Lephisto/src/perlin.c

309 lines
7.4 KiB
C

#include <math.h>
#include <stdlib.h>
#include <string.h>
#include "SDL.h"
#include "lephisto.h"
#include "log.h"
#include "rng.h"
#include "lfile.h"
#include "perlin.h"
#define NOISE_MAX_OCTAVES 128
#define NOISE_DEFAULT_HURST 0.5
#define NOISE_DEFAULT_LACUNARITY 2.
#define LERP(a, b, x) (a + x * (b - a))
#define CLAMP(a, b, x) ((x) < (a) ? (a) : ((x) > (b) ? (b) : (x)))
typedef void* noise_t;
/* Used internally. */
typedef struct {
unsigned char map[256]; /* Randomized map of indexes into buffer. */
float buffer[256][3]; /* Random 256x3 buffer. */
/* Fractal stuff. */
float H;
float lacunarity;
float exponent[NOISE_MAX_OCTAVES];
} perlin_data_t;
static perlin_data_t* noise_new(float hurst, float lacunarity);
/* Basic perlin noise. */
static float noise_get(perlin_data_t* pdata, float* f);
/* Fractional brownian motion. */
/* Turbulence. */
static float noise_turbulence(perlin_data_t* noise, float* f, float octaves);
static void noise_delete(perlin_data_t* noise);
static float lattice(perlin_data_t* pdata, int ix, float fx, int iy,
float fy, int iz, float fz) {
int nindex;
float value;
nindex = 0;
nindex = pdata->map[(nindex + ix) & 0xFF];
nindex = pdata->map[(nindex + iy) & 0xFF];
nindex = pdata->map[(nindex + iz) & 0xFF];
value = pdata->buffer[nindex][0] * fx;
value += pdata->buffer[nindex][1] * fy;
value += pdata->buffer[nindex][2] * fz;
return value;
}
#define SWAP(a, b, t) t = a; a = b; b = t
#define FLOOR(a) ((int) a - (a < 0 && a != (int)a))
#define CUBIC(a) (a * a * (3 - 2 * a))
static void normalize(float f[3]) {
float magnitude;
magnitude = 1. / sqrtf(f[0]*f[0] + f[1]*f[1] + f[2]*f[2]);
f[0] *= magnitude;
f[1] *= magnitude;
f[2] *= magnitude;
}
static perlin_data_t* noise_new(float hurst, float lacunarity) {
perlin_data_t* pdata = (perlin_data_t*)calloc(sizeof(perlin_data_t), 1);
int i, j;
unsigned char tmp;
float f = 1;
for(i = 0; i < 256; i++) {
pdata->map[i] = (unsigned char)i;
pdata->buffer[i][0] = RNGF()-0.5;
pdata->buffer[i][1] = RNGF()-0.5;
pdata->buffer[i][2] = RNGF()-0.5;
normalize(pdata->buffer[i]);
}
while(--i) {
j = RNG(0, 255);
SWAP(pdata->map[i], pdata->map[j], tmp);
}
pdata->H = hurst;
pdata->lacunarity = lacunarity;
for(i = 0; i < NOISE_MAX_OCTAVES; i++) {
/*exponent[i] = powf(f, -H);*/
pdata->exponent[i] = 1. / f;
f *= lacunarity;
}
return (noise_t)pdata;
}
static float noise_get(perlin_data_t* pdata, float *f ) {
int n[3]; /* Indexes to pass to lattice function. */
float r[3]; /* Remainders to pass to lattice function. */
float w[3]; /* Cubic values to pass to interpolation function. */
float value;
n[0] = FLOOR(f[0]);
n[1] = FLOOR(f[1]);
n[2] = FLOOR(f[2]);
r[0] = f[0] - n[0];
r[1] = f[1] - n[1];
r[2] = f[2] - n[2];
w[0] = CUBIC(r[0]);
w[1] = CUBIC(r[1]);
w[2] = CUBIC(r[2]);
/*
* This is the big ugly part that is in dire need
* of optimisation!!!!
*/
value = LERP(LERP(LERP(lattice(pdata,n[0], r[0], n[1], r[1], n[2], r[2]),
lattice(pdata,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2]),
w[0]),
LERP(lattice(pdata,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2]),
lattice(pdata,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2]),
w[0]),
w[1]),
LERP(LERP(lattice(pdata,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1),
lattice(pdata,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1),
w[0]),
LERP(lattice(pdata,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1),
lattice(pdata,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1),
w[0]),
w[1]),
w[2]);
return CLAMP(-0.99999f, 0.99999f, value);
}
static float noise_turbulence(perlin_data_t* noise, float* f, float octaves) {
float tf[3];
perlin_data_t* pdata = (perlin_data_t*) noise;
/* Init locals. */
float value = 0;
int i;
tf[0] = f[0];
tf[1] = f[1];
tf[2] = f[2];
/* Inner loop of spectral construction, where the fractal is built. */
for(i = 0; i < octaves; i++) {
value += ABS(noise_get(noise, tf)) * pdata->exponent[i];
tf[0] *= pdata->lacunarity;
tf[1] *= pdata->lacunarity;
tf[2] *= pdata->lacunarity;
}
return CLAMP(-0.99999f, 0.99999f, value);
}
void noise_delete(perlin_data_t* noise) {
free(noise);
}
/* Generate a 3d nebulae map of dimensions w,h,n with ruggedness rig. */
float* noise_genNebulaeMap(const int w, const int h, const int n, float rug) {
int x, y, z;
float f[3];
int octaves;
float hurst;
float lacunarity;
perlin_data_t* noise;
float* nebulae;;
float value;
float zoom;
float max;
unsigned int* t, s;
/* Pretty default values. */
octaves = 3;
hurst = NOISE_DEFAULT_HURST;
lacunarity = NOISE_DEFAULT_LACUNARITY;
zoom = rug * ((float)h/768.)*((float)w/1024.);
/* Create noise and data. */
noise = noise_new(hurst, lacunarity);
nebulae = malloc(sizeof(float)*w*h*n);
if(nebulae == NULL) {
WARN("Out of memory!");
return NULL;
}
/* Some debug information and time setting. */
s = SDL_GetTicks();
t = malloc(sizeof(unsigned int)*n);
DEBUG("Generating Nebulae of size %dx%dx%d", w, h, n);
/* Start to create the nebulae. */
max = 0.;
for(z = 0; z < n; z++) {
f[2] = zoom * (float)z / (float)n;
for(y = 0; y < h; y++) {
f[1] = zoom * (float)y / (float)h;
for(x = 0; x < w; x++) {
f[0] = zoom * (float)x / (float)w;
value = noise_turbulence(noise, f, octaves);
if(max < value) max = value;
nebulae[z*w*h + y*w+x] = value;
}
}
/* More time magic debug. */
t[z] = SDL_GetTicks();
DEBUG(" Layer %d/%d generated in %dms", z+1, n,
(z>0) ? t[z] - t[z-1] : t[z] - s);
}
/* Post filtering. */
value = 1. - max;
for(z = 0; x < n; z++)
for(y = 0; y < h; y++)
for(x = 0; x < w; x++)
nebulae[z*w*h + y*w + x] += value;
/* Cleanup. */
noise_delete(noise);
/* Results. */
DEBUG("Nebulae Generated in %dms", SDL_GetTicks() - s);
return nebulae;
}
/* Generate tiny nebuale puffs */
float* noise_genNebulaePuffMap(const int w, const int h, float rug) {
int x, y, hw, hh;
float d;
float f[3];
int octaves;
float hurst;
float lacunarity;
perlin_data_t* noise;
float* nebulae;
float value;
float zoom;
float max;
/* Pretty default values. */
octaves = 3;
hurst = NOISE_DEFAULT_HURST;
lacunarity = NOISE_DEFAULT_LACUNARITY;
zoom = rug;
/* Create noise and data. */
noise = noise_new(hurst, lacunarity);
nebulae = malloc(sizeof(float)*w*h);
if(nebulae == NULL) {
WARN("Out of memory!");
return NULL;
}
/* Start to create the nebulae. */
max = 0.;
f[2] = 0.;
hw = w/2;
hh = h/2;
d = (float)MIN(hw, hh);
for(y = 0; y < h; y++) {
f[1] = zoom * (float)y / (float)h;
for(x = 0; x < w; x++) {
f[0] = zoom * (float)x / (float)w;
value = noise_turbulence(noise, f, octaves);
/* Make value also depend on distance from center. */
value *= (d - 1. - sqrtf((float)((x-hw)*(x-hw)+(y-hh)*(y-hh))))/d;
if(value < 0.) value = 0.;
if(max < value) max = value;
nebulae[y*w + x] = value;
}
}
/* Post filtering. */
/*value = 1. - max;
for(y = 0; y < h; y++)
for(x = 0; x < w; x++)
if(nebulae[y*w+x] > 0.)
nebulae[y*w + x] += value;*/
/* Clean up. */
noise_delete(noise);
/* Results. */
return nebulae;
}