250 lines
8.6 KiB
C++
250 lines
8.6 KiB
C++
#if GLM_ARCH & GLM_ARCH_SSE2_BIT
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#include "type_mat4x4.hpp"
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#include "../geometric.hpp"
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#include "../simd/matrix.h"
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#include <cstring>
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namespace glm{
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namespace detail
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{
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# if GLM_CONFIG_ALIGNED_GENTYPES == GLM_ENABLE
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template<qualifier Q>
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struct compute_matrixCompMult<4, 4, float, Q, true>
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{
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GLM_STATIC_ASSERT(detail::is_aligned<Q>::value, "Specialization requires aligned");
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GLM_FUNC_QUALIFIER static mat<4, 4, float, Q> call(mat<4, 4, float, Q> const& x, mat<4, 4, float, Q> const& y)
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{
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mat<4, 4, float, Q> Result;
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glm_mat4_matrixCompMult(
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*static_cast<glm_vec4 const (*)[4]>(&x[0].data),
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*static_cast<glm_vec4 const (*)[4]>(&y[0].data),
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*static_cast<glm_vec4(*)[4]>(&Result[0].data));
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return Result;
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}
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};
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# endif
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template<qualifier Q>
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struct compute_transpose<4, 4, float, Q, true>
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{
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GLM_FUNC_QUALIFIER static mat<4, 4, float, Q> call(mat<4, 4, float, Q> const& m)
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{
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mat<4, 4, float, Q> Result;
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glm_mat4_transpose(&m[0].data, &Result[0].data);
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return Result;
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}
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};
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template<qualifier Q>
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struct compute_determinant<4, 4, float, Q, true>
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{
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GLM_FUNC_QUALIFIER static float call(mat<4, 4, float, Q> const& m)
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{
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return _mm_cvtss_f32(glm_mat4_determinant(&m[0].data));
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}
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};
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template<qualifier Q>
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struct compute_inverse<4, 4, float, Q, true>
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{
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GLM_FUNC_QUALIFIER static mat<4, 4, float, Q> call(mat<4, 4, float, Q> const& m)
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{
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mat<4, 4, float, Q> Result;
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glm_mat4_inverse(&m[0].data, &Result[0].data);
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return Result;
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}
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};
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}//namespace detail
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# if GLM_CONFIG_ALIGNED_GENTYPES == GLM_ENABLE
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template<>
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GLM_FUNC_QUALIFIER mat<4, 4, float, aligned_lowp> outerProduct<4, 4, float, aligned_lowp>(vec<4, float, aligned_lowp> const& c, vec<4, float, aligned_lowp> const& r)
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{
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__m128 NativeResult[4];
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glm_mat4_outerProduct(c.data, r.data, NativeResult);
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mat<4, 4, float, aligned_lowp> Result;
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std::memcpy(&Result[0], &NativeResult[0], sizeof(Result));
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return Result;
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}
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template<>
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GLM_FUNC_QUALIFIER mat<4, 4, float, aligned_mediump> outerProduct<4, 4, float, aligned_mediump>(vec<4, float, aligned_mediump> const& c, vec<4, float, aligned_mediump> const& r)
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{
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__m128 NativeResult[4];
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glm_mat4_outerProduct(c.data, r.data, NativeResult);
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mat<4, 4, float, aligned_mediump> Result;
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std::memcpy(&Result[0], &NativeResult[0], sizeof(Result));
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return Result;
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}
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template<>
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GLM_FUNC_QUALIFIER mat<4, 4, float, aligned_highp> outerProduct<4, 4, float, aligned_highp>(vec<4, float, aligned_highp> const& c, vec<4, float, aligned_highp> const& r)
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{
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__m128 NativeResult[4];
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glm_mat4_outerProduct(c.data, r.data, NativeResult);
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mat<4, 4, float, aligned_highp> Result;
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std::memcpy(&Result[0], &NativeResult[0], sizeof(Result));
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return Result;
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}
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# endif
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}//namespace glm
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#elif GLM_ARCH & GLM_ARCH_NEON_BIT
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namespace glm {
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#if GLM_LANG & GLM_LANG_CXX11_FLAG
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template <qualifier Q>
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GLM_FUNC_QUALIFIER
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typename std::enable_if<detail::is_aligned<Q>::value, mat<4, 4, float, Q>>::type
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operator*(mat<4, 4, float, Q> const & m1, mat<4, 4, float, Q> const & m2)
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{
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auto MulRow = [&](int l) {
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float32x4_t const SrcA = m2[l].data;
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float32x4_t r = neon::mul_lane(m1[0].data, SrcA, 0);
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r = neon::madd_lane(r, m1[1].data, SrcA, 1);
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r = neon::madd_lane(r, m1[2].data, SrcA, 2);
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r = neon::madd_lane(r, m1[3].data, SrcA, 3);
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return r;
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};
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mat<4, 4, float, aligned_highp> Result;
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Result[0].data = MulRow(0);
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Result[1].data = MulRow(1);
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Result[2].data = MulRow(2);
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Result[3].data = MulRow(3);
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return Result;
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}
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#endif // CXX11
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template<qualifier Q>
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struct detail::compute_inverse<4, 4, float, Q, true>
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{
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GLM_FUNC_QUALIFIER static mat<4, 4, float, Q> call(mat<4, 4, float, Q> const& m)
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{
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float32x4_t const& m0 = m[0].data;
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float32x4_t const& m1 = m[1].data;
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float32x4_t const& m2 = m[2].data;
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float32x4_t const& m3 = m[3].data;
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// m[2][2] * m[3][3] - m[3][2] * m[2][3];
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// m[2][2] * m[3][3] - m[3][2] * m[2][3];
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// m[1][2] * m[3][3] - m[3][2] * m[1][3];
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// m[1][2] * m[2][3] - m[2][2] * m[1][3];
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float32x4_t Fac0;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 2), neon::dup_lane(m1, 2));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 3), 3, m2, 3);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 2), 3, m2, 2);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 3), neon::dup_lane(m1, 3));
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Fac0 = w0 * w1 - w2 * w3;
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}
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// m[2][1] * m[3][3] - m[3][1] * m[2][3];
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// m[2][1] * m[3][3] - m[3][1] * m[2][3];
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// m[1][1] * m[3][3] - m[3][1] * m[1][3];
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// m[1][1] * m[2][3] - m[2][1] * m[1][3];
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float32x4_t Fac1;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 1), neon::dup_lane(m1, 1));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 3), 3, m2, 3);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 1), 3, m2, 1);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 3), neon::dup_lane(m1, 3));
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Fac1 = w0 * w1 - w2 * w3;
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}
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// m[2][1] * m[3][2] - m[3][1] * m[2][2];
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// m[2][1] * m[3][2] - m[3][1] * m[2][2];
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// m[1][1] * m[3][2] - m[3][1] * m[1][2];
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// m[1][1] * m[2][2] - m[2][1] * m[1][2];
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float32x4_t Fac2;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 1), neon::dup_lane(m1, 1));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 2), 3, m2, 2);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 1), 3, m2, 1);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 2), neon::dup_lane(m1, 2));
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Fac2 = w0 * w1 - w2 * w3;
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}
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// m[2][0] * m[3][3] - m[3][0] * m[2][3];
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// m[2][0] * m[3][3] - m[3][0] * m[2][3];
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// m[1][0] * m[3][3] - m[3][0] * m[1][3];
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// m[1][0] * m[2][3] - m[2][0] * m[1][3];
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float32x4_t Fac3;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 0), neon::dup_lane(m1, 0));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 3), 3, m2, 3);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 0), 3, m2, 0);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 3), neon::dup_lane(m1, 3));
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Fac3 = w0 * w1 - w2 * w3;
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}
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// m[2][0] * m[3][2] - m[3][0] * m[2][2];
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// m[2][0] * m[3][2] - m[3][0] * m[2][2];
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// m[1][0] * m[3][2] - m[3][0] * m[1][2];
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// m[1][0] * m[2][2] - m[2][0] * m[1][2];
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float32x4_t Fac4;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 0), neon::dup_lane(m1, 0));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 2), 3, m2, 2);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 0), 3, m2, 0);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 2), neon::dup_lane(m1, 2));
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Fac4 = w0 * w1 - w2 * w3;
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}
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// m[2][0] * m[3][1] - m[3][0] * m[2][1];
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// m[2][0] * m[3][1] - m[3][0] * m[2][1];
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// m[1][0] * m[3][1] - m[3][0] * m[1][1];
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// m[1][0] * m[2][1] - m[2][0] * m[1][1];
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float32x4_t Fac5;
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{
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float32x4_t w0 = vcombine_f32(neon::dup_lane(m2, 0), neon::dup_lane(m1, 0));
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float32x4_t w1 = neon::copy_lane(neon::dupq_lane(m3, 1), 3, m2, 1);
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float32x4_t w2 = neon::copy_lane(neon::dupq_lane(m3, 0), 3, m2, 0);
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float32x4_t w3 = vcombine_f32(neon::dup_lane(m2, 1), neon::dup_lane(m1, 1));
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Fac5 = w0 * w1 - w2 * w3;
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}
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float32x4_t Vec0 = neon::copy_lane(neon::dupq_lane(m0, 0), 0, m1, 0); // (m[1][0], m[0][0], m[0][0], m[0][0]);
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float32x4_t Vec1 = neon::copy_lane(neon::dupq_lane(m0, 1), 0, m1, 1); // (m[1][1], m[0][1], m[0][1], m[0][1]);
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float32x4_t Vec2 = neon::copy_lane(neon::dupq_lane(m0, 2), 0, m1, 2); // (m[1][2], m[0][2], m[0][2], m[0][2]);
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float32x4_t Vec3 = neon::copy_lane(neon::dupq_lane(m0, 3), 0, m1, 3); // (m[1][3], m[0][3], m[0][3], m[0][3]);
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float32x4_t Inv0 = Vec1 * Fac0 - Vec2 * Fac1 + Vec3 * Fac2;
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float32x4_t Inv1 = Vec0 * Fac0 - Vec2 * Fac3 + Vec3 * Fac4;
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float32x4_t Inv2 = Vec0 * Fac1 - Vec1 * Fac3 + Vec3 * Fac5;
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float32x4_t Inv3 = Vec0 * Fac2 - Vec1 * Fac4 + Vec2 * Fac5;
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float32x4_t r0 = float32x4_t{-1, +1, -1, +1} * Inv0;
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float32x4_t r1 = float32x4_t{+1, -1, +1, -1} * Inv1;
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float32x4_t r2 = float32x4_t{-1, +1, -1, +1} * Inv2;
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float32x4_t r3 = float32x4_t{+1, -1, +1, -1} * Inv3;
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float32x4_t det = neon::mul_lane(r0, m0, 0);
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det = neon::madd_lane(det, r1, m0, 1);
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det = neon::madd_lane(det, r2, m0, 2);
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det = neon::madd_lane(det, r3, m0, 3);
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float32x4_t rdet = vdupq_n_f32(1 / vgetq_lane_f32(det, 0));
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mat<4, 4, float, Q> r;
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r[0].data = vmulq_f32(r0, rdet);
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r[1].data = vmulq_f32(r1, rdet);
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r[2].data = vmulq_f32(r2, rdet);
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r[3].data = vmulq_f32(r3, rdet);
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return r;
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}
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};
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}//namespace glm
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#endif
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