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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
# Authors: Jussi Nurminen <jnu@iki.fi>
# License: BSD Style.
import tarfile
import os.path as op
import os
from ...utils import _fetch_file, verbose
from ..utils import _get_path, logger, _do_path_update
@verbose
def data_path(dataset='evoked', path=None, force_update=False,
update_path=True, verbose=None):
u"""Get path to local copy of the high frequency SEF dataset.
Gets a local copy of the high frequency SEF MEG dataset [1]_.
Parameters
----------
dataset : 'evoked' | 'raw'
Whether to get the main dataset (evoked, structural and the rest) or
the separate dataset containing raw MEG data only.
path : None | str
Where to look for the HF-SEF data storing location.
If None, the environment variable or config parameter
``MNE_DATASETS_HF_SEF_PATH`` is used. If it doesn't exist, the
"~/mne_data" directory is used. If the HF-SEF dataset
is not found under the given path, the data
will be automatically downloaded to the specified folder.
force_update : bool
Force update of the dataset even if a local copy exists.
update_path : bool | None
If True, set the MNE_DATASETS_HF_SEF_PATH in mne-python
config to the given path. If None, the user is prompted.
verbose : bool, str, int, or None
If not None, override default verbose level (see :func:`mne.verbose`).
Returns
-------
path : str
Local path to the directory where the HF-SEF data is stored.
References
----------
.. [1] Nurminen, J., Paananen, H., Mäkelä, J. (2017): High frequency
somatosensory MEG dataset. https://doi.org/10.5281/zenodo.889234
"""
key = 'MNE_DATASETS_HF_SEF_PATH'
name = 'HF_SEF'
path = _get_path(path, key, name)
destdir = op.join(path, 'HF_SEF')
urls = {'evoked':
'https://zenodo.org/record/889235/files/hf_sef_evoked.tar.gz',
'raw':
'https://zenodo.org/record/889296/files/hf_sef_raw.tar.gz'}
if dataset not in urls:
raise ValueError('Invalid dataset specified')
url = urls[dataset]
fn = url.split('/')[-1] # pick the filename from the url
archive = op.join(destdir, fn)
# check for existence of evoked and raw sets
has = dict()
subjdir = op.join(destdir, 'subjects')
megdir_a = op.join(destdir, 'MEG', 'subject_a')
has['evoked'] = op.isdir(destdir) and op.isdir(subjdir)
has['raw'] = op.isdir(destdir) and any(['raw' in fn_ for fn_ in
os.listdir(megdir_a)])
if not has[dataset] or force_update:
if not op.isdir(destdir):
os.mkdir(destdir)
_fetch_file(url, archive)
with tarfile.open(archive) as tar:
logger.info('Decompressing %s' % archive)
for member in tar.getmembers():
# strip the leading dirname 'hf_sef/' from the archive paths
# this should be fixed when making next version of archives
member.name = member.name[7:]
try:
tar.extract(member, destdir)
except IOError:
# check whether file exists but could not be overwritten
fn_full = op.join(destdir, member.name)
if op.isfile(fn_full):
os.remove(fn_full)
tar.extract(member, destdir)
else: # some more sinister cause for IOError
raise
os.remove(archive)
path = _do_path_update(path, update_path, key, name)
return destdir
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