class TrainUtils:
def __init__(self) -> None:
super().__init__()
self.dataUtils = DataUtils()
def prepareData(self, delay=5):
ecgAll, fecg = self.dataUtils.readData(0)
ecgAll = ecgAll[range(1), :]
delayNum = ecgAll.shape[0]
fecgAll = self.dataUtils.createDelayRepetition(fecg, delayNum, delay)
for i in range(1, 2):
ecg, fecg = self.dataUtils.readData(i)
ecg = ecg[range(1), :]
fecgDelayed = self.dataUtils.createDelayRepetition(
fecg, delayNum, delay)
ecgAll = np.append(ecgAll, ecg, axis=1)
fecgAll = np.append(fecgAll, fecgDelayed, axis=1)
ecgWindows, fecgWindows = self.dataUtils.windowingSig(ecgAll,
fecgAll,
windowSize=200)
# fecgWindows = self.dataUtils.adaptFilterOnSig(ecgWindows, fecgWindows)
# ecgWindows = self.dataUtils.calculateICA(ecgWindows, component=2)
return ecgWindows, fecgWindows
def trainTestSplit(self, sig, label, trainPercent, shuffle=True):
X_train, X_test, y_train, y_test = train_test_split(
sig, label, train_size=trainPercent, shuffle=shuffle)
X_train = np.array(X_train)
X_test = np.array(X_test)
y_train = np.array(y_train)
y_test = np.array(y_test)
return X_train, X_test, y_train, y_test
class TestDataUtils(TestCase):
def __init__(self, methodName: str = ...) -> None:
super().__init__(methodName)
self.dataUtils = DataUtils()
def test_read_data(self):
ecg, fecg = self.dataUtils.readData(0)
self.assertIsNotNone(ecg)
def test_addRepetitionDelay(self):
ecg, fecg = self.dataUtils.readData(0)
detectors = Detectors(200)
# fecgDelayed = self.dataUtils.createDelayRepetition(fecg, 4, 5)
# self.assertIsNotNone(fecgDelayed)
r_peaks = detectors.hamilton_detector(ecg)
pass
