mne.time_frequency.EpochsTFR¶

class mne.time_frequency.EpochsTFR(info, data, times, freqs, comment=None, method=None, verbose=None)[source]¶

Container for Time-Frequency data on epochs.

Can for example store induced power at sensor level.

Parameters:

Parameters:	info : Info The measurement info. data : ndarray, shape (n_epochs, n_channels, n_freqs, n_times) The data. times : ndarray, shape (n_times,) The time values in seconds. freqs : ndarray, shape (n_freqs,) The frequencies in Hz. comment : str \| None, defaults to None Comment on the data, e.g., the experimental condition. method : str \| None, defaults to None Comment on the method used to compute the data, e.g., morlet wavelet. verbose : bool, str, int, or None If not None, override default verbose level (see `mne.verbose()` and Logging documentation for more).

info : Info: The measurement info.
data : ndarray, shape (n_epochs, n_channels, n_freqs, n_times): The data.
times : ndarray, shape (n_times,): The time values in seconds.
freqs : ndarray, shape (n_freqs,): The frequencies in Hz.
comment : str | None, defaults to None: Comment on the data, e.g., the experimental condition.
method : str | None, defaults to None: Comment on the method used to compute the data, e.g., morlet wavelet.
verbose : bool, str, int, or None: If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Notes

New in version 0.13.0.

Attributes:

Attributes:	info : instance of Info Measurement info. `ch_names` : list Channel names. data : ndarray, shape (n_epochs, n_channels, n_freqs, n_times) The data array. times : ndarray, shape (n_times,) The time values in seconds. freqs : ndarray, shape (n_freqs,) The frequencies in Hz. comment : string Comment on dataset. Can be the condition. method : str \| None, defaults to None Comment on the method used to compute the data, e.g., morlet wavelet.

info : instance of Info: Measurement info.
ch_names : list: Channel names.
data : ndarray, shape (n_epochs, n_channels, n_freqs, n_times): The data array.
times : ndarray, shape (n_times,): The time values in seconds.
freqs : ndarray, shape (n_freqs,): The frequencies in Hz.
comment : string: Comment on dataset. Can be the condition.
method : str | None, defaults to None: Comment on the method used to compute the data, e.g., morlet wavelet.

Methods

`__contains__`(ch_type)	Check channel type membership.
`__hash__`()	Hash the object.
`add_channels`(add_list[, force_update_info])	Append new channels to the instance.
`apply_baseline`(baseline[, mode, verbose])	Baseline correct the data.
`average`()	Average the data across epochs.
`copy`()	Give a copy of the EpochsTFR.
`crop`([tmin, tmax])	Crop data to a given time interval in place.
`drop_channels`(ch_names)	Drop some channels.
`pick_channels`(ch_names)	Pick some channels.
`pick_types`([meg, eeg, stim, eog, ecg, emg, …])	Pick some channels by type and names.
`reorder_channels`(ch_names)	Reorder channels.
`save`(fname[, overwrite])	Save TFR object to hdf5 file.

__contains__(ch_type)[source]¶

Check channel type membership.

Parameters:	ch_type : str Channel type to check for. Can be e.g. ‘meg’, ‘eeg’, ‘stim’, etc.
Returns:	in : bool Whether or not the instance contains the given channel type.

Examples

Channel type membership can be tested as:

>>> 'meg' in inst  
True
>>> 'seeg' in inst  
False

__hash__()[source]¶

Hash the object.

Returns:	hash : int The hash

add_channels(add_list, force_update_info=False)[source]¶

Append new channels to the instance.

Parameters:	add_list : list A list of objects to append to self. Must contain all the same type as the current object force_update_info : bool If True, force the info for objects to be appended to match the values in self. This should generally only be used when adding stim channels for which important metadata won’t be overwritten. New in version 0.12.
Returns:	inst : instance of Raw, Epochs, or Evoked The modified instance.

See also

drop_channels

apply_baseline(baseline, mode='mean', verbose=None)[source]¶

Baseline correct the data.

Parameters:

Parameters:	baseline : tuple or list of length 2 The time interval to apply rescaling / baseline correction. If None do not apply it. If baseline is (a, b) the interval is between “a (s)” and “b (s)”. If a is None the beginning of the data is used and if b is None then b is set to the end of the interval. If baseline is equal to (None, None) all the time interval is used. mode : ‘mean’ \| ‘ratio’ \| ‘logratio’ \| ‘percent’ \| ‘zscore’ \| ‘zlogratio’ Perform baseline correction by subtracting the mean of baseline values (‘mean’) dividing by the mean of baseline values (‘ratio’) dividing by the mean of baseline values and taking the log (‘logratio’) subtracting the mean of baseline values followed by dividing by the mean of baseline values (‘percent’) subtracting the mean of baseline values and dividing by the standard deviation of baseline values (‘zscore’) dividing by the mean of baseline values, taking the log, and dividing by the standard deviation of log baseline values (‘zlogratio’) verbose : bool, str, int, or None If not None, override default verbose level (see `mne.verbose()`).
Returns:	inst : instance of AverageTFR The modified instance.

baseline : tuple or list of length 2

The time interval to apply rescaling / baseline correction. If None do not apply it. If baseline is (a, b) the interval is between “a (s)” and “b (s)”. If a is None the beginning of the data is used and if b is None then b is set to the end of the interval. If baseline is equal to (None, None) all the time interval is used.

Perform baseline correction by

subtracting the mean of baseline values (‘mean’)
dividing by the mean of baseline values (‘ratio’)
dividing by the mean of baseline values and taking the log (‘logratio’)
subtracting the mean of baseline values followed by dividing by the mean of baseline values (‘percent’)
subtracting the mean of baseline values and dividing by the standard deviation of baseline values (‘zscore’)
dividing by the mean of baseline values, taking the log, and dividing by the standard deviation of log baseline values (‘zlogratio’)

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose()).

Returns:

inst : instance of AverageTFR: The modified instance.

average()[source]¶

Average the data across epochs.

Returns:	ave : instance of AverageTFR The averaged data.

ch_names¶: Channel names.

compensation_grade¶: The current gradient compensation grade.

copy()[source]¶

Give a copy of the EpochsTFR.

Returns:	tfr : instance of EpochsTFR The copy.

crop(tmin=None, tmax=None)[source]¶

Crop data to a given time interval in place.

Parameters:	tmin : float \| None Start time of selection in seconds. tmax : float \| None End time of selection in seconds.
Returns:	inst : instance of AverageTFR The modified instance.

drop_channels(ch_names)[source]¶

Drop some channels.

Parameters:	ch_names : list List of the names of the channels to remove.
Returns:	inst : instance of Raw, Epochs, or Evoked The modified instance.

Notes

New in version 0.9.0.

pick_channels(ch_names)[source]¶

Pick some channels.

Parameters:	ch_names : list The list of channels to select.
Returns:	inst : instance of Raw, Epochs, or Evoked The modified instance.

Notes

The channel names given are assumed to be a set, i.e. the order does not matter. The original order of the channels is preserved. You can use reorder_channels to set channel order if necessary.

New in version 0.9.0.

pick_types(meg=True, eeg=False, stim=False, eog=False, ecg=False, emg=False, ref_meg='auto', misc=False, resp=False, chpi=False, exci=False, ias=False, syst=False, seeg=False, dipole=False, gof=False, bio=False, ecog=False, fnirs=False, include=(), exclude='bads', selection=None, verbose=None)[source]¶

Pick some channels by type and names.

Parameters:

Parameters:	meg : bool \| str If True include all MEG channels. If False include None If string it can be ‘mag’, ‘grad’, ‘planar1’ or ‘planar2’ to select only magnetometers, all gradiometers, or a specific type of gradiometer. eeg : bool If True include EEG channels. stim : bool If True include stimulus channels. eog : bool If True include EOG channels. ecg : bool If True include ECG channels. emg : bool If True include EMG channels. ref_meg: bool \| str If True include CTF / 4D reference channels. If ‘auto’, the reference channels are only included if compensations are present. misc : bool If True include miscellaneous analog channels. resp : bool If True include response-trigger channel. For some MEG systems this is separate from the stim channel. chpi : bool If True include continuous HPI coil channels. exci : bool Flux excitation channel used to be a stimulus channel. ias : bool Internal Active Shielding data (maybe on Triux only). syst : bool System status channel information (on Triux systems only). seeg : bool Stereotactic EEG channels. dipole : bool Dipole time course channels. gof : bool Dipole goodness of fit channels. bio : bool Bio channels. ecog : bool Electrocorticography channels. fnirs : bool \| str Functional near-infrared spectroscopy channels. If True include all fNIRS channels. If False (default) include none. If string it can be ‘hbo’ (to include channels measuring oxyhemoglobin) or ‘hbr’ (to include channels measuring deoxyhemoglobin). include : list of string List of additional channels to include. If empty do not include any. exclude : list of string \| str List of channels to exclude. If ‘bads’ (default), exclude channels in `info['bads']`. selection : list of string Restrict sensor channels (MEG, EEG) to this list of channel names. verbose : bool, str, int, or None If not None, override default verbose level (see `mne.verbose()` and Logging documentation for more).
Returns:	inst : instance of Raw, Epochs, or Evoked The modified instance.

meg : bool | str: If True include all MEG channels. If False include None If string it can be ‘mag’, ‘grad’, ‘planar1’ or ‘planar2’ to select only magnetometers, all gradiometers, or a specific type of gradiometer.
eeg : bool: If True include EEG channels.
stim : bool: If True include stimulus channels.
eog : bool: If True include EOG channels.
ecg : bool: If True include ECG channels.
emg : bool: If True include EMG channels.
ref_meg: bool | str: If True include CTF / 4D reference channels. If ‘auto’, the reference channels are only included if compensations are present.
misc : bool: If True include miscellaneous analog channels.
resp : bool: If True include response-trigger channel. For some MEG systems this is separate from the stim channel.
chpi : bool: If True include continuous HPI coil channels.
exci : bool: Flux excitation channel used to be a stimulus channel.
ias : bool: Internal Active Shielding data (maybe on Triux only).
syst : bool: System status channel information (on Triux systems only).
seeg : bool: Stereotactic EEG channels.
dipole : bool: Dipole time course channels.
gof : bool: Dipole goodness of fit channels.
bio : bool: Bio channels.
ecog : bool: Electrocorticography channels.
fnirs : bool | str: Functional near-infrared spectroscopy channels. If True include all fNIRS channels. If False (default) include none. If string it can be ‘hbo’ (to include channels measuring oxyhemoglobin) or ‘hbr’ (to include channels measuring deoxyhemoglobin).
include : list of string: List of additional channels to include. If empty do not include any.
exclude : list of string | str: List of channels to exclude. If ‘bads’ (default), exclude channels in info['bads'].
selection : list of string: Restrict sensor channels (MEG, EEG) to this list of channel names.
verbose : bool, str, int, or None: If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns:

inst : instance of Raw, Epochs, or Evoked: The modified instance.

See also

pick_channels

Notes

New in version 0.9.0.

reorder_channels(ch_names)[source]¶

Reorder channels.

Parameters:	ch_names : list The desired channel order.
Returns:	inst : instance of Raw, Epochs, or Evoked The modified instance.

Notes

Channel names must be unique. Channels that are not in ch_names are dropped.

New in version 0.16.0.

save(fname, overwrite=False)[source]¶

Save TFR object to hdf5 file.

Parameters:	fname : str The file name, which should end with -tfr.h5 . overwrite : bool If True, overwrite file (if it exists). Defaults to false