# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.

import numpy as np
import pytest
from numpy.testing import assert_allclose

from mne import read_source_spaces
from mne.datasets import testing
from mne.simulation import simulate_sparse_stc
from mne.simulation.metrics import source_estimate_quantification

data_path = testing.data_path(download=False)
src_fname = 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) / 1000.0
    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 == 0.0
    assert E2_rms == 0.0
    assert_allclose(E1_cos, 0.0, atol=1e-08)
    assert_allclose(E2_cos, 0.0, atol=1e-08)

    stc_bad = stc2.copy().crop(0, 0.5)
    with pytest.raises(ValueError, match="must have the same size"):
        source_estimate_quantification(stc1, stc_bad)
    stc_bad = stc2.copy()
    stc_bad.tmin -= 0.1
    with pytest.raises(ValueError, match="Times.*must match"):
        source_estimate_quantification(stc1, stc_bad)
    with pytest.raises(ValueError, match="Invalid value for the 'metric'"):
        source_estimate_quantification(stc1, stc2, metric="foo")