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# -*- coding: UTF-8 -*-
# Authors: Thomas Hartmann <thomas.hartmann@th-ht.de>
# Dirk Gütlin <dirk.guetlin@stud.sbg.ac.at>
#
# License: BSD (3-clause)
import numpy as np
from .utils import _create_info, _set_tmin, _create_events, \
_create_event_metadata
from .. import RawArray
from ...epochs import EpochsArray
from ...evoked import EvokedArray
def read_raw_fieldtrip(fname, info, data_name='data'):
"""Load continuous (raw) data from a FieldTrip preprocessing structure.
This function expects to find single trial raw data (FT_DATATYPE_RAW) in
the structure data_name is pointing at.
.. warning:: FieldTrip does not normally store the original information
concerning channel location, orientation, type etc. It is
therefore **highly recommended** to provide the info field.
This can be obtained by reading the original raw data file
with MNE functions (without preload). The returned object
contains the necessary info field.
Parameters
----------
fname: str
Path and filename of the .mat file containing the data.
info: dict or None
The info dict of the raw data file corresponding to the data to import.
If this is set to None, limited information is extracted from the
FieldTrip structure.
data_name: str
Name of heading dict/ variable name under which the data was originally
saved in MATLAB.
Returns
-------
raw: Instance of RawArray
A Raw Object containing the loaded data.
"""
from ...externals.pymatreader.pymatreader import read_mat
ft_struct = read_mat(fname,
ignore_fields=['previous'],
variable_names=[data_name])
# load data and set ft_struct to the heading dictionary
ft_struct = ft_struct[data_name]
info = _create_info(ft_struct, info) # create info structure
data = np.array(ft_struct['trial']) # create the main data array
if data.ndim > 2:
data = np.squeeze(data)
if data.ndim == 1:
data = data[np.newaxis, ...]
if data.ndim != 2:
raise RuntimeError('The data you are trying to load does not seem to '
'be raw data')
raw = RawArray(data, info) # create an MNE RawArray
return raw
def read_epochs_fieldtrip(fname, info, data_name='data',
trialinfo_column=0):
"""Load epoched data from a FieldTrip preprocessing structure.
This function expects to find epoched data in the structure data_name is
pointing at.
.. warning:: Only epochs with the same amount of channels and samples are
supported!
.. warning:: FieldTrip does not normally store the original information
concerning channel location, orientation, type etc. It is
therefore **highly recommended** to provide the info field.
This can be obtained by reading the original raw data file
with MNE functions (without preload). The returned object
contains the necessary info field.
Parameters
----------
fname: str
Path and filename of the .mat file containing the data.
info: dict or None
The info dict of the raw data file corresponding to the data to import.
If this is set to None, limited information is extracted from the
FieldTrip structure.
data_name: str
Name of heading dict/ variable name under which the data was originally
saved in MATLAB.
trialinfo_column: int
Column of the trialinfo matrix to use for the event codes
Returns
-------
epochs: Instance of EpochsArray
An EpochsArray containing the loaded data.
"""
from ...externals.pymatreader.pymatreader import read_mat
ft_struct = read_mat(fname,
ignore_fields=['previous'],
variable_names=[data_name])
# load data and set ft_struct to the heading dictionary
ft_struct = ft_struct[data_name]
info = _create_info(ft_struct, info) # create info structure
data = np.array(ft_struct['trial']) # create the epochs data array
events = _create_events(ft_struct, trialinfo_column)
metadata = _create_event_metadata(ft_struct)
tmin = _set_tmin(ft_struct) # create start time
epochs = EpochsArray(data=data, info=info, tmin=tmin,
events=events, metadata=metadata, proj=False)
return epochs
def read_evoked_fieldtrip(fname, info, comment=None,
data_name='data'):
"""Load evoked data from a FieldTrip timelocked structure.
This function expects to find timelocked data in the structure data_name is
pointing at.
.. warning:: FieldTrip does not normally store the original information
concerning channel location, orientation, type etc. It is
therefore **highly recommended** to provide the info field.
This can be obtained by reading the original raw data file
with MNE functions (without preload). The returned object
contains the necessary info field.
Parameters
----------
fname: str
Path and filename of the .mat file containing the data.
info: dict or None
The info dict of the raw data file corresponding to the data to import.
If this is set to None, limited information is extracted from the
FieldTrip structure.
comment: str
Comment on dataset. Can be the condition.
data_name: str
Name of heading dict/ variable name under which the data was originally
saved in MATLAB.
Returns
-------
evoked: Instance of EvokedArray
An EvokedArray containing the loaded data.
"""
from ...externals.pymatreader.pymatreader import read_mat
ft_struct = read_mat(fname,
ignore_fields=['previous'],
variable_names=[data_name])
ft_struct = ft_struct[data_name]
info = _create_info(ft_struct, info) # create info structure
data_evoked = ft_struct['avg'] # create evoked data
evoked = EvokedArray(data_evoked, info, comment=comment)
return evoked
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