def test_gdf2_data():
    """Test reading raw GDF 2.x files."""
    raw = read_raw_edf(gdf2_path + '.gdf', eog=None, misc=None, preload=True,
                       stim_channel='STATUS')

    nchan = raw.info['nchan']
    ch_names = raw.ch_names  # Renamed STATUS -> STI 014.
    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # This .mat was generated using the official biosig matlab package
    mat = sio.loadmat(gdf2_path + '_biosig.mat')
    data_biosig = mat['dat'] * 1e-6  # data are stored in microvolts
    data_biosig = data_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Find events
    events = find_events(raw, verbose=1)
    events[:, 2] >>= 8  # last 8 bits are system events in biosemi files
    assert_equal(events.shape[0], 2)  # 2 events in file
    assert_array_equal(events[:, 2], [20, 28])

    with pytest.warns(RuntimeWarning, match='No events found'):
        # header contains no events
        raw = read_raw_edf(gdf2_path + '.gdf', stim_channel='auto')
    assert_equal(nchan, raw.info['nchan'])  # stim channel not constructed
    assert_array_equal(ch_names[1:], raw.ch_names[1:])

    # gh-5604
    assert raw.info['meas_date'] == DATE_NONE
    _test_raw_reader(read_raw_edf, input_fname=gdf2_path + '.gdf',
                     eog=None, misc=None, stim_channel='STATUS')

def test_gdf2_data():
    """Test reading raw GDF 2.x files."""
    raw = read_raw_edf(gdf2_path + '.gdf', eog=None, misc=None, preload=True,
                       stim_channel='STATUS')

    nchan = raw.info['nchan']
    ch_names = raw.ch_names  # Renamed STATUS -> STI 014.
    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # This .mat was generated using the official biosig matlab package
    mat = sio.loadmat(gdf2_path + '_biosig.mat')
    data_biosig = mat['dat'] * 1e-6  # data are stored in microvolts
    data_biosig = data_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Find events
    events = find_events(raw, verbose=1)
    events[:, 2] >>= 8  # last 8 bits are system events in biosemi files
    assert_equal(events.shape[0], 2)  # 2 events in file
    assert_array_equal(events[:, 2], [20, 28])

    with warnings.catch_warnings(record=True) as w:
        # header contains no events
        raw = read_raw_edf(gdf2_path + '.gdf', stim_channel='auto')
        assert_equal(len(w), 1)
        assert_true(str(w[0].message).startswith('No events found.'))
    assert_equal(nchan, raw.info['nchan'])  # stim channel not constructed
    assert_array_equal(ch_names[1:], raw.ch_names[1:])

def test_edf_data():
    """Test reading raw edf files"""
    raw_py = read_raw_edf(edf_path, misc=range(-4, 0), stim_channel=139,
                          preload=True)

    picks = pick_types(raw_py.info, meg=False, eeg=True,
                       exclude=['EDF Annotations'])
    data_py, _ = raw_py[picks]

    print(raw_py)  # to test repr
    print(raw_py.info)  # to test Info repr

    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_eeglab_path)
    raw_eeglab = raw_eeglab['data'] * 1e-6  # data are stored in microvolts
    data_eeglab = raw_eeglab[picks]

    assert_array_almost_equal(data_py, data_eeglab, 10)

    # Make sure concatenation works
    raw_concat = concatenate_raws([raw_py.copy(), raw_py])
    assert_equal(raw_concat.n_times, 2 * raw_py.n_times)

    # Test uneven sampling
    raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
    data_py, _ = raw_py[0]
    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
    raw_eeglab = raw_eeglab['data']
    data_eeglab = raw_eeglab[0]

    # match upsampling
    upsample = len(data_eeglab) / len(raw_py)
    data_py = np.repeat(data_py, repeats=upsample)
    assert_array_equal(data_py, data_eeglab)

def test_read_segment():
    """Test writing raw edf files when preload is False
    """
    tempdir = _TempDir()
    raw1 = read_raw_edf(edf_path, stim_channel=139, preload=False)
    raw1_file = op.join(tempdir, 'test1-raw.fif')
    raw1.save(raw1_file, overwrite=True, buffer_size_sec=1)
    raw11 = Raw(raw1_file, preload=True)
    data1, times1 = raw1[:139, :]
    data11, times11 = raw11[:139, :]
    assert_allclose(data1, data11, rtol=1e-6)
    assert_array_almost_equal(times1, times11)
    assert_equal(sorted(raw1.info.keys()), sorted(raw11.info.keys()))

    raw2 = read_raw_edf(edf_path, stim_channel=139, preload=True)
    raw2_file = op.join(tempdir, 'test2-raw.fif')
    raw2.save(raw2_file, overwrite=True)
    data2, times2 = raw2[:139, :]
    assert_allclose(data1, data2, rtol=1e-6)
    assert_array_equal(times1, times2)

    raw1 = Raw(raw1_file, preload=True)
    raw2 = Raw(raw2_file, preload=True)
    assert_array_equal(raw1._data, raw2._data)

    # test the _read_segment function by only loading some of the data
    raw1 = read_raw_edf(edf_path, preload=False)
    raw2 = read_raw_edf(edf_path, preload=True)

    # select some random range of data to compare
    data1, times1 = raw1[:, 345:417]
    data2, times2 = raw2[:, 345:417]
    assert_array_equal(data1, data2)
    assert_array_equal(times1, times2)

def test_bdf_stim_channel():
    """Test BDF stim channel."""
    # test if last channel is detected as STIM by default
    raw_py = _test_raw_reader(read_raw_edf, input_fname=bdf_path,
                              stim_channel='auto')
    assert channel_type(raw_py.info, raw_py.info["nchan"] - 1) == 'stim'

    # test BDF file with wrong scaling info in header - this should be ignored
    # for BDF stim channels
    events = [[242, 0, 4],
              [310, 0, 2],
              [952, 0, 1],
              [1606, 0, 1],
              [2249, 0, 1],
              [2900, 0, 1],
              [3537, 0, 1],
              [4162, 0, 1],
              [4790, 0, 1]]
    with pytest.deprecated_call(match='stim_channel'):
        raw = read_raw_edf(bdf_stim_channel_path, preload=True)
    bdf_events = find_events(raw)
    assert_array_equal(events, bdf_events)
    raw = read_raw_edf(bdf_stim_channel_path, preload=False,
                       stim_channel='auto')
    bdf_events = find_events(raw)
    assert_array_equal(events, bdf_events)

def test_edf_overlapping_annotations():
    """Test EDF with overlapping annotations."""
    n_warning = 2
    with warnings.catch_warnings(record=True) as w:
        read_raw_edf(edf_overlap_annot_path, preload=True, verbose=True)
        assert_equal(sum('overlapping' in str(ww.message) for ww in w),
                     n_warning)

def test_stim_channel():
    """Test reading raw edf files with stim channel"""
    raw_py = read_raw_edf(edf_path, misc=range(-4, 0), stim_channel=139,
                          preload=True)

    picks = pick_types(raw_py.info, meg=False, eeg=True,
                       exclude=['EDF Annotations'])
    data_py, _ = raw_py[picks]

    print(raw_py)  # to test repr
    print(raw_py.info)  # to test Info repr

    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_eeglab_path)
    raw_eeglab = raw_eeglab['data'] * 1e-6  # data are stored in microvolts
    data_eeglab = raw_eeglab[picks]

    assert_array_almost_equal(data_py, data_eeglab, 10)

    # Test uneven sampling
    raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
    data_py, _ = raw_py[0]
    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
    raw_eeglab = raw_eeglab['data']
    data_eeglab = raw_eeglab[0]

    # match upsampling
    upsample = len(data_eeglab) / len(raw_py)
    data_py = np.repeat(data_py, repeats=upsample)
    assert_array_equal(data_py, data_eeglab)

    assert_raises(RuntimeError, read_raw_edf, edf_path, preload=False)

def test_read_raw_edf_stim_channel_input_parameters():
    """Test edf raw reader deprecation."""
    _MSG = "`read_raw_edf` is not supposed to trigger a deprecation warning"
    with pytest.warns(None) as recwarn:
        read_raw_edf(edf_path)
    assert all([w.category != DeprecationWarning for w in recwarn.list]), _MSG

    for invalid_stim_parameter in ['EDF Annotations', 'BDF Annotations']:
        with pytest.raises(ValueError,
                           match="stim channel is not supported"):
            read_raw_edf(edf_path, stim_channel=invalid_stim_parameter)

def test_stim_channel():
    """Test reading raw edf files with stim channel."""
    raw_py = read_raw_edf(edf_path, misc=range(-4, 0), stim_channel=139,
                          preload=True)

    picks = pick_types(raw_py.info, meg=False, eeg=True,
                       exclude=['EDF Annotations'])
    data_py, _ = raw_py[picks]

    print(raw_py)  # to test repr
    print(raw_py.info)  # to test Info repr

    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_eeglab_path)
    raw_eeglab = raw_eeglab['data'] * 1e-6  # data are stored in microvolts
    data_eeglab = raw_eeglab[picks]

    assert_array_almost_equal(data_py, data_eeglab, 10)
    events = find_edf_events(raw_py)
    assert_true(len(events) - 1 == len(find_events(raw_py)))  # start not found

    # Test uneven sampling
    raw_py = read_raw_edf(edf_uneven_path, stim_channel=None)
    data_py, _ = raw_py[0]
    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(edf_uneven_eeglab_path)
    raw_eeglab = raw_eeglab['data']
    data_eeglab = raw_eeglab[0]

    # match upsampling
    upsample = len(data_eeglab) / len(raw_py)
    data_py = np.repeat(data_py, repeats=upsample)
    assert_array_equal(data_py, data_eeglab)

    assert_raises(RuntimeError, read_raw_edf, edf_path, preload=False,
                  stim_channel=-1)

    with warnings.catch_warnings(record=True) as w:
        warnings.simplefilter('always')
        raw = read_raw_edf(edf_stim_resamp_path, verbose=True, stim_channel=-1)
    assert_equal(len(w), 2)
    assert_true(any('Events may jitter' in str(ww.message) for ww in w))
    assert_true(any('truncated' in str(ww.message) for ww in w))
    with warnings.catch_warnings(record=True) as w:
        warnings.simplefilter('always')
        raw[:]
    assert_equal(len(w), 0)

    events = raw_py.find_edf_events()
    assert_true(len(events) == 0)

def test_read_raw_edf_deprecation_of_annot_annotmap(tmpdir):
    """Test deprecation of annot and annotmap."""
    annot = (b'+0.1344\x150.2560\x14two\x14\x00\x00\x00\x00'
             b'+0.3904\x151.0\x14two\x14\x00\x00\x00\x00'
             b'+2.0\x14three\x14\x00\x00\x00\x00\x00\x00\x00\x00'
             b'+2.5\x152.5\x14two\x14\x00\x00\x00\x00')
    annot_file = tmpdir.join('annotations.txt')
    annot_file.write(annot)
    annotmap_file = tmpdir.join('annotations_map.txt')
    annotmap_file.write('two:2,three:3')

    with pytest.warns(DeprecationWarning, match="annot.*annotmap.*"):
        read_raw_edf(input_fname=edf_path, annot=str(annot_file),
                     annotmap=str(annotmap_file), preload=True)

def test_edf_data():
    """Test edf files."""
    raw = _test_raw_reader(read_raw_edf, input_fname=edf_path,
                           stim_channel=None, exclude=['Ergo-Left', 'H10'],
                           verbose='error')
    raw_py = read_raw_edf(edf_path, stim_channel='auto', preload=True)

    assert_equal(len(raw.ch_names) + 2, len(raw_py.ch_names))
    # Test saving and loading when annotations were parsed.
    edf_events = find_events(raw_py, output='step', shortest_event=0,
                             stim_channel='STI 014')

    # onset, duration, id
    events = [[0.1344, 0.2560, 2],
              [0.3904, 1.0000, 2],
              [2.0000, 0.0000, 3],
              [2.5000, 2.5000, 2]]
    events = np.array(events)
    events[:, :2] *= 512  # convert time to samples
    events = np.array(events, dtype=int)
    events[:, 1] -= 1
    events[events[:, 1] <= 0, 1] = 1
    events[:, 1] += events[:, 0]

    onsets = events[:, [0, 2]]
    offsets = events[:, [1, 2]]

    events = np.zeros((2 * events.shape[0], 3), dtype=int)
    events[0::2, [0, 2]] = onsets
    events[1::2, [0, 1]] = offsets

    assert_array_equal(edf_events, events)

    # Test with number of records not in header (-1).
    tempdir = _TempDir()
    broken_fname = op.join(tempdir, 'broken.edf')
    with open(edf_path, 'rb') as fid_in:
        fid_in.seek(0, 2)
        n_bytes = fid_in.tell()
        fid_in.seek(0, 0)
        rbytes = fid_in.read(int(n_bytes * 0.4))
    with open(broken_fname, 'wb') as fid_out:
        fid_out.write(rbytes[:236])
        fid_out.write(b'-1      ')
        fid_out.write(rbytes[244:])
    with pytest.warns(RuntimeWarning,
                      match='records .* not match the file size'):
        raw = read_raw_edf(broken_fname, preload=True, stim_channel='auto')
        read_raw_edf(broken_fname, exclude=raw.ch_names[:132], preload=True,
                     stim_channel='auto')

def test_gdf_data():
    """Test reading raw GDF 1.x files."""
    with warnings.catch_warnings(record=True):  # interpolate / overlap events
        raw = read_raw_edf(gdf1_path + '.gdf', eog=None,
                           misc=None, preload=True, stim_channel='auto')
    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # this .npy was generated using the official biosig python package
    raw_biosig = np.load(gdf1_path + '_biosig.npy')
    raw_biosig = raw_biosig * 1e-6  # data are stored in microvolts
    data_biosig = raw_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Test for stim channel
    events = find_events(raw, shortest_event=1)
    # The events are overlapping.
    assert_array_equal(events[:, 0], raw._raw_extras[0]['events'][1][::2])

    # Test events are encoded to stim channel.
    events = find_events(raw)
    evs = raw.find_edf_events()
    assert_true(all([event in evs[1] for event in events[:, 0]]))

def test_gdf2_data():
    """Test reading raw GDF 2.x files."""
    raw = read_raw_edf(gdf2_path + '.gdf', eog=None, misc=None, preload=True)

    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # This .mat was generated using the official biosig matlab package
    mat = sio.loadmat(gdf2_path + '_biosig.mat')
    data_biosig = mat['dat'] * 1e-6  # data are stored in microvolts
    data_biosig = data_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Find events
    events = find_events(raw, verbose=1)
    events[:, 2] >>= 8  # last 8 bits are system events in biosemi files
    assert_equal(events.shape[0], 2)  # 2 events in file
    assert_array_equal(events[:, 2], [20, 28])

    # gh-5604
    assert raw.info['meas_date'] == DATE_NONE
    _test_raw_reader(read_raw_edf, input_fname=gdf2_path + '.gdf',
                     eog=None, misc=None)

def test_gdf_data():
    """Test reading raw GDF 1.x files."""
    raw = read_raw_edf(gdf1_path + '.gdf', eog=None, misc=None, preload=True)
    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # Test Status is added as event
    EXPECTED_EVS_ONSETS = raw._raw_extras[0]['events'][1]
    evs, evs_id = events_from_annotations(raw)
    assert_array_equal(evs[:, 0], EXPECTED_EVS_ONSETS)
    assert evs_id == {'Unknown': 1}

    # this .npy was generated using the official biosig python package
    raw_biosig = np.load(gdf1_path + '_biosig.npy')
    raw_biosig = raw_biosig * 1e-6  # data are stored in microvolts
    data_biosig = raw_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Test for events
    assert len(raw.annotations.duration == 963)

    # gh-5604
    assert raw.info['meas_date'] == DATE_NONE

def test_gdf_data():
    """Test reading raw GDF 1.x files."""
    with pytest.warns(RuntimeWarning, match='Overlapping events'):
        raw = read_raw_edf(gdf1_path + '.gdf', eog=None,
                           misc=None, preload=True, stim_channel='auto')
    picks = pick_types(raw.info, meg=False, eeg=True, exclude='bads')
    data, _ = raw[picks]

    # this .npy was generated using the official biosig python package
    raw_biosig = np.load(gdf1_path + '_biosig.npy')
    raw_biosig = raw_biosig * 1e-6  # data are stored in microvolts
    data_biosig = raw_biosig[picks]

    # Assert data are almost equal
    assert_array_almost_equal(data, data_biosig, 8)

    # Test for stim channel
    events = find_events(raw, shortest_event=1)
    # The events are overlapping.
    assert_array_equal(events[:, 0], raw._raw_extras[0]['events'][1][::2])

    # Test events are encoded to stim channel.
    events = find_events(raw)
    evs = raw.find_edf_events()
    assert (all([event in evs[1] for event in events[:, 0]]))

    # gh-5604
    assert raw.info['meas_date'] == DATE_NONE
    with pytest.warns(RuntimeWarning, match='Overlapping events'):
        _test_raw_reader(read_raw_edf, input_fname=gdf1_path + '.gdf',
                         eog=None, misc=None, stim_channel='auto')

def test_edf_data():
    """Test edf files"""
    _test_raw_reader(read_raw_edf, input_fname=edf_path, stim_channel=None)
    raw_py = read_raw_edf(edf_path, preload=True)
    # Test saving and loading when annotations were parsed.
    tempdir = _TempDir()
    raw_file = op.join(tempdir, 'test-raw.fif')
    raw_py.save(raw_file, overwrite=True, buffer_size_sec=1)
    Raw(raw_file, preload=True)

    edf_events = find_events(raw_py, output='step', shortest_event=0,
                             stim_channel='STI 014')

    # onset, duration, id
    events = [[0.1344, 0.2560, 2],
              [0.3904, 1.0000, 2],
              [2.0000, 0.0000, 3],
              [2.5000, 2.5000, 2]]
    events = np.array(events)
    events[:, :2] *= 512  # convert time to samples
    events = np.array(events, dtype=int)
    events[:, 1] -= 1
    events[events[:, 1] <= 0, 1] = 1
    events[:, 1] += events[:, 0]

    onsets = events[:, [0, 2]]
    offsets = events[:, [1, 2]]

    events = np.zeros((2 * events.shape[0], 3), dtype=int)
    events[0::2, [0, 2]] = onsets
    events[1::2, [0, 1]] = offsets

    assert_array_equal(edf_events, events)

def test_duplicate_channel_labels_edf():
    """Test reading edf file with duplicate channel names."""
    EXPECTED_CHANNEL_NAMES = ['EEG F1-Ref-0', 'EEG F2-Ref', 'EEG F1-Ref-1']
    with pytest.warns(RuntimeWarning, match='Channel names are not unique'):
        raw = read_raw_edf(duplicate_channel_labels_path, preload=False)

    assert raw.ch_names == EXPECTED_CHANNEL_NAMES

def test_edf_annotations():
    """Test if events are detected correctly in a typical MNE workflow."""

    # test an actual file
    raw = read_raw_edf(edf_path, preload=True)
    edf_events = find_events(raw, output='step', shortest_event=0,
                             stim_channel='STI 014')

    # onset, duration, id
    events = [[0.1344, 0.2560, 2],
              [0.3904, 1.0000, 2],
              [2.0000, 0.0000, 3],
              [2.5000, 2.5000, 2]]
    events = np.array(events)
    events[:, :2] *= 512  # convert time to samples
    events = np.array(events, dtype=int)
    events[:, 1] -= 1
    events[events[:, 1] <= 0, 1] = 1
    events[:, 1] += events[:, 0]

    onsets = events[:, [0, 2]]
    offsets = events[:, [1, 2]]

    events = np.zeros((2 * events.shape[0], 3), dtype=int)
    events[0::2, [0, 2]] = onsets
    events[1::2, [0, 1]] = offsets

    assert_array_equal(edf_events, events)

def test_bdf_data():
    """Test reading raw bdf files
    """
    raw_py = read_raw_edf(bdf_path, montage=montage_path, eog=eog,
                          misc=misc, preload=True)
    picks = pick_types(raw_py.info, meg=False, eeg=True, exclude='bads')
    data_py, _ = raw_py[picks]

    print(raw_py)  # to test repr
    print(raw_py.info)  # to test Info repr

    # this .mat was generated using the EEG Lab Biosemi Reader
    raw_eeglab = io.loadmat(bdf_eeglab_path)
    raw_eeglab = raw_eeglab['data'] * 1e-6  # data are stored in microvolts
    data_eeglab = raw_eeglab[picks]

    assert_array_almost_equal(data_py, data_eeglab)

    # Manually checking that float coordinates are imported
    assert_true((raw_py.info['chs'][0]['eeg_loc']).any())
    assert_true((raw_py.info['chs'][25]['eeg_loc']).any())
    assert_true((raw_py.info['chs'][63]['eeg_loc']).any())

    # Make sure concatenation works
    raw_concat = concatenate_raws([raw_py.copy(), raw_py])
    assert_equal(raw_concat.n_times, 2 * raw_py.n_times)

def test_append():
    """Test appending raw edf objects using Raw.append"""
    for preload in (True, False):
        raw = read_raw_edf(bdf_path, preload=False)
        raw0 = raw.copy()
        raw1 = raw.copy()
        raw0.append(raw1)
        assert_true(2 * len(raw) == len(raw0))
        assert_allclose(np.tile(raw[:, :][0], (1, 2)), raw0[:, :][0])

    # different types can't combine
    raw = read_raw_edf(bdf_path, preload=True)
    raw0 = raw.copy()
    raw1 = raw.copy()
    raw2 = RawArray(raw[:, :][0], raw.info)
    assert_raises(ValueError, raw.append, raw2)