def test_max_sensitivity_specificity(self):
filename = '../../data/emotiv/EEG_Data_filtered.csv'
dataset = DataReader.read_data(filename, ',')
training_set, test_set = ExperimentorService.split_dataset(dataset, ratio=0.1)
artifact_size = 20
window_size = 20
threshold_max, threshold_avg, threshold_avg_max = ExperimentorService.calibrate(training_set, window_size)
artifact_test_set, artifact_list = ExperimentorService.artifactify(test_set, artifact_size, randomly_add_artifacts=True)
reconstructed_test_set_max, rejections_max = ExperimentorService.pca_reconstruction(artifact_test_set, window_size, threshold_max)
reconstructed_test_set_avg, rejections_avg = ExperimentorService.pca_reconstruction(artifact_test_set, window_size, threshold_avg)
reconstructed_test_set_avg_max, rejections_max_avg = ExperimentorService.pca_reconstruction(artifact_test_set, window_size, threshold_avg_max)
sensitivity_max, specificity_max = ExperimentorService.sensitivity_specificity(rejections_max, artifact_list)
sensitivity_avg, specificity_avg = ExperimentorService.sensitivity_specificity(rejections_avg, artifact_list)
sensitivity_avg_max, specificity_avg_max = ExperimentorService.sensitivity_specificity(rejections_max_avg, artifact_list)
print '--- MAX THRESHOLD ---'
print 'Sensitivity: ', sensitivity_max
print 'Specificity: ', specificity_max
print '--- AVG THRESHOLD ---'
print 'Sensitivity: ', sensitivity_avg
print 'Specificity: ', specificity_avg
print '--- AVG_MAX THRESHOLD ---'
print 'Sensitivity: ', sensitivity_avg_max
print 'Specificity: ', specificity_avg_max
