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annotate src/dmperlin.c @ 2289:81b561abb6e9

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Cleanup.
author Matti Hamalainen <ccr@tnsp.org>
date Thu, 27 Jun 2019 14:19:33 +0300
parents 848a88ce7a57
children 69a5af2eb1ea
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1 /*
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2 * DMLib
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3 * -- Perlin noise functionality
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4 * Programmed and designed by Matti 'ccr' Hamalainen
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5 * (C) Copyright 2012 Tecnic Software productions (TNSP)
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6 */
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7 #include "dmperlin.h"
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8 #include "dmcurves.h"
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9 #include <math.h>
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10
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11
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12 #define DM_PERLIN_SETUP(i, b0, b1, r0, r1) \
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13 { \
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14 t = (vec[i] + DM_PLNS_N); \
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15 b0 = (((int) t) & DM_PLNS_BM); \
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16 b1 = ((b0 + 1) & DM_PLNS_BM); \
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17 r0 = (t - ((int) t)); \
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18 r1 = (r0 - 1.0f); \
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19 }
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20
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21 #define DM_PERLIN_AT2(rx,ry) ((rx) * q[0] + (ry) * q[1])
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23
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24 static DMFloat dmPerlinDoNoise2(const DMPerlinContext *ctx, const DMFloat vec[2])
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25 {
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26 int bx0, bx1, by0, by1, b00, b10, b01, b11;
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27 DMFloat rx0, rx1, ry0, ry1, sx, sy, a, b, t, u, v;
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28 const DMFloat *q;
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29 int i, j;
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30
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31 DM_PERLIN_SETUP(0, bx0, bx1, rx0, rx1);
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32 DM_PERLIN_SETUP(1, by0, by1, ry0, ry1);
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33
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34 i = ctx->p[bx0];
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35 j = ctx->p[bx1];
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36
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37 b00 = ctx->p[i + by0];
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38 b10 = ctx->p[j + by0];
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39 b01 = ctx->p[i + by1];
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40 b11 = ctx->p[j + by1];
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41
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42 sx = DMM_S_CURVE(rx0);
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43 sy = DMM_S_CURVE(ry0);
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44
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45 q = ctx->g2[b00];
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46 u = DM_PERLIN_AT2(rx0, ry0);
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47
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48 q = ctx->g2[b10];
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49 v = DM_PERLIN_AT2(rx1, ry0);
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50 a = DMM_LERP(sx, u, v);
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51
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52 q = ctx->g2[b01];
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53 u = DM_PERLIN_AT2(rx0, ry1);
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54
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55 q = ctx->g2[b11];
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56 v = DM_PERLIN_AT2(rx1, ry1);
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57 b = DMM_LERP(sx, u, v);
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58
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59 return DMM_LERP(sy, a, b);
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60 }
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61
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62
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63 static void dmPerlinNormalize2(DMFloat v[2])
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64 {
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65 DMFloat s = sqrt(v[0] * v[0] + v[1] * v[1]);
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66 v[0] /= s;
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67 v[1] /= s;
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68 }
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69
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70
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71 int dmPerlinInit(DMPerlinContext *ctx, const int seed)
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72 {
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73 int i, j;
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74
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75 if (ctx == NULL)
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76 return DMERR_NULLPTR;
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77
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78 dmMemset(ctx, 0, sizeof(*ctx));
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79
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80 if (seed < 0)
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81 return DMERR_INVALID_ARGS;
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82
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83 srand(seed);
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84
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85 for (i = 0; i < DM_PLNS_B; i++)
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86 {
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87 ctx->p[i] = i;
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88 ctx->g1[i] = (DMFloat) ((rand() % (DM_PLNS_B + DM_PLNS_B)) - DM_PLNS_B) / DM_PLNS_B;
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89
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90 for (j = 0; j < 2; j++)
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91 ctx->g2[i][j] = (DMFloat) ((rand() % (DM_PLNS_B + DM_PLNS_B)) - DM_PLNS_B) / DM_PLNS_B;
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92
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93 dmPerlinNormalize2(ctx->g2[i]);
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94 }
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95
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96 while (--i)
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97 {
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98 int k = ctx->p[i];
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99 ctx->p[i] = ctx->p[j = rand() % DM_PLNS_B];
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100 ctx->p[j] = k;
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101 }
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102
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103 for (i = 0; i < DM_PLNS_B + 2; i++)
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104 {
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105 ctx->p[DM_PLNS_B + i] = ctx->p[i];
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106 ctx->g1[DM_PLNS_B + i] = ctx->g1[i];
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107
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108 for (j = 0; j < 2; j++)
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109 ctx->g2[DM_PLNS_B + i][j] = ctx->g2[i][j];
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110 }
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111
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112 return DMERR_OK;
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113 }
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114
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115
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116 /* Harmonic summing functions - PDB
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117 * In what follows "alpha" is the weight when the sum is formed.
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118 * Typically it is 2, As this approaches 1 the function is noisier.
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119 * "beta" is the harmonic scaling/spacing, typically 2.
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120 */
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121 DMFloat dmPerlinNoise2D(const DMPerlinContext *ctx, DMFloat x, DMFloat y, DMFloat alpha, DMFloat beta, int n)
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122 {
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123 DMFloat val, sum = 0;
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124 DMFloat p[2], scale = 1;
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125
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126 p[0] = x;
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127 p[1] = y;
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128 for (int i = 0; i < n; i++)
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129 {
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130 val = dmPerlinDoNoise2(ctx, p);
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131 sum += val / scale;
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132 scale *= alpha;
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133 p[0] *= beta;
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134 p[1] *= beta;
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135 }
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136
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137 return sum;
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Matti Hamalainen <ccr@tnsp.org>
parents:
diff changeset
138 }