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

from pathlib import Path

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

import mne
from mne.preprocessing import annotate_nan

raw_fname = Path(__file__).parents[2] / "io" / "tests" / "data" / "test_raw.fif"


@pytest.mark.parametrize("meas_date", (None, "orig"))
def test_annotate_nan(meas_date):
    """Tests automatic NaN annotation generation."""
    # Load data
    raw = mne.io.read_raw_fif(raw_fname)
    sfreq = 100
    raw.resample(sfreq)
    if meas_date is None:
        raw.set_meas_date(None)

    # No Nans, annotate returns empty annots
    assert not np.isnan(raw._data).any()
    annot_nan = annotate_nan(raw)
    assert len(annot_nan) == 0

    # but orig_time should be meas_date
    assert annot_nan.orig_time == raw.info["meas_date"]

    # insert block of NaN from 1s to 3s for one channel
    nan_ch_idx = 0
    raw._data[nan_ch_idx, 1 * sfreq : 3 * sfreq] = np.nan

    # annotate_nan accurately finds this
    annot_nan = annotate_nan(raw)
    onset = np.array([1.0])
    if raw.info["meas_date"]:
        onset += raw.first_time
    assert_array_equal(annot_nan.onset, onset)
    assert_array_equal(annot_nan.duration, np.array([2]))
    assert_array_equal(annot_nan.description, np.array(["BAD_NAN"]))
    assert len(annot_nan.ch_names) == 1
    assert annot_nan.ch_names[0] == (raw.ch_names[nan_ch_idx],)

    # Set the NaN annotations to the raw object
    raw.set_annotations(annot_nan)
