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