tcod-haskell-0.1.0.0: libtcod/src/noise_c.c
/*
* libtcod 1.6.3
* Copyright (c) 2008,2009,2010,2012,2013,2016,2017 Jice & Mingos & rmtew
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * The name of Jice or Mingos may not be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY JICE, MINGOS AND RMTEW ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL JICE, MINGOS OR RMTEW BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#include <noise.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include <mersenne.h>
#include <libtcod_utility.h>
#define WAVELET_TILE_SIZE 32
#define WAVELET_ARAD 16
#define SIMPLEX_SCALE 0.5f
#define WAVELET_SCALE 2.0f
typedef struct {
int ndim;
unsigned char map[256]; /* Randomized map of indexes into buffer */
float buffer[256][TCOD_NOISE_MAX_DIMENSIONS]; /* Random 256 x ndim buffer */
/* fractal stuff */
float H;
float lacunarity;
float exponent[TCOD_NOISE_MAX_OCTAVES];
float *waveletTileData;
TCOD_random_t rand;
/* noise type */
TCOD_noise_type_t noise_type;
} perlin_data_t;
static float lattice( perlin_data_t *data, int ix, float fx, int iy, float fy, int iz, float fz, int iw, float fw)
{
int n[4] = {ix, iy, iz, iw};
float f[4] = {fx, fy, fz, fw};
int nIndex = 0;
int i;
float value = 0;
for(i=0; i<data->ndim; i++)
nIndex = data->map[(nIndex + n[i]) & 0xFF];
for(i=0; i<data->ndim; i++)
value += data->buffer[nIndex][i] * f[i];
return value;
}
#define DEFAULT_SEED 0x15687436
#define DELTA 1e-6f
#define SWAP(a, b, t) t = a; a = b; b = t
#define FLOOR(a) ((a)> 0 ? ((int)a) : (((int)a)-1) )
#define CUBIC(a) ( a * a * (3 - 2*a) )
static void normalize(perlin_data_t *data, float *f)
{
float magnitude = 0;
int i;
for(i=0; i<data->ndim; i++)
magnitude += f[i]*f[i];
magnitude = 1.0f / (float)sqrt(magnitude);
for(i=0; i<data->ndim; i++)
f[i] *= magnitude;
}
TCOD_noise_t TCOD_noise_new(int ndim, float hurst, float lacunarity, TCOD_random_t random)
{
perlin_data_t *data=(perlin_data_t *)calloc(sizeof(perlin_data_t),1);
int i, j;
unsigned char tmp;
float f = 1;
data->rand = random ? random : TCOD_random_get_instance();
data->ndim = ndim;
for(i=0; i<256; i++)
{
data->map[i] = (unsigned char)i;
for(j=0; j<data->ndim; j++)
data->buffer[i][j] = TCOD_random_get_float(data->rand,-0.5, 0.5);
normalize(data,data->buffer[i]);
}
while(--i)
{
j = TCOD_random_get_int(data->rand,0, 255);
SWAP(data->map[i], data->map[j], tmp);
}
data->H = hurst;
data->lacunarity = lacunarity;
for(i=0; i<TCOD_NOISE_MAX_OCTAVES; i++)
{
/*exponent[i] = powf(f, -H); */
data->exponent[i] = 1.0f / f;
f *= lacunarity;
}
data->noise_type = TCOD_NOISE_DEFAULT;
return (TCOD_noise_t)data;
}
float TCOD_noise_perlin( TCOD_noise_t noise, float *f )
{
perlin_data_t *data=(perlin_data_t *)noise;
int n[TCOD_NOISE_MAX_DIMENSIONS]; /* Indexes to pass to lattice function */
int i;
float r[TCOD_NOISE_MAX_DIMENSIONS]; /* Remainders to pass to lattice function */
float w[TCOD_NOISE_MAX_DIMENSIONS]; /* Cubic values to pass to interpolation function */
float value;
for(i=0; i<data->ndim; i++)
{
n[i] = FLOOR(f[i]);
r[i] = f[i] - n[i];
w[i] = CUBIC(r[i]);
}
switch(data->ndim)
{
case 1:
value = LERP(lattice(data,n[0], r[0],0,0,0,0,0,0),
lattice(data,n[0]+1, r[0]-1,0,0,0,0,0,0),
w[0]);
break;
case 2:
value = LERP(LERP(lattice(data,n[0], r[0], n[1], r[1],0,0,0,0),
lattice(data,n[0]+1, r[0]-1, n[1], r[1],0,0,0,0),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1,0,0,0,0),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1,0,0,0,0),
w[0]),
w[1]);
break;
case 3:
value = LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2],0,0),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2],0,0),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2],0,0),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2],0,0),
w[0]),
w[1]),
LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1,0,0),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1,0,0),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
w[0]),
w[1]),
w[2]);
break;
case 4:
default:
value = LERP(LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2], n[3], r[3]),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2], n[3], r[3]),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2], n[3], r[3]),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2], n[3], r[3]),
w[0]),
w[1]),
LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1, n[3], r[3]),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1, n[3], r[3]),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1, n[3], r[3]),
w[0]),
w[1]),
w[2]),
LERP(LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2], r[2], n[3]+1, r[3]-1),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2], r[2], n[3]+1, r[3]-1),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2], r[2], n[3]+1, r[3]-1),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2], r[2], n[3]+1, r[3]-1),
w[0]),
w[1]),
LERP(LERP(lattice(data,n[0], r[0], n[1], r[1], n[2]+1, r[2]-1, n[3]+1, r[3]-1),
lattice(data,n[0]+1, r[0]-1, n[1], r[1], n[2]+1, r[2]-1, n[3]+1, r[3]-1),
w[0]),
LERP(lattice(data,n[0], r[0], n[1]+1, r[1]-1, n[2]+1, r[2]-1,0,0),
lattice(data,n[0]+1, r[0]-1, n[1]+1, r[1]-1, n[2]+1, r[2]-1, n[3]+1, r[3]-1),
w[0]),
w[1]),
w[2]),
w[3]);
break;
}
return CLAMP(-0.99999f, 0.99999f, value);
}
static int absmod(int x, int n) {
int m=x%n;
return m < 0 ? m+n : m;
}
/* simplex noise, adapted from Ken Perlin's presentation at Siggraph 2001 */
/* and Stefan Gustavson implementation */
#define TCOD_NOISE_SIMPLEX_GRADIENT_1D(n,h,x) { float grad; h &= 0xF; grad=1.0f+(h & 7); if ( h & 8 ) grad = -grad; n = grad * x; }
#define TCOD_NOISE_SIMPLEX_GRADIENT_2D(n,h,x,y) { float u,v; h &= 0x7; if ( h < 4 ) { u=x; v=2.0f*y; } else { u=y; v=2.0f*x; } n = ((h & 1) ? -u : u) + ((h & 2) ? -v :v ); }
#define TCOD_NOISE_SIMPLEX_GRADIENT_3D(n,h,x,y,z) { float u,v; h &= 0xF; u = (h < 8 ? x : y); v = (h < 4 ? y : ( h == 12 || h == 14 ? x : z ) ); n= ((h & 1) ? -u : u ) + ((h & 2) ? -v : v); }
#define TCOD_NOISE_SIMPLEX_GRADIENT_4D(n,h,x,y,z,t) { float u,v,w; h &= 0x1F; u = (h < 24 ? x:y); v = (h < 16 ? y:z); w = (h < 8 ? z:t); n= ((h & 1) ? -u : u ) + ((h & 2) ? -v : v) + ((h & 4) ? -w : w);}
static float simplex[64][4] = {
{0,1,2,3},{0,1,3,2},{0,0,0,0},{0,2,3,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,2,3,0},
{0,2,1,3},{0,0,0,0},{0,3,1,2},{0,3,2,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,3,2,0},
{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},
{1,2,0,3},{0,0,0,0},{1,3,0,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,3,0,1},{2,3,1,0},
{1,0,2,3},{1,0,3,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,0,3,1},{0,0,0,0},{2,1,3,0},
{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},
{2,0,1,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,0,1,2},{3,0,2,1},{0,0,0,0},{3,1,2,0},
{2,1,0,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,1,0,2},{0,0,0,0},{3,2,0,1},{3,2,1,0},
};
float TCOD_noise_simplex(TCOD_noise_t noise, float *f) {
perlin_data_t *data=(perlin_data_t *)noise;
switch(data->ndim) {
case 1 :
{
int i0=(int)FLOOR(f[0]*SIMPLEX_SCALE);
int i1=i0+1;
float x0 = f[0]*SIMPLEX_SCALE - i0;
float x1 = x0 - 1.0f;
float t0 = 1.0f - x0*x0;
float t1 = 1.0f - x1*x1;
float n0,n1;
t0 = t0*t0;
t1 = t1*t1;
i0=data->map[i0&0xFF];
TCOD_NOISE_SIMPLEX_GRADIENT_1D(n0,i0,x0);
n0*=t0*t0;
i1=data->map[i1&0xFF];
TCOD_NOISE_SIMPLEX_GRADIENT_1D(n1,i1,x1);
n1*=t1*t1;
return 0.25f * (n0+n1);
}
break;
case 2 :
{
#define F2 0.366025403f /* 0.5f * (sqrtf(3.0f)-1.0f); */
#define G2 0.211324865f /* (3.0f - sqrtf(3.0f))/6.0f; */
float s = (f[0]+f[1])*F2*SIMPLEX_SCALE;
float xs = f[0]*SIMPLEX_SCALE+s;
float ys = f[1]*SIMPLEX_SCALE+s;
int i=FLOOR(xs);
int j=FLOOR(ys);
float t = (i+j)*G2;
float xo = i-t;
float yo = j-t;
float x0 = f[0]*SIMPLEX_SCALE-xo;
float y0 = f[1]*SIMPLEX_SCALE-yo;
int i1,j1,ii = absmod(i ,256),jj = absmod(j, 256);
float n0,n1,n2,x1,y1,x2,y2,t0,t1,t2;
if ( x0 > y0 ) {
i1=1;j1=0;
} else {
i1=0;j1=1;
}
x1 = x0 - i1 + G2;
y1 = y0 - j1 + G2;
x2 = x0 - 1.0f + 2.0f * G2;
y2 = y0 - 1.0f + 2.0f * G2;
t0 = 0.5f - x0*x0 - y0*y0;
if ( t0 < 0.0f ) {
n0 = 0.0f;
} else {
int idx = (ii + data->map[jj])&0xFF;
t0 *= t0;
idx=data->map[idx];
TCOD_NOISE_SIMPLEX_GRADIENT_2D(n0,idx,x0,y0);
n0 *= t0*t0;
}
t1 = 0.5f - x1*x1 -y1*y1;
if ( t1 < 0.0f ) {
n1 = 0.0f;
} else {
int idx = (ii + i1 + data->map[(jj+j1)&0xFF]) & 0xFF;
t1 *= t1;
idx=data->map[idx];
TCOD_NOISE_SIMPLEX_GRADIENT_2D(n1,idx,x1,y1);
n1 *= t1*t1;
}
t2 = 0.5f - x2*x2 -y2*y2;
if ( t2 < 0.0f ) {
n2 = 0.0f;
} else {
int idx = (ii + 1 + data->map[(jj+1)&0xFF]) & 0xFF;
t2 *= t2;
idx=data->map[idx];
TCOD_NOISE_SIMPLEX_GRADIENT_2D(n2,idx,x2,y2);
n2 *= t2*t2;
}
return 40.0f * (n0+n1+n2);
}
break;
case 3 :
{
#define F3 0.333333333f
#define G3 0.166666667f
float n0,n1,n2,n3;
float s =(f[0]+f[1]+f[2])*F3*SIMPLEX_SCALE;
float xs=f[0]*SIMPLEX_SCALE+s;
float ys=f[1]*SIMPLEX_SCALE+s;
float zs=f[2]*SIMPLEX_SCALE+s;
int i=FLOOR(xs);
int j=FLOOR(ys);
int k=FLOOR(zs);
float t=(float)(i+j+k)*G3;
float xo = i-t;
float yo = j-t;
float zo = k-t;
float x0 = f[0]*SIMPLEX_SCALE-xo;
float y0 = f[1]*SIMPLEX_SCALE-yo;
float z0 = f[2]*SIMPLEX_SCALE-zo;
int i1,j1,k1,i2,j2,k2,ii,jj,kk;
float x1,y1,z1,x2,y2,z2,x3,y3,z3,t0,t1,t2,t3;
if ( x0 >= y0 ) {
if ( y0 >= z0 ) {
i1=1;j1=0;k1=0;i2=1;j2=1;k2=0;
} else if ( x0 >= z0 ) {
i1=1;j1=0;k1=0;i2=1;j2=0;k2=1;
} else {
i1=0;j1=0;k1=1;i2=1;j2=0;k2=1;
}
} else {
if ( y0 < z0 ) {
i1=0;j1=0;k1=1;i2=0;j2=1;k2=1;
} else if ( x0 < z0 ) {
i1=0;j1=1;k1=0;i2=0;j2=1;k2=1;
} else {
i1=0;j1=1;k1=0;i2=1;j2=1;k2=0;
}
}
x1 = x0 -i1 + G3;
y1 = y0 -j1 + G3;
z1 = z0 -k1 + G3;
x2 = x0 -i2 + 2.0f*G3;
y2 = y0 -j2 + 2.0f*G3;
z2 = z0 -k2 + 2.0f*G3;
x3 = x0 - 1.0f +3.0f * G3;
y3 = y0 - 1.0f +3.0f * G3;
z3 = z0 - 1.0f +3.0f * G3;
ii = absmod(i, 256);
jj = absmod(j, 256);
kk = absmod(k, 256);
t0 = 0.6f - x0*x0 -y0*y0 -z0*z0;
if ( t0 < 0.0f ) n0 = 0.0f;
else {
int idx = data->map[ (ii + data->map[ (jj + data->map[ kk ]) &0xFF ])& 0xFF ];
t0 *= t0;
TCOD_NOISE_SIMPLEX_GRADIENT_3D(n0,idx,x0,y0,z0);
n0 *= t0*t0;
}
t1 = 0.6f - x1*x1 -y1*y1 -z1*z1;
if ( t1 < 0.0f ) n1 = 0.0f;
else {
int idx = data->map[ (ii + i1 + data->map[ (jj + j1 + data->map[ (kk + k1)& 0xFF ]) &0xFF ])& 0xFF ];
t1 *= t1;
TCOD_NOISE_SIMPLEX_GRADIENT_3D(n1,idx,x1,y1,z1);
n1 *= t1*t1;
}
t2 = 0.6f - x2*x2 -y2*y2 -z2*z2;
if ( t2 < 0.0f ) n2 = 0.0f;
else {
int idx = data->map[ (ii + i2 + data->map[ (jj + j2 + data->map[ (kk + k2)& 0xFF ]) &0xFF ])& 0xFF ];
t2 *= t2;
TCOD_NOISE_SIMPLEX_GRADIENT_3D(n2,idx,x2,y2,z2);
n2 *= t2*t2;
}
t3 = 0.6f - x3*x3 -y3*y3 -z3*z3;
if ( t3 < 0.0f ) n3 = 0.0f;
else {
int idx = data->map[ (ii + 1 + data->map[ (jj + 1 + data->map[ (kk + 1)& 0xFF ]) &0xFF ])& 0xFF ];
t3 *= t3;
TCOD_NOISE_SIMPLEX_GRADIENT_3D(n3,idx,x3,y3,z3);
n3 *= t3*t3;
}
return 32.0f * (n0+n1+n2+n3);
}
break;
case 4 :
{
#define F4 0.309016994f /* (sqrtf(5.0f)-1.0f)/4.0f */
#define G4 0.138196601f /* (5.0f - sqrtf(5.0f))/20.0f */
float n0,n1,n2,n3,n4;
float s = (f[0]+f[1]+f[2]+f[3])*F4 * SIMPLEX_SCALE;
float xs=f[0]*SIMPLEX_SCALE+s;
float ys=f[1]*SIMPLEX_SCALE+s;
float zs=f[2]*SIMPLEX_SCALE+s;
float ws=f[3]*SIMPLEX_SCALE+s;
int i=FLOOR(xs);
int j=FLOOR(ys);
int k=FLOOR(zs);
int l=FLOOR(ws);
float t=(float)(i+j+k+l)*G4;
float xo = i-t;
float yo = j-t;
float zo = k-t;
float wo = l-t;
float x0 = f[0]*SIMPLEX_SCALE-xo;
float y0 = f[1]*SIMPLEX_SCALE-yo;
float z0 = f[2]*SIMPLEX_SCALE-zo;
float w0 = f[3]*SIMPLEX_SCALE-wo;
int c1 = (x0 > y0 ? 32 : 0);
int c2 = (x0 > z0 ? 16 : 0);
int c3 = (y0 > z0 ? 8 : 0);
int c4 = (x0 > w0 ? 4 : 0);
int c5 = (y0 > w0 ? 2 : 0);
int c6 = (z0 > w0 ? 1 : 0);
int c = c1+c2+c3+c4+c5+c6;
int i1,j1,k1,l1,i2,j2,k2,l2,i3,j3,k3,l3,ii,jj,kk,ll;
float x1,y1,z1,w1,x2,y2,z2,w2,x3,y3,z3,w3,x4,y4,z4,w4,t0,t1,t2,t3,t4;
i1 = simplex[c][0] >= 3 ? 1:0;
j1 = simplex[c][1] >= 3 ? 1:0;
k1 = simplex[c][2] >= 3 ? 1:0;
l1 = simplex[c][3] >= 3 ? 1:0;
i2 = simplex[c][0] >= 2 ? 1:0;
j2 = simplex[c][1] >= 2 ? 1:0;
k2 = simplex[c][2] >= 2 ? 1:0;
l2 = simplex[c][3] >= 2 ? 1:0;
i3 = simplex[c][0] >= 1 ? 1:0;
j3 = simplex[c][1] >= 1 ? 1:0;
k3 = simplex[c][2] >= 1 ? 1:0;
l3 = simplex[c][3] >= 1 ? 1:0;
x1 = x0 -i1 + G4;
y1 = y0 -j1 + G4;
z1 = z0 -k1 + G4;
w1 = w0 -l1 + G4;
x2 = x0 -i2 + 2.0f*G4;
y2 = y0 -j2 + 2.0f*G4;
z2 = z0 -k2 + 2.0f*G4;
w2 = w0 -l2 + 2.0f*G4;
x3 = x0 -i3 + 3.0f*G4;
y3 = y0 -j3 + 3.0f*G4;
z3 = z0 -k3 + 3.0f*G4;
w3 = w0 -l3 + 3.0f*G4;
x4 = x0 - 1.0f +4.0f * G4;
y4 = y0 - 1.0f +4.0f * G4;
z4 = z0 - 1.0f +4.0f * G4;
w4 = w0 - 1.0f +4.0f * G4;
ii = absmod(i, 256);
jj = absmod(j, 256);
kk = absmod(k, 256);
ll = absmod(l, 256);
t0 = 0.6f - x0*x0 -y0*y0 -z0*z0 -w0*w0;
if ( t0 < 0.0f ) n0 = 0.0f;
else {
int idx = data->map[ (ii + data->map[ (jj + data->map[ (kk + data->map[ ll ] ) &0xFF]) &0xFF ])& 0xFF ];
t0 *= t0;
TCOD_NOISE_SIMPLEX_GRADIENT_4D(n0,idx,x0,y0,z0,w0);
n0 *= t0*t0;
}
t1 = 0.6f - x1*x1 -y1*y1 -z1*z1 -w1*w1;
if ( t1 < 0.0f ) n1 = 0.0f;
else {
int idx = data->map[ (ii + i1 + data->map[ (jj + j1 + data->map[ (kk + k1 + data->map[ (ll+l1)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
t1 *= t1;
TCOD_NOISE_SIMPLEX_GRADIENT_4D(n1,idx,x1,y1,z1,w1);
n1 *= t1*t1;
}
t2 = 0.6f - x2*x2 -y2*y2 -z2*z2 -w2*w2;
if ( t2 < 0.0f ) n2 = 0.0f;
else {
int idx = data->map[ (ii + i2 + data->map[ (jj + j2 + data->map[ (kk + k2 + data->map[(ll+l2)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
t2 *= t2;
TCOD_NOISE_SIMPLEX_GRADIENT_4D(n2,idx,x2,y2,z2,w2);
n2 *= t2*t2;
}
t3 = 0.6f - x3*x3 -y3*y3 -z3*z3 -w3*w3;
if ( t3 < 0.0f ) n3 = 0.0f;
else {
int idx = data->map[ (ii + i3 + data->map[ (jj + j3 + data->map[ (kk + k3 + data->map[(ll+l3)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
t3 *= t3;
TCOD_NOISE_SIMPLEX_GRADIENT_4D(n3,idx,x3,y3,z3,w3);
n3 *= t3*t3;
}
t4 = 0.6f - x4*x4 -y4*y4 -z4*z4 -w4*w4;
if ( t4 < 0.0f ) n4 = 0.0f;
else {
int idx = data->map[ (ii + 1 + data->map[ (jj + 1 + data->map[ (kk + 1 + data->map[(ll+1)&0xFF])& 0xFF ]) &0xFF ])& 0xFF ];
t4 *= t4;
TCOD_NOISE_SIMPLEX_GRADIENT_4D(n4,idx,x4,y4,z4,w4);
n4 *= t4*t4;
}
return 27.0f * (n0+n1+n2+n3+n4);
}
break;
}
return 0.0f;
}
typedef float (*TCOD_noise_func_t)( TCOD_noise_t noise, float *f );
static float TCOD_noise_fbm_int(TCOD_noise_t noise, float *f, float octaves, TCOD_noise_func_t func ) {
float tf[TCOD_NOISE_MAX_DIMENSIONS];
perlin_data_t *data=(perlin_data_t *)noise;
/* Initialize locals */
double value = 0;
int i,j;
memcpy(tf,f,sizeof(float)*data->ndim);
/* Inner loop of spectral construction, where the fractal is built */
for(i=0; i<(int)octaves; i++)
{
value += (double)(func(noise,tf)) * data->exponent[i];
for (j=0; j < data->ndim; j++) tf[j] *= data->lacunarity;
}
/* Take care of remainder in octaves */
octaves -= (int)octaves;
if(octaves > DELTA)
value += (double)(octaves * func(noise,tf)) * data->exponent[i];
return CLAMP(-0.99999f, 0.99999f, (float)value);
}
float TCOD_noise_fbm_perlin( TCOD_noise_t noise, float *f, float octaves )
{
return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_perlin);
}
float TCOD_noise_fbm_simplex( TCOD_noise_t noise, float *f, float octaves )
{
return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_simplex);
}
static float TCOD_noise_turbulence_int( TCOD_noise_t noise, float *f, float octaves, TCOD_noise_func_t func )
{
float tf[TCOD_NOISE_MAX_DIMENSIONS];
perlin_data_t *data=(perlin_data_t *)noise;
/* Initialize locals */
double value = 0;
int i,j;
memcpy(tf,f,sizeof(float)*data->ndim);
/* Inner loop of spectral construction, where the fractal is built */
for(i=0; i<(int)octaves; i++)
{
float nval=func(noise,tf);
value += (double)(ABS(nval)) * data->exponent[i];
for (j=0; j < data->ndim; j++) tf[j] *= data->lacunarity;
}
/* Take care of remainder in octaves */
octaves -= (int)octaves;
if(octaves > DELTA) {
float nval=func(noise,tf);
value += (double)(octaves * ABS(nval)) * data->exponent[i];
}
return CLAMP(-0.99999f, 0.99999f, (float)value);
}
float TCOD_noise_turbulence_perlin( TCOD_noise_t noise, float *f, float octaves ) {
return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_perlin);
}
float TCOD_noise_turbulence_simplex( TCOD_noise_t noise, float *f, float octaves ) {
return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_simplex);
}
/* wavelet noise, adapted from Robert L. Cook and Tony Derose 'Wavelet noise' paper */
static void TCOD_noise_wavelet_downsample(float *from, float *to, int stride) {
static float acoeffs[2*WAVELET_ARAD]= {
0.000334f, -0.001528f, 0.000410f, 0.003545f, -0.000938f, -0.008233f, 0.002172f, 0.019120f,
-0.005040f,-0.044412f, 0.011655f, 0.103311f, -0.025936f, -0.243780f, 0.033979f, 0.655340f,
0.655340f, 0.033979f,-0.243780f,-0.025936f, 0.103311f, 0.011655f,-0.044412f,-0.005040f,
0.019120f, 0.002172f,-0.008233f,-0.000938f, 0.003546f, 0.000410f,-0.001528f, 0.000334f,
};
static float *a = &acoeffs[WAVELET_ARAD];
int i;
for (i=0; i < WAVELET_TILE_SIZE/2; i++) {
int k;
to[i*stride]=0;
for (k=2*i-WAVELET_ARAD; k <2*i+WAVELET_ARAD; k++) {
to[i*stride] += a[k-2*i]* from[ absmod(k,WAVELET_TILE_SIZE) * stride ];
}
}
}
static void TCOD_noise_wavelet_upsample(float *from, float *to, int stride) {
static float pcoeffs[4]= { 0.25f, 0.75f, 0.75f, 0.25f };
static float *p = &pcoeffs[2];
int i;
for (i=0; i < WAVELET_TILE_SIZE; i++) {
int k;
to[i*stride]=0;
for (k=i/2; k <i/2+1; k++) {
to[i*stride] += p[i-2*k]* from[ absmod(k,WAVELET_TILE_SIZE/2) * stride ];
}
}
}
static void TCOD_noise_wavelet_init(TCOD_noise_t pnoise) {
perlin_data_t *data=(perlin_data_t *)pnoise;
int ix,iy,iz,i,sz=WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*sizeof(float);
float *temp1=(float *)malloc(sz);
float *temp2=(float *)malloc(sz);
float *noise=(float *)malloc(sz);
int offset;
for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
noise[i]=TCOD_random_get_float(data->rand,-1.0f,1.0f);
}
for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
i = iy * WAVELET_TILE_SIZE + iz * WAVELET_TILE_SIZE * WAVELET_TILE_SIZE;
TCOD_noise_wavelet_downsample(&noise[i], &temp1[i], 1);
TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], 1);
}
}
for (ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
i = ix + iz * WAVELET_TILE_SIZE * WAVELET_TILE_SIZE;
TCOD_noise_wavelet_downsample(&temp2[i], &temp1[i], WAVELET_TILE_SIZE);
TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], WAVELET_TILE_SIZE);
}
}
for (ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
i = ix + iy * WAVELET_TILE_SIZE;
TCOD_noise_wavelet_downsample(&temp2[i], &temp1[i], WAVELET_TILE_SIZE * WAVELET_TILE_SIZE);
TCOD_noise_wavelet_upsample(&temp1[i], &temp2[i], WAVELET_TILE_SIZE * WAVELET_TILE_SIZE);
}
}
for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
noise[i] -= temp2[i];
}
offset = WAVELET_TILE_SIZE/2;
if ( (offset & 1) == 0 ) offset++;
for (i=0,ix=0; ix < WAVELET_TILE_SIZE; ix++ ) {
for (iy=0; iy < WAVELET_TILE_SIZE; iy++ ) {
for (iz=0; iz < WAVELET_TILE_SIZE; iz++ ) {
temp1[i++]=noise[ absmod(ix+offset,WAVELET_TILE_SIZE)
+ absmod(iy+offset,WAVELET_TILE_SIZE)*WAVELET_TILE_SIZE
+ absmod(iz+offset,WAVELET_TILE_SIZE)*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE
];
}
}
}
for (i=0; i < WAVELET_TILE_SIZE*WAVELET_TILE_SIZE*WAVELET_TILE_SIZE; i++ ) {
noise[i] += temp1[i];
}
data->waveletTileData=noise;
free(temp1);
free(temp2);
}
float TCOD_noise_wavelet (TCOD_noise_t noise, float *f) {
perlin_data_t *data=(perlin_data_t *)noise;
float pf[3];
int i;
int p[3],c[3],mid[3],n=WAVELET_TILE_SIZE;
float w[3][3],t,result=0.0f;
if ( data->ndim > 3 ) return 0.0f; /* not supported */
if (! data->waveletTileData ) TCOD_noise_wavelet_init(noise);
for (i=0; i < data->ndim; i++ ) pf[i]=f[i]*WAVELET_SCALE;
for (i=data->ndim; i < 3; i++ ) pf[i]=0.0f;
for (i=0; i < 3; i++ ) {
mid[i]=(int)ceil(pf[i]-0.5f);
t=mid[i] - (pf[i]-0.5f);
w[i][0]=t*t*0.5f;
w[i][2]=(1.0f-t)*(1.0f-t)*0.5f;
w[i][1]=1.0f - w[i][0]-w[i][2];
}
for (p[2]=-1; p[2]<=1; p[2]++) {
for (p[1]=-1; p[1]<=1; p[1]++) {
for (p[0]=-1; p[0]<=1; p[0]++) {
float weight=1.0f;
for (i=0;i<3;i++) {
c[i]=absmod(mid[i]+p[i],n);
weight *= w[i][p[i]+1];
}
result += weight * data->waveletTileData[ c[2]*n*n + c[1]*n + c[0] ];
}
}
}
return CLAMP(-1.0f,1.0f,result);
}
float TCOD_noise_fbm_wavelet(TCOD_noise_t noise, float *f, float octaves) {
return TCOD_noise_fbm_int(noise,f,octaves,TCOD_noise_wavelet);
}
float TCOD_noise_turbulence_wavelet(TCOD_noise_t noise, float *f, float octaves) {
return TCOD_noise_turbulence_int(noise,f,octaves,TCOD_noise_wavelet);
}
void TCOD_noise_set_type (TCOD_noise_t noise, TCOD_noise_type_t type) {
((perlin_data_t *)noise)->noise_type = type;
}
float TCOD_noise_get_ex (TCOD_noise_t noise, float *f, TCOD_noise_type_t type) {
switch (type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_perlin(noise,f); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_simplex(noise,f); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_wavelet(noise,f); break;
default:
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_perlin(noise,f); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_simplex(noise,f); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_wavelet(noise,f); break;
default: return TCOD_noise_simplex(noise,f); break;
}
break;
}
}
float TCOD_noise_get_fbm_ex (TCOD_noise_t noise, float *f, float octaves, TCOD_noise_type_t type) {
switch (type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_fbm_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_fbm_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_fbm_wavelet(noise,f,octaves); break;
default:
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_fbm_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_fbm_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_fbm_wavelet(noise,f,octaves); break;
default: return TCOD_noise_fbm_simplex(noise,f,octaves); break;
}
break;
}
}
float TCOD_noise_get_turbulence_ex (TCOD_noise_t noise, float *f, float octaves, TCOD_noise_type_t type) {
switch (type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_turbulence_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_turbulence_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_turbulence_wavelet(noise,f,octaves); break;
default:
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_turbulence_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_turbulence_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_turbulence_wavelet(noise,f,octaves); break;
default: return TCOD_noise_turbulence_simplex(noise,f,octaves); break;
}
break;
}
}
float TCOD_noise_get (TCOD_noise_t noise, float *f) {
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_perlin(noise,f); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_simplex(noise,f); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_wavelet(noise,f); break;
default: return TCOD_noise_simplex(noise,f); break;
}
}
float TCOD_noise_get_fbm (TCOD_noise_t noise, float *f, float octaves) {
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_fbm_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_fbm_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_fbm_wavelet(noise,f,octaves); break;
default: return TCOD_noise_fbm_simplex(noise,f,octaves); break;
}
}
float TCOD_noise_get_turbulence (TCOD_noise_t noise, float *f, float octaves) {
switch (((perlin_data_t *)noise)->noise_type) {
case (TCOD_NOISE_PERLIN): return TCOD_noise_turbulence_perlin(noise,f,octaves); break;
case (TCOD_NOISE_SIMPLEX): return TCOD_noise_turbulence_simplex(noise,f,octaves); break;
case (TCOD_NOISE_WAVELET): return TCOD_noise_turbulence_wavelet(noise,f,octaves); break;
default: return TCOD_noise_turbulence_simplex(noise,f,octaves); break;
}
}
void TCOD_noise_delete(TCOD_noise_t noise) {
if (((perlin_data_t *)noise)->waveletTileData) {
free(((perlin_data_t *)noise)->waveletTileData);
}
free((perlin_data_t *)noise);
}