# Author: Eric Larson # License: BSD Style. from ...externals.six import string_types import os from os import path as op import zipfile from sys import stdout from ...utils import _fetch_file, get_config, set_config, _url_to_local_path from .urls import (url_match, valid_data_types, valid_data_formats, valid_conditions) def data_path(url, path=None, force_update=False, update_path=None): """Get path to local copy of MEGSIM dataset URL This is a low-level function useful for getting a local copy of a remote MEGSIM dataet. Parameters ---------- url : str The dataset to use. path : None | str Location of where to look for the MEGSIM data storing location. If None, the environment variable or config parameter MNE_DATASETS_MEGSIM_PATH is used. If it doesn't exist, the "mne-python/examples" directory is used. If the MEGSIM dataset is not found under the given path (e.g., as "mne-python/examples/MEGSIM"), 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_MEGSIM_PATH in mne-python config to the given path. If None, the user is prompted. Returns ------- path : list of str Local paths to the given data files. If URL was a .fif file, this will be a list of length 1. If it was a .zip file, it may potentially be many files. Notes ----- For example, one could do: >>> from mne.datasets import megsim >>> url = 'http://cobre.mrn.org/megsim/simdata/neuromag/visual/M87174545_vis_sim1A_4mm_30na_neuro_rn.fif' >>> megsim.data_path(url, os.getenv('HOME') + '/datasets') # doctest:+SKIP And this would download the given MEGSIM data file to the 'datasets' folder, and prompt the user to save the 'datasets' path to the mne-python config, if it isn't there already. The MEGSIM dataset is documented in the following publication: Aine CJ, Sanfratello L, Ranken D, Best E, MacArthur JA, Wallace T, Gilliam K, Donahue CH, Montano R, Bryant JE, Scott A, Stephen JM (2012) MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data. Neuroinform 10:141-158 """ if path is None: # use an intelligent guess if it's not defined def_path = op.realpath(op.join(op.dirname(__file__), '..', '..', '..', 'examples')) key = 'MNE_DATASETS_MEGSIM_PATH' if get_config(key) is None: key = 'MNE_DATA' path = get_config(key, def_path) # use the same for all datasets if not op.exists(path) or not os.access(path, os.W_OK): try: os.mkdir(path) except OSError: try: logger.info("Checking for megsim data in '~/mne_data'...") path = op.join(op.expanduser("~"), "mne_data") if not op.exists(path): logger.info("Trying to create " "'~/mne_data' in home directory") os.mkdir(path) except OSError: raise OSError("User does not have write permissions " "at '%s', try giving the path as an argument " "to data_path() where user has write " "permissions, for ex:data_path" "('/home/xyz/me2/')" % (path)) if not isinstance(path, string_types): raise ValueError('path must be a string or None') destination = _url_to_local_path(url, op.join(path, 'MEGSIM')) destinations = [destination] split = op.splitext(destination) is_zip = True if split[1].lower() == '.zip' else False # Fetch the file do_unzip = False if not op.isfile(destination) or force_update: if op.isfile(destination): os.remove(destination) if not op.isdir(op.dirname(destination)): os.makedirs(op.dirname(destination)) _fetch_file(url, destination, print_destination=False) do_unzip = True if is_zip: z = zipfile.ZipFile(destination) decomp_dir, name = op.split(destination) files = z.namelist() # decompress if necessary (if download was re-done) if do_unzip: stdout.write('Decompressing %g files from\n' '"%s" ...' % (len(files), name)) z.extractall(decomp_dir) stdout.write(' [done]\n') z.close() destinations = [op.join(decomp_dir, f) for f in files] # Offer to update the path path = op.abspath(path) if update_path is None: if get_config(key, '') != path: update_path = True msg = ('Do you want to set the path:\n %s\nas the default ' 'MEGSIM dataset path in the mne-python config ([y]/n)? ' % path) answer = raw_input(msg) if answer.lower() == 'n': update_path = False else: update_path = False if update_path is True: set_config(key, path) return destinations def load_data(condition='visual', data_format='raw', data_type='experimental', path=None, force_update=False, update_path=None): """Get path to local copy of MEGSIM dataset type Parameters ---------- condition : str The condition to use. Either 'visual', 'auditory', or 'somatosensory'. data_format : str The data format. Either 'raw', 'evoked', or 'single-trial'. data_type : str The type of data. Either 'experimental' or 'simulation'. path : None | str Location of where to look for the MEGSIM data storing location. If None, the environment variable or config parameter MNE_DATASETS_MEGSIM_PATH is used. If it doesn't exist, the "mne-python/examples" directory is used. If the MEGSIM dataset is not found under the given path (e.g., as "mne-python/examples/MEGSIM"), 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_MEGSIM_PATH in mne-python config to the given path. If None, the user is prompted. Returns ------- paths : list List of local data paths of the given type. Notes ----- For example, one could do: >>> from mne.datasets import megsim >>> megsim.load_data('visual', 'raw', 'experimental', os.getenv('HOME') + '/datasets') # doctest:+SKIP And this would download the raw visual experimental MEGSIM dataset to the 'datasets' folder, and prompt the user to save the 'datasets' path to the mne-python config, if it isn't there already. The MEGSIM dataset is documented in the following publication: Aine CJ, Sanfratello L, Ranken D, Best E, MacArthur JA, Wallace T, Gilliam K, Donahue CH, Montano R, Bryant JE, Scott A, Stephen JM (2012) MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data. Neuroinform 10:141-158 """ if not condition.lower() in valid_conditions: raise ValueError('Unknown condition "%s"' % condition) if not data_format in valid_data_formats: raise ValueError('Unknown data_format "%s"' % data_format) if not data_type in valid_data_types: raise ValueError('Unknown data_type "%s"' % data_type) urls = url_match(condition, data_format, data_type) data_paths = list() for url in urls: data_paths.extend(data_path(url, path, force_update, update_path)) return data_paths