[yul-phaser] Temporarily disable very slow tests for the classic algorithm

This commit is contained in:
Kamil Śliwak 2020-07-07 16:47:31 +02:00
parent c16d7d0891
commit b23f7d8790

View File

@ -212,7 +212,8 @@ BOOST_FIXTURE_TEST_CASE(runNextRound_should_generate_individuals_in_the_crossove
BOOST_AUTO_TEST_SUITE_END() BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE(ClassicGeneticAlgorithmTest) BOOST_AUTO_TEST_SUITE(ClassicGeneticAlgorithmTest)
BOOST_FIXTURE_TEST_CASE(runNextRound_should_select_individuals_with_probability_proportional_to_fitness, ClassicGeneticAlgorithmFixture) // FIXME: This test runs *very* slowly (tens of seconds). Investigate, fix and re-enable.
BOOST_FIXTURE_TEST_CASE(runNextRound_should_select_individuals_with_probability_proportional_to_fitness, ClassicGeneticAlgorithmFixture, *boost::unit_test::disabled())
{ {
constexpr double relativeTolerance = 0.1; constexpr double relativeTolerance = 0.1;
constexpr size_t populationSize = 1000; constexpr size_t populationSize = 1000;
@ -253,7 +254,8 @@ BOOST_FIXTURE_TEST_CASE(runNextRound_should_select_individuals_with_probability_
BOOST_TEST(abs(meanSquaredError(newFitness, expectedValue) - variance) < variance * relativeTolerance); BOOST_TEST(abs(meanSquaredError(newFitness, expectedValue) - variance) < variance * relativeTolerance);
} }
BOOST_FIXTURE_TEST_CASE(runNextRound_should_select_only_individuals_existing_in_the_original_population, ClassicGeneticAlgorithmFixture) // FIXME: This test runs *very* slowly (tens of seconds). Investigate, fix and re-enable.
BOOST_FIXTURE_TEST_CASE(runNextRound_should_select_only_individuals_existing_in_the_original_population, ClassicGeneticAlgorithmFixture, *boost::unit_test::disabled())
{ {
constexpr size_t populationSize = 1000; constexpr size_t populationSize = 1000;
auto population = Population::makeRandom(m_fitnessMetric, populationSize, 1, 10); auto population = Population::makeRandom(m_fitnessMetric, populationSize, 1, 10);
@ -297,7 +299,8 @@ BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_crossover, ClassicGeneticAlgorith
BOOST_TEST(totalCrossed >= 2); BOOST_TEST(totalCrossed >= 2);
} }
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_mutation, ClassicGeneticAlgorithmFixture) // FIXME: This test runs *very* slowly (tens of seconds). Investigate, fix and re-enable.
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_mutation, ClassicGeneticAlgorithmFixture, *boost::unit_test::disabled())
{ {
m_options.mutationChance = 0.6; m_options.mutationChance = 0.6;
ClassicGeneticAlgorithm algorithm(m_options); ClassicGeneticAlgorithm algorithm(m_options);
@ -326,7 +329,8 @@ BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_mutation, ClassicGeneticAlgorithm
BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance); BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
} }
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_deletion, ClassicGeneticAlgorithmFixture) // FIXME: This test runs *very* slowly (tens of seconds). Investigate, fix and re-enable.
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_deletion, ClassicGeneticAlgorithmFixture, *boost::unit_test::disabled())
{ {
m_options.deletionChance = 0.6; m_options.deletionChance = 0.6;
ClassicGeneticAlgorithm algorithm(m_options); ClassicGeneticAlgorithm algorithm(m_options);
@ -355,7 +359,8 @@ BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_deletion, ClassicGeneticAlgorithm
BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance); BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
} }
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_addition, ClassicGeneticAlgorithmFixture) // FIXME: This test runs *very* slowly (tens of seconds). Investigate, fix and re-enable.
BOOST_FIXTURE_TEST_CASE(runNextRound_should_do_addition, ClassicGeneticAlgorithmFixture, *boost::unit_test::disabled())
{ {
m_options.additionChance = 0.6; m_options.additionChance = 0.6;
ClassicGeneticAlgorithm algorithm(m_options); ClassicGeneticAlgorithm algorithm(m_options);