131 lines
3.6 KiB
C++
131 lines
3.6 KiB
C++
#pragma once
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namespace DFHack {
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namespace Random {
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/*
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* A good explanation:
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* http://webstaff.itn.liu.se/~stegu/TNM022-2005/perlinnoiselinks/perlin-noise-math-faq.html
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*/
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// Interpolation functions
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template<class T>
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inline T s_curve(T t)
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{
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// Classical function
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//return t * t * (3 - 2*t);
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// 2002 version from http://mrl.nyu.edu/~perlin/paper445.pdf
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return t * t * t * (t * (t * 6 - 15) + 10);
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}
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template<class T>
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inline T lerp(T s, T a, T b)
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{
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return a + s * (b-a);
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}
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// Dot product of VSIZE vectors pointed by pa, pb
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template<class T, unsigned i>
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struct DotProduct {
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static inline T eval(T *pa, T *pb);
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};
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template<class T>
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struct DotProduct<T,0> {
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static inline T eval(T *pa, T *pb) { return pa[0]*pb[0]; }
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};
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template<class T, unsigned i>
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inline T DotProduct<T,i>::eval(T *pa, T *pb) {
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return DotProduct<T,i-1>::eval(pa, pb) + pa[i]*pb[i];
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}
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// Templates used to force unrolling and inlining of the loops
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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template<unsigned mask>
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struct PerlinNoise<T,VSIZE,BITS,IDXT>::Impl<mask,-1> {
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typedef typename PerlinNoise<T,VSIZE,BITS,IDXT>::Temp Temp;
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static inline void setup(PerlinNoise<T,VSIZE,BITS,IDXT> *, const T *, Temp *) {}
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static inline T eval(PerlinNoise<T,VSIZE,BITS,IDXT> *self, Temp *pt, unsigned idx, T *pq);
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};
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// Initialization of the temporaries from input coordinates
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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template<unsigned mask, int i>
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inline void PerlinNoise<T,VSIZE,BITS,IDXT>::Impl<mask,i>::setup(
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PerlinNoise<T,VSIZE,BITS,IDXT> *self, const T *pv, Temp *pt
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) {
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Impl<mask,i-1>::setup(self, pv, pt);
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T t = std::floor(pv[i]);
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pt[i].s = s_curve(pt[i].r0 = pv[i] - t);
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unsigned b = unsigned(int32_t(t));
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pt[i].b0 = self->idxmap[i][b & mask];
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pt[i].b1 = self->idxmap[i][(b+1) & mask];
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}
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// Main recursion. Uses tables from self and pt.
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// Recursion changes current index idx, and current offset vector pq.
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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template<unsigned mask>
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inline T PerlinNoise<T,VSIZE,BITS,IDXT>::Impl<mask, -1>::eval(
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PerlinNoise<T,VSIZE,BITS,IDXT> *self, Temp *pt, unsigned idx, T *pq
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) {
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return DotProduct<T,VSIZE-1>::eval(pq, self->gradients[idx]);
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}
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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template<unsigned mask, int i>
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inline T PerlinNoise<T,VSIZE,BITS,IDXT>::Impl<mask,i>::eval(
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PerlinNoise<T,VSIZE,BITS,IDXT> *self, Temp *pt, unsigned idx, T *pq
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) {
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pq[i] = pt[i].r0;
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T u = Impl<mask,i-1>::eval(self, pt, idx ^ pt[i].b0, pq);
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pq[i] -= 1;
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T v = Impl<mask,i-1>::eval(self, pt, idx ^ pt[i].b1, pq);
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return lerp(pt[i].s, u, v);
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}
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// Actual methods of the object
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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void PerlinNoise<T,VSIZE,BITS,IDXT>::init(MersenneRNG &rng)
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{
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STATIC_ASSERT(VSIZE > 0 && BITS <= 8*sizeof(IDXT));
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// Random unit gradient vectors
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for (unsigned i = 0; i < TSIZE; i++)
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rng.unitvector(gradients[i], VSIZE);
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// Random permutation tables
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for (unsigned j = 0; j < VSIZE; j++)
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{
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for (unsigned i = 0; i < TSIZE; i++)
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idxmap[j][i] = i;
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rng.permute(idxmap[j], TSIZE);
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}
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}
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template<class T, unsigned VSIZE, unsigned BITS, class IDXT>
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T PerlinNoise<T,VSIZE,BITS,IDXT>::eval(const T coords[VSIZE])
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{
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// Precomputed properties from the coordinates
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Temp tmp[VSIZE];
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// Temporary used to build the current offset vector
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T q[VSIZE];
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Impl<TSIZE-1,VSIZE-1>::setup(this, coords, tmp);
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return Impl<TSIZE-1,VSIZE-1>::eval(this, tmp, 0, q);
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}
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}} // namespace
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