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//========= Copyright � 1996-2006, Valve Corporation, All rights reserved. ============//
//
// Purpose: noise() primitives.
//
//=====================================================================================//
#include <math.h>
#include "basetypes.h"
#ifndef _PS3
#include <memory.h>
#endif
#include "tier0/dbg.h"
#include "mathlib/mathlib.h"
#include "mathlib/vector.h"
#include "mathlib/noise.h"
// memdbgon must be the last include file in a .cpp file!!!
#include "tier0/memdbgon.h"
// generate high quality noise based upon "sparse convolution". HIgher quality than perlin noise,
// and no direcitonal artifacts.
#include "noisedata.h"
#define N_IMPULSES_PER_CELL 5
#define NORMALIZING_FACTOR 1.0
//(0.5/N_IMPULSES_PER_CELL)
static inline int LatticeCoord(float x){ return ((int) floor(x)) & 0xff;}
static inline int Hash4D(int ix, int iy, int iz, int idx){ int ret=perm_a[ix]; ret=perm_b[(ret+iy) & 0xff]; ret=perm_c[(ret+iz) & 0xff]; ret=perm_d[(ret+idx) & 0xff]; return ret;}
#define SQ(x) ((x)*(x))
static float CellNoise( int ix, int iy, int iz, float xfrac, float yfrac, float zfrac, float (*pNoiseShapeFunction)(float) ){ float ret=0; for(int idx=0;idx<N_IMPULSES_PER_CELL;idx++) { int coord_idx=Hash4D( ix, iy, iz, idx ); float dsq=SQ(impulse_xcoords[coord_idx]-xfrac)+ SQ(impulse_ycoords[coord_idx]-yfrac)+ SQ(impulse_zcoords[coord_idx]-zfrac); dsq = sqrt( dsq ); if (dsq < 1.0 ) { ret += (*pNoiseShapeFunction)( 1-dsq ); } } return ret;}
float SparseConvolutionNoise( Vector const &pnt ){ return SparseConvolutionNoise( pnt, QuinticInterpolatingPolynomial );}
float FractalNoise( Vector const &pnt, int n_octaves){ float scale=1.0; float iscale=1.0; float ret=0; float sumscale=0; for(int o=0;o<n_octaves;o++) { Vector p1=pnt; p1 *= scale; ret+=iscale * SparseConvolutionNoise( p1 ); sumscale += iscale; scale *= 2.0; iscale *= 0.5; } return ret * ( 1.0/sumscale );}
float Turbulence( Vector const &pnt, int n_octaves){ float scale=1.0; float iscale=1.0; float ret=0; float sumscale=0; for(int o=0;o<n_octaves;o++) { Vector p1=pnt; p1 *= scale; ret+=iscale * fabs ( 2.0*( SparseConvolutionNoise( p1 )-.5 ) ); sumscale += iscale; scale *= 2.0; iscale *= 0.5; } return ret * ( 1.0/sumscale );}
#ifdef MEASURE_RANGE
float fmin1=10000000.0;float fmax1=-1000000.0;#endif
float SparseConvolutionNoise(Vector const &pnt, float (*pNoiseShapeFunction)(float) ){ // computer integer lattice point
int ix=LatticeCoord(pnt.x); int iy=LatticeCoord(pnt.y); int iz=LatticeCoord(pnt.z);
// compute offsets within unit cube
float xfrac=pnt.x-floor(pnt.x); float yfrac=pnt.y-floor(pnt.y); float zfrac=pnt.z-floor(pnt.z);
float sum_out=0.;
for(int ox=-1; ox<=1; ox++) for(int oy=-1; oy<=1; oy++) for(int oz=-1; oz<=1; oz++) { sum_out += CellNoise( ix+ox, iy+oy, iz+oz, xfrac-ox, yfrac-oy, zfrac-oz, pNoiseShapeFunction ); }#ifdef MEASURE_RANGE
fmin1=min(sum_out,fmin1); fmax1=max(sum_out,fmax1);#endif
return RemapValClamped( sum_out, .544487, 9.219176, 0.0, 1.0 );}
float TileableSparseConvolutionNoise(Vector const &pnt, float (*pNoiseShapeFunction)(float) ){ // computer integer lattice point
int ix=LatticeCoord(pnt.x); int iy=LatticeCoord(pnt.y); int iz=LatticeCoord(pnt.z);
// compute offsets within unit cube
float xfrac=pnt.x-floor(pnt.x); float yfrac=pnt.y-floor(pnt.y); float zfrac=pnt.z-floor(pnt.z);
float sum_out=0.;
for(int ox=-1; ox<=1; ox++) for(int oy=-1; oy<=1; oy++) for(int oz=-1; oz<=1; oz++) { sum_out += CellNoise( ix+ox, iy+oy, iz+oz, xfrac-ox, yfrac-oy, zfrac-oz, pNoiseShapeFunction ); }#ifdef MEASURE_RANGE
fmin1=min(sum_out,fmin1); fmax1=max(sum_out,fmax1);#endif
return RemapValClamped( sum_out, .544487, 9.219176, 0.0, 1.0 );}
// Improved Perlin Noise
// The following code is the c-ification of Ken Perlin's new noise algorithm
// "JAVA REFERENCE IMPLEMENTATION OF IMPROVED NOISE - COPYRIGHT 2002 KEN PERLIN"
// as available here: http://mrl.nyu.edu/~perlin/noise/
float NoiseGradient(int hash, float x, float y, float z){ int h = hash & 15; // CONVERT LO 4 BITS OF HASH CODE
float u = h<8 ? x : y; // INTO 12 GRADIENT DIRECTIONS.
float v = h<4 ? y : (h==12||h==14 ? x : z); return ((h&1) == 0 ? u : -u) + ((h&2) == 0 ? v : -v);}
int NoiseHashIndex( int i ){ static int s_permutation[] = { 151,160,137,91,90,15, 131,13,201,95,96,53,194,233,7,225,140,36,103,30,69,142,8,99,37,240,21,10,23, 190, 6,148,247,120,234,75,0,26,197,62,94,252,219,203,117,35,11,32,57,177,33, 88,237,149,56,87,174,20,125,136,171,168, 68,175,74,165,71,134,139,48,27,166, 77,146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55,46,245,40,244, 102,143,54, 65,25,63,161, 1,216,80,73,209,76,132,187,208, 89,18,169,200,196, 135,130,116,188,159,86,164,100,109,198,173,186, 3,64,52,217,226,250,124,123, 5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,182,189,28,42, 223,183,170,213,119,248,152, 2,44,154,163, 70,221,153,101,155,167, 43,172,9, 129,22,39,253, 19,98,108,110,79,113,224,232,178,185, 112,104,218,246,97,228, 251,34,242,193,238,210,144,12,191,179,162,241, 81,51,145,235,249,14,239,107, 49,192,214, 31,181,199,106,157,184, 84,204,176,115,121,50,45,127, 4,150,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61,156,180 };
return s_permutation[ i & 0xff ];}
float ImprovedPerlinNoise( Vector const &pnt ){ float fx = floor(pnt.x); float fy = floor(pnt.y); float fz = floor(pnt.z);
int X = (int)fx & 255; // FIND UNIT CUBE THAT
int Y = (int)fy & 255; // CONTAINS POINT.
int Z = (int)fz & 255;
float x = pnt.x - fx; // FIND RELATIVE X,Y,Z
float y = pnt.y - fy; // OF POINT IN CUBE.
float z = pnt.z - fz;
float u = QuinticInterpolatingPolynomial(x); // COMPUTE FADE CURVES
float v = QuinticInterpolatingPolynomial(y); // FOR EACH OF X,Y,Z.
float w = QuinticInterpolatingPolynomial(z);
int A = NoiseHashIndex( X ) + Y; // HASH COORDINATES OF
int AA = NoiseHashIndex( A ) + Z; // THE 8 CUBE CORNERS,
int AB = NoiseHashIndex( A + 1 ) + Z; int B = NoiseHashIndex( X + 1 ) + Y; int BA = NoiseHashIndex( B ) + Z; int BB = NoiseHashIndex( B + 1 ) + Z;
float g0 = NoiseGradient(NoiseHashIndex(AA ), x , y , z ); float g1 = NoiseGradient(NoiseHashIndex(BA ), x-1, y , z ); float g2 = NoiseGradient(NoiseHashIndex(AB ), x , y-1, z ); float g3 = NoiseGradient(NoiseHashIndex(BB ), x-1, y-1, z ); float g4 = NoiseGradient(NoiseHashIndex(AA+1), x , y , z-1 ); float g5 = NoiseGradient(NoiseHashIndex(BA+1), x-1, y , z-1 ); float g6 = NoiseGradient(NoiseHashIndex(AB+1), x , y-1, z-1 ); float g7 = NoiseGradient(NoiseHashIndex(BB+1), x-1, y-1, z-1 );
// AND ADD BLENDED RESULTS FROM 8 CORNERS OF CUBE
float g01 = Lerp( u, g0, g1 ); float g23 = Lerp( u, g2, g3 ); float g45 = Lerp( u, g4, g5 ); float g67 = Lerp( u, g6, g7 ); float g0123 = Lerp( v, g01, g23 ); float g4567 = Lerp( v, g45, g67 );
return Lerp( w, g0123,g4567 );}
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