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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
from pathlib import Path
import pytest
from mne.io import read_raw_fif
from mne.preprocessing import find_bad_channels_lof
base_dir = Path(__file__).parent.parent.parent / "io" / "tests" / "data"
raw_fname = base_dir / "test_raw.fif"
@pytest.mark.parametrize(
"n_neighbors, ch_type, n_ch, n_bad",
[
(8, "eeg", 60, 8),
(10, "grad", 204, 2),
(20, "mag", 102, 0),
(30, "grad", 204, 2),
],
)
def test_lof(n_neighbors, ch_type, n_ch, n_bad):
"""Test LOF detection."""
pytest.importorskip("sklearn")
raw = read_raw_fif(raw_fname).load_data()
assert raw.info["bads"] == []
bads, scores = find_bad_channels_lof(
raw, n_neighbors, picks=ch_type, return_scores=True
)
bads_2 = find_bad_channels_lof(raw, n_neighbors, picks=ch_type)
assert len(scores) == n_ch
assert len(bads) == n_bad
assert bads == bads_2
with pytest.raises(ValueError, match="channel type"):
find_bad_channels_lof(raw)
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