tracking-parametrisation-tuner/neural_net_training/result/matching.hpp

29 lines
1.7 KiB
C++
Raw Normal View History

2024-01-15 09:39:38 +01:00
const auto fMin = std::array<simd::float_v, 8>{
{1.4334048501e-05, 1.63528045505e-06, 9.53674316406e-06, 3.0517578125e-05,
7.06594437361e-06, 1.16415321827e-09, -3.14159274101, 1.99012887478}};
const auto fMax = std::array<simd::float_v, 8>{
{14.9999303818, 0.150984346867, 249.944519043, 249.72227478, 1.2982006073,
0.14879232645, 3.14159274101, 5.00999403}};
const auto fWeightMatrix0to1 = std::array<std::array<simd::float_v, 9>, 10>{
{{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan},
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan}}};
const auto fWeightMatrix1to2 = std::array<std::array<simd::float_v, 11>, 8>{
{{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan},
{nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan}}};
const auto fWeightMatrix2to3 = std::array<simd::float_v, 9>{
{-nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan, -nan}};