/* * * Copyright (C) 2025 Brett Terpstra * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include #include "../examples/symbolic_regression.h" #include #include #include #include #include #include using namespace blt::gp; struct context { float x, y; }; prog_config_t config = prog_config_t() .set_initial_min_tree_size(2) .set_initial_max_tree_size(6) .set_elite_count(2) .set_crossover_chance(0.8) .set_mutation_chance(0.1) .set_reproduction_chance(0.1) .set_max_generations(50) .set_pop_size(500) .set_thread_count(0); example::symbolic_regression_t regression{691ul, config}; operation_t addf{[](const float a, const float b) { return a + b; }, "addf"}; operation_t subf([](const float a, const float b) { return a - b; }, "subf"); operation_t mulf([](const float a, const float b) { return a * b; }, "mulf"); operation_t pro_divf([](const float a, const float b) { return b == 0.0f ? 0.0f : a / b; }, "divf"); operation_t op_sinf([](const float a) { return std::sin(a); }, "sinf"); operation_t op_cosf([](const float a) { return std::cos(a); }, "cosf"); operation_t op_expf([](const float a) { return std::exp(a); }, "expf"); operation_t op_logf([](const float a) { return a <= 0.0f ? 0.0f : std::log(a); }, "logf"); auto litf = operation_t([]() { return regression.get_program().get_random().get_float(-1.0f, 1.0f); }, "litf").set_ephemeral(); operation_t op_xf([](const context& context) { return context.x; }, "xf"); bool fitness_function(const tree_t& current_tree, fitness_t& fitness, size_t) { constexpr static double value_cutoff = 1.e15; for (auto& fitness_case : regression.get_training_cases()) { BLT_GP_UPDATE_CONTEXT(fitness_case); auto val = current_tree.get_evaluation_ref(fitness_case); const auto diff = std::abs(fitness_case.y - val.get()); if (diff < value_cutoff) { fitness.raw_fitness += diff; if (diff <= 0.01) fitness.hits++; } else fitness.raw_fitness += value_cutoff; } fitness.standardized_fitness = fitness.raw_fitness; fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness)); return static_cast(fitness.hits) == regression.get_training_cases().size(); } int main() { operator_builder builder{}; const auto& operators = builder.build(addf, subf, mulf, pro_divf, op_sinf, op_cosf, op_expf, op_logf, litf, op_xf); regression.get_program().set_operations(operators); auto& program = regression.get_program(); static auto sel = select_tournament_t{}; gp_program test_program{691}; test_program.set_operations(operators); test_program.setup_generational_evaluation(fitness_function, sel, sel, sel, false); // simulate a program which is similar but incompatible with the other programs. operator_builder builder2{}; gp_program bad_program{691}; bad_program.set_operations(builder2.build(addf, subf, mulf, op_sinf, op_cosf, litf, op_xf)); bad_program.setup_generational_evaluation(fitness_function, sel, sel, sel, false); program.generate_initial_population(program.get_typesystem().get_type().id()); program.setup_generational_evaluation(fitness_function, sel, sel, sel); while (!program.should_terminate()) { BLT_TRACE("---------------\\{Begin Generation {}}---------------", program.get_current_generation()); BLT_TRACE("Creating next generation"); program.create_next_generation(); BLT_TRACE("Move to next generation"); program.next_generation(); BLT_TRACE("Evaluate Fitness"); program.evaluate_fitness(); { std::ofstream stream{"serialization_test.data", std::ios::binary | std::ios::trunc}; blt::fs::fstream_writer_t writer{stream}; program.save_generation(writer); } { std::ifstream stream{"serialization_test.data", std::ios::binary}; blt::fs::fstream_reader_t reader{stream}; test_program.load_generation(reader); } // do a quick validation check for (const auto& [saved, loaded] : blt::zip(program.get_current_pop(), test_program.get_current_pop())) { if (saved.tree != loaded.tree) { BLT_ERROR("Serializer Failed to correctly serialize tree to disk, trees are not equal!"); std::exit(1); } } } { std::ofstream stream{"serialization_test2.data", std::ios::binary | std::ios::trunc}; blt::fs::fstream_writer_t writer{stream}; program.save_state(writer); } { std::ifstream stream{"serialization_test2.data", std::ios::binary}; blt::fs::fstream_reader_t reader{stream}; test_program.load_state(reader); for (const auto [saved, loaded] : blt::zip(program.get_stats_histories(), test_program.get_stats_histories())) { if (saved != loaded) { BLT_ERROR("Serializer Failed to correctly serialize histories to disk, histories are not equal!"); std::exit(1); } } } std::ifstream stream{"serialization_test2.data", std::ios::binary}; blt::fs::fstream_reader_t reader{stream}; if (auto err = bad_program.load_state(reader)) { BLT_ERROR(blt::gp::errors::serialization::to_string(*err)); BLT_ASSERT(false && "Expected program to throw an exception when parsing state data into an incompatible program!"); } }