def lldetect_events(d, sfx):
"""Performs line-length transform on data, then detects events in data and identifies start/stop times and channels
involved.
Takes 1d/2d list (L) of data, performs line-length transform on it and detects events on transformed data.
Returns start & stop times of detected events and channels involved in the form of 2d lists.
Parameters
----------
d : list of float values
EEG data to be detected for events
sfx : int
sampling frequency of data
Returns
-------
ets : 2d list of start and stop times of detected events
each row is 1 event
column 0 is start times
column 1 is stop times
ech : 1d list of strings which hold channel #s involved in event
each string is 1 event
each element in each string is the number of the channel involved
"""
transformed_data = lltransform(d, sfx)
prc = 99.9 # percentile needed for lleventdetector.py
mel = 100 # minimum event length in milliseconds, needed for lleventdetector.py
ets, ech = lleventdetector(transformed_data, sfx, prc, mel)
return ets, ech
def test_lleventdetector_2(example_eeg_data):
# should return correct channels for EON/EOFF
expected_ch = ['3,', '3,']
l = example_eeg_data[2]
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
assert actual[1] == expected_ch
def test_lleventdetector_4(example_eeg_data):
# tests edge case 1 for channels
l = example_eeg_data[2]
l[4][0:4] = 40000
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
expected_ch = ['4,', '3,', '3,']
assert actual[1] == expected_ch
def test_lleventdetector_9(example_eeg_data):
# tests deleting short events channels
l = example_eeg_data[2]
sfx = example_eeg_data[1]
minimum_event_time = 16
actual = lleventdetector(l, sfx, 99.9, minimum_event_time)
expected_ch = ['3,']
assert expected_ch == actual[1]
def test_lleventdetector_6(example_eeg_data):
# tests edge case 2 for channels
l = example_eeg_data[2]
end = len(l[0])
l[1][end - 4:end] = 40000
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
expected_ch = ['3,', '3,', '1,']
assert actual[1] == expected_ch
def test_lleventdetector_1(example_eeg_data):
# should return correct time stamps for EON/EOFF
expected_ts = np.column_stack(([1344, 4156], [1351, 4180]))
l = example_eeg_data[2]
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
if np.size(actual[0]) == np.size(expected_ts):
assert [a == b for a, b in zip(list(actual[0]), list(expected_ts))]
else:
assert False
def test_lleventdetector_11(example_eeg_data):
# tests that ech merges events correctly
l = example_eeg_data[2]
end = len(l[0])
l[1][end - 4:end] = 40000
l[2][end - 3] = 40000
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
expected_ch = ['3,', '3,', '1,2,']
assert expected_ch == actual[1]
def test_lleventdetector_3(example_eeg_data):
# tests edge case 1 for time stamps
l = example_eeg_data[2]
l[4][0:4] = 40000
sfx = example_eeg_data[1]
expected_ts = np.column_stack([[10, 13], [1344, 1355], [4159, 4180]])
actual = lleventdetector(l, sfx, 99.9, 3)
if np.size(actual[0]) == np.size(expected_ts):
assert [a == b for a, b in zip(list(actual[0]), list(expected_ts))]
else:
assert False
def test_lleventdetector_8(example_eeg_data):
# tests deleting short events time stamps
l = example_eeg_data[2]
sfx = example_eeg_data[1]
minimum_event_time = 16
actual = lleventdetector(l, sfx, 99.9, minimum_event_time)
expected_ts = np.column_stack([[4156, 4180]])
if np.size(actual[0]) == np.size(expected_ts):
assert [a == b for a, b in zip(list(actual[0]), list(expected_ts))]
else:
assert False
def test_lleventdetector_10(example_eeg_data):
# test that error is raised when EON and EOFF lengths are different
l = example_eeg_data[2]
end = len(l[0])
sfx = example_eeg_data[1]
l[1][end - 1] = 40000
minimum_event_time = 1
with pytest.raises(
RuntimeError,
match='eON and eOFF are different lengths, check your code.'):
actual = lleventdetector(l, sfx, 99.9, minimum_event_time)
raise RuntimeError(
'eON and eOFF are different lengths, check your code.')
def test_lleventdetector_5(example_eeg_data):
# tests edge case 2 for time stamps
l = example_eeg_data[2]
end = len(l[0])
l[1][end - 4:end] = 40000
sfx = example_eeg_data[1]
actual = lleventdetector(l, sfx, 99.9, 3)
expected_ts = np.column_stack([[1344., 1350.], [4159., 4180.],
[5126., 5130.]])
if np.size(actual[0]) == np.size(expected_ts):
assert [a == b for a, b in zip(list(actual[0]), list(expected_ts))]
else:
assert False
