blender/intern/smoke/intern/WAVELET_NOISE.h
Daniel Genrich 58c88bcf76 BF2.5: First commit of smoke code.
Not working: 
a) rendering (since volumterics branch is not merged yet)
b) moving collision objects of any kind
c) saving of collision objects (because that's what I am working on)
d) pointcache
e) A bunch of other things I already know of 

So please do not report any bugs on this one yet :-)
2009-07-30 15:00:26 +00:00

457 lines
15 KiB
C++

//////////////////////////////////////////////////////////////////////
// This file is part of Wavelet Turbulence.
//
// Wavelet Turbulence is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// Wavelet Turbulence is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Wavelet Turbulence. If not, see <http://www.gnu.org/licenses/>.
//
// Copyright 2008 Theodore Kim and Nils Thuerey
//
//////////////////////////////////////////////////////////////////////////////////////////
// Wavelet noise functions
//
// This code is based on the C code provided in the appendices of:
//
// @article{1073264,
// author = {Robert L. Cook and Tony DeRose},
// title = {Wavelet noise},
// journal = {ACM Trans. Graph.},
// volume = {24},
// number = {3},
// year = {2005},
// issn = {0730-0301},
// pages = {803--811},
// doi = {http://doi.acm.org/10.1145/1073204.1073264},
// publisher = {ACM},
// address = {New York, NY, USA},
// }
//
//////////////////////////////////////////////////////////////////////////////////////////
#ifndef WAVELET_NOISE_H
#define WAVELET_NOISE_H
#include <MERSENNETWISTER.h>
#define NOISE_TILE_SIZE 128
static const int noiseTileSize = NOISE_TILE_SIZE;
// warning - noiseTileSize has to be 128^3!
#define modFast128(x) ((x) & 127)
#define modFast64(x) ((x) & 63)
#define DOWNCOEFFS 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
//////////////////////////////////////////////////////////////////////////////////////////
// Wavelet downsampling -- periodic boundary conditions
//////////////////////////////////////////////////////////////////////////////////////////
static void downsampleX(float *from, float *to, int n){
// if these values are not local incorrect results are generated
float downCoeffs[32] = { DOWNCOEFFS };
const float *a = &downCoeffs[16];
for (int i = 0; i < n / 2; i++) {
to[i] = 0;
for (int k = 2 * i - 16; k <= 2 * i + 16; k++)
to[i] += a[k - 2 * i] * from[modFast128(k)];
}
}
static void downsampleY(float *from, float *to, int n){
// if these values are not local incorrect results are generated
float downCoeffs[32] = { DOWNCOEFFS };
const float *a = &downCoeffs[16];
for (int i = 0; i < n / 2; i++) {
to[i * n] = 0;
for (int k = 2 * i - 16; k <= 2 * i + 16; k++)
to[i * n] += a[k - 2 * i] * from[modFast128(k) * n];
}
}
static void downsampleZ(float *from, float *to, int n){
// if these values are not local incorrect results are generated
float downCoeffs[32] = { DOWNCOEFFS };
const float *a = &downCoeffs[16];
for (int i = 0; i < n / 2; i++) {
to[i * n * n] = 0;
for (int k = 2 * i - 16; k <= 2 * i + 16; k++)
to[i * n * n] += a[k - 2 * i] * from[modFast128(k) * n * n];
}
}
//////////////////////////////////////////////////////////////////////////////////////////
// Wavelet downsampling -- Neumann boundary conditions
//////////////////////////////////////////////////////////////////////////////////////////
static void downsampleNeumann(const float *from, float *to, int n, int stride)
{
// if these values are not local incorrect results are generated
float downCoeffs[32] = { DOWNCOEFFS };
static const float *const aCoCenter= &downCoeffs[16];
for (int i = 0; i < n / 2; i++) {
to[i * stride] = 0;
for (int k = 2 * i - 16; k < 2 * i + 16; k++) {
// handle boundary
float fromval;
if (k < 0) {
fromval = from[0];
} else if(k > n - 1) {
fromval = from[(n - 1) * stride];
} else {
fromval = from[k * stride];
}
to[i * stride] += aCoCenter[k - 2 * i] * fromval;
}
}
}
static void downsampleXNeumann(float* to, const float* from, int sx,int sy, int sz) {
for (int iy = 0; iy < sy; iy++)
for (int iz = 0; iz < sz; iz++) {
const int i = iy * sx + iz*sx*sy;
downsampleNeumann(&from[i], &to[i], sx, 1);
}
}
static void downsampleYNeumann(float* to, const float* from, int sx,int sy, int sz) {
for (int ix = 0; ix < sx; ix++)
for (int iz = 0; iz < sz; iz++) {
const int i = ix + iz*sx*sy;
downsampleNeumann(&from[i], &to[i], sy, sx);
}
}
static void downsampleZNeumann(float* to, const float* from, int sx,int sy, int sz) {
for (int ix = 0; ix < sx; ix++)
for (int iy = 0; iy < sy; iy++) {
const int i = ix + iy*sx;
downsampleNeumann(&from[i], &to[i], sz, sx*sy);
}
}
//////////////////////////////////////////////////////////////////////////////////////////
// Wavelet upsampling - periodic boundary conditions
//////////////////////////////////////////////////////////////////////////////////////////
static float _upCoeffs[4] = {0.25f, 0.75f, 0.75f, 0.25f};
static void upsampleX(float *from, float *to, int n) {
const float *p = &_upCoeffs[2];
for (int i = 0; i < n; i++) {
to[i] = 0;
for (int k = i / 2; k <= i / 2 + 1; k++)
to[i] += p[i - 2 * k] * from[modFast64(k)];
}
}
static void upsampleY(float *from, float *to, int n) {
const float *p = &_upCoeffs[2];
for (int i = 0; i < n; i++) {
to[i * n] = 0;
for (int k = i / 2; k <= i / 2 + 1; k++)
to[i * n] += p[i - 2 * k] * from[modFast64(k) * n];
}
}
static void upsampleZ(float *from, float *to, int n) {
const float *p = &_upCoeffs[2];
for (int i = 0; i < n; i++) {
to[i * n * n] = 0;
for (int k = i / 2; k <= i / 2 + 1; k++)
to[i * n * n] += p[i - 2 * k] * from[modFast64(k) * n * n];
}
}
//////////////////////////////////////////////////////////////////////////////////////////
// Wavelet upsampling - Neumann boundary conditions
//////////////////////////////////////////////////////////////////////////////////////////
static void upsampleNeumann(const float *from, float *to, int n, int stride) {
static const float *const pCoCenter = &_upCoeffs[2];
for (int i = 0; i < n; i++) {
to[i * stride] = 0;
for (int k = i / 2; k <= i / 2 + 1; k++) {
float fromval;
if(k>n/2) {
fromval = from[(n/2) * stride];
} else {
fromval = from[k * stride];
}
to[i * stride] += pCoCenter[i - 2 * k] * fromval;
}
}
}
static void upsampleXNeumann(float* to, const float* from, int sx, int sy, int sz) {
for (int iy = 0; iy < sy; iy++)
for (int iz = 0; iz < sz; iz++) {
const int i = iy * sx + iz*sx*sy;
upsampleNeumann(&from[i], &to[i], sx, 1);
}
}
static void upsampleYNeumann(float* to, const float* from, int sx, int sy, int sz) {
for (int ix = 0; ix < sx; ix++)
for (int iz = 0; iz < sz; iz++) {
const int i = ix + iz*sx*sy;
upsampleNeumann(&from[i], &to[i], sy, sx);
}
}
static void upsampleZNeumann(float* to, const float* from, int sx, int sy, int sz) {
for (int ix = 0; ix < sx; ix++)
for (int iy = 0; iy < sy; iy++) {
const int i = ix + iy*sx;
upsampleNeumann(&from[i], &to[i], sz, sx*sy);
}
}
//////////////////////////////////////////////////////////////////////////////////////////
// load in an existing noise tile
//////////////////////////////////////////////////////////////////////////////////////////
static bool loadTile(float* const noiseTileData, std::string filename)
{
FILE* file;
file = fopen(filename.c_str(), "rb");
if (file == NULL) {
printf("loadTile: No noise tile '%s' found.\n", filename.c_str());
return false;
}
// dimensions
int gridSize = noiseTileSize * noiseTileSize * noiseTileSize;
// noiseTileData memory is managed by caller
int bread = fread((void*)noiseTileData, sizeof(float), gridSize, file);
fclose(file);
printf("Noise tile file '%s' loaded.\n", filename.c_str());
if (bread != gridSize) {
printf("loadTile: Noise tile '%s' is wrong size %d.\n", filename.c_str(), bread);
return false;
}
return true;
}
//////////////////////////////////////////////////////////////////////////////////////////
// write out an existing noise tile
//////////////////////////////////////////////////////////////////////////////////////////
static void saveTile(float* const noiseTileData, std::string filename)
{
FILE* file;
file = fopen(filename.c_str(), "wb");
if (file == NULL) {
printf("saveTile: Noise tile '%s' could not be saved.\n", filename.c_str());
return;
}
fwrite((void*)noiseTileData, sizeof(float), noiseTileSize * noiseTileSize * noiseTileSize, file);
fclose(file);
printf("saveTile: Noise tile file '%s' saved.\n", filename.c_str());
}
//////////////////////////////////////////////////////////////////////////////////////////
// create a new noise tile if necessary
//////////////////////////////////////////////////////////////////////////////////////////
static void generateTile_WAVELET(float* const noiseTileData, std::string filename) {
// if a tile already exists, just use that
if (loadTile(noiseTileData, filename)) return;
const int n = noiseTileSize;
const int n3 = n*n*n;
std::cout <<"Generating new 3d noise tile size="<<n<<"^3 \n";
MTRand twister;
float *temp13 = new float[n3];
float *temp23 = new float[n3];
float *noise3 = new float[n3];
// initialize
for (int i = 0; i < n3; i++) {
temp13[i] = temp23[i] = noise3[i] = 0.;
}
// Step 1. Fill the tile with random numbers in the range -1 to 1.
for (int i = 0; i < n3; i++)
noise3[i] = twister.randNorm();
// Steps 2 and 3. Downsample and upsample the tile
for (int iy = 0; iy < n; iy++)
for (int iz = 0; iz < n; iz++) {
const int i = iy * n + iz*n*n;
downsampleX(&noise3[i], &temp13[i], n);
upsampleX (&temp13[i], &temp23[i], n);
}
for (int ix = 0; ix < n; ix++)
for (int iz = 0; iz < n; iz++) {
const int i = ix + iz*n*n;
downsampleY(&temp23[i], &temp13[i], n);
upsampleY (&temp13[i], &temp23[i], n);
}
for (int ix = 0; ix < n; ix++)
for (int iy = 0; iy < n; iy++) {
const int i = ix + iy*n;
downsampleZ(&temp23[i], &temp13[i], n);
upsampleZ (&temp13[i], &temp23[i], n);
}
// Step 4. Subtract out the coarse-scale contribution
for (int i = 0; i < n3; i++)
noise3[i] -= temp23[i];
// Avoid even/odd variance difference by adding odd-offset version of noise to itself.
int offset = n / 2;
if (offset % 2 == 0) offset++;
int icnt=0;
for (int ix = 0; ix < n; ix++)
for (int iy = 0; iy < n; iy++)
for (int iz = 0; iz < n; iz++) {
temp13[icnt] = noise3[modFast128(ix+offset) + modFast128(iy+offset)*n + modFast128(iz+offset)*n*n];
icnt++;
}
for (int i = 0; i < n3; i++)
noise3[i] += temp13[i];
for (int i = 0; i < n3; i++)
noiseTileData[i] = noise3[i];
saveTile(noise3, filename);
delete[] temp13;
delete[] temp23;
std::cout <<"Generating new 3d noise done\n";
}
//////////////////////////////////////////////////////////////////////////////////////////
// x derivative of noise
//////////////////////////////////////////////////////////////////////////////////////////
static inline float WNoiseDx(Vec3 p, float* data) {
int i, f[3], c[3], mid[3], n = noiseTileSize;
float w[3][3], t, result = 0;
mid[0] = ceil(p[0] - 0.5);
t = mid[0] - (p[0] - 0.5);
w[0][0] = -t;
w[0][2] = (1.f - t);
w[0][1] = 2.0f * t - 1.0f;
mid[1] = ceil(p[1] - 0.5);
t = mid[1] - (p[1] - 0.5);
w[1][0] = t * t / 2;
w[1][2] = (1 - t) * (1 - t) / 2;
w[1][1] = 1 - w[1][0] - w[1][2];
mid[2] = ceil(p[2] - 0.5);
t = mid[2] - (p[2] - 0.5);
w[2][0] = t * t / 2;
w[2][2] = (1 - t) * (1 - t)/2;
w[2][1] = 1 - w[2][0] - w[2][2];
// to optimize, explicitly unroll this loop
for (int z = -1; z <=1; z++)
for (int y = -1; y <=1; y++)
for (int x = -1; x <=1; x++)
{
float weight = 1.0f;
c[0] = modFast128(mid[0] + x);
weight *= w[0][x+1];
c[1] = modFast128(mid[1] + y);
weight *= w[1][y+1];
c[2] = modFast128(mid[2] + z);
weight *= w[2][z+1];
result += weight * data[c[2]*n*n+c[1]*n+c[0]];
}
return result;
}
//////////////////////////////////////////////////////////////////////////////////////////
// y derivative of noise
//////////////////////////////////////////////////////////////////////////////////////////
static inline float WNoiseDy(Vec3 p, float* data) {
int i, f[3], c[3], mid[3], n=noiseTileSize;
float w[3][3], t, result =0;
mid[0] = ceil(p[0] - 0.5);
t = mid[0]-(p[0] - 0.5);
w[0][0] = t * t / 2;
w[0][2] = (1 - t) * (1 - t) / 2;
w[0][1] = 1 - w[0][0] - w[0][2];
mid[1] = ceil(p[1] - 0.5);
t = mid[1]-(p[1] - 0.5);
w[1][0] = -t;
w[1][2] = (1.f - t);
w[1][1] = 2.0f * t - 1.0f;
mid[2] = ceil(p[2] - 0.5);
t = mid[2] - (p[2] - 0.5);
w[2][0] = t * t / 2;
w[2][2] = (1 - t) * (1 - t)/2;
w[2][1] = 1 - w[2][0] - w[2][2];
// to optimize, explicitly unroll this loop
for (int z = -1; z <=1; z++)
for (int y = -1; y <=1; y++)
for (int x = -1; x <=1; x++)
{
float weight = 1.0f;
c[0] = modFast128(mid[0] + x);
weight *= w[0][x+1];
c[1] = modFast128(mid[1] + y);
weight *= w[1][y+1];
c[2] = modFast128(mid[2] + z);
weight *= w[2][z+1];
result += weight * data[c[2]*n*n+c[1]*n+c[0]];
}
return result;
}
//////////////////////////////////////////////////////////////////////////////////////////
// z derivative of noise
//////////////////////////////////////////////////////////////////////////////////////////
static inline float WNoiseDz(Vec3 p, float* data) {
int i, f[3], c[3], mid[3], n=noiseTileSize;
float w[3][3], t, result =0;
mid[0] = ceil(p[0] - 0.5);
t = mid[0]-(p[0] - 0.5);
w[0][0] = t * t / 2;
w[0][2] = (1 - t) * (1 - t) / 2;
w[0][1] = 1 - w[0][0] - w[0][2];
mid[1] = ceil(p[1] - 0.5);
t = mid[1]-(p[1] - 0.5);
w[1][0] = t * t / 2;
w[1][2] = (1 - t) * (1 - t) / 2;
w[1][1] = 1 - w[1][0] - w[1][2];
mid[2] = ceil(p[2] - 0.5);
t = mid[2] - (p[2] - 0.5);
w[2][0] = -t;
w[2][2] = (1.f - t);
w[2][1] = 2.0f * t - 1.0f;
// to optimize, explicitly unroll this loop
for (int z = -1; z <=1; z++)
for (int y = -1; y <=1; y++)
for (int x = -1; x <=1; x++)
{
float weight = 1.0f;
c[0] = modFast128(mid[0] + x);
weight *= w[0][x+1];
c[1] = modFast128(mid[1] + y);
weight *= w[1][y+1];
c[2] = modFast128(mid[2] + z);
weight *= w[2][z+1];
result += weight * data[c[2]*n*n+c[1]*n+c[0]];
}
return result;
}
#endif