# Authors: Alexandre Gramfort # Matti Hämäläinen # Martin Luessi # Denis Engemann # Teon Brooks # # License: BSD-3-Clause import copy import os import os.path as op import numpy as np from ..constants import FIFF from ..open import fiff_open, _fiff_get_fid, _get_next_fname from ..meas_info import read_meas_info from ..tree import dir_tree_find from ..tag import read_tag, read_tag_info from ..base import (BaseRaw, _RawShell, _check_raw_compatibility, _check_maxshield) from ..utils import _mult_cal_one from ...annotations import Annotations, _read_annotations_fif from ...event import AcqParserFIF from ...utils import (check_fname, logger, verbose, warn, fill_doc, _file_like, _on_missing, _check_fname) @fill_doc class Raw(BaseRaw): """Raw data in FIF format. Parameters ---------- fname : str | file-like The raw filename to load. For files that have automatically been split, the split part will be automatically loaded. Filenames not ending with ``raw.fif``, ``raw_sss.fif``, ``raw_tsss.fif``, ``_meg.fif``, ``_eeg.fif``, or ``_ieeg.fif`` (with or without an optional additional ``.gz`` extension) will generate a warning. If a file-like object is provided, preloading must be used. .. versionchanged:: 0.18 Support for file-like objects. allow_maxshield : bool | str (default False) If True, allow loading of data that has been recorded with internal active compensation (MaxShield). Data recorded with MaxShield should generally not be loaded directly, but should first be processed using SSS/tSSS to remove the compensation signals that may also affect brain activity. Can also be "yes" to load without eliciting a warning. %(preload)s %(on_split_missing)s %(verbose)s Attributes ---------- %(info_not_none)s ch_names : list of string List of channels' names. n_times : int Total number of time points in the raw file. times : ndarray Time vector in seconds. Starts from 0, independently of `first_samp` value. Time interval between consecutive time samples is equal to the inverse of the sampling frequency. preload : bool Indicates whether raw data are in memory. %(verbose)s """ @verbose def __init__(self, fname, allow_maxshield=False, preload=False, on_split_missing='raise', verbose=None): # noqa: D102 raws = [] do_check_ext = not _file_like(fname) next_fname = fname while next_fname is not None: raw, next_fname, buffer_size_sec = \ self._read_raw_file(next_fname, allow_maxshield, preload, do_check_ext) do_check_ext = False raws.append(raw) if next_fname is not None: if not op.exists(next_fname): msg = ( f'Split raw file detected but next file {next_fname} ' 'does not exist. Ensure all files were transferred ' 'properly and that split and original files were not ' 'manually renamed on disk (split files should be ' 'renamed by loading and re-saving with MNE-Python to ' 'preserve proper filename linkage).') _on_missing(on_split_missing, msg, name='on_split_missing') break if _file_like(fname): # avoid serialization error when copying file-like fname = None # noqa _check_raw_compatibility(raws) super(Raw, self).__init__( copy.deepcopy(raws[0].info), False, [r.first_samp for r in raws], [r.last_samp for r in raws], [r.filename for r in raws], [r._raw_extras for r in raws], raws[0].orig_format, None, buffer_size_sec=buffer_size_sec, verbose=verbose) # combine annotations self.set_annotations(raws[0].annotations, emit_warning=False) # Add annotations for in-data skips for extra in self._raw_extras: mask = [ent is None for ent in extra['ent']] start = extra['bounds'][:-1][mask] stop = extra['bounds'][1:][mask] - 1 duration = (stop - start + 1.) / self.info['sfreq'] annot = Annotations(onset=(start / self.info['sfreq']), duration=duration, description='BAD_ACQ_SKIP', orig_time=self.info['meas_date']) self._annotations += annot if preload: self._preload_data(preload) else: self.preload = False # If using a file-like object, fix the filenames to be representative # strings now instead of the file-like objects self._filenames = [_get_fname_rep(fname) for fname in self._filenames] @verbose def _read_raw_file(self, fname, allow_maxshield, preload, do_check_ext=True, verbose=None): """Read in header information from a raw file.""" logger.info('Opening raw data file %s...' % fname) # Read in the whole file if preload is on and .fif.gz (saves time) if not _file_like(fname): if do_check_ext: endings = ('raw.fif', 'raw_sss.fif', 'raw_tsss.fif', '_meg.fif', '_eeg.fif', '_ieeg.fif') endings += tuple([f'{e}.gz' for e in endings]) check_fname(fname, 'raw', endings) # filename fname = _check_fname(fname, 'read', True, 'fname') ext = os.path.splitext(fname)[1].lower() whole_file = preload if '.gz' in ext else False del ext else: # file-like if not preload: raise ValueError('preload must be used with file-like objects') whole_file = True fname_rep = _get_fname_rep(fname) ff, tree, _ = fiff_open(fname, preload=whole_file) with ff as fid: # Read the measurement info info, meas = read_meas_info(fid, tree, clean_bads=True) annotations = _read_annotations_fif(fid, tree) # Locate the data of interest raw_node = dir_tree_find(meas, FIFF.FIFFB_RAW_DATA) if len(raw_node) == 0: raw_node = dir_tree_find(meas, FIFF.FIFFB_CONTINUOUS_DATA) if (len(raw_node) == 0): raw_node = dir_tree_find(meas, FIFF.FIFFB_IAS_RAW_DATA) if (len(raw_node) == 0): raise ValueError('No raw data in %s' % fname_rep) _check_maxshield(allow_maxshield) with info._unlock(): info['maxshield'] = True del meas if len(raw_node) == 1: raw_node = raw_node[0] # Process the directory directory = raw_node['directory'] nent = raw_node['nent'] nchan = int(info['nchan']) first = 0 first_samp = 0 first_skip = 0 # Get first sample tag if it is there if directory[first].kind == FIFF.FIFF_FIRST_SAMPLE: tag = read_tag(fid, directory[first].pos) first_samp = int(tag.data) first += 1 _check_entry(first, nent) # Omit initial skip if directory[first].kind == FIFF.FIFF_DATA_SKIP: # This first skip can be applied only after we know the bufsize tag = read_tag(fid, directory[first].pos) first_skip = int(tag.data) first += 1 _check_entry(first, nent) raw = _RawShell() raw.filename = fname raw.first_samp = first_samp if info['meas_date'] is None and annotations is not None: # we need to adjust annotations.onset as when there is no meas # date set_annotations considers that the origin of time is the # first available sample (ignores first_samp) annotations.onset -= first_samp / info['sfreq'] raw.set_annotations(annotations) # Go through the remaining tags in the directory raw_extras = list() nskip = 0 orig_format = None for k in range(first, nent): ent = directory[k] # There can be skips in the data (e.g., if the user unclicked) # an re-clicked the button if ent.kind == FIFF.FIFF_DATA_SKIP: tag = read_tag(fid, ent.pos) nskip = int(tag.data) elif ent.kind == FIFF.FIFF_DATA_BUFFER: # Figure out the number of samples in this buffer if ent.type == FIFF.FIFFT_DAU_PACK16: nsamp = ent.size // (2 * nchan) elif ent.type == FIFF.FIFFT_SHORT: nsamp = ent.size // (2 * nchan) elif ent.type == FIFF.FIFFT_FLOAT: nsamp = ent.size // (4 * nchan) elif ent.type == FIFF.FIFFT_DOUBLE: nsamp = ent.size // (8 * nchan) elif ent.type == FIFF.FIFFT_INT: nsamp = ent.size // (4 * nchan) elif ent.type == FIFF.FIFFT_COMPLEX_FLOAT: nsamp = ent.size // (8 * nchan) elif ent.type == FIFF.FIFFT_COMPLEX_DOUBLE: nsamp = ent.size // (16 * nchan) else: raise ValueError('Cannot handle data buffers of type ' '%d' % ent.type) if orig_format is None: if ent.type == FIFF.FIFFT_DAU_PACK16: orig_format = 'short' elif ent.type == FIFF.FIFFT_SHORT: orig_format = 'short' elif ent.type == FIFF.FIFFT_FLOAT: orig_format = 'single' elif ent.type == FIFF.FIFFT_DOUBLE: orig_format = 'double' elif ent.type == FIFF.FIFFT_INT: orig_format = 'int' elif ent.type == FIFF.FIFFT_COMPLEX_FLOAT: orig_format = 'single' elif ent.type == FIFF.FIFFT_COMPLEX_DOUBLE: orig_format = 'double' # Do we have an initial skip pending? if first_skip > 0: first_samp += nsamp * first_skip raw.first_samp = first_samp first_skip = 0 # Do we have a skip pending? if nskip > 0: raw_extras.append(dict( ent=None, first=first_samp, nsamp=nskip * nsamp, last=first_samp + nskip * nsamp - 1)) first_samp += nskip * nsamp nskip = 0 # Add a data buffer raw_extras.append(dict(ent=ent, first=first_samp, last=first_samp + nsamp - 1, nsamp=nsamp)) first_samp += nsamp next_fname = _get_next_fname(fid, fname_rep, tree) # reformat raw_extras to be a dict of list/ndarray rather than # list of dict (faster access) raw_extras = {key: [r[key] for r in raw_extras] for key in raw_extras[0]} for key in raw_extras: if key != 'ent': # dict or None raw_extras[key] = np.array(raw_extras[key], int) if not np.array_equal(raw_extras['last'][:-1], raw_extras['first'][1:] - 1): raise RuntimeError('FIF file appears to be broken') bounds = np.cumsum(np.concatenate( [raw_extras['first'][:1], raw_extras['nsamp']])) raw_extras['bounds'] = bounds assert len(raw_extras['bounds']) == len(raw_extras['ent']) + 1 # store the original buffer size buffer_size_sec = np.median(raw_extras['nsamp']) / info['sfreq'] del raw_extras['first'] del raw_extras['last'] del raw_extras['nsamp'] raw.last_samp = first_samp - 1 raw.orig_format = orig_format # Add the calibration factors cals = np.zeros(info['nchan']) for k in range(info['nchan']): cals[k] = info['chs'][k]['range'] * info['chs'][k]['cal'] raw._cals = cals raw._raw_extras = raw_extras logger.info(' Range : %d ... %d = %9.3f ... %9.3f secs' % ( raw.first_samp, raw.last_samp, float(raw.first_samp) / info['sfreq'], float(raw.last_samp) / info['sfreq'])) raw.info = info logger.info('Ready.') return raw, next_fname, buffer_size_sec @property def _dtype(self): """Get the dtype to use to store data from disk.""" if self._dtype_ is not None: return self._dtype_ dtype = None for raw_extra, filename in zip(self._raw_extras, self._filenames): for ent in raw_extra['ent']: if ent is not None: with _fiff_get_fid(filename) as fid: fid.seek(ent.pos, 0) tag = read_tag_info(fid) if tag is not None: if tag.type in (FIFF.FIFFT_COMPLEX_FLOAT, FIFF.FIFFT_COMPLEX_DOUBLE): dtype = np.complex128 else: dtype = np.float64 if dtype is not None: break if dtype is not None: break if dtype is None: raise RuntimeError('bug in reading') self._dtype_ = dtype return dtype def _read_segment_file(self, data, idx, fi, start, stop, cals, mult): """Read a segment of data from a file.""" n_bad = 0 with _fiff_get_fid(self._filenames[fi]) as fid: bounds = self._raw_extras[fi]['bounds'] ents = self._raw_extras[fi]['ent'] nchan = self._raw_extras[fi]['orig_nchan'] use = (stop > bounds[:-1]) & (start < bounds[1:]) offset = 0 for ei in np.where(use)[0]: first = bounds[ei] last = bounds[ei + 1] nsamp = last - first ent = ents[ei] first_pick = max(start - first, 0) last_pick = min(nsamp, stop - first) picksamp = last_pick - first_pick # only read data if it exists if ent is not None: one = read_tag(fid, ent.pos, shape=(nsamp, nchan), rlims=(first_pick, last_pick)).data try: one.shape = (picksamp, nchan) except AttributeError: # one is None n_bad += picksamp else: _mult_cal_one(data[:, offset:(offset + picksamp)], one.T, idx, cals, mult) offset += picksamp if n_bad: warn(f'FIF raw buffer could not be read, acquisition error ' f'likely: {n_bad} samples set to zero') assert offset == stop - start def fix_mag_coil_types(self): """Fix Elekta magnetometer coil types. Returns ------- raw : instance of Raw The raw object. Operates in place. Notes ----- This function changes magnetometer coil types 3022 (T1: SQ20483N) and 3023 (T2: SQ20483-A) to 3024 (T3: SQ20950N) in the channel definition records in the info structure. Neuromag Vectorview systems can contain magnetometers with two different coil sizes (3022 and 3023 vs. 3024). The systems incorporating coils of type 3024 were introduced last and are used at the majority of MEG sites. At some sites with 3024 magnetometers, the data files have still defined the magnetometers to be of type 3022 to ensure compatibility with older versions of Neuromag software. In the MNE software as well as in the present version of Neuromag software coil type 3024 is fully supported. Therefore, it is now safe to upgrade the data files to use the true coil type. .. note:: The effect of the difference between the coil sizes on the current estimates computed by the MNE software is very small. Therefore the use of mne_fix_mag_coil_types is not mandatory. """ from ...channels import fix_mag_coil_types fix_mag_coil_types(self.info) return self @property def acqparser(self): """The AcqParserFIF for the measurement info. See Also -------- mne.AcqParserFIF """ if getattr(self, '_acqparser', None) is None: self._acqparser = AcqParserFIF(self.info) return self._acqparser def _get_fname_rep(fname): if not _file_like(fname): return fname else: return 'File-like' def _check_entry(first, nent): """Sanity check entries.""" if first >= nent: raise IOError('Could not read data, perhaps this is a corrupt file') @fill_doc def read_raw_fif(fname, allow_maxshield=False, preload=False, on_split_missing='raise', verbose=None): """Reader function for Raw FIF data. Parameters ---------- fname : str | file-like The raw filename to load. For files that have automatically been split, the split part will be automatically loaded. Filenames should end with raw.fif, raw.fif.gz, raw_sss.fif, raw_sss.fif.gz, raw_tsss.fif, raw_tsss.fif.gz, or _meg.fif. If a file-like object is provided, preloading must be used. .. versionchanged:: 0.18 Support for file-like objects. allow_maxshield : bool | str (default False) If True, allow loading of data that has been recorded with internal active compensation (MaxShield). Data recorded with MaxShield should generally not be loaded directly, but should first be processed using SSS/tSSS to remove the compensation signals that may also affect brain activity. Can also be "yes" to load without eliciting a warning. %(preload)s %(on_split_missing)s %(verbose)s Returns ------- raw : instance of Raw A Raw object containing FIF data. Notes ----- .. versionadded:: 0.9.0 When reading a FIF file, note that the first N seconds annotated ``BAD_ACQ_SKIP`` are **skipped**. They are removed from ``raw.times`` and ``raw.n_times`` parameters but ``raw.first_samp`` and ``raw.first_time`` are updated accordingly. """ return Raw(fname=fname, allow_maxshield=allow_maxshield, preload=preload, verbose=verbose, on_split_missing=on_split_missing)