77 lines
2.2 KiB
C++
77 lines
2.2 KiB
C++
#pragma once
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#include <Eigen/Eigen>
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#include <autoopt/btls.hpp>
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#include <autoopt/optimization_problem.hpp>
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#include <cmath>
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#include <cstddef>
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#include <optional>
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#include <utility>
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#include <vector>
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#include "autoopt/util.hpp"
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namespace autoopt {
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struct test_data {
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Eigen::VectorXd _xs;
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Eigen::VectorXd _ys;
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double _center;
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size_t size() const { return _xs.size(); }
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std::pair<double, double> operator[](size_t i) const {
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return {_xs(i) - _center, _ys(i)};
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};
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};
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struct curve_base {
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Eigen::VectorXd initial;
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Eigen::VectorXd delta;
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std::vector<const char*> param_names;
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bool flip = false;
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std::pair<Eigen::VectorXd, double> fit(this auto&& self,
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const test_data& measurements) {
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auto opt_func = [&]<typename T>(const Eigen::VectorX<T>& params) {
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auto grapher = self.template grapher_from_params<T>(params);
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T error{0.0};
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for (size_t i = 0; i < measurements.size(); i++) {
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auto [x, y] = measurements[i];
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T distance = T{self.flip ? -1.0 : 1.0} *
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std::atan(grapher.slope_at(T{self.flip ? -x : x})) -
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T{arcsec2rad(y)};
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error = error + distance * distance;
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}
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return error / T(measurements.size());
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};
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auto_diff_optimization_problem problem(opt_func, self.initial);
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log_barrier_optimization_problem lb_problem(problem, self.delta, 1e-4);
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while (lb_problem._barrier_strength > 1e-20) {
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btls(lb_problem);
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lb_problem._barrier_strength *= 1e-2;
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}
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Eigen::VectorX<double> fitted_params = problem.x();
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return {fitted_params, std::sqrt(problem.objective(fitted_params))};
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}
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Eigen::VectorXd plot(this auto&& self, const test_data& measurements,
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std::optional<Eigen::VectorXd> params = {}) {
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auto grapher = self.template grapher_from_params<double>(
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params.value_or(self.initial));
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Eigen::VectorXd ys(measurements.size());
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for (size_t i = 0; i < measurements.size(); i++) {
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double x = measurements[i].first;
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ys(i) = rad2arcsec((self.flip ? -1.0 : 1.0) *
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atan(grapher.slope_at(self.flip ? -x : x)));
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}
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return ys;
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}
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};
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} // namespace autoopt
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