0; i < n; i++)
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127 {
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128 val = dmPerlinDoNoise2(p);
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129 sum += val / scale;
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130 scale *= alpha;
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131 p[0] *= beta;
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132 p[1] *= beta;
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133 }
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134
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135 return (sum);
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136 }
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