def test_check_peak(self):
data = [0, 1, 2, 1, 0]
self.assertTrue(check_peak(data)) # TODO: Change these to datapoints
data = [0, 1, 0, 1, 0]
self.assertFalse(check_peak(data)) # TODO: Change these to datapoints
data = [0, 1, 2, 3, 4, 3, 2, 1]
self.assertTrue(check_peak(data)) # TODO: Change these to datapoints
data = [0, 1]
self.assertFalse(check_peak(data)) # TODO: Change these to datapoints
def test_check_peak(self):
data = [0, 1, 2, 1, 0]
self.assertTrue(check_peak(data))
data = [0, 1, 0, 1, 0]
self.assertFalse(check_peak(data))
data = [0, 1, 2, 3, 4, 3, 2, 1]
self.assertTrue(check_peak(data))
data = [0, 1]
self.assertRaises(Exception, check_peak, data)
def test_detect_rpeak(self, threshold: float = .5): sample = np.array([i.sample for i in self.ecg]) blackman_win_len = np.ceil(self._fs / 5) y = compute_moving_window_int(sample, self._fs, blackman_win_len) peak_location_values = [(i, y[i]) for i in range(2, len(y) - 1) if check_peak(y[i - 2:i + 3])] peak_location = [i[0] for i in peak_location_values] running_rr_avg = sum(np.diff(peak_location)) / (len(peak_location) - 1) rpeak_temp1 = compute_r_peaks(threshold, running_rr_avg, y, peak_location_values) first_index_file = os.path.join(os.path.dirname(__file__), 'res/testmatlab_firstindex.csv') peak_index1_from_data = np.genfromtxt(first_index_file, delimiter=',') test_result = (len(list(set(rpeak_temp1) & set(peak_index1_from_data - 1))) * 100) / len(rpeak_temp1) self.assertGreaterEqual(test_result, 99, 'Peaks after adaptive threshold is less than a 99 percent match') rpeak_temp2 = remove_close_peaks(rpeak_temp1, sample, self._fs) second_index_file = os.path.join(os.path.dirname(__file__), 'res/testmatlab_secondindex.csv') peak_index2_from_data = np.genfromtxt(second_index_file, delimiter=',') test_result = (len(list(set(rpeak_temp2) & set(peak_index2_from_data - 1))) * 100) / len(rpeak_temp2) self.assertGreaterEqual(test_result, 99, 'Peaks after removing close peaks is less than a 99 percent match') index = confirm_peaks(rpeak_temp2, sample, self._fs) final_index_file = os.path.join(os.path.dirname(__file__), 'res/testmatlab_finalindex.csv') peak_index3_from_data = np.genfromtxt(final_index_file, delimiter=',') test_result = (len(list(set(index) & set(peak_index3_from_data - 1))) * 100) / len(index) self.assertGreaterEqual(test_result, 99, 'Peaks after confirmation is less than a 99 percent match')