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313 lines
9.8 KiB
C++
313 lines
9.8 KiB
C++
#ifndef NLOPTOPTIMIZER_HPP
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#define NLOPTOPTIMIZER_HPP
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#ifdef _MSC_VER
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#pragma warning(push)
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#pragma warning(disable: 4244)
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#pragma warning(disable: 4267)
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#endif
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#include <nlopt.h>
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#ifdef _MSC_VER
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#pragma warning(pop)
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#endif
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#include <utility>
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#include "Optimizer.hpp"
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namespace Slic3r { namespace opt {
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namespace detail {
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// Helper types for NLopt algorithm selection in template contexts
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template<nlopt_algorithm alg> struct NLoptAlg {};
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// NLopt can combine multiple algorithms if one is global an other is a local
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// method. This is how template specializations can be informed about this fact.
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template<nlopt_algorithm gl_alg, nlopt_algorithm lc_alg = NLOPT_LN_NELDERMEAD>
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struct NLoptAlgComb {};
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template<class M> struct IsNLoptAlg {
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static const constexpr bool value = false;
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};
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template<nlopt_algorithm a> struct IsNLoptAlg<NLoptAlg<a>> {
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static const constexpr bool value = true;
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};
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template<nlopt_algorithm a1, nlopt_algorithm a2>
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struct IsNLoptAlg<NLoptAlgComb<a1, a2>> {
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static const constexpr bool value = true;
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};
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template<class M, class T = void>
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using NLoptOnly = std::enable_if_t<IsNLoptAlg<M>::value, T>;
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enum class OptDir { MIN, MAX }; // Where to optimize
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struct NLopt { // Helper RAII class for nlopt_opt
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nlopt_opt ptr = nullptr;
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template<class...A> explicit NLopt(A&&...a)
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{
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ptr = nlopt_create(std::forward<A>(a)...);
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}
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NLopt(const NLopt&) = delete;
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NLopt(NLopt&&) = delete;
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NLopt& operator=(const NLopt&) = delete;
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NLopt& operator=(NLopt&&) = delete;
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~NLopt() { nlopt_destroy(ptr); }
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};
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template<class Method> class NLoptOpt {};
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// Map a generic function to each argument following the mapping function
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template<class Fn, class...Args>
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Fn for_each_argument(Fn &&fn, Args&&...args)
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{
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// see https://www.fluentcpp.com/2019/03/05/for_each_arg-applying-a-function-to-each-argument-of-a-function-in-cpp/
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(fn(std::forward<Args>(args)),...);
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return fn;
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}
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template<class Fn, class...Args>
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Fn for_each_in_tuple(Fn fn, const std::tuple<Args...> &tup)
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{
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auto arg = std::tuple_cat(std::make_tuple(fn), tup);
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auto mpfn = [](auto fn, auto...pack) {
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return for_each_argument(fn, pack...);
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};
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std::apply(mpfn, arg);
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return fn;
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}
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// Optimizers based on NLopt.
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template<nlopt_algorithm alg> class NLoptOpt<NLoptAlg<alg>> {
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protected:
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StopCriteria m_stopcr;
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OptDir m_dir = OptDir::MIN;
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static constexpr double ConstraintEps = 1e-6;
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template<class Fn> using TOptData =
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std::tuple<std::remove_reference_t<Fn>*, NLoptOpt*, nlopt_opt>;
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template<class Fn, size_t N>
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static double optfunc(unsigned n, const double *params,
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double *gradient,
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void *data)
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{
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assert(n == N);
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auto tdata = static_cast<TOptData<Fn>*>(data);
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if (std::get<1>(*tdata)->m_stopcr.stop_condition())
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nlopt_force_stop(std::get<2>(*tdata));
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auto fnptr = std::get<0>(*tdata);
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auto funval = to_arr<N>(params);
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double scoreval = 0.;
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using RetT = decltype((*fnptr)(funval));
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if constexpr (std::is_convertible_v<RetT, ScoreGradient<N>>) {
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ScoreGradient<N> score = (*fnptr)(funval);
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for (size_t i = 0; i < n; ++i) gradient[i] = (*score.gradient)[i];
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scoreval = score.score;
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} else {
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scoreval = (*fnptr)(funval);
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}
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return scoreval;
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}
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template<class Fn, size_t N>
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static double constrain_func(unsigned n, const double *params,
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double *gradient,
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void *data)
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{
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assert(n == N);
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auto tdata = static_cast<TOptData<Fn>*>(data);
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auto &fnptr = std::get<0>(*tdata);
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auto funval = to_arr<N>(params);
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return (*fnptr)(funval);
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}
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template<size_t N>
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static void set_up(NLopt &nl,
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const Bounds<N> &bounds,
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const StopCriteria &stopcr)
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{
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std::array<double, N> lb, ub;
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for (size_t i = 0; i < N; ++i) {
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lb[i] = bounds[i].min();
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ub[i] = bounds[i].max();
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}
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nlopt_set_lower_bounds(nl.ptr, lb.data());
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nlopt_set_upper_bounds(nl.ptr, ub.data());
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double abs_diff = stopcr.abs_score_diff();
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double rel_diff = stopcr.rel_score_diff();
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double stopval = stopcr.stop_score();
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if(!std::isnan(abs_diff)) nlopt_set_ftol_abs(nl.ptr, abs_diff);
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if(!std::isnan(rel_diff)) nlopt_set_ftol_rel(nl.ptr, rel_diff);
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if(!std::isnan(stopval)) nlopt_set_stopval(nl.ptr, stopval);
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if(stopcr.max_iterations() > 0)
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nlopt_set_maxeval(nl.ptr, stopcr.max_iterations());
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}
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template<class Fn, size_t N, class...EqFns, class...IneqFns>
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Result<N> optimize(NLopt &nl, Fn &&fn, const Input<N> &initvals,
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const std::tuple<EqFns...> &equalities,
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const std::tuple<IneqFns...> &inequalities)
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{
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Result<N> r;
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TOptData<Fn> data = std::make_tuple(&fn, this, nl.ptr);
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auto do_for_each_eq = [this, &nl](auto &&arg) {
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auto data = std::make_tuple(&arg, this, nl.ptr);
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using F = std::remove_cv_t<decltype(arg)>;
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nlopt_add_equality_constraint (nl.ptr, constrain_func<F, N>, &data, ConstraintEps);
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};
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auto do_for_each_ineq = [this, &nl](auto &&arg) {
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auto data = std::make_tuple(&arg, this, nl.ptr);
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using F = std::remove_cv_t<decltype(arg)>;
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nlopt_add_inequality_constraint (nl.ptr, constrain_func<F, N>, &data, ConstraintEps);
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};
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for_each_in_tuple(do_for_each_eq, equalities);
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for_each_in_tuple(do_for_each_ineq, inequalities);
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switch(m_dir) {
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case OptDir::MIN:
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nlopt_set_min_objective(nl.ptr, optfunc<Fn, N>, &data); break;
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case OptDir::MAX:
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nlopt_set_max_objective(nl.ptr, optfunc<Fn, N>, &data); break;
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}
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r.optimum = initvals;
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r.resultcode = nlopt_optimize(nl.ptr, r.optimum.data(), &r.score);
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return r;
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}
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public:
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template<class Func, size_t N, class...EqFns, class...IneqFns>
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Result<N> optimize(Func&& func,
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const Input<N> &initvals,
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const Bounds<N>& bounds,
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const std::tuple<EqFns...> &equalities,
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const std::tuple<IneqFns...> &inequalities)
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{
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NLopt nl{alg, N};
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set_up(nl, bounds, m_stopcr);
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return optimize(nl, std::forward<Func>(func), initvals,
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equalities, inequalities);
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}
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explicit NLoptOpt(const StopCriteria &stopcr = {}) : m_stopcr(stopcr) {}
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void set_criteria(const StopCriteria &cr) { m_stopcr = cr; }
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const StopCriteria &get_criteria() const noexcept { return m_stopcr; }
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void set_dir(OptDir dir) noexcept { m_dir = dir; }
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void seed(long s) { nlopt_srand(s); }
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};
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template<nlopt_algorithm glob, nlopt_algorithm loc>
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class NLoptOpt<NLoptAlgComb<glob, loc>>: public NLoptOpt<NLoptAlg<glob>>
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{
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using Base = NLoptOpt<NLoptAlg<glob>>;
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StopCriteria m_loc_stopcr;
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public:
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template<class Fn, size_t N, class...EqFns, class...IneqFns>
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Result<N> optimize(Fn&& f,
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const Input<N> &initvals,
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const Bounds<N>& bounds,
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const std::tuple<EqFns...> &equalities,
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const std::tuple<IneqFns...> &inequalities)
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{
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NLopt nl_glob{glob, N}, nl_loc{loc, N};
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Base::set_up(nl_glob, bounds, Base::get_criteria());
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Base::set_up(nl_loc, bounds, m_loc_stopcr);
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nlopt_set_local_optimizer(nl_glob.ptr, nl_loc.ptr);
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return Base::optimize(nl_glob, std::forward<Fn>(f), initvals,
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equalities, inequalities);
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}
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explicit NLoptOpt(StopCriteria stopcr = {})
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: Base{stopcr}, m_loc_stopcr{stopcr}
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{}
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void set_loc_criteria(const StopCriteria &cr) { m_loc_stopcr = cr; }
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const StopCriteria &get_loc_criteria() const noexcept { return m_loc_stopcr; }
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};
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} // namespace detail;
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// Optimizers based on NLopt.
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template<class M> class Optimizer<M, detail::NLoptOnly<M>> {
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detail::NLoptOpt<M> m_opt;
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public:
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Optimizer& to_max() { m_opt.set_dir(detail::OptDir::MAX); return *this; }
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Optimizer& to_min() { m_opt.set_dir(detail::OptDir::MIN); return *this; }
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template<class Func, size_t N, class...EqFns, class...IneqFns>
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Result<N> optimize(Func&& func,
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const Input<N> &initvals,
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const Bounds<N>& bounds,
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const std::tuple<EqFns...> &eq_constraints = {},
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const std::tuple<IneqFns...> &ineq_constraint = {})
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{
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return m_opt.optimize(std::forward<Func>(func), initvals, bounds,
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eq_constraints,
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ineq_constraint);
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}
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explicit Optimizer(StopCriteria stopcr = {}) : m_opt(stopcr) {}
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Optimizer &set_criteria(const StopCriteria &cr)
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{
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m_opt.set_criteria(cr); return *this;
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}
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const StopCriteria &get_criteria() const { return m_opt.get_criteria(); }
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void seed(long s) { m_opt.seed(s); }
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void set_loc_criteria(const StopCriteria &cr) { m_opt.set_loc_criteria(cr); }
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const StopCriteria &get_loc_criteria() const noexcept { return m_opt.get_loc_criteria(); }
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};
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// Predefinded NLopt algorithms
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using AlgNLoptGenetic = detail::NLoptAlgComb<NLOPT_GN_ESCH>;
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using AlgNLoptSubplex = detail::NLoptAlg<NLOPT_LN_SBPLX>;
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using AlgNLoptSimplex = detail::NLoptAlg<NLOPT_LN_NELDERMEAD>;
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using AlgNLoptCobyla = detail::NLoptAlg<NLOPT_LN_COBYLA>;
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using AlgNLoptDIRECT = detail::NLoptAlg<NLOPT_GN_DIRECT>;
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using AlgNLoptISRES = detail::NLoptAlg<NLOPT_GN_ISRES>;
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using AlgNLoptMLSL = detail::NLoptAlgComb<NLOPT_GN_MLSL, NLOPT_LN_SBPLX>;
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}} // namespace Slic3r::opt
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#endif // NLOPTOPTIMIZER_HPP
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