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431 lines
17 KiB
431 lines
17 KiB
/*
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* Copyright 2015 Google Inc.
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*
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* Use of this source code is governed by a BSD-style license that can be
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* found in the LICENSE file.
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*/
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#ifndef SkNx_DEFINED
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#define SkNx_DEFINED
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#include "include/core/SkScalar.h"
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#include "include/core/SkTypes.h"
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#include "include/private/SkSafe_math.h"
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#include <algorithm>
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#include <limits>
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#include <type_traits>
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// Every single SkNx method wants to be fully inlined. (We know better than MSVC).
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#define AI SK_ALWAYS_INLINE
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namespace { // NOLINT(google-build-namespaces)
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// The default SkNx<N,T> just proxies down to a pair of SkNx<N/2, T>.
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template <int N, typename T>
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struct SkNx {
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typedef SkNx<N/2, T> Half;
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Half fLo, fHi;
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AI SkNx() = default;
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AI SkNx(const Half& lo, const Half& hi) : fLo(lo), fHi(hi) {}
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AI SkNx(T v) : fLo(v), fHi(v) {}
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AI SkNx(T a, T b) : fLo(a) , fHi(b) { static_assert(N==2, ""); }
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AI SkNx(T a, T b, T c, T d) : fLo(a,b), fHi(c,d) { static_assert(N==4, ""); }
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AI SkNx(T a, T b, T c, T d, T e, T f, T g, T h) : fLo(a,b,c,d), fHi(e,f,g,h) {
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static_assert(N==8, "");
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}
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AI SkNx(T a, T b, T c, T d, T e, T f, T g, T h,
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T i, T j, T k, T l, T m, T n, T o, T p)
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: fLo(a,b,c,d, e,f,g,h), fHi(i,j,k,l, m,n,o,p) {
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static_assert(N==16, "");
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}
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AI T operator[](int k) const {
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SkASSERT(0 <= k && k < N);
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return k < N/2 ? fLo[k] : fHi[k-N/2];
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}
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AI static SkNx Load(const void* vptr) {
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auto ptr = (const char*)vptr;
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return { Half::Load(ptr), Half::Load(ptr + N/2*sizeof(T)) };
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}
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AI void store(void* vptr) const {
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auto ptr = (char*)vptr;
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fLo.store(ptr);
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fHi.store(ptr + N/2*sizeof(T));
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}
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AI static void Load4(const void* vptr, SkNx* a, SkNx* b, SkNx* c, SkNx* d) {
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auto ptr = (const char*)vptr;
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Half al, bl, cl, dl,
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ah, bh, ch, dh;
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Half::Load4(ptr , &al, &bl, &cl, &dl);
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Half::Load4(ptr + 4*N/2*sizeof(T), &ah, &bh, &ch, &dh);
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*a = SkNx{al, ah};
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*b = SkNx{bl, bh};
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*c = SkNx{cl, ch};
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*d = SkNx{dl, dh};
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}
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AI static void Load3(const void* vptr, SkNx* a, SkNx* b, SkNx* c) {
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auto ptr = (const char*)vptr;
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Half al, bl, cl,
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ah, bh, ch;
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Half::Load3(ptr , &al, &bl, &cl);
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Half::Load3(ptr + 3*N/2*sizeof(T), &ah, &bh, &ch);
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*a = SkNx{al, ah};
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*b = SkNx{bl, bh};
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*c = SkNx{cl, ch};
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}
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AI static void Load2(const void* vptr, SkNx* a, SkNx* b) {
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auto ptr = (const char*)vptr;
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Half al, bl,
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ah, bh;
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Half::Load2(ptr , &al, &bl);
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Half::Load2(ptr + 2*N/2*sizeof(T), &ah, &bh);
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*a = SkNx{al, ah};
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*b = SkNx{bl, bh};
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}
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AI static void Store4(void* vptr, const SkNx& a, const SkNx& b, const SkNx& c, const SkNx& d) {
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auto ptr = (char*)vptr;
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Half::Store4(ptr, a.fLo, b.fLo, c.fLo, d.fLo);
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Half::Store4(ptr + 4*N/2*sizeof(T), a.fHi, b.fHi, c.fHi, d.fHi);
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}
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AI static void Store3(void* vptr, const SkNx& a, const SkNx& b, const SkNx& c) {
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auto ptr = (char*)vptr;
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Half::Store3(ptr, a.fLo, b.fLo, c.fLo);
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Half::Store3(ptr + 3*N/2*sizeof(T), a.fHi, b.fHi, c.fHi);
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}
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AI static void Store2(void* vptr, const SkNx& a, const SkNx& b) {
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auto ptr = (char*)vptr;
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Half::Store2(ptr, a.fLo, b.fLo);
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Half::Store2(ptr + 2*N/2*sizeof(T), a.fHi, b.fHi);
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}
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AI T min() const { return std::min(fLo.min(), fHi.min()); }
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AI T max() const { return std::max(fLo.max(), fHi.max()); }
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AI bool anyTrue() const { return fLo.anyTrue() || fHi.anyTrue(); }
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AI bool allTrue() const { return fLo.allTrue() && fHi.allTrue(); }
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AI SkNx abs() const { return { fLo. abs(), fHi. abs() }; }
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AI SkNx sqrt() const { return { fLo. sqrt(), fHi. sqrt() }; }
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AI SkNx floor() const { return { fLo. floor(), fHi. floor() }; }
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AI SkNx operator!() const { return { !fLo, !fHi }; }
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AI SkNx operator-() const { return { -fLo, -fHi }; }
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AI SkNx operator~() const { return { ~fLo, ~fHi }; }
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AI SkNx operator<<(int bits) const { return { fLo << bits, fHi << bits }; }
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AI SkNx operator>>(int bits) const { return { fLo >> bits, fHi >> bits }; }
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AI SkNx operator+(const SkNx& y) const { return { fLo + y.fLo, fHi + y.fHi }; }
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AI SkNx operator-(const SkNx& y) const { return { fLo - y.fLo, fHi - y.fHi }; }
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AI SkNx operator*(const SkNx& y) const { return { fLo * y.fLo, fHi * y.fHi }; }
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AI SkNx operator/(const SkNx& y) const { return { fLo / y.fLo, fHi / y.fHi }; }
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AI SkNx operator&(const SkNx& y) const { return { fLo & y.fLo, fHi & y.fHi }; }
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AI SkNx operator|(const SkNx& y) const { return { fLo | y.fLo, fHi | y.fHi }; }
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AI SkNx operator^(const SkNx& y) const { return { fLo ^ y.fLo, fHi ^ y.fHi }; }
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AI SkNx operator==(const SkNx& y) const { return { fLo == y.fLo, fHi == y.fHi }; }
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AI SkNx operator!=(const SkNx& y) const { return { fLo != y.fLo, fHi != y.fHi }; }
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AI SkNx operator<=(const SkNx& y) const { return { fLo <= y.fLo, fHi <= y.fHi }; }
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AI SkNx operator>=(const SkNx& y) const { return { fLo >= y.fLo, fHi >= y.fHi }; }
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AI SkNx operator< (const SkNx& y) const { return { fLo < y.fLo, fHi < y.fHi }; }
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AI SkNx operator> (const SkNx& y) const { return { fLo > y.fLo, fHi > y.fHi }; }
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AI SkNx saturatedAdd(const SkNx& y) const {
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return { fLo.saturatedAdd(y.fLo), fHi.saturatedAdd(y.fHi) };
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}
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AI SkNx mulHi(const SkNx& m) const {
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return { fLo.mulHi(m.fLo), fHi.mulHi(m.fHi) };
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}
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AI SkNx thenElse(const SkNx& t, const SkNx& e) const {
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return { fLo.thenElse(t.fLo, e.fLo), fHi.thenElse(t.fHi, e.fHi) };
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}
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AI static SkNx Min(const SkNx& x, const SkNx& y) {
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return { Half::Min(x.fLo, y.fLo), Half::Min(x.fHi, y.fHi) };
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}
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AI static SkNx Max(const SkNx& x, const SkNx& y) {
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return { Half::Max(x.fLo, y.fLo), Half::Max(x.fHi, y.fHi) };
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}
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};
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// The N -> N/2 recursion bottoms out at N == 1, a scalar value.
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template <typename T>
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struct SkNx<1,T> {
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T fVal;
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AI SkNx() = default;
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AI SkNx(T v) : fVal(v) {}
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// Android complains against unused parameters, so we guard it
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AI T operator[](int SkDEBUGCODE(k)) const {
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SkASSERT(k == 0);
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return fVal;
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}
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AI static SkNx Load(const void* ptr) {
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SkNx v;
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memcpy(&v, ptr, sizeof(T));
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return v;
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}
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AI void store(void* ptr) const { memcpy(ptr, &fVal, sizeof(T)); }
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AI static void Load4(const void* vptr, SkNx* a, SkNx* b, SkNx* c, SkNx* d) {
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auto ptr = (const char*)vptr;
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*a = Load(ptr + 0*sizeof(T));
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*b = Load(ptr + 1*sizeof(T));
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*c = Load(ptr + 2*sizeof(T));
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*d = Load(ptr + 3*sizeof(T));
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}
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AI static void Load3(const void* vptr, SkNx* a, SkNx* b, SkNx* c) {
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auto ptr = (const char*)vptr;
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*a = Load(ptr + 0*sizeof(T));
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*b = Load(ptr + 1*sizeof(T));
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*c = Load(ptr + 2*sizeof(T));
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}
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AI static void Load2(const void* vptr, SkNx* a, SkNx* b) {
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auto ptr = (const char*)vptr;
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*a = Load(ptr + 0*sizeof(T));
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*b = Load(ptr + 1*sizeof(T));
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}
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AI static void Store4(void* vptr, const SkNx& a, const SkNx& b, const SkNx& c, const SkNx& d) {
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auto ptr = (char*)vptr;
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a.store(ptr + 0*sizeof(T));
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b.store(ptr + 1*sizeof(T));
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c.store(ptr + 2*sizeof(T));
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d.store(ptr + 3*sizeof(T));
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}
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AI static void Store3(void* vptr, const SkNx& a, const SkNx& b, const SkNx& c) {
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auto ptr = (char*)vptr;
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a.store(ptr + 0*sizeof(T));
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b.store(ptr + 1*sizeof(T));
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c.store(ptr + 2*sizeof(T));
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}
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AI static void Store2(void* vptr, const SkNx& a, const SkNx& b) {
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auto ptr = (char*)vptr;
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a.store(ptr + 0*sizeof(T));
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b.store(ptr + 1*sizeof(T));
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}
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AI T min() const { return fVal; }
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AI T max() const { return fVal; }
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AI bool anyTrue() const { return fVal != 0; }
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AI bool allTrue() const { return fVal != 0; }
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AI SkNx abs() const { return Abs(fVal); }
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AI SkNx sqrt() const { return Sqrt(fVal); }
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AI SkNx floor() const { return Floor(fVal); }
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AI SkNx operator!() const { return !fVal; }
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AI SkNx operator-() const { return -fVal; }
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AI SkNx operator~() const { return FromBits(~ToBits(fVal)); }
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AI SkNx operator<<(int bits) const { return fVal << bits; }
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AI SkNx operator>>(int bits) const { return fVal >> bits; }
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AI SkNx operator+(const SkNx& y) const { return fVal + y.fVal; }
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AI SkNx operator-(const SkNx& y) const { return fVal - y.fVal; }
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AI SkNx operator*(const SkNx& y) const { return fVal * y.fVal; }
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AI SkNx operator/(const SkNx& y) const { return fVal / y.fVal; }
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AI SkNx operator&(const SkNx& y) const { return FromBits(ToBits(fVal) & ToBits(y.fVal)); }
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AI SkNx operator|(const SkNx& y) const { return FromBits(ToBits(fVal) | ToBits(y.fVal)); }
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AI SkNx operator^(const SkNx& y) const { return FromBits(ToBits(fVal) ^ ToBits(y.fVal)); }
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AI SkNx operator==(const SkNx& y) const { return FromBits(fVal == y.fVal ? ~0 : 0); }
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AI SkNx operator!=(const SkNx& y) const { return FromBits(fVal != y.fVal ? ~0 : 0); }
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AI SkNx operator<=(const SkNx& y) const { return FromBits(fVal <= y.fVal ? ~0 : 0); }
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AI SkNx operator>=(const SkNx& y) const { return FromBits(fVal >= y.fVal ? ~0 : 0); }
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AI SkNx operator< (const SkNx& y) const { return FromBits(fVal < y.fVal ? ~0 : 0); }
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AI SkNx operator> (const SkNx& y) const { return FromBits(fVal > y.fVal ? ~0 : 0); }
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AI static SkNx Min(const SkNx& x, const SkNx& y) { return x.fVal < y.fVal ? x : y; }
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AI static SkNx Max(const SkNx& x, const SkNx& y) { return x.fVal > y.fVal ? x : y; }
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AI SkNx saturatedAdd(const SkNx& y) const {
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static_assert(std::is_unsigned<T>::value, "");
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T sum = fVal + y.fVal;
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return sum < fVal ? std::numeric_limits<T>::max() : sum;
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}
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AI SkNx mulHi(const SkNx& m) const {
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static_assert(std::is_unsigned<T>::value, "");
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static_assert(sizeof(T) <= 4, "");
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return static_cast<T>((static_cast<uint64_t>(fVal) * m.fVal) >> (sizeof(T)*8));
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}
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AI SkNx thenElse(const SkNx& t, const SkNx& e) const { return fVal != 0 ? t : e; }
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private:
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// Helper functions to choose the right float/double methods. (In <cmath> madness lies...)
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AI static int Abs(int val) { return val < 0 ? -val : val; }
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AI static float Abs(float val) { return ::fabsf(val); }
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AI static float Sqrt(float val) { return ::sqrtf(val); }
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AI static float Floor(float val) { return ::floorf(val); }
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AI static double Abs(double val) { return ::fabs(val); }
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AI static double Sqrt(double val) { return ::sqrt(val); }
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AI static double Floor(double val) { return ::floor(val); }
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// Helper functions for working with floats/doubles as bit patterns.
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template <typename U>
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AI static U ToBits(U v) { return v; }
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AI static int32_t ToBits(float v) { int32_t bits; memcpy(&bits, &v, sizeof(v)); return bits; }
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AI static int64_t ToBits(double v) { int64_t bits; memcpy(&bits, &v, sizeof(v)); return bits; }
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template <typename Bits>
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AI static T FromBits(Bits bits) {
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static_assert(std::is_pod<T >::value &&
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std::is_pod<Bits>::value &&
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sizeof(T) <= sizeof(Bits), "");
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T val;
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memcpy(&val, &bits, sizeof(T));
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return val;
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}
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};
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// Allow scalars on the left or right of binary operators, and things like +=, &=, etc.
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#define V template <int N, typename T> AI static SkNx<N,T>
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V operator+ (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) + y; }
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V operator- (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) - y; }
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V operator* (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) * y; }
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V operator/ (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) / y; }
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V operator& (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) & y; }
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V operator| (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) | y; }
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V operator^ (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) ^ y; }
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V operator==(T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) == y; }
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V operator!=(T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) != y; }
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V operator<=(T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) <= y; }
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V operator>=(T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) >= y; }
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V operator< (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) < y; }
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V operator> (T x, const SkNx<N,T>& y) { return SkNx<N,T>(x) > y; }
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V operator+ (const SkNx<N,T>& x, T y) { return x + SkNx<N,T>(y); }
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V operator- (const SkNx<N,T>& x, T y) { return x - SkNx<N,T>(y); }
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V operator* (const SkNx<N,T>& x, T y) { return x * SkNx<N,T>(y); }
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V operator/ (const SkNx<N,T>& x, T y) { return x / SkNx<N,T>(y); }
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V operator& (const SkNx<N,T>& x, T y) { return x & SkNx<N,T>(y); }
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V operator| (const SkNx<N,T>& x, T y) { return x | SkNx<N,T>(y); }
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V operator^ (const SkNx<N,T>& x, T y) { return x ^ SkNx<N,T>(y); }
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V operator==(const SkNx<N,T>& x, T y) { return x == SkNx<N,T>(y); }
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V operator!=(const SkNx<N,T>& x, T y) { return x != SkNx<N,T>(y); }
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V operator<=(const SkNx<N,T>& x, T y) { return x <= SkNx<N,T>(y); }
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V operator>=(const SkNx<N,T>& x, T y) { return x >= SkNx<N,T>(y); }
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V operator< (const SkNx<N,T>& x, T y) { return x < SkNx<N,T>(y); }
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V operator> (const SkNx<N,T>& x, T y) { return x > SkNx<N,T>(y); }
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V& operator<<=(SkNx<N,T>& x, int bits) { return (x = x << bits); }
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V& operator>>=(SkNx<N,T>& x, int bits) { return (x = x >> bits); }
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V& operator +=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x + y); }
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V& operator -=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x - y); }
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V& operator *=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x * y); }
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V& operator /=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x / y); }
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V& operator &=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x & y); }
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V& operator |=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x | y); }
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V& operator ^=(SkNx<N,T>& x, const SkNx<N,T>& y) { return (x = x ^ y); }
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V& operator +=(SkNx<N,T>& x, T y) { return (x = x + SkNx<N,T>(y)); }
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V& operator -=(SkNx<N,T>& x, T y) { return (x = x - SkNx<N,T>(y)); }
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V& operator *=(SkNx<N,T>& x, T y) { return (x = x * SkNx<N,T>(y)); }
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V& operator /=(SkNx<N,T>& x, T y) { return (x = x / SkNx<N,T>(y)); }
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V& operator &=(SkNx<N,T>& x, T y) { return (x = x & SkNx<N,T>(y)); }
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V& operator |=(SkNx<N,T>& x, T y) { return (x = x | SkNx<N,T>(y)); }
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V& operator ^=(SkNx<N,T>& x, T y) { return (x = x ^ SkNx<N,T>(y)); }
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#undef V
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// SkNx<N,T> ~~> SkNx<N/2,T> + SkNx<N/2,T>
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template <int N, typename T>
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AI static void SkNx_split(const SkNx<N,T>& v, SkNx<N/2,T>* lo, SkNx<N/2,T>* hi) {
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*lo = v.fLo;
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*hi = v.fHi;
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}
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// SkNx<N/2,T> + SkNx<N/2,T> ~~> SkNx<N,T>
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template <int N, typename T>
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AI static SkNx<N*2,T> SkNx_join(const SkNx<N,T>& lo, const SkNx<N,T>& hi) {
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return { lo, hi };
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}
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// A very generic shuffle. Can reorder, duplicate, contract, expand...
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// Sk4f v = { R,G,B,A };
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// SkNx_shuffle<2,1,0,3>(v) ~~> {B,G,R,A}
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// SkNx_shuffle<2,1>(v) ~~> {B,G}
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// SkNx_shuffle<2,1,2,1,2,1,2,1>(v) ~~> {B,G,B,G,B,G,B,G}
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// SkNx_shuffle<3,3,3,3>(v) ~~> {A,A,A,A}
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template <int... Ix, int N, typename T>
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AI static SkNx<sizeof...(Ix),T> SkNx_shuffle(const SkNx<N,T>& v) {
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return { v[Ix]... };
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}
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// Cast from SkNx<N, Src> to SkNx<N, Dst>, as if you called static_cast<Dst>(Src).
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template <typename Dst, typename Src, int N>
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AI static SkNx<N,Dst> SkNx_cast(const SkNx<N,Src>& v) {
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return { SkNx_cast<Dst>(v.fLo), SkNx_cast<Dst>(v.fHi) };
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}
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template <typename Dst, typename Src>
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AI static SkNx<1,Dst> SkNx_cast(const SkNx<1,Src>& v) {
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return static_cast<Dst>(v.fVal);
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}
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|
|
template <int N, typename T>
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AI static SkNx<N,T> SkNx_fma(const SkNx<N,T>& f, const SkNx<N,T>& m, const SkNx<N,T>& a) {
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return f*m+a;
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}
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} // namespace
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typedef SkNx<2, float> Sk2f;
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typedef SkNx<4, float> Sk4f;
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typedef SkNx<8, float> Sk8f;
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typedef SkNx<16, float> Sk16f;
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typedef SkNx<2, SkScalar> Sk2s;
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typedef SkNx<4, SkScalar> Sk4s;
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typedef SkNx<8, SkScalar> Sk8s;
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typedef SkNx<16, SkScalar> Sk16s;
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|
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typedef SkNx<4, uint8_t> Sk4b;
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typedef SkNx<8, uint8_t> Sk8b;
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typedef SkNx<16, uint8_t> Sk16b;
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|
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typedef SkNx<4, uint16_t> Sk4h;
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typedef SkNx<8, uint16_t> Sk8h;
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typedef SkNx<16, uint16_t> Sk16h;
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|
|
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typedef SkNx<4, int32_t> Sk4i;
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typedef SkNx<8, int32_t> Sk8i;
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typedef SkNx<4, uint32_t> Sk4u;
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|
|
|
// Include platform specific specializations if available.
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|
#if !defined(SKNX_NO_SIMD) && SK_CPU_SSE_LEVEL >= SK_CPU_SSE_LEVEL_SSE2
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|
#include "include/private/SkNx_sse.h"
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|
#elif !defined(SKNX_NO_SIMD) && defined(SK_ARM_HAS_NEON)
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|
#include "include/private/SkNx_neon.h"
|
|
#else
|
|
|
|
AI static Sk4i Sk4f_round(const Sk4f& x) {
|
|
return { (int) lrintf (x[0]),
|
|
(int) lrintf (x[1]),
|
|
(int) lrintf (x[2]),
|
|
(int) lrintf (x[3]), };
|
|
}
|
|
|
|
#endif
|
|
|
|
AI static void Sk4f_ToBytes(uint8_t p[16],
|
|
const Sk4f& a, const Sk4f& b, const Sk4f& c, const Sk4f& d) {
|
|
SkNx_cast<uint8_t>(SkNx_join(SkNx_join(a,b), SkNx_join(c,d))).store(p);
|
|
}
|
|
|
|
#undef AI
|
|
|
|
#endif//SkNx_DEFINED
|