"""Data Equivalence Tests""" from __future__ import print_function # Authors: Teon Brooks # Martin Billinger # # License: BSD (3-clause) import os.path as op import inspect from nose.tools import assert_equal, assert_true from numpy.testing import assert_array_almost_equal, assert_array_equal from numpy.testing import assert_raises from scipy import io import numpy as np from mne.externals.six import iterbytes from mne.utils import _TempDir from mne import pick_types from mne.io import Raw from mne.io import read_raw_edf import mne.io.edf.edf as edfmodule from mne.event import find_events FILE = inspect.getfile(inspect.currentframe()) data_dir = op.join(op.dirname(op.abspath(FILE)), 'data') hpts_path = op.join(data_dir, 'biosemi.hpts') bdf_path = op.join(data_dir, 'test.bdf') edf_path = op.join(data_dir, 'test.edf') bdf_eeglab_path = op.join(data_dir, 'test_bdf_eeglab.mat') edf_eeglab_path = op.join(data_dir, 'test_edf_eeglab.mat') tempdir = _TempDir() def test_bdf_data(): """Test reading raw bdf files """ raw_py = read_raw_edf(bdf_path, hpts=hpts_path, 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()) def test_edf_data(): """Test reading raw edf files """ raw_py = read_raw_edf(edf_path, 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) def test_read_segment(): """Test writing raw edf files when preload is False """ 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_array_almost_equal(data1, data11, 10) 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_array_equal(data1, data2) 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_append(): """Test appending raw edf objects using Raw.append """ # Author: Alan Leggitt raw = read_raw_edf(bdf_path, hpts=hpts_path, preload=False) raw0 = raw.copy() raw1 = raw.copy() raw0.append(raw1) assert_true(2 * len(raw) == len(raw0)) def test_parse_annotation(): """Test parsing the tal channel """ # test the parser annot = (b'+180\x14Lights off\x14Close door\x14\x00\x00\x00\x00\x00' b'+180\x14Lights off\x14\x00\x00\x00\x00\x00\x00\x00\x00' b'+180\x14Close door\x14\x00\x00\x00\x00\x00\x00\x00\x00' b'+3.14\x1504.20\x14nothing\x14\x00\x00\x00\x00' b'+1800.2\x1525.5\x14Apnea\x14\x00\x00\x00\x00\x00\x00\x00' b'+123\x14\x14\x00\x00\x00\x00\x00\x00\x00') annot = [a for a in iterbytes(annot)] annot[1::2] = [a * 256 for a in annot[1::2]] tal_channel = map(sum, zip(annot[0::2], annot[1::2])) events = edfmodule._parse_tal_channel(tal_channel) assert_equal(events, [[180.0, 0, 'Lights off'], [180.0, 0, 'Close door'], [180.0, 0, 'Lights off'], [180.0, 0, 'Close door'], [3.14, 4.2, 'nothing'], [1800.2, 25.5, 'Apnea']]) 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, tal_channel=-1, hpts=hpts_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_write_annotations(): """Test writing raw files when annotations were parsed. """ raw1 = read_raw_edf(edf_path, tal_channel=-1, preload=True) 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[:, :] data11, times11 = raw11[:, :] assert_array_almost_equal(data1, data11) assert_array_almost_equal(times1, times11) assert_equal(sorted(raw1.info.keys()), sorted(raw11.info.keys())) assert_raises(RuntimeError, read_raw_edf, edf_path, tal_channel=-1, preload=False)