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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import os
from os import path as op
import numpy as np
from numpy.testing import assert_allclose
from mne import read_evokeds
from mne.datasets import testing
from mne.minimum_norm import estimate_snr, read_inverse_operator
from mne.utils import requires_mne, run_subprocess
s_path = op.join(testing.data_path(download=False), "MEG", "sample")
fname_inv = op.join(s_path, "sample_audvis_trunc-meg-eeg-oct-6-meg-inv.fif")
fname_evoked = op.join(s_path, "sample_audvis-ave.fif")
@testing.requires_testing_data
@requires_mne
def test_snr(tmp_path):
"""Test SNR calculation."""
tempdir = str(tmp_path)
inv = read_inverse_operator(fname_inv)
evoked = read_evokeds(fname_evoked, baseline=(None, 0))[0]
snr = estimate_snr(evoked, inv)[0]
orig_dir = os.getcwd()
os.chdir(tempdir)
try:
cmd = [
"mne_compute_mne",
"--inv",
fname_inv,
"--meas",
fname_evoked,
"--snronly",
"--bmin",
"-200",
"--bmax",
"0",
]
run_subprocess(cmd)
except Exception:
pass # this returns 1 for some reason
finally:
os.chdir(orig_dir)
times, snr_c, _ = np.loadtxt(op.join(tempdir, "SNR")).T
assert_allclose(times / 1000.0, evoked.times, atol=1e-2)
assert_allclose(snr, snr_c, atol=1e-2, rtol=1e-2)
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