mirror of
https://github.com/ethereum/solidity
synced 2023-10-03 13:03:40 +00:00
318 lines
9.2 KiB
C++
318 lines
9.2 KiB
C++
/*
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This file is part of solidity.
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solidity is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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solidity is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with solidity. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <tools/yulPhaser/Mutations.h>
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#include <tools/yulPhaser/SimulationRNG.h>
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#include <libsolutil/CommonData.h>
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#include <algorithm>
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#include <cassert>
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#include <cmath>
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#include <string>
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#include <vector>
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using namespace std;
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using namespace solidity;
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using namespace solidity::phaser;
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function<Mutation> phaser::geneRandomisation(double _chance)
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{
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return [=](Chromosome const& _chromosome)
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{
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vector<string> optimisationSteps;
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for (auto const& step: _chromosome.optimisationSteps())
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optimisationSteps.push_back(
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SimulationRNG::bernoulliTrial(_chance) ?
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Chromosome::randomOptimisationStep() :
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step
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);
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return Chromosome(move(optimisationSteps));
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};
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}
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function<Mutation> phaser::geneDeletion(double _chance)
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{
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return [=](Chromosome const& _chromosome)
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{
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vector<string> optimisationSteps;
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for (auto const& step: _chromosome.optimisationSteps())
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if (!SimulationRNG::bernoulliTrial(_chance))
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optimisationSteps.push_back(step);
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return Chromosome(move(optimisationSteps));
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};
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}
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function<Mutation> phaser::geneAddition(double _chance)
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{
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return [=](Chromosome const& _chromosome)
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{
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vector<string> optimisationSteps;
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if (SimulationRNG::bernoulliTrial(_chance))
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optimisationSteps.push_back(Chromosome::randomOptimisationStep());
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for (auto const& step: _chromosome.optimisationSteps())
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{
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optimisationSteps.push_back(step);
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if (SimulationRNG::bernoulliTrial(_chance))
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optimisationSteps.push_back(Chromosome::randomOptimisationStep());
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}
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return Chromosome(move(optimisationSteps));
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};
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}
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function<Mutation> phaser::alternativeMutations(
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double _firstMutationChance,
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function<Mutation> _mutation1,
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function<Mutation> _mutation2
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)
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{
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return [=](Chromosome const& _chromosome)
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{
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if (SimulationRNG::bernoulliTrial(_firstMutationChance))
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return _mutation1(_chromosome);
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else
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return _mutation2(_chromosome);
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};
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}
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function<Mutation> phaser::mutationSequence(vector<function<Mutation>> _mutations)
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{
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return [=](Chromosome const& _chromosome)
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{
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Chromosome mutatedChromosome = _chromosome;
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for (size_t i = 0; i < _mutations.size(); ++i)
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mutatedChromosome = _mutations[i](move(mutatedChromosome));
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return mutatedChromosome;
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};
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}
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namespace
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{
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ChromosomePair fixedPointSwap(
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Chromosome const& _chromosome1,
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Chromosome const& _chromosome2,
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size_t _crossoverPoint
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)
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{
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assert(_crossoverPoint <= _chromosome1.length());
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assert(_crossoverPoint <= _chromosome2.length());
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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 + static_cast<ptrdiff_t>(_crossoverPoint)) +
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vector<string>(begin2 + static_cast<ptrdiff_t>(_crossoverPoint), end2)
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),
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Chromosome(
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vector<string>(begin2, begin2 + static_cast<ptrdiff_t>(_crossoverPoint)) +
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vector<string>(begin1 + static_cast<ptrdiff_t>(_crossoverPoint), end1)
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),
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};
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}
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}
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function<Crossover> phaser::randomPointCrossover()
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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 randomPoint = SimulationRNG::uniformInt(minPoint, minLength);
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return get<0>(fixedPointSwap(_chromosome1, _chromosome2, randomPoint));
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};
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}
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function<SymmetricCrossover> phaser::symmetricRandomPointCrossover()
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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 randomPoint = SimulationRNG::uniformInt(minPoint, minLength);
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return fixedPointSwap(_chromosome1, _chromosome2, randomPoint);
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};
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}
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function<Crossover> phaser::fixedPointCrossover(double _crossoverPoint)
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{
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assert(0.0 <= _crossoverPoint && _crossoverPoint <= 1.0);
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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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size_t concretePoint = static_cast<size_t>(round(minLength * _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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auto lowPoint = static_cast<ptrdiff_t>(min(_crossoverPoint1, _crossoverPoint2));
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auto highPoint = static_cast<ptrdiff_t>(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 + static_cast<ptrdiff_t>(minLength), end1);
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else
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steps1.insert(steps1.end(), begin1 + static_cast<ptrdiff_t>(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 + static_cast<ptrdiff_t>(minLength), end2);
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else
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steps2.insert(steps2.end(), begin2 + static_cast<ptrdiff_t>(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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