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# Author: Yousra Bekhti <yousra.bekhti@gmail.com>
# Mark Wronkiewicz <wronk@uw.edu>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from numpy.testing import assert_almost_equal
import pytest
from mne import read_source_spaces
from mne.datasets import testing
from mne.simulation import simulate_sparse_stc, source_estimate_quantification
from mne.utils import run_tests_if_main
data_path = testing.data_path(download=False)
src_fname = op.join(data_path, 'subjects', 'sample', 'bem',
'sample-oct-6-src.fif')
@testing.requires_testing_data
def test_metrics():
"""Test simulation metrics."""
src = read_source_spaces(src_fname)
times = np.arange(600) / 1000.
rng = np.random.RandomState(42)
stc1 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
stc2 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
E1_rms = source_estimate_quantification(stc1, stc1, metric='rms')
E2_rms = source_estimate_quantification(stc2, stc2, metric='rms')
E1_cos = source_estimate_quantification(stc1, stc1, metric='cosine')
E2_cos = source_estimate_quantification(stc2, stc2, metric='cosine')
# ### Tests to add
assert (E1_rms == 0.)
assert (E2_rms == 0.)
assert_almost_equal(E1_cos, 0.)
assert_almost_equal(E2_cos, 0.)
stc_bad = stc2.copy().crop(0, 0.5)
pytest.raises(ValueError, source_estimate_quantification, stc1, stc_bad)
stc_bad = stc2.copy()
stc_bad.tmin -= 0.1
pytest.raises(ValueError, source_estimate_quantification, stc1, stc_bad)
pytest.raises(ValueError, source_estimate_quantification, stc1, stc2,
metric='foo')
run_tests_if_main()
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