| 1 | #include <math.h> |
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| 2 | #include <stdlib.h> |
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| 3 | |
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| 4 | /* Coherent noise function over 1, 2 or 3 dimensions */ |
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| 5 | /* (copyright Ken Perlin) */ |
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| 6 | |
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| 7 | #define MAXB 0x100 |
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| 8 | #define N 0x1000 |
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| 9 | #define NP 12 /* 2^N */ |
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| 10 | #define NM 0xfff |
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| 11 | |
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| 12 | #define s_curve(t) ( t * t * (3. - 2. * t) ) |
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| 13 | #define lerp(t, a, b) ( a + t * (b - a) ) |
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| 14 | #define 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.; |
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| 20 | #define at2(rx,ry) ( rx * q[0] + ry * q[1] ) |
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| 21 | #define at3(rx,ry,rz) ( rx * q[0] + ry * q[1] + rz * q[2] ) |
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| 22 | |
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| 23 | static void initNoise(void); |
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| 24 | |
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| 25 | static int p[MAXB + MAXB + 2]; |
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| 26 | static double g3[MAXB + MAXB + 2][3]; |
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| 27 | static double g2[MAXB + MAXB + 2][2]; |
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| 28 | static double g1[MAXB + MAXB + 2]; |
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| 29 | |
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| 30 | int start; |
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| 31 | int B; |
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| 32 | int BM; |
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| 33 | |
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| 34 | |
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| 35 | void SetNoiseFrequency(int frequency) |
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| 36 | { |
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| 37 | start = 1; |
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| 38 | B = frequency; |
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| 39 | BM = B-1; |
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| 40 | } |
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| 41 | |
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| 42 | double noise1(double arg) |
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| 43 | { |
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| 44 | int bx0, bx1; |
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| 45 | double rx0, rx1, sx, t, u, v, vec[1]; |
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| 46 | |
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| 47 | vec[0] = arg; |
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| 48 | if (start) { |
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| 49 | start = 0; |
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| 50 | initNoise(); |
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| 51 | } |
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| 52 | |
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| 53 | setup(0,bx0,bx1,rx0,rx1); |
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| 54 | |
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| 55 | sx = s_curve(rx0); |
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| 56 | u = rx0 * g1[ p[ bx0 ] ]; |
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| 57 | v = rx1 * g1[ p[ bx1 ] ]; |
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| 58 | |
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| 59 | return(lerp(sx, u, v)); |
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| 60 | } |
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| 61 | |
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| 62 | double noise2(double vec[2]) |
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| 63 | { |
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| 64 | int bx0, bx1, by0, by1, b00, b10, b01, b11; |
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| 65 | double rx0, rx1, ry0, ry1, *q, sx, sy, a, b, t, u, v; |
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| 66 | int i, j; |
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| 67 | |
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| 68 | if (start) { |
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| 69 | start = 0; |
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| 70 | initNoise(); |
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| 71 | } |
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| 72 | |
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| 73 | setup(0, bx0,bx1, rx0,rx1); |
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| 74 | setup(1, by0,by1, ry0,ry1); |
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| 75 | |
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| 76 | i = p[ bx0 ]; |
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| 77 | j = p[ bx1 ]; |
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| 78 | |
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| 79 | b00 = p[ i + by0 ]; |
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| 80 | b10 = p[ j + by0 ]; |
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| 81 | b01 = p[ i + by1 ]; |
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| 82 | b11 = p[ j + by1 ]; |
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| 83 | |
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| 84 | sx = s_curve(rx0); |
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| 85 | sy = s_curve(ry0); |
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| 86 | |
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| 87 | q = g2[ b00 ] ; u = at2(rx0,ry0); |
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| 88 | q = g2[ b10 ] ; v = at2(rx1,ry0); |
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| 89 | a = lerp(sx, u, v); |
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| 90 | |
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| 91 | q = g2[ b01 ] ; u = at2(rx0,ry1); |
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| 92 | q = g2[ b11 ] ; v = at2(rx1,ry1); |
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| 93 | b = lerp(sx, u, v); |
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| 94 | |
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| 95 | return lerp(sy, a, b); |
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| 96 | } |
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| 97 | |
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| 98 | double noise3(double vec[3]) |
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| 99 | { |
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| 100 | int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11; |
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| 101 | double rx0, rx1, ry0, ry1, rz0, rz1, *q, sy, sz, a, b, c, d, t, u, v; |
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| 102 | int i, j; |
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| 103 | |
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| 104 | if (start) { |
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| 105 | start = 0; |
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| 106 | initNoise(); |
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| 107 | } |
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| 108 | |
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| 109 | setup(0, bx0,bx1, rx0,rx1); |
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| 110 | setup(1, by0,by1, ry0,ry1); |
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| 111 | setup(2, bz0,bz1, rz0,rz1); |
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| 112 | |
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| 113 | i = p[ bx0 ]; |
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| 114 | j = p[ bx1 ]; |
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| 115 | |
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| 116 | b00 = p[ i + by0 ]; |
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| 117 | b10 = p[ j + by0 ]; |
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| 118 | b01 = p[ i + by1 ]; |
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| 119 | b11 = p[ j + by1 ]; |
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| 120 | |
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| 121 | t = s_curve(rx0); |
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| 122 | sy = s_curve(ry0); |
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| 123 | sz = s_curve(rz0); |
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| 124 | |
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| 125 | q = g3[ b00 + bz0 ] ; u = at3(rx0,ry0,rz0); |
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| 126 | q = g3[ b10 + bz0 ] ; v = at3(rx1,ry0,rz0); |
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| 127 | a = lerp(t, u, v); |
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| 128 | |
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| 129 | q = g3[ b01 + bz0 ] ; u = at3(rx0,ry1,rz0); |
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| 130 | q = g3[ b11 + bz0 ] ; v = at3(rx1,ry1,rz0); |
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| 131 | b = lerp(t, u, v); |
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| 132 | |
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| 133 | c = lerp(sy, a, b); |
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| 134 | |
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| 135 | q = g3[ b00 + bz1 ] ; u = at3(rx0,ry0,rz1); |
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| 136 | q = g3[ b10 + bz1 ] ; v = at3(rx1,ry0,rz1); |
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| 137 | a = lerp(t, u, v); |
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| 138 | |
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| 139 | q = g3[ b01 + bz1 ] ; u = at3(rx0,ry1,rz1); |
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| 140 | q = g3[ b11 + bz1 ] ; v = at3(rx1,ry1,rz1); |
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| 141 | b = lerp(t, u, v); |
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| 142 | |
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| 143 | d = lerp(sy, a, b); |
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| 144 | |
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| 145 | //fprintf(stderr, "%f\n", lerp(sz, c, d)); |
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| 146 | |
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| 147 | return lerp(sz, c, d); |
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| 148 | } |
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| 149 | |
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| 150 | void normalize2(double v[2]) |
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| 151 | { |
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| 152 | double s; |
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| 153 | |
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| 154 | s = sqrt(v[0] * v[0] + v[1] * v[1]); |
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| 155 | v[0] = v[0] / s; |
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| 156 | v[1] = v[1] / s; |
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| 157 | } |
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| 158 | |
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| 159 | void normalize3(double v[3]) |
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| 160 | { |
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| 161 | double s; |
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| 162 | |
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| 163 | s = sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]); |
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| 164 | v[0] = v[0] / s; |
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| 165 | v[1] = v[1] / s; |
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| 166 | v[2] = v[2] / s; |
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| 167 | } |
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| 168 | |
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| 169 | void initNoise(void) |
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| 170 | { |
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| 171 | int i, j, k; |
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| 172 | |
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| 173 | srand(30757); |
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| 174 | for (i = 0 ; i < B ; i++) { |
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| 175 | p[i] = i; |
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| 176 | g1[i] = (double)((rand() % (B + B)) - B) / B; |
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| 177 | |
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| 178 | for (j = 0 ; j < 2 ; j++) |
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| 179 | g2[i][j] = (double)((rand() % (B + B)) - B) / B; |
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| 180 | normalize2(g2[i]); |
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| 181 | |
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| 182 | for (j = 0 ; j < 3 ; j++) |
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| 183 | g3[i][j] = (double)((rand() % (B + B)) - B) / B; |
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| 184 | normalize3(g3[i]); |
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| 185 | } |
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| 186 | |
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| 187 | while (--i) { |
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| 188 | k = p[i]; |
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| 189 | p[i] = p[j = rand() % B]; |
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| 190 | p[j] = k; |
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| 191 | } |
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| 192 | |
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| 193 | for (i = 0 ; i < B + 2 ; i++) { |
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| 194 | p[B + i] = p[i]; |
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| 195 | g1[B + i] = g1[i]; |
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| 196 | for (j = 0 ; j < 2 ; j++) |
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| 197 | g2[B + i][j] = g2[i][j]; |
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| 198 | for (j = 0 ; j < 3 ; j++) |
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| 199 | g3[B + i][j] = g3[i][j]; |
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| 200 | } |
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| 201 | } |
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| 202 | |
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| 203 | /* --- My harmonic summing functions - PDB --------------------------*/ |
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| 204 | |
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| 205 | /* |
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| 206 | In what follows "alpha" is the weight when the sum is formed. |
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| 207 | Typically it is 2, As this approaches 1 the function is noisier. |
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| 208 | "beta" is the harmonic scaling/spacing, typically 2. |
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| 209 | */ |
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| 210 | |
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| 211 | double PerlinNoise1D(double x,double alpha,double beta,int n) |
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| 212 | { |
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| 213 | int i; |
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| 214 | double val,sum = 0; |
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| 215 | double p,scale = 1; |
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| 216 | |
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| 217 | p = x; |
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| 218 | for (i=0;i<n;i++) { |
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| 219 | val = noise1(p); |
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| 220 | sum += val / scale; |
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| 221 | scale *= alpha; |
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| 222 | p *= beta; |
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| 223 | } |
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| 224 | return(sum); |
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| 225 | } |
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| 226 | |
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| 227 | double PerlinNoise2D(double x,double y,double alpha,double beta,int n) |
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| 228 | { |
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| 229 | int i; |
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| 230 | double val,sum = 0; |
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| 231 | double p[2],scale = 1; |
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| 232 | |
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| 233 | p[0] = x; |
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| 234 | p[1] = y; |
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| 235 | for (i=0;i<n;i++) { |
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| 236 | val = noise2(p); |
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| 237 | sum += val / scale; |
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| 238 | scale *= alpha; |
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| 239 | p[0] *= beta; |
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| 240 | p[1] *= beta; |
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| 241 | } |
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| 242 | return(sum); |
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| 243 | } |
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| 244 | |
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| 245 | double PerlinNoise3D(double x,double y,double z,double alpha,double beta,int n) |
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| 246 | { |
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| 247 | int i; |
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| 248 | double val,sum = 0; |
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| 249 | double p[3],scale = 1; |
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| 250 | |
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| 251 | p[0] = x; |
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| 252 | p[1] = y; |
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| 253 | p[2] = z; |
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| 254 | for (i=0;i<n;i++) { |
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| 255 | val = noise3(p); |
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| 256 | sum += val / scale; |
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| 257 | scale *= alpha; |
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| 258 | p[0] *= beta; |
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| 259 | p[1] *= beta; |
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| 260 | p[2] *= beta; |
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| 261 | } |
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| 262 | return(sum); |
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| 263 | } |
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