58a9549a58
It's too unstable with larger vectors. Even when the source and listener positions are the same, floating point precision can cause noticeable rounding errors.
128 lines
3.9 KiB
C++
128 lines
3.9 KiB
C++
#ifndef COMMON_VECMAT_H
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#define COMMON_VECMAT_H
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#include <array>
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#include <cmath>
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#include <cstddef>
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#include <limits>
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#include "alspan.h"
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namespace alu {
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template<typename T>
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class VectorR {
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static_assert(std::is_floating_point<T>::value, "Must use floating-point types");
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alignas(16) std::array<T,4> mVals;
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public:
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constexpr VectorR() noexcept = default;
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constexpr VectorR(const VectorR&) noexcept = default;
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constexpr VectorR(T a, T b, T c, T d) noexcept : mVals{{a, b, c, d}} { }
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constexpr VectorR& operator=(const VectorR&) noexcept = default;
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T& operator[](size_t idx) noexcept { return mVals[idx]; }
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constexpr const T& operator[](size_t idx) const noexcept { return mVals[idx]; }
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VectorR& operator+=(const VectorR &rhs) noexcept
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{
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mVals[0] += rhs.mVals[0];
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mVals[1] += rhs.mVals[1];
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mVals[2] += rhs.mVals[2];
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mVals[3] += rhs.mVals[3];
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return *this;
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}
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VectorR operator-(const VectorR &rhs) const noexcept
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{
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const VectorR ret{mVals[0] - rhs.mVals[0], mVals[1] - rhs.mVals[1],
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mVals[2] - rhs.mVals[2], mVals[3] - rhs.mVals[3]};
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return ret;
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}
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T normalize(T limit = std::numeric_limits<T>::epsilon())
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{
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limit = std::max(limit, std::numeric_limits<T>::epsilon());
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const T length_sqr{mVals[0]*mVals[0] + mVals[1]*mVals[1] + mVals[2]*mVals[2]};
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if(length_sqr > limit*limit)
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{
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const T length{std::sqrt(length_sqr)};
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T inv_length{T{1}/length};
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mVals[0] *= inv_length;
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mVals[1] *= inv_length;
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mVals[2] *= inv_length;
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return length;
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}
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mVals[0] = mVals[1] = mVals[2] = T{0};
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return T{0};
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}
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constexpr VectorR cross_product(const alu::VectorR<T> &rhs) const
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{
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return VectorR{
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(*this)[1]*rhs[2] - (*this)[2]*rhs[1],
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(*this)[2]*rhs[0] - (*this)[0]*rhs[2],
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(*this)[0]*rhs[1] - (*this)[1]*rhs[0],
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T{0}};
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}
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constexpr T dot_product(const alu::VectorR<T> &rhs) const
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{ return (*this)[0]*rhs[0] + (*this)[1]*rhs[1] + (*this)[2]*rhs[2]; }
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};
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using Vector = VectorR<float>;
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template<typename T>
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class MatrixR {
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static_assert(std::is_floating_point<T>::value, "Must use floating-point types");
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alignas(16) std::array<T,16> mVals;
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public:
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constexpr MatrixR() noexcept = default;
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constexpr MatrixR(const MatrixR&) noexcept = default;
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constexpr MatrixR(T aa, T ab, T ac, T ad,
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T ba, T bb, T bc, T bd,
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T ca, T cb, T cc, T cd,
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T da, T db, T dc, T dd) noexcept
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: mVals{{aa,ab,ac,ad, ba,bb,bc,bd, ca,cb,cc,cd, da,db,dc,dd}}
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{ }
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constexpr MatrixR& operator=(const MatrixR&) noexcept = default;
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auto operator[](size_t idx) noexcept { return al::span<T,4>{&mVals[idx*4], 4}; }
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constexpr auto operator[](size_t idx) const noexcept
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{ return al::span<const T,4>{&mVals[idx*4], 4}; }
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static constexpr MatrixR Identity() noexcept
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{
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return MatrixR{
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T{1}, T{0}, T{0}, T{0},
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T{0}, T{1}, T{0}, T{0},
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T{0}, T{0}, T{1}, T{0},
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T{0}, T{0}, T{0}, T{1}};
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}
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};
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using Matrix = MatrixR<float>;
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template<typename T>
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inline VectorR<T> operator*(const MatrixR<T> &mtx, const VectorR<T> &vec) noexcept
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{
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return VectorR<T>{
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vec[0]*mtx[0][0] + vec[1]*mtx[1][0] + vec[2]*mtx[2][0] + vec[3]*mtx[3][0],
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vec[0]*mtx[0][1] + vec[1]*mtx[1][1] + vec[2]*mtx[2][1] + vec[3]*mtx[3][1],
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vec[0]*mtx[0][2] + vec[1]*mtx[1][2] + vec[2]*mtx[2][2] + vec[3]*mtx[3][2],
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vec[0]*mtx[0][3] + vec[1]*mtx[1][3] + vec[2]*mtx[2][3] + vec[3]*mtx[3][3]};
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}
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template<typename U, typename T>
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inline VectorR<U> cast_to(const VectorR<T> &vec) noexcept
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{
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return VectorR<U>{static_cast<U>(vec[0]), static_cast<U>(vec[1]),
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static_cast<U>(vec[2]), static_cast<U>(vec[3])};
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}
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} // namespace alu
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#endif /* COMMON_VECMAT_H */
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