cerc-io/solidity
11
0
Fork 0
mirror of https://github.com/ethereum/solidity synced 2023-10-03 13:03:40 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

[yul-phaser] Population+Chromosome: Better tests for makeRandom()

Browse Source
This commit is contained in:
Kamil Śliwak
2020-02-18 19:40:37 +01:00
parent 806891f494
commit 823e715902
2 changed files with 36 additions and 27 deletions
Download Patch File Download Diff File Expand all files Collapse all files
test/yulPhaser/Population.cpp
+15 -12
View File
@@ -159,21 +159,24 @@ BOOST_FIXTURE_TEST_CASE(makeRandom_should_use_random_chromosome_length, Populati
BOOST_FIXTURE_TEST_CASE(makeRandom_should_return_population_with_random_chromosomes, PopulationFixture)
{
auto population1 = Population::makeRandom(m_program, 100, 30, 30);
auto population2 = Population::makeRandom(m_program, 100, 30, 30);
SimulationRNG::reset(1);
constexpr int populationSize = 100;
constexpr int chromosomeLength = 30;
constexpr double relativeTolerance = 0.01;
BOOST_TEST(population1.individuals().size() == 100);
BOOST_TEST(population2.individuals().size() == 100);
map<string, size_t> stepIndices = enumerateOptmisationSteps();
auto population = Population::makeRandom(m_program, populationSize, chromosomeLength, chromosomeLength);
int numMatchingPositions = 0;
for (size_t i = 0; i < 100; ++i)
if (population1.individuals()[i].chromosome == population2.individuals()[i].chromosome)
++numMatchingPositions;
vector<size_t> samples;
for (auto& individual: population.individuals())
for (auto& step: individual.chromosome.optimisationSteps())
samples.push_back(stepIndices.at(step));
// Assume that the results are random if there are no more than 10 identical chromosomes on the
// same positions. One duplicate is very unlikely but still possible after billions of runs
// (especially for short chromosomes). For ten the probability is so small that we can ignore it.
BOOST_TEST(numMatchingPositions < 10);
const double expectedValue = (stepIndices.size() - 1) / 2.0;
const double variance = (stepIndices.size() * stepIndices.size() - 1) / 12.0;
BOOST_TEST(abs(mean(samples) - expectedValue) < expectedValue * relativeTolerance);
BOOST_TEST(abs(meanSquaredError(samples, expectedValue) - variance) < variance * relativeTolerance);
}
BOOST_FIXTURE_TEST_CASE(makeRandom_should_not_compute_fitness, PopulationFixture)