def test_apply_interbundle_correction(bedmaster_reader: BedmasterReader):
def _create_ib_corr_dict(signal: BedmasterSignal, cut_idx: int, time_corr: int):
source_corr = {
"maxTime": signal.time[cut_idx],
"timeCorr": time_corr,
}
return source_corr
def _apply_and_assert_ib(signal: Optional[BedmasterSignal], sig_type: str):
if signal is None:
assert False
signal.time_corr_arr = np.unpackbits(signal.time_corr_arr)
signal_original = copy.deepcopy(signal)
bedmaster_reader.interbundle_corr[sig_type] = _create_ib_corr_dict(
signal,
cut_idx[sig_type],
time_corr[sig_type],
)
bedmaster_reader.apply_ibcorr(signal)
_assert_ib_correction(
signal_original,
signal,
cut_idx[sig_type],
time_corr[sig_type],
)
bedmaster_reader.interbundle_corr[sig_type] = None
cut_idx = {"wv": 10, "vs": 4}
time_corr = {"wv": 5, "vs": 3}
# Standard case
ecgi = bedmaster_reader.get_wv("ch7", "I")
_apply_and_assert_ib(ecgi, "wv")
cuff = bedmaster_reader.get_vs("CUFF")
_apply_and_assert_ib(cuff, "vs")
# With DE
ecgv = bedmaster_reader.get_wv("ch10", "V")
_apply_and_assert_ib(ecgv, "wv")
hr = bedmaster_reader.get_vs("HR")
_apply_and_assert_ib(hr, "vs")
# With missing values
ecgiii = bedmaster_reader.get_wv("ch9", "prova")
_apply_and_assert_ib(ecgiii, "wv")
# Multiple sf
ecgii = bedmaster_reader.get_wv("ch8", "II")
_apply_and_assert_ib(ecgii, "wv")
def test_contiguous_nparrays(bedmaster_reader: BedmasterReader):
heart_rate = bedmaster_reader.get_vs("HR")
if heart_rate is None:
assert False
ecgv = bedmaster_reader.get_wv("ch10", "V")
if ecgv is None:
assert False
signals = [heart_rate, ecgv]
for signal in signals:
assert not signal.value.dtype == object
assert not signal.time.dtype == object
def test_get_interbundle_correction(bedmaster_reader: BedmasterReader):
art1d = bedmaster_reader.get_vs("CO")
if art1d is None:
assert False
ch10 = bedmaster_reader.get_wv("ch10", "v")
if ch10 is None:
assert False
no_correction = {"vs": None, "wv": None}
prev_max_vs = {
"segmentNo": 2,
"maxTime": art1d.time[4],
"signalName": "CO",
}
prev_max_wv = {
"segmentNo": 1,
"maxTime": ch10.time[14],
"signalName": "ch10",
}
prev_max_info = {"vs": prev_max_vs, "wv": prev_max_wv}
expected_vs = {"maxTime": art1d.time[3], "timeCorr": 2}
expected_wv = {"maxTime": ch10.time[15], "timeCorr": -0.25}
def _change_ibcor_dict(source_type, **kwargs):
new_dict = prev_max_info.copy()
for source in source_type:
for key in kwargs:
new_dict[source][key] = kwargs[key]
return new_dict
assert bedmaster_reader.interbundle_corr == no_correction
# Normal case:
bedmaster_reader.get_interbundle_correction(prev_max_info)
assert bedmaster_reader.interbundle_corr["vs"] == expected_vs
assert bedmaster_reader.interbundle_corr["wv"] == expected_wv
# Case: signal does not exist on current bundle
previous = _change_ibcor_dict(["vs", "wv"], signalName="Random")
bedmaster_reader.get_interbundle_correction(previous)
assert bedmaster_reader.interbundle_corr == no_correction
# Case: no overlap between previous and current bundle
previous = _change_ibcor_dict(["vs", "wv"], segmentNo=-1)
bedmaster_reader.get_interbundle_correction(previous)
assert bedmaster_reader.interbundle_corr == no_correction
# Case: complete overlap between previous and current
previous = _change_ibcor_dict(["vs", "wv"], segmentNo=100)
bedmaster_reader.get_interbundle_correction(previous)
assert bedmaster_reader.interbundle_corr == no_correction
def test_max_segment(bedmaster_reader: BedmasterReader):
def _create_max_seg_dict(seg_no, max_time, signal_name):
return {
"segmentNo": seg_no,
"maxTime": max_time,
"signalName": signal_name,
}
empty_vs_dict = _create_max_seg_dict(0, -1, "")
empty_wv_dict = _create_max_seg_dict(0, -1, "")
expected_wv_max = _create_max_seg_dict(
seg_no=6,
max_time=1452438403.75,
signal_name="ch10",
)
expected_vs_max = _create_max_seg_dict(
seg_no=6,
max_time=1452438402.0,
signal_name="CO",
)
assert bedmaster_reader.max_segment["vs"] == empty_vs_dict
assert bedmaster_reader.max_segment["wv"] == empty_wv_dict
wv_signals = bedmaster_reader.list_wv()
for wv_signal_name, channel in wv_signals.items():
bedmaster_reader.get_wv(channel, wv_signal_name)
assert bedmaster_reader.max_segment["vs"] == empty_vs_dict
assert bedmaster_reader.max_segment["wv"] == expected_wv_max
vs_signals = bedmaster_reader.list_vs()
for vs_signal_name in vs_signals:
bedmaster_reader.get_vs(vs_signal_name)
assert bedmaster_reader.max_segment["vs"] == expected_vs_max
assert bedmaster_reader.max_segment["wv"] == expected_wv_max
def test_get_wv(bedmaster_reader: BedmasterReader, matfile: h5py.File):
def linearize(arr):
return np.transpose(arr)[0]
# Check standard case
ecgv = bedmaster_reader.get_wv("ch10", "V")
if ecgv is None:
assert False
assert ecgv.name == "V"
assert np.array_equal(ecgv.value, linearize(matfile["wv/ch10"][()]))
assert np.array_equal(
ecgv.time,
linearize(matfile["wv_time_corrected/ch10/res_wv"][()]),
)
assert ecgv.units == "mV"
assert ecgv.scale_factor == 0.0243
assert np.array_equal(ecgv.sample_freq, np.array([(240, 0)], dtype="float,int"))
# Check that it works without specifying signal name
ecgv_copy = bedmaster_reader.get_wv("ch10")
if ecgv_copy is None:
assert False
assert ecgv_copy.name == ecgv.name
assert np.array_equal(ecgv_copy.value, ecgv.value)
# Check dataevents are collected
time_corr_arr = np.unpackbits(ecgv.time_corr_arr, axis=None)
irregularities = np.where(time_corr_arr)[0]
expected_irr_idx = np.array([3, 4, 20, 32, 40, 50, 54])
assert np.array_equal(irregularities, expected_irr_idx)
# Case with multiple sample frequency
ecg2 = bedmaster_reader.get_wv("ch8", "II")
if ecg2 is None:
assert False
assert np.array_equal(
ecg2.sample_freq,
np.array([(240, 0), (120, 80)], dtype="float,int"),
)
# Check that interbundle correction is applied
overlap = 5
bedmaster_reader.interbundle_corr["wv"] = {
"maxTime": ecgv.time[overlap - 1],
"timeCorr": 8,
}
ecg2_corr = bedmaster_reader.get_wv("ch8", "II")
if ecg2_corr is None:
assert False
values_cut = overlap * ecg2_corr.sample_freq[0][0] / 4
assert len(ecg2_corr.time) == len(ecgv.time) - overlap
assert len(ecg2_corr.value) == len(ecgv.value) - values_cut
assert np.array_equal(
ecg2_corr.sample_freq,
np.array([(240, 0), (120, 75)], dtype="float,int"),
)
# Case with unknown scale factor and unit
ecg3 = bedmaster_reader.get_wv("ch9", "III")
if ecg3 is None:
assert False
assert ecg3.units == "??V"
assert ecg3.scale_factor == 2.44
assert np.array_equal(ecg3.sample_freq, np.array([(240, 0)], dtype="float,int"))