def test_averages(self):
sleep_wake_performance_1 = SleepWakePerformance(
accuracy=0,
wake_correct=0.1,
sleep_correct=0.2,
auc=0.3,
kappa=0.4,
wake_predictive_value=0.5,
sleep_predictive_value=0.6)
sleep_wake_performance_2 = SleepWakePerformance(
accuracy=0.2,
wake_correct=0.3,
sleep_correct=0.4,
auc=0.5,
kappa=0.6,
wake_predictive_value=0.7,
sleep_predictive_value=0.8)
expected_performance = SleepWakePerformance(accuracy=0.1,
wake_correct=0.2,
sleep_correct=0.3,
auc=0.4,
kappa=0.5,
wake_predictive_value=0.6,
sleep_predictive_value=0.7)
performance_list = [sleep_wake_performance_1, sleep_wake_performance_2]
actual_averaged_performance = PerformanceSummarizer.average(
performance_list)
TestHelper.assert_models_equal(self, expected_performance,
actual_averaged_performance)
def test_leave_one_out(self):
subject_ids = ["subjectA", "subjectB", "subjectC"]
results = TrainTestSplitter.leave_one_out(subject_ids)
TestHelper.assert_models_equal(
self,
DataSplit(training_set=["subjectB", "subjectC"],
testing_set=["subjectA"]), results[0])
TestHelper.assert_models_equal(
self,
DataSplit(training_set=["subjectA", "subjectC"],
testing_set=["subjectB"]), results[1])
TestHelper.assert_models_equal(
self,
DataSplit(training_set=["subjectA", "subjectB"],
testing_set=["subjectC"]), results[2])
