def test_threshold_filter(self):
fake_rri = RRi([810, 830, 860, 865, 804, 1100, 800], time=[0, 1, 2, 3, 4, 5, 6])
rri_filt = threshold_filter(fake_rri, threshold=250)
expected_rri = [810, 830, 860, 865, 804, 748.40625, 800]
expected_time = [0, 1, 2, 3, 4, 5, 6]
assert isinstance(rri_filt, RRi)
np.testing.assert_almost_equal(rri_filt.values, expected_rri, decimal=2)
np.testing.assert_almost_equal(rri_filt.time, expected_time, decimal=2)
def test_threshold_filter_noise_in_the_beginning(self):
fake_rri = RRi([810, 500, 860, 865, 804, 810, 800], time=[0, 1, 2, 3, 4, 5, 6])
rri_filt = threshold_filter(fake_rri, threshold=250)
expected_rri = [810, 814.34375, 860, 865, 804, 810, 800]
expected_time = [0, 1, 2, 3, 4, 5, 6]
assert isinstance(rri_filt, RRi)
np.testing.assert_almost_equal(rri_filt.values, expected_rri, decimal=2)
np.testing.assert_almost_equal(rri_filt.time, expected_time, decimal=2)
def test_threshold_filter_string_threshold(self):
fake_rri = RRi([810, 650, 860, 865, 804, 810, 800], time=[0, 1, 2, 3, 4, 5, 6])
rri_filt = threshold_filter(fake_rri, threshold="strong")
expected_rri = [810, 814.34375, 860, 865, 804, 810, 800]
expected_time = [0, 1, 2, 3, 4, 5, 6]
assert isinstance(rri_filt, RRi)
np.testing.assert_almost_equal(rri_filt.values, expected_rri, decimal=2)
np.testing.assert_almost_equal(rri_filt.time, expected_time, decimal=2)
def preprocess_hr_signal(raw_signal,
fs,
sig_len,
desired_fs: int = 1,
interval: int = 1):
"""
correct sampling bias by making a frequency shift, moving average filter and threshold LPF
:param raw_signal: signal to be preprocessed
:param fs: the raw_signal's sampling frequency
:param sig_len: raw signal's number of samples
:param desired_fs: desired sampling frequency
:param interval: window for moving average filter
:return: processed signal
"""
# interval in hours
signal = Waveforms.frequency_shift(raw_signal, sig_len, fs, desired_fs)
signal = pos_sig(signal)
if np.isnan(signal).all():
return np.nan
signal = RRi(signal)
window = desired_fs * interval * 3600
return threshold_filter(moving_average(signal, window),
threshold='strong')