/*****************************************************************

  Implementation of the fractional Brownian motion algorithm. These

  functions were originally the work of F. Kenton Musgrave.

  For documentation of the different functions please refer to the

  book: 

  "Texturing and modeling: a procedural approach"

  by David S. Ebert et. al.

******************************************************************/

#if defined (_MSC_VER)

#include <qglobal.h>

#endif

#include <time.h>

#include <stdlib.h>

#include "fbm.h"

#if defined(Q_CC_MSVC)

#pragma warning(disable:4244)

#endif

/* Definitions used by the noise2() functions */

//#define B 0x100

//#define BM 0xff

#define B 0x20

#define BM 0x1f

#define N 0x1000

#define NP 12   /* 2^N */

#define NM 0xfff

static int   p[B + B + 2];

static float g3[B + B + 2][3];

static float g2[B + B + 2][2];

static float g1[B + B + 2];

static int   start = 1;

static void init(void);

#define s_curve(t) ( t * t * (3. - 2. * t) )

#define lerp(t, a, b) ( a + t * (b - a) )

#define setup(i,b0,b1,r0,r1)\

	t = vec[i] + N;\

	b0 = ((int)t) & BM;\

	b1 = (b0+1) & BM;\

	r0 = t - (int)t;\

	r1 = r0 - 1.;

#define at3(rx,ry,rz) ( rx * q[0] + ry * q[1] + rz * q[2] )

/* Fractional Brownian Motion function */

double fBm( Vector point, double H, double lacunarity, double octaves,

	    int init )

{

    double            value, frequency, remainder;

    int               i;

    static double     exponent_array[10];

    float             vec[3];

    /* precompute and store spectral weights */

    if ( init ) {

	start = 1;

	srand( time(0) );

	/* seize required memory for exponent_array */

	frequency = 1.0;

	for (i=0; i<=octaves; i++) {

	    /* compute weight for each frequency */

	    exponent_array[i] = pow( frequency, -H );

	    frequency *= lacunarity;

	}

    }

    value = 0.0;            /* initialize vars to proper values */

    frequency = 1.0;

    vec[0]=point.x;

    vec[1]=point.y;

    vec[2]=point.z;

    /* inner loop of spectral construction */

    for (i=0; i<octaves; i++) {

	/* value += noise3( vec ) * exponent_array[i];*/

	value += noise3( vec ) * exponent_array[i];

	vec[0] *= lacunarity;

	vec[1] *= lacunarity;

	vec[2] *= lacunarity;

    } /* for */

    remainder = octaves - (int)octaves;

    if ( remainder )      /* add in ``octaves''  remainder */

	/* ``i''  and spatial freq. are preset in loop above */

	value += remainder * noise3( vec ) * exponent_array[i];

    return( value );

} /* fBm() */

float noise3(float vec[3])

{

    int bx0, bx1, by0, by1, bz0, bz1, b00, b10, b01, b11;

    float rx0, rx1, ry0, ry1, rz0, rz1, *q, sy, sz, a, b, c, d, t, u, v;

    register int i, j;

    if (start) {

	start = 0;

	init();

    }

    setup(0, bx0,bx1, rx0,rx1);

    setup(1, by0,by1, ry0,ry1);

    setup(2, bz0,bz1, rz0,rz1);

    i = p[ bx0 ];

    j = p[ bx1 ];

    b00 = p[ i + by0 ];

    b10 = p[ j + by0 ];

    b01 = p[ i + by1 ];

    b11 = p[ j + by1 ];

    t  = s_curve(rx0);

    sy = s_curve(ry0);

    sz = s_curve(rz0);

    q = g3[ b00 + bz0 ] ; u = at3(rx0,ry0,rz0);

    q = g3[ b10 + bz0 ] ; v = at3(rx1,ry0,rz0);

    a = lerp(t, u, v);

    q = g3[ b01 + bz0 ] ; u = at3(rx0,ry1,rz0);

    q = g3[ b11 + bz0 ] ; v = at3(rx1,ry1,rz0);

    b = lerp(t, u, v);

    c = lerp(sy, a, b);

    q = g3[ b00 + bz1 ] ; u = at3(rx0,ry0,rz1);

    q = g3[ b10 + bz1 ] ; v = at3(rx1,ry0,rz1);

    a = lerp(t, u, v);

    q = g3[ b01 + bz1 ] ; u = at3(rx0,ry1,rz1);

    q = g3[ b11 + bz1 ] ; v = at3(rx1,ry1,rz1);

    b = lerp(t, u, v);

    d = lerp(sy, a, b);

    return lerp(sz, c, d);

}

static void normalize2(float v[2])

{

    float s;

    s = sqrt(v[0] * v[0] + v[1] * v[1]);

    v[0] = v[0] / s;

    v[1] = v[1] / s;

}

static void normalize3(float v[3])

{

    float s;

    s = sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]);

    v[0] = v[0] / s;

    v[1] = v[1] / s;

    v[2] = v[2] / s;

}

static void init(void)

{

    int i, j, k;

    for (i = 0 ; i < B ; i++) {

	p[i] = i;

	g1[i] = (float)((rand() % (B + B)) - B) / B;

	for (j = 0 ; j < 2 ; j++)

	    g2[i][j] = (float)((rand() % (B + B)) - B) / B;

	normalize2(g2[i]);

	for (j = 0 ; j < 3 ; j++)

	    g3[i][j] = (float)((rand() % (B + B)) - B) / B;

	normalize3(g3[i]);

    }

    while (--i) {

	k = p[i];

	p[i] = p[j = rand() % B];

	p[j] = k;

    }

    for (i = 0 ; i < B + 2 ; i++) {

	p[B + i] = p[i];

	g1[B + i] = g1[i];

	for (j = 0 ; j < 2 ; j++)

	    g2[B + i][j] = g2[i][j];

	for (j = 0 ; j < 3 ; j++)

	    g3[B + i][j] = g3[i][j];

    }

}