"""test_adjusters.py -- test pipeline Adjusters (eg TargetTimeAdjuster)""" import unittest import unittest.mock as mock import pipeline.adjusters as adjusters from test.mocks import MockFeature, MockInterval class TestAdjuster(unittest.TestCase): """Test the generic Adjuster class""" def test_init(self): """Test the Adjuster can be initialised""" adjuster = adjusters.Adjuster() self.assertEqual(adjuster.features, []) def test_adjust(self): """Test the generic adjust""" adjuster = adjusters.Adjuster() self.assertEqual(adjuster.adjust(), []) self.assertEqual(adjuster.features, []) class TestTargetTimeAdjuster(unittest.TestCase): """Test the TargetTimeAdjuster TTA drops Features until the target time is reached (or within a margin)""" def test_init(self): """Test the TTA can be initialised""" tta = adjusters.TargetTimeAdjuster() self.assertEqual(tta.features, []) def test_features_total_time(self): """Test the TTA can calculate the total time of Features Test: - input duration floats: 1.0, 2.0, 3.0, 4.0 == 10.0 """ tta = adjusters.TargetTimeAdjuster() features = [] for i in range(1, 5): features.append(make_feature(duration=i*1.0)) self.assertEqual(tta._features_total_time(features), 10.0) self.assertEqual(tta._features_total_time([]), 0.0) self.assertIs(type(tta._features_total_time([])), float) def test_determine_margin(self): """Test the TTA can determine the target time margins Args: time, margin, strategy (strategy in: ABSOLUTE, PERCENT) Test: - margin of zero - margin of 5.0 - margin of 10.0 - margin of 100.0 - both ABSOLUTE and PERCENT strategies TODO: figure out what should be done with negative margins & margins > 100.0 """ tta = adjusters.TargetTimeAdjuster() with self.subTest("ABSOLUTE"): strategy = adjusters.TargetTimeAdjuster._STRATEGY.ABSOLUTE test_cases = [] # populate test cases with tuples of (time, margin, expected) # zero margin test_cases.append((60.0, 0.0, (60.0, 60.0))) # margin of 5.0 test_cases.append((60.0, 5.0, (55.0, 65.0))) # margin of 10.0 test_cases.append((60.0, 10.0, (50.0, 70.0))) # margin of 100.0 test_cases.append((60.0, 100.0, (0.0, 160.0))) # test for time, margin, expected in test_cases: self.assertEqual(tta._determine_margin(time, margin, strategy), expected) with self.subTest("PERCENT"): strategy = adjusters.TargetTimeAdjuster._STRATEGY.PERCENT test_cases = [] # populate test cases with tuples of (time, margin, expected) as above # zero margin test_cases.append((60.0, 0.0, (60.0, 60.0))) # margin of 5.0 test_cases.append((60.0, 5.0, (57.0, 63.0))) # margin of 10.0 test_cases.append((60.0, 10.0, (54.0, 66.0))) # margin of 100.0 test_cases.append((60.0, 100.0, (0.0, 120.0))) # test for time, margin, expected in test_cases: self.assertEqual(tta._determine_margin(time, margin, strategy), expected) def test_adjust_no_change(self): """Test adjusting of list of Features using TTA -- no change to list of Features Cases: - no Features --> [] - [Features] with total time < target time --> unchanged list - [Features] with total time = target time --> unchanged list TODO: test with Features > target """ with self.subTest("no Features"): tta = adjusters.TargetTimeAdjuster() self.assertEqual(tta.adjust(), []) with self.subTest("Features < target time"): features = [] for i in range(1, 5): features.append(make_feature(duration=i*1.0)) tta = adjusters.TargetTimeAdjuster(features=features, target_time=20.0) self.assertEqual(tta.adjust(), features) with self.subTest("Features = target time"): features = [] for i in range(1, 5): features.append(make_feature(duration=i*1.0)) tta = adjusters.TargetTimeAdjuster(features=features, target_time=10.0) self.assertEqual(tta.adjust(), features) def test_sort_by_score_time(self): """Test sorting of list of Features by score (primary) and time (secondary) Cases: - [(15.0, 1.0), (10.0, 1.0), (12.0, 1.0)] --> [(10.0, 1.0), (12.0, 1.0), (15.0, 1.0)] # score equal, sort by time - [(15.0, 1.0), (10.0, 4.0), (12.0, 3.0)] --> [(15.0, 1.0), (12.0, 3.0), (10.0, 4.0)] # sort by score - [(15.0, 1.0), (10.0, 1.0), (12.0, 2.0)] --> [(10.0, 1.0), (15.0, 1.0), (12.0, 2.0)] # mixed: scores below duration - [] --> [] - [(15.0, 1.0)] --> [(15.0, 1.0)] Cases giving RDH trouble: - [(16.0, 1.0), (16.0, 1.0), (1.0, 1.0), (1.0, 1.0)] --> [(1.0, 1.0), (1.0, 1.0), (16.0, 1.0), (16.0, 1.0)] # multiple lowest scoring, multiple shortest duration """ tta = adjusters.TargetTimeAdjuster() with self.subTest("score equal, sort by duration"): features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=1.0), make_feature(duration=12.0, score=1.0) ] self.assertEqual(tta._sort_by_score_time(features), [features[1], features[2], features[0]]) with self.subTest("sort by score, duration irrelevant"): features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=4.0), make_feature(duration=12.0, score=3.0) ] self.assertEqual(tta._sort_by_score_time(features), [features[0], features[2], features[1]]) with self.subTest("mixed: scores below duration"): features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=1.0), make_feature(duration=12.0, score=2.0) ] self.assertEqual(tta._sort_by_score_time(features), [features[1], features[0], features[2]]) with self.subTest("empty"): self.assertEqual(tta._sort_by_score_time([]), []) with self.subTest("single"): features = [mock.Mock(duration=15.0, score=1.0)] self.assertEqual(tta._sort_by_score_time(features), features) with self.subTest("multiple lowest scoring, multiple shortest duration"): features = [ make_feature(duration=16.0, score=1.0), make_feature(duration=16.0, score=1.0), make_feature(duration=1.0, score=1.0), make_feature(duration=1.0, score=1.0) ] self.assertEqual(tta._sort_by_score_time(features), [features[2], features[3], features[0], features[1]]) def test_adjust_changes(self): """Test adjusting of list of Features using TTA -- changes to list of Features All cases have total time > target time. In the cases, specification is Feature(duration, score) Cases: - target = 30.0, margin = 0.0 + [(15.0, 1.0), (10.0, 1.0), (12.0, 1.0)] --> [(15.0, 1.0), (12.0, 1.0)] # scores equal, drop smallest + [(15.0, 2.0), (10.0, 2.0), (12.0, 1.0)] --> [(15.0, 1.0), (10.0, 1.0)] # drop lowest scoring (1) + [(15.0, 1.0), (10.0, 1.0), (12.0, 2.0)] --> [(15.0, 1.0), (12.0, 2.0)] # drop lowest scoring (2) - target = 30.0, margin = 4.0 + [(15.0, 1.0), (10.0, 2.0), (12.0, 1.0)] --> [(15.0, 1.0), (12.0, 1.0)] # not lowest scoring, but within margin + [(16.0, 1.0), (16.0, 1.0), (1.0, 1.0), (1.0, 1.0)] --> [(16.0, 1.0), (16.0, 1.0)] # drop multiple lowest scoring, shortest duration """ # target 30.0, margin 0.0 cases target, margin = 30.0, 0.0 with self.subTest(f"target {target} margin {margin}"): with self.subTest("scores equal"): features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=1.0), make_feature(duration=12.0, score=1.0) ] tta = adjusters.TargetTimeAdjuster(features=features, target_time=target, margin=margin) expected = [features[0], features[2]] output = tta.adjust() self.assertEqual(len(output), 2) self.assertEqual(output, expected) self.assertEqual(tta.features, expected) with self.subTest("drop lowest scoring (1)"): features = [ make_feature(duration=15.0, score=2.0), make_feature(duration=10.0, score=2.0), make_feature(duration=12.0, score=1.0) ] tta = adjusters.TargetTimeAdjuster(features=features, target_time=target, margin=margin) expected = [features[0], features[1]] output = tta.adjust() self.assertEqual(len(output), 2) self.assertEqual(output, expected) self.assertEqual(tta.features, expected) with self.subTest("drop lowest scoring (2)"): features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=1.0), make_feature(duration=12.0, score=2.0) ] tta = adjusters.TargetTimeAdjuster(features=features, target_time=target, margin=margin) expected = [features[0], features[2]] output = tta.adjust() self.assertEqual(len(output), 2) self.assertEqual(output, expected) self.assertEqual(tta.features, expected) # target 30.0, margin 4.0 cases target, margin, strategy = 30.0, 4.0, adjusters.TargetTimeAdjuster._STRATEGY.ABSOLUTE with self.subTest(f"target {target} margin {margin}"): with self.subTest("not lowest scoring, but within margin"): # explanation: dropping the 10.0 feature would put us at 27.0, which is within the margin (26.0, 34.0) features = [ make_feature(duration=15.0, score=1.0), make_feature(duration=10.0, score=2.0), make_feature(duration=12.0, score=1.0) ] tta = adjusters.TargetTimeAdjuster(features=features, target_time=target, margin=margin, strategy=strategy) expected = [features[0], features[2]] output = tta.adjust() self.assertEqual(len(output), 2) self.assertEqual(output, expected) self.assertEqual(tta.features, expected) with self.subTest("drop multiple lowest scoring, shortest duration"): # explanation: dropping the 1.0 features would put us at 32.0, which is within the margin (26.0, 34.0) features = [ make_feature(duration=16.0, score=1.0), make_feature(duration=16.0, score=1.0), make_feature(duration=1.0, score=1.0), make_feature(duration=1.0, score=1.0), make_feature(duration=1.0, score=1.0), make_feature(duration=1.0, score=1.0) ] tta = adjusters.TargetTimeAdjuster(features=features, target_time=target, margin=margin, strategy=strategy) expected = [features[0], features[1], features[2], features[3]] output = tta.adjust() self.assertEqual(len(output), 4) self.assertEqual(output, expected) self.assertEqual(tta.features, expected) def make_feature(duration, score=1.0): """Helper function to create a MockFeature from duration and score""" return MockFeature(interval=MockInterval.from_duration(duration), score=score)