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refactor: relative() renamed to delta()

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Mateusz Pusz
2024-06-20 07:31:22 +02:00
parent dfac87c631
commit b38b23ece2
15 changed files with 83 additions and 87 deletions
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15
example/kalman_filter/kalman_filter-example_6.cpp
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@ -62,14 +62,13 @@ int main()
using estimate = kalman::system_state_estimate<qp>;
using state = estimate::state_type;
const quantity process_noise_variance = 0.0001 * relative(pow<2>(deg_C));
const estimate initial{state{qp{60. * relative(deg_C)}}, 100. * relative(deg_C)};
const std::array measurements = {qp{49.986 * relative(deg_C)}, qp{49.963 * relative(deg_C)},
qp{50.097 * relative(deg_C)}, qp{50.001 * relative(deg_C)},
qp{50.018 * relative(deg_C)}, qp{50.05 * relative(deg_C)},
qp{49.938 * relative(deg_C)}, qp{49.858 * relative(deg_C)},
qp{49.965 * relative(deg_C)}, qp{50.114 * relative(deg_C)}};
const quantity measurement_error = 0.1 * relative(deg_C);
const quantity process_noise_variance = 0.0001 * delta(pow<2>(deg_C));
const estimate initial{state{qp{60. * delta(deg_C)}}, 100. * delta(deg_C)};
const std::array measurements = {qp{49.986 * delta(deg_C)}, qp{49.963 * delta(deg_C)}, qp{50.097 * delta(deg_C)},
qp{50.001 * delta(deg_C)}, qp{50.018 * delta(deg_C)}, qp{50.05 * delta(deg_C)},
qp{49.938 * delta(deg_C)}, qp{49.858 * delta(deg_C)}, qp{49.965 * delta(deg_C)},
qp{50.114 * delta(deg_C)}};
const quantity measurement_error = 0.1 * delta(deg_C);
const quantity measurement_variance = pow<2>(measurement_error);
auto predict = [=](const estimate& current) {

15
example/kalman_filter/kalman_filter-example_7.cpp
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@ -62,14 +62,13 @@ int main()
using estimate = kalman::system_state_estimate<qp>;
using state = estimate::state_type;
const quantity process_noise_variance = 0.0001 * relative(pow<2>(deg_C));
const estimate initial{state{qp{10. * relative(deg_C)}}, 100. * relative(deg_C)};
const std::array measurements = {qp{50.486 * relative(deg_C)}, qp{50.963 * relative(deg_C)},
qp{51.597 * relative(deg_C)}, qp{52.001 * relative(deg_C)},
qp{52.518 * relative(deg_C)}, qp{53.05 * relative(deg_C)},
qp{53.438 * relative(deg_C)}, qp{53.858 * relative(deg_C)},
qp{54.465 * relative(deg_C)}, qp{55.114 * relative(deg_C)}};
const quantity measurement_error = 0.1 * relative(deg_C);
const quantity process_noise_variance = 0.0001 * delta(pow<2>(deg_C));
const estimate initial{state{qp{10. * delta(deg_C)}}, 100. * delta(deg_C)};
const std::array measurements = {qp{50.486 * delta(deg_C)}, qp{50.963 * delta(deg_C)}, qp{51.597 * delta(deg_C)},
qp{52.001 * delta(deg_C)}, qp{52.518 * delta(deg_C)}, qp{53.05 * delta(deg_C)},
qp{53.438 * delta(deg_C)}, qp{53.858 * delta(deg_C)}, qp{54.465 * delta(deg_C)},
qp{55.114 * delta(deg_C)}};
const quantity measurement_error = 0.1 * delta(deg_C);
const quantity measurement_variance = pow<2>(measurement_error);
auto predict = [=](const estimate& current) {

15
example/kalman_filter/kalman_filter-example_8.cpp
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@ -62,14 +62,13 @@ int main()
using estimate = kalman::system_state_estimate<qp>;
using state = estimate::state_type;
const quantity process_noise_variance = 0.15 * relative(pow<2>(deg_C));
const estimate initial{state{qp{10. * relative(deg_C)}}, 100. * relative(deg_C)};
const std::array measurements = {qp{50.486 * relative(deg_C)}, qp{50.963 * relative(deg_C)},
qp{51.597 * relative(deg_C)}, qp{52.001 * relative(deg_C)},
qp{52.518 * relative(deg_C)}, qp{53.05 * relative(deg_C)},
qp{53.438 * relative(deg_C)}, qp{53.858 * relative(deg_C)},
qp{54.465 * relative(deg_C)}, qp{55.114 * relative(deg_C)}};
const quantity measurement_error = 0.1 * relative(deg_C);
const quantity process_noise_variance = 0.15 * delta(pow<2>(deg_C));
const estimate initial{state{qp{10. * delta(deg_C)}}, 100. * delta(deg_C)};
const std::array measurements = {qp{50.486 * delta(deg_C)}, qp{50.963 * delta(deg_C)}, qp{51.597 * delta(deg_C)},
qp{52.001 * delta(deg_C)}, qp{52.518 * delta(deg_C)}, qp{53.05 * delta(deg_C)},
qp{53.438 * delta(deg_C)}, qp{53.858 * delta(deg_C)}, qp{54.465 * delta(deg_C)},
qp{55.114 * delta(deg_C)}};
const quantity measurement_error = 0.1 * delta(deg_C);
const quantity measurement_variance = pow<2>(measurement_error);
auto predict = [=](const estimate& current) {

2
example/spectroscopy_units.cpp
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@ -84,7 +84,7 @@ int main()
const auto t3 = std::make_tuple(isq::energy(q3 * h), isq::wavenumber(q3 / c), q3,
isq::thermodynamic_temperature(q3 * h / kb), isq::wavelength(c / q3));
const auto q4 = isq::thermodynamic_temperature(1. * relative(K));
const auto q4 = isq::thermodynamic_temperature(1. * delta(K));
const auto t4 = std::make_tuple(isq::energy(q4 * kb), isq::wavenumber(q4 * kb / (h * c)), isq::frequency(q4 * kb / h),
q4, isq::wavelength(h * c / (q4 * kb)));