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https://github.com/ethereum/solidity
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[yul-phaser] Mutations: Add two-point and uniform crossover operators
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@ -18,15 +18,17 @@
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#include <test/yulPhaser/TestHelpers.h>
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#include <tools/yulPhaser/Mutations.h>
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#include <tools/yulPhaser/SimulationRNG.h>
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#include <libsolutil/CommonIO.h>
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#include <boost/test/unit_test.hpp>
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#include <algorithm>
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#include <vector>
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using namespace std;
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using namespace solidity::util;
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namespace solidity::phaser::test
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{
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@ -434,6 +436,181 @@ BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_always_use_position_zero_as_spli
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BOOST_CHECK(crossover10(empty, splittable) == splittable);
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}
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BOOST_AUTO_TEST_CASE(randomTwoPointCrossover_should_swap_chromosome_parts_between_two_random_points)
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{
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function<Crossover> crossover = randomTwoPointCrossover();
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SimulationRNG::reset(1);
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Chromosome result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
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BOOST_TEST(result1 == Chromosome("aaacccaaaa"));
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SimulationRNG::reset(1);
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Chromosome result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
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BOOST_TEST(result2 == Chromosome("cccaaa"));
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}
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BOOST_AUTO_TEST_CASE(symmetricRandomTwoPointCrossover_should_swap_chromosome_parts_at_random_point)
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{
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function<SymmetricCrossover> crossover = symmetricRandomTwoPointCrossover();
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SimulationRNG::reset(1);
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tuple<Chromosome, Chromosome> result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
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tuple<Chromosome, Chromosome> expectedPair1 = {Chromosome("aaacccaaaa"), Chromosome("cccaaa")};
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BOOST_TEST(result1 == expectedPair1);
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tuple<Chromosome, Chromosome> result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
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tuple<Chromosome, Chromosome> expectedPair2 = {Chromosome("ccccca"), Chromosome("aaaaacaaaa")};
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BOOST_TEST(result2 == expectedPair2);
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}
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BOOST_AUTO_TEST_CASE(randomTwoPointCrossover_should_only_consider_points_available_on_both_chromosomes)
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{
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function<Crossover> crossover = randomTwoPointCrossover();
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for (size_t i = 0; i < 30; ++i)
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{
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Chromosome result1 = crossover(Chromosome("aaa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
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Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aaa"));
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BOOST_TEST((
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result1 == Chromosome("aaa") ||
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result1 == Chromosome("Taa") ||
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result1 == Chromosome("TTa") ||
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result1 == Chromosome("TTT") ||
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result1 == Chromosome("aTa") ||
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result1 == Chromosome("aTT") ||
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result1 == Chromosome("aaT")
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));
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BOOST_TEST((
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result2 == Chromosome("TTTTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("aTTTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("aaTTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("aaaTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("TaTTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("TaaTTTTTTTTTTTTTTTTT") ||
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result2 == Chromosome("TTaTTTTTTTTTTTTTTTTT")
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));
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}
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_randomly_selected_genes)
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{
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function<Crossover> crossover = uniformCrossover(0.7);
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SimulationRNG::reset(1);
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Chromosome result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
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BOOST_TEST(result1 == Chromosome("caaacc"));
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SimulationRNG::reset(1);
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Chromosome result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
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BOOST_TEST(result2 == Chromosome("acccaaaaaa"));
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}
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BOOST_AUTO_TEST_CASE(symmetricUniformCrossover_should_swap_randomly_selected_genes)
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{
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function<SymmetricCrossover> crossover = symmetricUniformCrossover(0.7);
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SimulationRNG::reset(1);
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tuple<Chromosome, Chromosome> result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
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tuple<Chromosome, Chromosome> expectedPair1 = {Chromosome("caaacc"), Chromosome("acccaaaaaa")};
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BOOST_TEST(result1 == expectedPair1);
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tuple<Chromosome, Chromosome> result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
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tuple<Chromosome, Chromosome> expectedPair2 = {Chromosome("caaaaaaaaa"), Chromosome("accccc")};
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BOOST_TEST(result2 == expectedPair2);
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_only_consider_points_available_on_both_chromosomes)
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{
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function<Crossover> crossover = uniformCrossover(0.7);
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set<string> expectedPatterns = {
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"TTTTTTTTTTTTTTTTTTTT",
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"aTTTTTTTTTTTTTTTTTTT",
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"TaTTTTTTTTTTTTTTTTTT",
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"TTaTTTTTTTTTTTTTTTTT",
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"aaTTTTTTTTTTTTTTTTTT",
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"TaaTTTTTTTTTTTTTTTTT",
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"aTaTTTTTTTTTTTTTTTTT",
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"aaaTTTTTTTTTTTTTTTTT",
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"aaa",
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"Taa",
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"aTa",
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"aaT",
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"TTa",
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"aTT",
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"TaT",
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"TTT",
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};
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for (size_t i = 0; i < 30; ++i)
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{
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Chromosome result1 = crossover(Chromosome("aaa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
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Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aaa"));
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BOOST_TEST(expectedPatterns.count(toString(result1)) == 1);
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BOOST_TEST(expectedPatterns.count(toString(result2)) == 1);
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}
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_not_swap_anything_if_chance_is_zero)
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{
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BOOST_TEST(uniformCrossover(0.0)(Chromosome("aaaaaaaaaa"), Chromosome("cccccc")) == Chromosome("aaaaaaaaaa"));
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BOOST_TEST(uniformCrossover(0.0)(Chromosome("cccccc"), Chromosome("aaaaaaaaaa")) == Chromosome("cccccc"));
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_whole_chromosomes_if_chance_is_one)
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{
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BOOST_TEST(uniformCrossover(1.0)(Chromosome("aaaaaaaaaa"), Chromosome("cccccc")) == Chromosome("cccccc"));
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BOOST_TEST(uniformCrossover(1.0)(Chromosome("cccccc"), Chromosome("aaaaaaaaaa")) == Chromosome("aaaaaaaaaa"));
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_genes_with_uniform_probability)
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{
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constexpr size_t operationCount = 1000;
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constexpr double swapChance = 0.8;
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constexpr double relativeTolerance = 0.05;
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double const expectedValue = swapChance;
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double const variance = swapChance * (1 - swapChance);
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function<Crossover> crossover = uniformCrossover(swapChance);
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Chromosome chromosome1("aaaaaaaaaa");
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Chromosome chromosome2("cccccccccc");
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vector<size_t> bernoulliTrials;
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for (size_t i = 0; i < operationCount; ++i)
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{
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string genes = toString(crossover(chromosome1, chromosome2));
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for (size_t j = 0; j < chromosome1.length(); ++j)
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bernoulliTrials.push_back(static_cast<size_t>(genes[j] == 'c'));
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}
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BOOST_TEST(abs(mean(bernoulliTrials) - expectedValue) < expectedValue * relativeTolerance);
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BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
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}
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BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_tail_with_uniform_probability)
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{
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constexpr size_t operationCount = 1000;
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constexpr double swapChance = 0.3;
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constexpr double relativeTolerance = 0.05;
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double const expectedValue = swapChance;
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double const variance = swapChance * (1 - swapChance);
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function<Crossover> crossover = uniformCrossover(swapChance);
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Chromosome chromosome1("aaaaa");
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Chromosome chromosome2("cccccccccc");
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vector<size_t> bernoulliTrials;
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for (size_t i = 0; i < operationCount; ++i)
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{
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string genes = toString(crossover(chromosome1, chromosome2));
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BOOST_REQUIRE(genes.size() == 5 || genes.size() == 10);
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bernoulliTrials.push_back(static_cast<size_t>(genes.size() == 10));
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}
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BOOST_TEST(abs(mean(bernoulliTrials) - expectedValue) < expectedValue * relativeTolerance);
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BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
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}
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BOOST_AUTO_TEST_SUITE_END()
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BOOST_AUTO_TEST_SUITE_END()
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BOOST_AUTO_TEST_SUITE_END()
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@ -180,3 +180,138 @@ function<Crossover> phaser::fixedPointCrossover(double _crossoverPoint)
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return get<0>(fixedPointSwap(_chromosome1, _chromosome2, concretePoint));
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};
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}
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namespace
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{
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ChromosomePair fixedTwoPointSwap(
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Chromosome const& _chromosome1,
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Chromosome const& _chromosome2,
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size_t _crossoverPoint1,
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size_t _crossoverPoint2
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)
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{
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assert(_crossoverPoint1 <= _chromosome1.length());
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assert(_crossoverPoint1 <= _chromosome2.length());
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assert(_crossoverPoint2 <= _chromosome1.length());
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assert(_crossoverPoint2 <= _chromosome2.length());
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size_t lowPoint = min(_crossoverPoint1, _crossoverPoint2);
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size_t highPoint = max(_crossoverPoint1, _crossoverPoint2);
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auto begin1 = _chromosome1.optimisationSteps().begin();
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auto begin2 = _chromosome2.optimisationSteps().begin();
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auto end1 = _chromosome1.optimisationSteps().end();
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auto end2 = _chromosome2.optimisationSteps().end();
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return {
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Chromosome(
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vector<string>(begin1, begin1 + lowPoint) +
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vector<string>(begin2 + lowPoint, begin2 + highPoint) +
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vector<string>(begin1 + highPoint, end1)
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),
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Chromosome(
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vector<string>(begin2, begin2 + lowPoint) +
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vector<string>(begin1 + lowPoint, begin1 + highPoint) +
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vector<string>(begin2 + highPoint, end2)
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),
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};
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}
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}
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function<Crossover> phaser::randomTwoPointCrossover()
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{
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return [=](Chromosome const& _chromosome1, Chromosome const& _chromosome2)
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{
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size_t minLength = min(_chromosome1.length(), _chromosome2.length());
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// Don't use position 0 (because this just swaps the values) unless it's the only choice.
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size_t minPoint = (minLength > 0 ? 1 : 0);
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assert(minPoint <= minLength);
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size_t randomPoint1 = SimulationRNG::uniformInt(minPoint, minLength);
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size_t randomPoint2 = SimulationRNG::uniformInt(randomPoint1, minLength);
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return get<0>(fixedTwoPointSwap(_chromosome1, _chromosome2, randomPoint1, randomPoint2));
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};
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}
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function<SymmetricCrossover> phaser::symmetricRandomTwoPointCrossover()
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{
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return [=](Chromosome const& _chromosome1, Chromosome const& _chromosome2)
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{
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size_t minLength = min(_chromosome1.length(), _chromosome2.length());
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// Don't use position 0 (because this just swaps the values) unless it's the only choice.
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size_t minPoint = (minLength > 0 ? 1 : 0);
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assert(minPoint <= minLength);
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size_t randomPoint1 = SimulationRNG::uniformInt(minPoint, minLength);
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size_t randomPoint2 = SimulationRNG::uniformInt(randomPoint1, minLength);
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return fixedTwoPointSwap(_chromosome1, _chromosome2, randomPoint1, randomPoint2);
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};
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}
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namespace
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{
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ChromosomePair uniformSwap(Chromosome const& _chromosome1, Chromosome const& _chromosome2, double _swapChance)
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{
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vector<string> steps1;
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vector<string> steps2;
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size_t minLength = min(_chromosome1.length(), _chromosome2.length());
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for (size_t i = 0; i < minLength; ++i)
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if (SimulationRNG::bernoulliTrial(_swapChance))
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{
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steps1.push_back(_chromosome2.optimisationSteps()[i]);
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steps2.push_back(_chromosome1.optimisationSteps()[i]);
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}
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else
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{
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steps1.push_back(_chromosome1.optimisationSteps()[i]);
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steps2.push_back(_chromosome2.optimisationSteps()[i]);
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}
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auto begin1 = _chromosome1.optimisationSteps().begin();
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auto begin2 = _chromosome2.optimisationSteps().begin();
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auto end1 = _chromosome1.optimisationSteps().end();
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auto end2 = _chromosome2.optimisationSteps().end();
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bool swapTail = SimulationRNG::bernoulliTrial(_swapChance);
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if (_chromosome1.length() > minLength)
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{
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if (swapTail)
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steps2.insert(steps2.end(), begin1 + minLength, end1);
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else
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steps1.insert(steps1.end(), begin1 + minLength, end1);
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}
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if (_chromosome2.length() > minLength)
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{
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if (swapTail)
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steps1.insert(steps1.end(), begin2 + minLength, end2);
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else
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steps2.insert(steps2.end(), begin2 + minLength, end2);
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}
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return {Chromosome(steps1), Chromosome(steps2)};
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}
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}
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function<Crossover> phaser::uniformCrossover(double _swapChance)
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{
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return [=](Chromosome const& _chromosome1, Chromosome const& _chromosome2)
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{
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return get<0>(uniformSwap(_chromosome1, _chromosome2, _swapChance));
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};
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}
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function<SymmetricCrossover> phaser::symmetricUniformCrossover(double _swapChance)
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{
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return [=](Chromosome const& _chromosome1, Chromosome const& _chromosome2)
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{
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return uniformSwap(_chromosome1, _chromosome2, _swapChance);
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};
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}
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@ -80,4 +80,22 @@ std::function<SymmetricCrossover> symmetricRandomPointCrossover();
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/// unless there is no other choice (i.e. one of the chromosomes is empty).
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std::function<Crossover> fixedPointCrossover(double _crossoverPoint);
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/// Creates a crossover operator that randomly selects two points between 0 and 1 and swaps genes
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/// from the resulting interval. The interval may be empty in which case no genes are swapped.
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std::function<Crossover> randomTwoPointCrossover();
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/// Symmetric version of @a randomTwoPointCrossover(). Creates an operator that returns a pair
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/// containing both possible results for the same crossover points.
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std::function<SymmetricCrossover> symmetricRandomTwoPointCrossover();
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/// Creates a crossover operator that goes over the length of the shorter chromosomes and for
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/// each gene independently decides whether to swap it or not (with probability given by
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/// @a _swapChance). The tail of the longer chromosome (the part that's past the length of the
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/// shorter one) is treated as a single gene and can potentially be swapped too.
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std::function<Crossover> uniformCrossover(double _swapChance);
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/// Symmetric version of @a uniformCrossover(). Creates an operator that returns a pair
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/// containing both possible results for the same set or swap decisions.
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std::function<SymmetricCrossover> symmetricUniformCrossover(double _swapChance);
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}
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