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# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import warnings
import os.path as op
from nose.tools import assert_true
from mne import io, Epochs, read_events, pick_types
from mne.utils import _TempDir, requires_sklearn
from mne.decoding import time_generalization
tempdir = _TempDir()
data_dir = op.join(op.dirname(__file__), '..', '..', 'io', 'tests', 'data')
raw_fname = op.join(data_dir, 'test_raw.fif')
event_name = op.join(data_dir, 'test-eve.fif')
tmin, tmax = -0.2, 0.5
event_id = dict(aud_l=1, vis_l=3)
@requires_sklearn
def test_time_generalization():
"""Test time generalization decoding
"""
raw = io.Raw(raw_fname, preload=False)
events = read_events(event_name)
picks = pick_types(raw.info, meg='mag', stim=False, ecg=False,
eog=False, exclude='bads')
picks = picks[1:13:3]
decim = 30
with warnings.catch_warnings(record=True) as w:
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=(None, 0), preload=True, decim=decim)
epochs_list = [epochs[k] for k in event_id.keys()]
scores = time_generalization(epochs_list, cv=2, random_state=42)
n_times = len(epochs.times)
assert_true(scores.shape == (n_times, n_times))
assert_true(scores.max() <= 1.)
assert_true(scores.min() >= 0.)
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