def setUp(self):
self.concept_class = Mock()
self.representation_class = [(0, 1, 1)]
selection_size = 5
self.performance_oracle = PerformanceOracle(self.concept_class, self.representation_class,
selection_size)
def test_performance_with_tolerance(length):
concept_class = MonotoneConjunction(length)
performance = PerformanceOracle(concept_class, 100)
performance_with_tolerance = PerformanceOracleWithTolerance(concept_class, 0)
random_func = tuple([choice([0, 1]) for _ in xrange(length)])
print performance.get_estimated_performance(random_func)
print performance_with_tolerance.get_estimated_performance(random_func)
print
def test_performance_with_tolerance(length):
concept_class = MonotoneConjunction(length)
performance = PerformanceOracle(concept_class, 100)
performance_with_tolerance = PerformanceOracleWithTolerance(
concept_class, 0)
random_func = tuple([choice([0, 1]) for _ in xrange(length)])
print performance.get_estimated_performance(random_func)
print performance_with_tolerance.get_estimated_performance(random_func)
print
class TestPerformanceOracle(unittest.TestCase):
def setUp(self):
self.concept_class = Mock()
self.representation_class = [(0, 1, 1)]
selection_size = 5
self.performance_oracle = PerformanceOracle(self.concept_class, self.representation_class,
selection_size)
def test_simple_perf(self):
self.concept_class.is_function_answering_yes_on_sample.side_effect = [True, True, False, False, True, False,
False, True, True, False]
representation = [1, 0, 0]
self.assertEqual(0.4, self.performance_oracle.get_estimated_performance(representation))
